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2005 AMA Winter Educators’ Conference
Marketing Theory and
Kathleen Seiders, Boston College
Glenn B. Voss, North Carolina State University
Track Chairs
Jeff Inman, University of Pittsburgh
Cheryl Nakata, University of Illinois at Chicago
K. Sivakumar, Lehigh University
Paul Bloom, University of North Carolina, Chapel Hill
Steve Hoeffler, University of North Carolina, Chapel Hill
Ronald C. Goodstein, Georgetown University
Brian Wansink, University of Illinois
David Henard, North Carolina State University
Mitzi Montoya-Weiss, North Carolina State University
Sandy Jap, Emory University
Rick Andrews, Louisiana State University
Danny Weathers, Louisiana State University
Peter Golder, New York University
Mike Ahearne, University of Connecticut
Eli Jones, University of Houston
Jagdip Singh, Case Western Reserve University
Deepak Sirdeshmukh, North Carolina State University
Linda Ferrell, University of Wyoming
O.C. Ferrell, Colorado State University
Rebecca Slotegraaf, Indiana University
Rosann Spiro, Indiana University
Volume 16
311 S. Wacker Drive • Chicago, Illinois 60606 • (312) 542 - 9000
© Copyright 2005, American Marketing Association
Printed in the United States of America
Publications Director: Francesca Van Gorp Cooley
Project Coordinator: Charles Chandler
Cover Design: Jeanne Nemcek
Typesetter: Marie Steinhoff
ISSN: 1054-0806
ISBN: 0-87757-314-X
All rights reserved. No part of the material protected by this copyright
notice may be reproduced or utilized in any form or by any means,
including photocopying and recording, or by any information storage
or retrieval system without the written permission of the American
Marketing Association.
Preface and Acknowledgements
The theme for the 2005 Winter Marketing Educators’ Conference is “Understanding Diverse and
Emerging Markets, Technologies, and Strategies.” The multicultural marketplace is the new mainstream and
sophisticated marketing technologies provide a better understanding of buyer behavior and the ability to reach
diverse segments more efficiently. This year’s conference includes a variety of innovative special sessions
presenting key thought leaders and paper sessions addressing research themes that are critical to marketing
scholars and educators.
Many dedicated individuals contributed to this conference. In particular, we acknowledge the outstanding
work of the Conference Track Chairs, whose stellar performances produced a truly distinguished program.
Reinforcing the role of the Winter Educator’s Conference as a premier research conference, the Track Chairs
worked to shape high-level special sessions and maintained a lofty bar for competitive paper sessions. The
Conference Track Chairs are as follows:
Consumer Behavior
Global Marketing:
Marketing and Society
Brand Marketing and Communications
Marketing, Technology, and Innovations
Inter-Organizational Issues
Marketing Research
Marketing Strategy
Selling and Sales Management
Services & Relationship Marketing
Instructional Innovations
Special Interest Group
Jeff Inman, University of Pittsburgh
Cheryl Nakata, University of Illinois – Chicago
K. Sivakumar, Lehigh University
Paul Bloom, University of North Carolina – Chapel Hill
Steve Hoeffler. University of North Carolina – Chapel Hill
Ronald C. Goodstein, Georgetown University
Brian Wansink, University of Illinois – Urbana-Champaign
David Henard, North Carolina State University
Mitzi Montoya-Weiss, North Carolina State University
Sandy Jap, Emory University
Rick Andrews, Louisiana State University
Danny Weathers, Louisiana State University
Peter Golder, New York University
Mike Ahearne, University of Houston
Eli Jones, University of Houston
Jagdip Singh, Case Western Reserve University
Deepak Sirdeshmukh, North Carolina State University
Linda Ferrell, University of Wyoming
O.C. Ferrell, Colorado State University
Rebecca Slotegraaf, Indiana University
Rosann Spiro, Indiana University
The program reflects the important contributions of the conference reviewers (listed on pp. iv-vii). All
those who submitted papers and special session proposals are to be thanked, as are members of the Academic
Council and AMA journal editors whose leadership in creating the featured Conference Special
Sessions was instrumental.
We are exceedingly grateful to Denise Smart, AMA Academic Council President, for her advice and
support throughout the conference planning process. Also, we acknowledge the significant implementation
efforts of the AMA staff: Nicole Morris, our Program Manager; Charles Chandler; Francesca Van Gorp
Cooley; and Pat Goodrich. Thanks also to Marie Steinhoff for typesetting the proceedings.
With deep appreciation, we thank all contributors for making this a conference that is worthy of our field.
Kathleen Seiders
Boston College
Glenn B. Voss
North Carolina State University
2005 AMA Winter Educators’ Conference List of Reviewers
Manoj Agarwal, Binghamton
Sanjeev Agarwal, Iowa State
Shanita Akintonde, Columbia
Joe Alba, University of Florida
Terri Albert, University of Hartford
Dana Alden, University of Hawaii
Alan Andreasen, Georgetown
Kersi Antia, University of Western
John Antil, University of Delaware
Syed Anwar, Western Texas A&M
Neeraj Arora, University of
Zeynep Arsel, University of
Kwaku Atuahene-Gima, City
University (Hong Kong)
Craig Atwater, Temple University
Anne-Francoise Audrain, Rouen
School of Management
Jon Austin, Cedarville University
Catherine Axinn, Ohio University
Julie A. Baker, University of
Texas – Arlington
Sridhar Balasubramanian,
University of North Carolina
Soumava Bandyopadhyay, Lamar
Yeqing Bao, University of
Fleura Bardhi, University of
Nebraska – Lincoln
Michael Basil, University of
Boris Becker, Oregon State
Joseph Bellizzi, Arizona State
University West
Neeraj Bharadwaj, University of
Sundar Bharadwaj, Emory
Mary J. Bitner, Arizona State
Carolyn Bonifield, University of
Greg Bonner, Villanova University
Doug Bowman, Emory University
Kevin Bradford, University of
Notre Dame
Michael Brady, Florida State
Steve Brown, University of
Tom Brown, Oklahoma State
Eileen L. Bridges, Kent State
Nancy Buchan, University of
Wisconsin – Madison
Margo Buchanan-Oliver,
University of Auckland
Cheryl Buff, Siena College
Al Burns, Louisiana State
Jim Burroughs, University of
Ronald Bush, University of West
Susan Cadwallader, Texas A&M
Richard Caldarola, American
Intercontinental University
Meg Campbell, University of
Les Carlson, Clemson University
Forrest Carter, Michigan State
Goutam Challagalla, Georgia
Institute of Technology
Fiona Chan, University of Hong
Rajesh Chandy, University of
Joseph Chang, University of
Amar Cheema, Washington
John Cherry, Southeast Missouri
State University
Lawrence B. Chonko, Baylor
Bruce Clark, Northeastern
Lucette B. Comer, Purdue
Robert Cosenza, University of
Nicole E. Coviello, University of
Bill Cron, Texas Christian
Lawrence Cunningham, University
of Colorado – Denver
Kerry P. Curtis, Golden Gate
Peter Dacin, Queens University
Kofi Dadzie, Georgia State
Robert Dahlstrom, University of
Rajiv Dant, Clarkson University
Prakash Das, Queen’s University
Kirk Davidson, Mount St. Mary’s
Marion Debruyne, Emory
David Dekker, University of
Benedict Dellaert, Universiteit
Carol Demoranville, Northern
Illinois University
Kalpesh Desai, University of
Sameer Deshpande, University of
Andrea Dixon, University of
Susan Douglas, New York
Kent Drummond, University of
Sean Dwyer, Louisiana Tech
Ike Ekeledo, Northeastern Illinois
Anita Elberse, Harvard University
Reham Eltantawy, Florida State
Sunil Erevelles, University of
North Carolina – Charlotte
Sevgin Eroglu, Georgia State
Lawrence Feick, University of
Reto Felix, University of
Karen Fernandez, University of
Rosie Ferraro, Duke University
Linda Ferrell, University of
Leslie Fine, Ohio State University
Bob Fisher, Western Ontario
Carlos Flavian, Universidad de
Thomas Foscht, University of Graz
Ellen Foxman, Bentley College
Dan Freeman, University of
Frank Fu, University of Houston
Larry Garber, Appalachian State
Nitika Garg, University of
Mrinal Ghosh, University of
Joan Giese, Washington State
Mary Gilly, University of
California – Irvine
Charlotte Greig, Golden Gate
Andy Grein, City University of
New York
Raj Grewal, Penn State University
Stephen J. Grove, Clemson
Julie Guidry, Texas A&M
John Hadjimarcou, University of
Texas – El Paso
Som Hanvanich, Xavier University
Angela Hausman, University of
Texas – Pan American
Xin He, University of Pittsburgh
Tim Heath, Miami University
Geraldine R. Henderson,
University of Texas – Austin
Neil Herndon, University of
Missouri – Columbia
Louise Heslop, Carleton University
Janet Hoek, Massey University
Susan Hogan, Emory University
Hartmut Holzmueller, University of
Lee Kam Hon, Chinese University
of Hong Kong
Heather Honea, San Diego State
Mark Houston, University of
Carol Howard, Oklahoma City
Frederick Hoyt, Illinois Wesleyan
Yili Huang, University of Illinois –
John Hulland, University of
Mike Hutt, Arizona State
Bruce Hutton, University of
Michael Hyman, New Mexico
State University
Subin Im, San Francisco State
Scott Inks, Ball State University
Koert van Ittersum, Georgia
Institute of Technology
Vish Iyer, University of Northern
Cheryl Jarvis, Arizona State
Rama Jayanti, Cleveland State
Devon Johnson, Northeastern
Chris Joiner, George Mason
Marilyn Jones, Bond University
Rajiv Kashyap, William Peterson
Harold Kassarjian, University of
California – Los Angeles
Carol Kaufman-Scarborough,
Rutgers University
Patrick Kaufmann, Boston
Erdener Kaynak, Penn State
Jeremy Kees, University of
Stephen Keysuk Kim, Oregon State
Adwait Khare, University of
Jaehwan Kim, University of
Noreen Klein, Virginia Tech
Thomas Klein, University of
Yu Jun Koernig, University of
Illinois – Chicago
Praveen Kopalle, Dartmouth
Scott Koslow, University of
Robert V. Kozinets, Northwestern
Ram Krishnan, California
Polytechnic State University
Hyojkin Kwak, Drexel University
Dan Ladik, Suffolk University
Michel Laroche, Concordia
Debra Laverie, Texas Tech
Ruby Lee, University of Nevada
James H. Leigh, Texas A&M
Tom Leigh, University of Georgia
Katherine Lemon, Boston College
Patrick Lentz, University of
Steven V. LeShay, Wilmington
Lewis Lim, Indiana University
Charles Lindsey, Indiana
Susan Lloyd, American University
Terry Loe, Kennesaw State
Brian Lofman, Ramapo College of
New Jersey
Ritu Lohtia, Georgia State
Peggy Sue Loroz, Gonzaga
Xueming Luo, University of
Texas – Arlington
Doug MacLachlan, University of
Humaira Mahi, Michigan State
Alan Malter, University of Arizona
Elliot Maltz, Willamette University
Detelina Marinova, Case Western
Reserve University
James Maskulka, Lehigh
Charlotte H. Mason, University of
North Carolina
Charla K. Mathwick, Portland State
Shashi Matta, University of
Southern California
Debbie McAlister, Texas State
University – San Marcos
Michael S. McCarthy, Miami
David Mick, University of Virginia
Sam Min, University of South
Vikas Mittal, University of
Risto Moisio, University of
Nebraska – Lincoln
Michael Mokwa, Arizona State
Sangkil Moon, North Carolina
State University
Bill Moore, University of Utah
David Moore, University of
Elizabeth Moore, University of
Notre Dame
Neil Morgan, University of North
Rob Morgan, University of
David Mothersbaugh, University of
Susan Mudambi, Temple
Paulo H. Muller, University
Federal do Paraná
Venkatapparao Mummalaneni,
Virginia State University
Patrick Murphy, University of
Notre Dame
Jim L. Murrow, Drury University
Kent Nakamoto, Virginia Tech
Om Narasimhan, University of
Ed Nijssen, University of Nijmegen
Rakesh K. Niraj, University of
South California
Thomas G. Noordewier, University
of Vermont
Patricia Norberg, Quinnipiac
Gillian Oakenfull, Miami
Matthew P. O’Brien, University of
Elie Ofek, Harvard University
Shintaro Okazaki, Universidad
Autónoma de Madrid
Ulrich Orth, Oregon State
David Ortinau, University of South
Photis M. Panayides, Cyprus
International Institute of
Veronika Papyrina, University of
Western Ontario
Leonard Parsons, Georgia Institute
of Technology
Vanessa Patrick, University of
Southern California
Joann Peck, University of
Antony Peloso, Arizona State
Robert Peterson, University of
Texas – Austin
Jeffrey Podoshen, Prado
Jaideep Prabhu, Imperial College
Devashish Pujari, McMaster
Ellen Pullins, University of Toledo
William Qualls, University of
Priya Raghubir, University of
California – Berkeley
Priyali Rajagopal, Ohio State
Deva Rangarajan, Vlerick-Leuven
Gent, Belgium
Peter Rea, Baldwin-Wallace
Kristy Reynolds, Louisiana State
Su Bom Rhee, Santa Clara
Greg Rich, Bowling Green State
Keith Richards, University of
Nora J. Rifon, Michigan State
Ed Rigdon, Georgia State
Aric Rindfleisch, University of
Deborah E. Rosen, University of
Rhode Island
Bill Ross, Penn State University
Abhijit Roy, Loyola College
Don Roy, Middle Tennessee State
Subroto Roy, University of New
Salvador Ruiz, Universidad de
Joel Saegert, University of Texas
at San Antonio
Jeff Sager, University of North
Kare Sandvik, Buskerud University
Nicola Sauer, University of
Paul Sauer, Canisius College
Saeed Samiee, University of Tulsa
Sanjit Sengupta, San Francisco
State University
Reshma Shah, Emory University
Tim Silk, University of Florida
Jim Simpson, University of
Alabama – Huntsville
Alina Sorescu, Texas A&M
Jelena Spanjol, Texas A&M
Richard Spreng, Michigan State
Srinivas Sridharan, University of
Western Ontario
Raji Srinivasan, University of
Texas – Austin
Srini Srinivasan, Drexel University
James A. Stephens, Emporia State
Rodney L. Stump, Morgan State
Ursula Y. Sullivan, University of
Tracy Suter, Oklahoma State
Scott D. Swain, Boston University
Debu Talukdar, University of
John F. Tanner, Jr, Baylor
Kimberly A. Taylor, Florida
International University
Stephen S. Tax, University of
Janet Tinoco, University of Central
Julie Toner (Schrader), Bellarmine
David Urban, Virginia
Commonwealth University
Rajiv Vaidyanathan, University of
Raj Venkatesan, University of
Alladi Venkatesh, University of
California – Irvine
Peter Verhoef, Erasmus University
Zannie Voss, Duke University
Frank Wadsworth, Indiana
University Southeast
Kirk Wakefield, Baylor University
Wakiuru Wamwara-Mbugua,
Wright State University
Florian Wangenheim, University of
Charles Weinberg, University of
British Columbia
Rebecca M. Wells, University of
Patricia West, Ohio State
Chris White, Michigan State
Tiffany Barnett White, University
of Illinois at Urbana
John Wong, Iowa State University
Arch Woodside, Boston College
Attila Yaprak, Wayne State
Jun Ye, Case Western Reserve
Virginia Yonkers, Siena College
Boonghee Yoo, Hofstra University
Gergana Yordanova, University of
Cliff Young, University of
Gail Zank, Texas State
University – San Marcos
Allen Zhang, University of Texas –
San Antonio
Zhu Zhen, Babson College
George Zinkhan, University of
The Impact of the Type, Frequency, and Quality of Customer Contact on Customer
Marshall Rice
Mirror, Mirror, on the Wall, Am I What I Consume After All: A Framework for
Ethnicity Based Consumption, a Social Identity Perspective
Tracy R. Harmon
Cultural Influence on Word-of-Mouth Communication
Desmond Lam, Dick Mizerski, Alvin Lee
The Effects of Authenticity Rift on Firm Performance
Zannie Giraud Voss, Glenn B. Voss, Daniel M. Cable
Positioning in Service Firms: Model Development and Some Basic Normative
Charles Blankson, Stavros P. Kalafatis
Antecedents and Consequences of Role Clarity in Explaining Employee-Perceived
Service Quality in Call Centers
Avinandan Mukherjee, Neeru Malhotra
The Status of Cross-Functional Education in Undergraduate Marketing Curricula
Within Management Education
Victoria L. Crittenden, Elizabeth J. Wilson, Cameron Duffy
On Different Teaching Pedagogies: What Happens to Your Course Evaluations?
Alma Mintu-Wimsatt, Kendra Ingram, Mary Anne Milward, Courtney Russ
An Assessment of a Consumer Behavior Multiple-Choice Question Taxonomy
John R. Dickinson
A Comparison of Consumers’ Responses to Traditional Advertising and Product
Placement Strategies: Implications for Advertisers
Terry Daugherty, Harsha Gangadharbatla
New Brand Worlds: A Comparison of College Student Attitudes Toward Brand
Placements in Four Media
Yongjun Sung, Federico de Gregorio
Brands in Action: The Role of Brand Placements in Building Consumer-Brand
Andrew T. Stephen, Leonard V. Coote
The Marketing Cocompetition Process and Strategic Alliance Instability: A System
Dynamics Model
Anna Shaojie Cui, Roger J. Calantone
Focal Supplier Opportunism in Retailer Category Management
Neil A. Morgan, Anna Kaleka, Richard A. Gooner
“No Greater Satisfaction Than to Vindicate Expectation” How Affective Expectations
Shape Consumption Experience
Andrew K.C. Wong
Customer Delight: An Attempt to Comprehend the Dimensions That Compose the
Construct and its Behavioral Consequences
Stefânia Ordovás de Almeida, Walter Meucci Nique
Towards a Conceptual Framework of E-Confusion
Vincent-Wayne Mitchell, Gianfranco Walsh
Differential Impacts of CRM on Consumer Responses: Toward an Integrative
Frederick Hong-Kit Yim
Exploring the Phenomenon of Buyer-Seller Mismatches in Business-to-Business
Christopher P. Blocker
Consumer Trust Norms in Multi-Channel Firms: The Role of Trust in Technology
and Firm Commitment to Privacy Protection in Technology-Based Service Delivery
Devon Johnson
Validation and Application of a Bi-Dimensional Long-Term Orientation Scale
William O. Bearden, R. Bruce Money, Jennifer L. Nevins
Consumer Socialization of Third Culture Kids in a Cosmopolitan City
Alfred Y. Sit, Haksin Chan
Consumer Ethnocentrism in the German Market
Heiner Evanschitzky, Florian V. Wangenheim
Identifying Information Search Patterns in a Web-Based Environment: Development
of a Search Pattern Index
Morris K. George, Girish N. Punj
Perceived Risk and Consumer Innovativeness Hierarchy: An Empirical Study of
Resistance to High Technology Product Adoption
Tanawat Hirunyawipada, Mohammadali Zolfagharian
Perceived Entitativity as a Moderator of Family Brand Evaluations
Joseph W. Chang, Yung-Chien Lou
The Performance Implications of Synergistic Knowledge Resource Effects in
Differing Environmental Conditions
David A. Griffith, Stephanie M. Noble, Qimei Chen
The Impact of Market Characteristics on Order-of-Brand Entry Strategy: An Empirical
Danielle A. Chmielewski, Bryan A. Lukas, Robert E. Widing II
Organizational Culture Antecedents of Market-Driven Positional Advantage and
Organizational Performance Consequences
Artur Baldauf, David W. Cravens, Christian Bischof
See No Evil, Hear No Evil, Speak No Evil: A Study of Defensive Organizational Behavior
Towards Customer Complaints
Christian Homburg, Andreas Fürst
The Rest of the Iceberg: An Examination of Noncomplaining Service Customers
Clay M. Voorhees, Michael K. Brady, David M. Horowitz
From Empathy to Forgiveness: A Prosocial Perspective in Service Failure and Recovery
Felix T. Tang
International Marketing Alliance Dynamics: Empirical Findings from the
Pharmaceutical Industry
Sengun Yeniyurt, Janell D. Townsend, Erin Cavusgil
A Cross-National Study of Consumer-Firm Exchange Relationships Within the
Context of Market Milieus
Patrick Lentz, Deepak Sirdeshmukh, Ed Nijssen, Hartmut H. Holzmüller,
Jagdip Singh
An Examination of IMC at the Tactical Level: Differences Across Time and Product
Stephen J. Grove, Les Carlson, Michael J. Dorsch, Christopher D. Hopkins
Assessing the Effects of In-School Point of Purchase and Sampling on the Choice of
a Healthy Food Option
Dafina Rexha, Katherine Mizerski, Richard Mizerski
Testing Why Adults Purchase Fast Food Cartoon Character Toy Premiums
Claire Lambert, Richard Mizerski
Multimarket Contact and the Moderating Role of Dominant Local Players: A Conceptual
Sweta Chaturvedi Thota
The Nature of Co-Opetition: Literature Review and Propositions
Pilsik Choi
Technology Versus People: Two Schools of Thought on Pricing Capability Development
Lewis K.S. Lim, Rebecca J. Slotegraaf, Rockney G. Walters
Dimensions and Outcomes of Relational Exchange in a Business-to-Business Context:
A Meta-Analysis
Mohammadali Zolfagharian, Rajasree K. Rajamma
Entry Mode and Level of Equity: A Simultaneous Examination of Foreign Direct
Investment Governance
Sudha Mani, Kersi D. Antia, Aric Rindfleisch
Towards an Understanding of the Governance of Complex Networks of Relationships:
Uncertainty, Governance System Choices, and Performance Outcomes
Andrew T. Stephen, Leonard V. Coote
Market Driving Relationship Marketing for Radical Innovations
Helder J. Sebastiao
An Investigation of Perceptual Factors Influencing Consumer’s Intention to Adopt
Radical Versus Incremental New Products
Audhesh K. Paswan, Lisa C. Troy
It’s All about Learning: What Firms Can Learn from Consumer Pioneers
Yun Ye
Will Consumers Prefer Global or Local Brands? The Role of Identity Accessibility in
Consumer Preference for Global Versus Local Brands
Yinlong Zhang, Lawrence Feick, Vikas Mittal
Why Do Conference Goers Return? A Model of Intentions to Attend and Recommend
Annie H. Liu, Mark P. Leach, Robert D. Winsor
Influence of Other Customers: A Scale Development
E. Deanne Brocato, Susan B. Kleiser
Beyond Just Being There: An Examination of the Impact of Attitudes, Materialism, and
Self-Esteem on the Quality of Helping Behavior in Youth Volunteers
Elten Briggs, Tim Landry, Charles Wood, Todd Arnold
A Cross-Cultural Examination of the Relationship Between Materialism and Individual
William Kilbourne, Marko Grünhagen, Janice Foley
M.E.A.L. Time: How Nutritional Disclosure Affects Gender Evaluations of Fast Food
Menu Items
Kenneth W. Bates, Kyle A. Huggins
Unlocking Value Through Customer Education
Thorsten Hennig-Thurau, Peter C. Honebein, Benoit Aubert
Organizational Learning and Dynamic Marketing Capabilities: Implications for
Organizational Performance
Linda M. Foley, Douglas W. Vorhies, Victoria D. Bush
Adopting RFID Technology: Does the Manager’s Attitude Matter?
Gilbert N. Nyaga, Roger J. Calantone, Thomas J. Page
A Synergistic Model for New Product Success
Russell Adams
Income Elasticity of Household’s Demand for Communication and its Products: Global
Measurement and its Marketing Implications
Min Lu, Yanbin Tu
Computational Estimation of Partioned Prices: Another Heuristic Moves into the
Marketing Neighborhood
William J. Jones, Devon S. DelVecchio, Terry L. Childers
The Effects of Magnitude Representation Encoding Interference and Order of Price
Exposure in Comparative Price Advertising
Keith S. Coulter, Robin A. Coulter
Influences on What Consumers Know and What They Think They Know Regarding
the Persuasive Aspects of Pricing-Related Selling Tactics
Jay P. Carlson, William O. Bearden, David M. Hardesty
Creativity in Advertising: Purchase Intent and Brand Attitude Effects
Brian D. Till, Daniel W. Baack
Where’s the Affect? An Investigation of the Effect of Three Advertising Scales on
Attitude to the Ad
Arjun Chaudhuri
Marketing Communication and Company Brand Attitude
Marc Weinberger, Dale Taoping Tzeng, Paul Bottomley, Harlan Spotts
Organizational Antecedents to and Outcomes of Marketing Strategy Development Styles:
A Contingency Model
J. Chris White, Jeffrey S. Conant, Raj Echambadi
Coordinating Marketing and Sales: Exploration of a Neglected Interface
Christian Homburg, Ove Jensen
The Effect of Interactional Justice on the Performance of Cross-Functional Product
Development Teams
Tianjiao Qiu, Deborah Rupp, William Qualls
Cross-Functional Integration and New Product Performance: A Meta-Analysis
Tanawat Hirunyawipada, Archna Vahie
The Contingent Effect of Product Quality on New Product Performance: A Conceptual
Kwaku Atuahene-Gima, Gloria Barczak
Consumer Experience of Social Power During Service Consumption: An Exploratory
Kalyani Menon, Harvir Bansal
What Drives Customer Success? Consumer Perceptions of Enabling and Restraining
Forces Associated with Performing Consumption Tasks
Pete C. Honebein
The Effect of Event Valence on Wait Management Strategies
Elizabeth G. Miller, Barbara E. Kahn, Mary Frances Luce
Seemingly Unrelated Regression: An Alternative to Traditional Bridging in Conjoint
Niels J. Blunch
Within-Informant Bias in Marketing Research
James R. Brown, Anjala S. Krishen, Pushkin Kachroo, Chekitan S. Dev
Building Formative Construct Measures: The Example of Corporate Reputation
Sabrina Helm
Effects of Online Store Attributes on Customer Satisfaction and Loyalty
Miao Zhao, Ruby Roy Dholakia
Organizational Factors Related to Effective Customer Information Systems Practices
Debra Zahay
Marketing Considerations in Weight Control: Preliminary Findings
Angela Hausman
Product Involvement and Place Attachment: Insights from the Environmental
Psychology Literature
Merlyn A. Griffiths
Emergency Contraception: Expectations of Product Need and Use
Andrew M. Parker, Melanie A. Gold
Investigating Drivers of Customer Defection: A Relative Weight Approach
Thomas Hollmann, Cheryl Burke Jarvis
Investigating the Moderators of the Customer Satisfaction-Loyalty Link: Evidence
from Retailing
Heiner Evanschitzky, Gianfranco Walsh
The Interplay of Cognition and Affect in the Formation of Customer Satisfaction:
A Dynamic Perspective
Christian Homburg, Nicole Koschate, Wayne D. Hoyer
Marketing Six Sigma: Zero Defects in Intercultural Service Quality
Martin C. Reimann, Ulrich F. Luenemann
The Impact of Experiential Knowledge and Creativity on Performance of International
Taewon Suh, Hongxin Zhao, Seung H. Kim, Mark J. Arnold, Mueun Bae
Change and the Marketing Organization
Kelly D. Martin, Jean L. Johnson
Privacy Concerns and Customers’ Willingness to Provide Information: A Review with
Implications for Future Research
Mona Srivastava, Robert Harmon
Shifts in Workplace Ethics: Opportunities for Conflict?
Paul L. Sauer, Paul Chao
Interaction Between the Salesperson and Customer: A Framework for Improving the
Sales Outcome
Elizabeth Hemphill, Chris Dubelaar, Steven Goodman, Gus Geursen
Coupons: The Inside Scoop
Somjit Barat
What Next? Explaining Repurchase Decisions After Joining a Loyalty Program
Shirley Y. Cheng, Jessica Y. Kwong
Not All Deals Are Created Equal: Two Different Roles of Sales Promotion
Dongwoo Shin, James H. Leigh
The Effects of Reserve Prices on Bidding Behavior in Online Auctions
Marla Royne Stafford, Ashley Kilburn, Barbara B. Stern
Advertising Goes Mobile: Explaining Attitude Toward M-Advertising
Parissa Haghirian
Regulatory Focus and Relationship Marketing Success
Maria Sääksjärvi, Johanna Gummerus
Predicting Usage Level and Upgrading Behavior of Service Customers: A Model for
Lifetime Value Estimation at Early Relationship Stages
Florian V. Wangenheim
The Impact of Perceived Language Status on Product and Service Quality Expectations
Melissa Maier Bishop
Effects of Positioning a Foreign Brand as a Domestic Brand in Countries with
Developed (U.S.) Versus Transitioning (Romania) Market Economies
Lada V. Kurpis, Simona Stan, Carmen Barb
Can Self-Affirmation Reduce Prejudice Expression Toward Stereotyped Brands?
Huimin Xu
Self and Brand Image Congruence: Driving Consumer Value
Adam Marquardt
The Spillover Effects of Product-Harm Crises in a Brand Portfolio
Jing Lei, Niraj Dawar, Jos Lemmink
Market Driven Intangibles and Sustainable Performance Advantages
Matti Tuominen, Sheelagh Matear, Sami Kajalo, Saara Hyvönen, Arto Rajala,
Kristian Möller, Gordon E. Greenley, Graham J. Hooley
Understanding Creative Campaign Implementation: An Investigation of its Antecedents
Atlanta L. Stoyle, Leonard V. Coote
Value-Based Differentiation in Business Relationships: Gaining and Maintaining Key
Supplier Status
Wolfgang Ulaga, Andreas Eggert
Affect and Conation in Business-to-Business Relationships: An Empirical Analysis of
Loyalty Lifecycle Sequence
Chad Ruel Allred
The Effect of Total and Asymmetric Specific Asset Investment on Supplier-Buyer
Relationship: A Structural Model
Taewon Suh, Henry Yu Xie, Ik-Whan G. Kwon
Marshall Rice, York University, Toronto
This paper presents an investigation of the impact of
81 distinct types of customer contact on customer satisfaction. Data from 8,836 respondents support the finding that
customer satisfaction is improved by increasing contact
points. In addition, certain types of contact and quality of
contact are shown to be important.
Over the past 20 years, customer satisfaction has
become a key concept in marketing (Harvey 1998). Academic research has focused on important customer satisfaction issues that include such topics as the conceptualization and measurement of satisfaction constructs, (Fourier and Mick 1999; Smith 1999), the impact of satisfaction on customer retention (Rust and Zahorik 1993),
customer satisfaction and profitability (Gurau and Ranchhod 2002), loyalty and customer satisfaction (Gronholdt,
Martensen, and Kristensen 2000), the role of value in
customer satisfaction (Day 2002) to name a few. Although the subject of customer satisfaction has been
extensively studied, research shows mixed findings and
complex relationships between the antecedents and outcomes of business having more versus less-satisfied customers (Szymanski and Henard 2001).
In addition, the impact of customer contact has been
extensively examined in the CRM literature (Winer 2001).
Research has shown that regular contact with customers
can improve profits (Reinartz and Kumar 2000), decrease
defection/increase retention (Verhoef 2003; Weinstein
2002) and increase the perceived relationship investment
(De Wulf, Odekerken-Schroder, and Lacobucci 2001).
Further, considerable research shows that increased customer contact by activities such as loyalty programs
improve acquisition, retention and customer development
(Stone, Bearman, Butscher, and Gilbert 2004), while
brand building contact improves loyalty (McAlexander,
Schouten, and Koening 2002).
Research on customer satisfaction has generally focused on understanding the impact of a limited number of
product or firm attributes. In particular, the research has
tended to focus on the impact of service and product
quality on overall customer satisfaction. It is reasonable to
assume, however, that many other contacts that an organization has with its customers can have an impact on
American Marketing Association / Winter 2005
satisfaction. For example, a customer’s level of satisfaction with a company (and it’s products and services) is
likely impacted by such factors as interaction with the
corporate Web site, exposure to marketing communications, participation in corporate events and training, interaction with sales representatives and many other contacts.
This paper presents an exploratory investigation of
the impact of a larger number of customer contacts than is
found in the academic literature. Specifically, this paper
examines the impact of the type, frequency and quality of
81 distinct contact points on customer satisfaction. By
examining 81 different contact points, we hope to provide
some preliminary insights into the following types of
managerial and research questions:
Can a company improve overall satisfaction by increasing its frequency of contact with customers?
Are certain types of customer contact more valuable
than others in improving overall satisfaction with a
Does frequency of contact or quality of contact have
a stronger relationship with overall satisfaction with
a company?
For this study, the researchers analyzed data provided
by a large company in the technology sector (the name of
the company is not revealed to protect proprietary data).
A total of 8,836 people were intercepted at the corporate
Web site and participated in the research which was
administered via an online survey. Respondents were
typical of those who come to the Web site (i.e., a mix of
IT Professionals and Developers and General Users). As
an incentive to participate, respondents were able to enter
a contest to win a $100 gift certificate from
Data was collected via an Internet population for several
reasons. First, experience and usage of many of the
variables that we examined (i.e., subscription to Internet
services, participation in online events etc.) are not common phenomenon and it would be difficult to obtain these
respondents via a simple random telephone sample. Second, the instrument was quite lengthy which would have
made it prohibitive to attempt to administer the survey via
traditional data collection methods.
The 81 contact points that were examined in this
paper were arrived at through extensive discussions with
decision makers at the company that provided the data. In
the discussion, the principal researcher and corporate
decision makers began with an informal listing of possible
contact variables that can have an impact on satisfaction
and that could be measured. This list was then judgmentally
reduced to produce the final 81 contact points.
Respondents answered a series of closed-ended questions that asked them to identify which of 81 unique types
of contact they have had with the company. These 81
contact points were then categorized for analysis into nine
distinct types of customer contact as listed in Table 1.
Cronbach’s Alpha was used to test the reliability of the
scales that make up the nine individual types of contact.
All nine items displayed an Alpha of > .85 which is
considered good (Nunnaly 1978) and indicates that the
individual contact points were measuring a unidimensional construct within each group.
Respondents also indicated their level of satisfaction
with each type of contact using nine point scales (where 1
indicated that they were “not at all satisfied” and 9
indicated that they were “very satisfied”). Respondents
were also asked to rate their overall satisfaction with the
company, its products, service and support organization
using the same nine point scale. This overall satisfaction
question served as the basis (dependent variable) for
much of the analysis that is presented in this paper. To
answer the research questions, analysis was performed
using a combination of cross-tabulation (X2 analysis),
analysis of variance (ANOVA) and regression.
Research Hypothesis
The following research hypothesis are investigated in this
H1: Increases in the amount of customer contact points
will correlate positively with overall company satisfaction.
Classification of Types of Contact
Category of Type of Contact
Number of Contacts Within This Group
1. Corporate Web sites visited
16 contact points
2. Received Information about the company/
the company Products
14 contact points: such as reading online reviews
about products, company Products seeing print ads,
meeting a sales representative, receiving direct mail,
3. Initiated Contact with the company
13 contact points: such as contacting the company by
telephone, e-mail communication, contacting support,
4. Subscribed to Newsletter(s)
11 contact points: a total of 11 newsletters were
offered and monitored
5. Participated in Training
7 contact points: such as taking an online course, using
training materials, etc.
6. Participated in Events/Community Activities
7 contact points: such as participating in an online
chat, attending a conference, etc.
7. Planned and Deployed corporate solutions
6 contact points: such as using company products,
upgrading a product/service, etc.
8. Subscribed to Services
5 contact points: a total of five services offered by the
company were available
9. Product/Service Purchase or Download
2 contact points: purchasing product/service or downloading product/service
American Marketing Association / Winter 2005
H2: Certain types of customer contacts are more valuable
(i.e., have more impact) than others in improving
overall satisfaction.
H3: Quality of contact will have a stronger relationship
with overall satisfaction than frequency of contact.
H1: Increases in the amount of customer contact will
correlate positively with overall company satisfaction.
Respondents were categorized into three levels of
frequency of contact, based on the number of contact
points (out of a possible 81 total number of contacts) they
had with the company. Table 2 details the definition of the
three categories of frequency of contact: Light Contact,
Medium Contact, and Heavy Contact.
The frequency of contact into light (10 or fewer
contacts), medium (11 to 20 contacts) and heavy contact
(21+ contacts) groups was determined judgmentally by
key decision makers at the company that provided the
data. Specifically, decision makers were asked how many
contacts they believe constituted “light,” “medium,” and
“heavy” contact with their customers.
Using analysis of variance (ANOVA), it was possible
to determine that overall satisfaction with the company
was significantly different across the three categories of
frequency of contact. Those respondents who had the
highest levels of contact with the company had a significantly higher mean score on satisfaction with the company as compared to those respondents who had lower
levels of contact. Similarly, those respondents who had
medium levels of contact had significantly higher satisfaction with the company as compared to those respondents in the light contact category. The mean values of
overall satisfaction with the company (on a nine point
scale with nine indicating “very satisfied”) for each of
these groups are shown in Table 3. A Duncan’s Multiple
Range test confirmed significant differences among the
mean values shown in Table 3.
This positive relationship between frequency of contact and increased overall satisfaction with the company
can also be seen in the percentage of respondents who
were classified as highly satisfied (HSAT is defined as
those respondents who indicated that their satisfaction
was either 8 or 9 on a 9 point scale) and those who are
classified as “not satisfied” (NSAT is defined as those
respondents who indicated that their satisfaction was 1, 2,
3, or 4) on overall satisfaction with the company across the
three categories of frequency of contact. As seen in Table
4, as the level of contact with the company increases, the
percentage of respondents who fall into the HSAT category goes up significantly, and the percentage of those in
the NSAT category goes down accordingly (Chi-square =
119.4, p. < .0001).
Categories of Frequency of Contact
Frequency of Contact
Light Contact
% of Sample
10 or fewer contacts
11 to 20 contacts
21+ contacts
Medium Contact
Heavy Contact
Impact on Satisfaction based on Frequency of Contact
Frequency of Contact
Satisfaction With the Company (Mean)
Light Contact
Medium Contact
Heavy Contact
(F = 78.61, Significance: < .0001)
American Marketing Association / Winter 2005
H2: Certain types of customer contact will be more valuable (i.e., have more impact) than others in improving
overall satisfaction.
Analysis of variance (ANOVA) was used to determine which types of contact were associated with the
greatest change in overall satisfaction with the company.
For each type of contact, the mean scores on overall
satisfaction with the company between those respondents
who had that contact and those who didn’t, were compared to determine if a significant difference existed.
Table 5 summarizes the change in the mean score of
overall satisfaction with the company as a result of each
type of customer contact.
As Table 5 shows, the most valuable types of contact
for the sample overall, based on change in the mean scores
of overall satisfaction with the company are:
HSAT and NSAT by Frequency of Contact
Frequency of Contact
Light Contact
Medium Contact
Heavy Contact
X2 shows significant differences between all groups: (X2 = 119.4 p. < .001)
Change in Overall Satisfaction With the Company By Type of Contact
Satisfaction of
Satisfaction of
Those Not
Change in
Satisfaction as
a Result of
Received Info. About The Company
F = 132.66
p < .0001
Visited Web sites
F = 57.43
p < .0001
Product/Service Purchase/Download
F = 80.19
p < .0001
Subscribed to Newsletter(s)
F = 108.53
p < .001
Participated in Events/Communities
F = 47.41
p < .0001
Subscribed to Services
F = 27.67
p < .0001
Planned/ Deployed corporate solutions
F = 18.40
p < .0001
Participated in Training
F = 36.76
P < .0001
Initiated Contact with the company
F = 10.95
P < .001
Type of Contact
American Marketing Association / Winter 2005
Received information about the company or the company products
Visited Web sites
Product or service purchase or download
It is important to note, however, that satisfaction was
higher in all categories if the respondent had been contacted.
H3: Quality of contact will have a stronger relationship
with overall satisfaction than frequency of contact.
From a managerial viewpoint it would be useful to
know whether frequency of contact or quality of contact
has a greater impact on customer satisfaction. That is,
given limited resources should organizations direct those
resources to trying to increase the number of contacts or
should it direct resources to trying to improve satisfaction
with some key types of customer contact? In order to study
this question, the survey asked respondents to rate their
satisfaction with contacts they had experienced on a ninepoint scale (1= not at all satisfied, 9 = very satisfied). A
regression analysis was then preformed with overall satisfaction with the company as the dependent variable and
aggregate satisfaction measures for the categories of contact that had the largest number of contacts (received
information about the company, visited Web sites, product or service download, planned or deployed solutions,
initiated contact with the company).
The results of this regression clearly show that satisfaction with key customer contact points (i.e., quality of
contact) is more strongly related than frequency of contact
to overall satisfaction (R2 = .52, all variables significant
at the .0001 level). Complete regression results are shown
in Table 6. Given these results, it suggests that organiza-
Regression Results
Type of Contact
Parameter Estimate
Initiated Contact with the company
p < .0001
Received Info. about The company
p < .0001
Product/Service Purchase/Download
p < .0001
Planned/ Deployed Corporate solutions
p < .0001
Visited Web sites
p < .0001
Frequency of contact
p < .0001
tions should consider putting more resources into improving the quality of contact rather than increasing the total
number of contacts.
overall company satisfaction. However, while the number
of contacts is clearly important more impact is seen by
increasing the quality of each contact.
As this is a exploratory study with only one company,
it is suggested that future research focus on different
companies and sectors in an attempt to see whether these
patterns exist in other industries. In addition, future research should investigate whether different taxonomy/
consumer groups for the same company respond in similar ways to both frequency and type of consumer contacts.
This paper is an exploratory study that attempted to
show the relationship between the amount and quality of
customer contact and it’s impact on satisfaction. As indicated in the paper, the research hypothesis were largely
confirmed. Specifically, the data show that increases in
the amount of contact points is correlated positively with
American Marketing Association / Winter 2005
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For further information contact
Marshall Rice
Marketing Area
Schulich School of Business
York University
4700 Keele Street
Toronto, Ontario
Canada M3J-1P3
Phone: 416.736.2100, Ext. 58241
E-Mail: [email protected]
American Marketing Association / Winter 2005
Tracy R. Harmon, University of South Florida, Tampa
The study of ethnicity as it relates to consumption is
fairly recent in the study of consumer behavior and
marketing (Ogden et al. 2004). Within the marketing
literature, many studies have shown how culture significantly impacts consumer’s perceptions and behavior in
the global marketplace (McCracken 1986). Deshpande
et al. (1986) suggests that the concept of strength of ethnic
identification leads us to believe the existence of fundamental differences between members of a particular ethnic group. Herche and Balasubramanian (1994) discovered that consumers who belonged to a specific ethnic
group were likely to display analogous shopping behaviors. Thus, the focus of this research does not address
aggregate national cultures; rather the intent is to understand the impact of strength of ethnic identity within a
national boundary. This paper therefore seeks to explain
the impact of intra-national cultural differences in ethnic
identity within the specific context of the United States on
consumption behavior.
This framework does not seek to underscore the role
of consumption in the construction of a socially based
ethnic identity, but examines the role of a socially based
ethnic identity as an antecedent to the act of consumption.
Attempts to assimilate the ethnic self into a one-dimensional “melting-pot” ideology fail to address the complexities of personal and social identities among diverse populations. Thus, the primary assumptions are (1) ethnic
identity precedes consumer consumption, (2) as the
strength of ethnic identity changes, so does consumption
practices, and (3) ethnicity based consumption does not
aid in the construction of a socially-based ethnic identity.
This research proposes that the strength of ethnic identification displayed by consumers is the focal construct of
interest during the investigation of ethnicity based consumption practices. The proposed study will relate the
four components of ethnicity (1) ethnic awareness, (2)
ethnic self-identification, (3) ethnic attitudes, and (4)
ethnic behaviors (Phinney 1990) to consumption practices. We expect the differences to be moderated by the
degree of formation of an ethnically based social identity.
Social cognition is one of the prevailing perspectives
in social psychology which provides the theoretical foundations of conventional conceptions of identity. The assumptions which underlie social cognitive theories of
American Marketing Association / Winter 2005
identity are: (1) human cognitive capacities are limited,
(2) individuals think about others in order to interact, and
(3) individual struggle for understanding in order to
predict and control their outcomes. As a result individuals
tend to categorize information about themselves, others,
objects, and situations before engaging in memory or
inferential processes, relevant to social interactions and
Gilly and Penaloza (1999) state that marketers investigate culture indirectly, resulting in references to disparate cultural groups and marketing practices, with less
attention to generalized adaptation processes. Their point
highlights what is missing form the ethnic identity consumption research, the underpinning foundation of ethnic
identity, which precedes consumption, which is addressed
with the proposed framework. Therefore ethnicity-based
consumption is more meaningful than the use of a sign, or
symbol that is consumed, it is a self-concept of image, that
cannot be expunged by the presence of a global marketplace.
Based upon the current research trends in consumer
acculturation and the lack of fit of acculturation to microcultures within a nation, as well as within an ethnic group,
a framework is presented that expands the study of consumer buyer behavior. This lack of fit leads to an important question relevant to marketing: Does the degree of
ethnic identity affect consumption practices? The framework suggests consumption practices are moderated by
the degree of ethnic identity formation. The framework
includes taking into the consideration the core self, identifying the strength of a consumer’s ethnic identity using
Phinney’s (1989) key dimensions which are influenced
by socialization processes, and determining whether purchase decisions vary by degree of ethnic identification
during the consumption process. The proposed framework considers the collective nature of ethnic identification, which considers the elements of the self, motive,
ethnicity, and factors of socialization. These four components capture the core of the individual while accommodating the situational and contextual factors of intersecting identities. The proposed framework is divided into
two distinct halves, which capture the core ethnic self, and
the apparent ethnic self.
After consideration of the core ethnic self and the
apparent ethnic self, which is influenced by social interac7
tions, the formation of ethnic identity emerges. The framework indicates four defined levels of ethnic identity
development, which are termed diffuse, foreclosed, moratorium, and achieved ethnic identities. A diffused ethnic
identity has little or no exploration of ethnicity, and lacks
a clear understanding of the issues. A foreclosed ethnic
identity has little exploration but a clearer understanding
of their ethnicity. Whereas, an ethnic identity in moratorium denotes evidence of exploration of ethnicity, but
some confusion about the meaning of ethnic groups.
Lastly, an achieved ethnic identity is one that has been
explored, understood and accepted.
It would be expected that during the diffuse stage, an
individual would be the least likely to reference his or her
ethnic identity during consumption. Whereas, an individual who has achieved development of their ethnic
identity, would readily access their ethnic identity more
frequently. Individuals who are in the foreclosed and
moratorium stages of development may development a
multicultural attitude of consumption, and may participate in more frequent culture swapping. Naturally the
levels of ethnic identification will vary within ethnic
groups and among subcultures within these groups. However these levels of identification will allow marketers to
better understand the consumption practices within a
particular ethnic group.
This framework helps to mitigate the premise of
contradictory consumption practices among those who
possess a subjectively, strong ethnic self-identity, by
providing a better understanding of the factors that help
shape a consumer’s ethnic identity. This will enhance the
ability to develop marketing communications appropriate
for the multicultural market.
For further information contact:
Tracy R. Harmon
Marketing Department
University of South Florida
4202 East Fowler Avenue – BSN 3222
Tampa, FL 33620
Phone: 813.74.6184
E-Mail: [email protected]
American Marketing Association / Winter 2005
Desmond Lam, University of Western Australia, Australia
Dick Mizerski, University of Western Australia, Australia
Alvin Lee, University of Western Australia, Australia
The power of word-of-mouth has considerable documentation since the 1960s. Word-of-mouth has been
widely reported to be many times more influential than
information from prints, radio, and personal selling. Despite the importance and influence of word-of-mouth, it
has remained one of the most neglected marketing areas.
In fact, many companies are still struggling to develop
effective marketing programs that encourage consumer
word-of-mouth communication. The authors of this current study believe that a sound understanding of factors
influencing word-of-mouth such as those relating to culture may help to create more proactive and targeted
promotional programs toward stimulating consumer wordof-mouth.
Consumers may engage in word-of-mouth for a number of intrinsic reasons. Word-of-mouth among consumers is also affected by other external factors. The influence
of culture appears to be the most important external
factors, particularly in the context of international marketing. While there are many studies on the impact of culture
on marketing, very few examined the effect of culture on
consumers’ word-of-mouth communication. This study
attempts to examine whether and how culture can influence consumers’ word-of-mouth behavior. In particular,
special attention will be given to distinguish word-ofmouth communication with people of strong ties (defined
as in-group) from communication with people of weaker
ties (defined as out-group). Consequently, this article
provides both theoretical and empirical contribution to the
word-of-mouth literature. Ultimately, it is the intention of
the authors to help companies to identify markets or
societies that may be more receptive to word-of-mouth
The reasons why one engages in word-of-mouth have
been extensively researched for about 40 years. Word-ofmouth activity has been shown to influence a variety of
consumer conditions, from awareness, expectations, perceptions, attitudes, behavioral intentions to actual behaviors. Past research found that consumers engaged in wordof-mouth mainly for altruistic, product involvement, and
self-enhancement reasons. The frequency and intensity of
word-of-mouth may also depend on situations, service
quality, types of products and markets, social networks,
social class, individual personality, and culture of the
American Marketing Association / Winter 2005
individuals. Culture, in particular, can have a strong
influence on one’s word-of-mouth behavior.
It is well documented that culture can have a strong
influence on consumers’ thoughts and actions. Hence,
culture can potentially have a significant influence on
consumers’ word-of-mouth behavior through its influence on individual values and group norms. In one of the
most widely cited work, Hofstede (1980) found many
differences between the perceptions and the working
styles of individuals in 53 countries. Hofstede identified
four basic dimensions of differences between national
cultures, namely, individualism, masculinity, uncertainty
avoidance, and power distance. In this current study,
Hofstede’s dimensions were employed to examine individual-level or within-culture differences.
A survey was conducted on a convenience sample of
228 total respondents from two universities in Australia.
Each respondent was given a questionnaire comprising a
number of items on issues relating to their cultural values
and word-of-mouth behavior. These items were measured
on a 5-point Likert scale from 1 (strongly disagree) to 5
(strongly agree). The data was subjected to confirmatory
factor analysis (CFA) and fitted to a structural equation
model with AMOS 6.0. The results gave strong support to
the influence of masculinity and power distance cultural
dimensions on individuals’ word-of-mouth behavior. The
influence of masculinity on out-group word-of-mouth
was significant and positive. Individuals high in masculinity are expected to be more assertive and aggressive in
their approach to communication. As such, they are more
likely to exchange product information with weaker ties
such as out-groups. The results of this study have supported this hypothesis. In addition, power distance has
significant positive influence on in-group word-of-mouth
and negative influence on out-group word-of-mouth. Individuals with high power distance are more likely to
engage in word-of-mouth within their in-groups than with
their out-groups. Those with low power distance are more
likely to feel less inhibited and, as such, will more likely
engage in out-group word-of-mouth. These phenomena
were observed in this current study. However, the study
did not find any evidence of influence of individualism on
either in-group or out-group word-of-mouth. At the same
time, contrary to expectations, uncertainty avoidance appeared to have little impact on both in-group and outgroup word-of-mouth.
It is important to note that any extrapolation of the
results must be made cautiously given that this research
was conducted on a single country and was only represented by a sample of higher-education student population. Future research will attempt to broaden the sample
frame across several countries to improve generalization.
Also, the support of the influence of culture does not rule
out the explanations of other factors that are not covered
in this study. Consumers’ word-of-mouth behavior may
also change depending upon consumption contexts and
on the types of products they consume. Research into
these areas will likely yield a more comprehensive insight
into the word-of-mouth construct.
Word-of-mouth is indeed a major force in the marketplace that should not be taken for granted. Individuals
with certain cultural values/dimensions may be more
receptive to the use of word-of-mouth compared to others.
This study examined and differentiated those cultural
values/dimensions that may be more likely to encourage
word-of-mouth from those that are less likely to do so.
Both word-of-mouth and mass media influence the adoption of new products. The results from this research can
provide businesses with greater insight into using wordof-mouth as a tool for marketing, especially in the international context, by examining critical factors that can affect
word-of-mouth. For example, if companies understand
the factors that affect business referral behaviors, they can
then try to create an environment to induce more customer
referrals. The results will also enable companies to estimate the potential impact of product or company-related
negative and positive word-of-mouth across different
national cultures.
For further information contact:
Desmond Lam
Faculty of Economics and Commerce
University of Western Australia
Social Sciences Building South
35 Stirling Highway
WA 6009, Australia
Phone: +61.8.6488.2890
FAX: +61.8.6488.1055
E-Mail: [email protected]
American Marketing Association / Winter 2005
Zannie Giraud Voss, Duke University, Durham
Glenn B. Voss, North Carolina State University, Raleigh
Daniel M. Cable, University of North Carolina at Chapel Hill, Chapel Hill
This research examines whether internal disagreements relating to organizational identity – authenticity
rift – influence firm performance. An authentic organizational identity represents a true, unique and singular
statement of core organizational values and beliefs held
by all organizational insiders and communicated to all
stakeholders. Rift in the authenticity of organizational
identity represents clefts or differences in the core organizational values and beliefs held by organizational insiders. These internal differences signal confusion regarding
the organization’s core values and lead to divergent goals
and strategies.
The notion of multiple organizational identities has
existed since early explorations by Albert and Whetten
(1985), who proposed that dual identity organizations
possess both normative and utilitarian orientations, and
that organizations may begin with a single identity but
acquire multiple identities over the course of time. Thus,
firms may have a constellation of values with some values
dominating (Gioia, Schultz, and Corley 2000; Voss, Cable,
and Voss 2000). As long as the identity of the organization – however complex the set of core values and beliefs – is commonly held and understood, it is still singular
and congruent.
When authenticity rift exists, an organization possesses diverse and competing responses to the questions
“Who are we?” and “What are our core values and
beliefs?” Rift occurs when multiple identities create confusion throughout the organization as to the firm’s identity or when different factions within the organization
actively espouse different organizational priorities and
values (Albert and Whetten 1985; Golden-Biddle and
Rao 1997; Pratt and Foreman 2000). Conceptual arguments support alternative hypotheses for the relationship
between authenticity rift and firm performance, including
(1) no relationship, (2) a negative relationship, or (3) a
positive relationship.
nonprofit professional theatre industry as the context. We
operationalized organizational identity using five organizational value dimensions relevant to the nonprofit professional theatre industry (Voss, Cable, and Voss 2000),
and we collected measures from two respondents (i.e., the
managing director and marketing director) at each theatre.
We tested the hypotheses by conducting polynomial regression analyses that modeled firm performance as a
function of the main and quadratic effect of each value
dimension reported by each respondent and the interaction between the managing director and marketing director value dimension report. We used two distinct measures of firm performance: customer support, measured
as the theatre’s total earned revenue and overall financial
performance, measured as net income.
Rift had a negative impact on firm performance for
four of the five values. These findings offer evidence that
multiple definitions of identity may hinder rather than
help the firm. Surprisingly, rift had a positive effect on
firm performance for the market value dimension, defined
as the organization’s commitment to customer satisfaction. Firm performance was lower when both marketing
and managing directors reported that market values were
either extremely important or not at all important. This
suggests that “extreme” market theatres either ignore
customers in pursuit of artistic experimentation or are too
focused on current customer preferences at the expense of
creating exciting new art. Balance appears to be achieved
when the marketing director reported that market values
were extremely important while the managing director
reported that market values were not important. This
result questions the wisdom of diffusing market values
throughout an arts organization.
While much research exists on organizational identity, this study is unique in its empirical examination of the
effect of internal discrepancies on firm performance. In
short, skillful management of a singular, clear, authentic
organizational identity may be more advantageous than
multiple, distinctive identities presented to different stakeholders. References available upon request.
To test these alternative hypotheses, we conducted a
longitudinal, two-wave empirical study using the U.S.
American Marketing Association / Winter 2005
For further information contact:
Zannie Giraud Voss
Duke University
Box 90680, 206 Bivins Building
Durham, NC 27708–0680
Phone: 919.660.3347
FAX: 919.684.8906
E-Mail: [email protected]
American Marketing Association / Winter 2005
Charles Blankson, Long Island University, New York
Stavros P. Kalafatis, Kingston University, United Kingdom
Despite the growing activities and interest attached to
the concept of positioning and the fact that the subject is
considered to be one of the key elements of modern
marketing management (Porter 1996; Kotler 1997), there
appears to be a paucity of documented strategic positioning models capable of being applied by managers and
advertising executives. This article deals with the actual
process of managing the concept of positioning. It attempts to put forward normative guidelines through the
formulation, development and operationalization of a
comprehensive composite strategic positioning framework. Using a triangulation research methodology, a
conceptual positioning framework that is the composite of
two extant positioning frameworks (Brand Concept Image Management (BCM) by Park et al. (1986) and the
Generic Positioning Framework (GPF) proposed by
Hooley et al. (1998)) is formulated, and given the difficulty in the positioning of services (Assael 1985; Zeithaml
and Bitner 1996), and the wide spectrum of services
available, it was decided to carry out the research in the
United Kingdom plastic card service firms (e.g., credit
cards, charge cards, store cards, debit cards industry). The
proposed framework thus represents the composite of the
BCM and GPF positioning framework. The rationale for
combining these two models (see Jacoby 1978; Wright
and Kearns 1998) stems from the need for the development of a comprehensive framework that incorporates the
management of positioning over time and at the same
time, ensures marketing synergy, i.e., congruence of related activities.
From the findings, the paper puts forward some basic
normative guidelines and in the process, reveals that
services pursue two key positioning aims (profit and
market share; profit and status) and two main positioning
objectives (functional and symbolic). Furthermore, this
study finds that services are managed within two broad
life cycle stages (fortification and membership) out of
seven (i.e., primal, consolidation, latent, deposition, fortification, membership, fallow). Moreover, they employ
“the name” (i.e., the brand name) as the dominant positioning strategy.
In conclusion, the general patterns of the components
of the model, i.e., decisions and activities, are described
and underline the comprehensiveness and robustness of
the new model. Concerning the definition of the decisions
and activities incorporated in the framework, on the basis
of inductive reasoning, the following three phases and the
related managerial decisions and activities have been
Phase 1
Definition, by management, of the overall positioning aim(s).
Phase 2
Identification of positioning objective(s),
which are deemed as, appropriate in order
to achieve the desired positioning aim(s).
Phase 3 – (i)
Decisions related to the selection of specific positioning strategies which reflect
both the life cycle stage of the offering
and the objectives identified in phase 2.
Phase 3 – (ii) Management (i.e., implementation and
monitoring) of the positioning related
Secondly, based on literature-derived descriptions
and in-depth face-to-face interview, the managerial decisions and activities were operationalized leading to the
following normative guidelines.
Positioning Aim(s)
Positioning Objective(s)
Life Cycle Stages (LCS)
Profit & Market Share
Profit & Status
Latent Position
American Marketing Association / Winter 2005
Thirdly, the resultant guidelines were applied in the
U.K. plastic card services domain and in this process, data
were collected using a combination of face-to-face interviews (executives/experts), survey (target group), and
content analysis (company communications). These have
been used in the descriptions of the four card brands’
positioning aim(s), objective(s), life cycle stages, and
strategies. The latter has been distilled into a simple
summary and is presented in Table 1. Our study calls for
new ways of thinking about and conceptualizing the
application of positioning in service organizations.
Summary of Application of the Comprehensive Strategic Positioning Model
Overall Positioning Strategies
Employed, i.e., Overlapping in
and Target Group
Card Brand
Credit Card:
Profit and Market
and Membership
Reliability and
The Brand Name
Charge Card:
Profit and Status
Top of the Range
and The Brand Name
Store Card:
Profit and Status
Service, Value for Money,
and The Brand Name
Debit Card:
Profit and Market
The Brand Name
For further information contact:
Charles Blankson
Department of Marketing
College of Management
Long Island University – C. W. Post Campus
Brookville, NY 11548–1300
Phone: 516.299.3094
FAX: 516.299.3917
E-Mail: [email protected]
American Marketing Association / Winter 2005
Avinandan Mukherjee, Montclair State University, New Jersey
Neeru Malhotra, Aston University, United Kingdom
Role clarity as perceived by frontline service employees is the extent to which they receive and understand
information required to do the job in the manner that is
expected by the management (Kelly and Hise 1980; Teas
et al. 1979). Role clarity is critical to delivering service
quality in service organizations. This is particularly true in
call centers, where customer contact employees are frequently subjected to conflicting demands of cost efficiency and customer service, thus leading to lower perceptions of role clarity. In the absence of adequate role
clarity, call center representatives (CCR) could end up
misguiding customers, providing wrong information to
them, transferring calls unnecessarily, putting calls on
hold or asking the customer to call later, all of which
would lead to poor service quality. Lack of role clarity can
also have negative effects on job satisfaction and organizational commitment (Ruyter et al. 2001). Hence, the key
purpose of this study is to investigate how frontline staff’s
role clarity in telephonic voice-to-voice service encounters affects their perception of the service quality delivered by them.
We also examine in this research the influence of
selected antecedents and consequences of role clarity in
explaining service quality. The conceptual model is provided in Figure 1. According to Singh (1993), the study of
relationships between organizational factors and role clarity
is rooted in the path-goal theory of leadership (House
1971) and the job characteristics model (Hackman and
Oldham 1976). Key antecedents of role clarity are five
variables mostly relating to organizational job design
characteristics – two job-related variables (feedback and
autonomy), two supervisory variables (participation and
supervisory consideration), and one social variable (teamsupport). Feedback refers to the degree to which carrying
out the work activities required by the job results in the
individual obtaining direct and clear information about
the effectiveness of his/her performance (Hackman and
Oldham 1976). Autonomy is the degree to which the job
provides substantial freedom, independence, and discretion to the individual in scheduling the work and in
determining the procedures to be used in carrying it out
(Hackman and Oldham 1976). Participation in decisionmaking refers to the degree to which employees are able
American Marketing Association / Winter 2005
to influence decisions about their job (Teas 1983). Supervisory consideration refers to leader behaviors concerned
with promoting the comfort and well-being of the subordinates (Boshoff and Mels 1995). Finally, team support –
support from co-workers – not only provides an outlet to
service burnouts arising from difficult service encounters,
but also acts as a channel for disseminating practical
knowledge and information relating to the jobs of the
frontline employees (Sergeant and Frenkel 2000). Key
consequences of role clarity are organizational commitment, job satisfaction, and service quality. Job satisfaction and organizational commitment also affect service
quality. Organizational (affective) commitment refers to
the employee’s emotional attachment to, identification
with and involvement in the organization (Meyer and
Allen 1991). Job satisfaction refers to the extent to which
the employees feel satisfied with the kind of work they do
and with the nature of their job. Service quality is the result
of human interaction between the service provider and the
customer. Service quality as perceived by frontline employees is chosen as the performance consequence of their
role clarity, as “customer contact employees are well
placed to effectively judge the quality of services that they
deliver” (Sergeant and Frenkel 2000, p. 19). We adapted
the SERVQUAL instrument (Parasuraman et al. 1988) to
include only those dimensions that relate to the employees’ service quality. As far as possible, measurement
items for the variables were drawn from standardized
scales well established in literature having acceptable
reliabilities. However, some items were adapted and the
shortened versions of some scales were used based on a 2stage pre-test. All items were linked to five point Likert
type scale ranging from “strongly agree” to “strongly
We based our study on an “in-house” call center of a
major retail bank, where customer satisfaction is one of
the main objectives. Self-administered anonymous questionnaires were mailed to their “Head of Customer Services” responsible for call centers who further forwarded
them to the respective CCRs. Questionnaires were distributed to 710 call center employees. Three hundred eighty
questionnaires were returned to the researchers, providing a response rate of 53.5 percent. These in turn yielded
342 useable questionnaires.
A structural equation model is developed and tested
on this sample of 342 call center representatives. A twostage approach was followed (Anderson and Gerbing
1990). First, the measurement model was estimated and
standardized regression coefficients obtained, and second, the structural model was estimated. The final model
satisfied all three criteria (absolute fit, incremental fit and
parsimonious fit) to determine goodness-of-fit for the
model. Of the 11 hypotheses, all except H2, H4, and H11
were accepted (see Figure 1).
Our study helps to understand the nature and significance of role clarity in customer service. Role clarity
affects service quality positively, and directly as well as
indirectly through organizational commitment and job
satisfaction. Although job satisfaction does not affect
service quality directly, it does so indirectly through
organizational commitment which has a positive effect on
service quality. Further, managers need to act upon the
key antecedents of role clarity in call centers. Detailed
scripting and setting clear expectations in call centers
would improve role clarity. Effective feedback based on
random call recording becomes vital in a highly mechanized call-center environment. Participation in decisionmaking by the customer contact employees on issues
concerning their jobs and going beyond scripts contribute
to role clarity. Team support, in terms of helpful and
supportive team workers, further assists in role clarity by
disseminating useful information concerning various issues in their jobs that are not explicitly known or instructed, and through sharing each other’s experiences
and learning from them. Overall, our research suggests
that boundary personnel in service firms should strive for
higher perceived role clarity to be able to deliver higher
service quality.
Our research reveals that role clarity plays a critical
role in explaining service quality. Further, feedback,
participation and team support positively influence role
clarity, which in turn increases job satisfaction, organizational commitment and service quality. However, autonomy and supervisory consideration have no significant effect on role clarity. Our research suggests that
boundary personnel in service firms should strive for
higher perceived role clarity to be able to deliver higher
service quality. Hence, this study establishes linkages
between internal marketing and external marketing in
service firms, demonstrating that customer contact employees, who are clear of their job roles, feel satisfied and
committed and deliver better service quality to customers.
The Research Framework with Hypothesized Relationships and Structural Model Coefficients
H1 (0.414*)
H7 (0.12*)
H3 (0.19*)
H9 (0.226*)
H6 (0.295*)
H5 (0.12*)
H8 (0.652*)
*Significant at p < .01, std parameter estimate within parenthesis.
American Marketing Association / Winter 2005
Anderson, J.C. and D.W. Gerbing (1990), “Structural
Equation Modeling in Practice: A Review and Recommended Two-Step Approach,” Psychological
Bulletin, 103 (3), 411–23.
Boshoff, C. and G. Mels (1995), “A Causal Model to
Evaluate the Relationships Among Supervision, Role
Stress, Organizational Commitment, and Internal Service Quality,” European Journal of Marketing, 29
(2), 23–42.
Hackman, J.R. and G.R. Oldham (1976), “Motivation
Through the Design of Work: Test of a Theory,”
Organizational Behaviour and Human Performance,
16, 250–79.
House, R.J. (1971), “A Path-Goal Theory of Leadership
Effectiveness,” Administrative Science Quarterly,
Kelly, J.P. and R.T. Hise (1980), “Role Conflict, Role
Clarity, Job Tension, and Job Satisfaction in the
Brand Manager Position,” Journal of the Academy of
Marketing Science, 8 (2), 120–37.
Meyer, J.P. and N.J. Allen (1991), “A Three-Component
Conceptualization of Organizational Commitment,”
Human Resource Management Review, 11 (1), 61–
Parasuraman, A., V.A. Zeithaml, and L.L. Berry (1988),
“SERVQUAL: A Multiple Item Scale for Measuring
Consumer Perceptions of Service Quality,” Journal
of Retailing, 64 (1), 12–40.
Ruyter, K. De, M. Wetzels, and R. Feinberg (2001), “Role
Stress in Call Centres: Its Effects on Employee Performance and Satisfaction,” Journal of Interactive
Marketing, 15 (2), 23–35.
Sergeant A. and S. Frenkel (2000), “When Do Customer
Contact Employees Satisfy Customers?” Journal of
Service Research, 3 (1), 18–34.
Singh, J. (1993), “Boundary Role Ambiguity: Facets,
Determinants, and Impacts,” Journal of Marketing,
57 (April), 11–31.
Teas, R.K., J.G. Wacker, and R.E. Hughes (1979), “A
Path Analysis of Causes and Consequences of
Salesmen’s Perceptions of Role Clarity,” Journal of
Marketing Research, 16 (August), 335–69.
____________ (1983), “Supervisory Behaviour, Role
Stress, and the Job Satisfaction of Industrial Salespeople,” Journal of Marketing Research, 20 (February), 84–91.
For further information please contact:
Avinandan Mukherjee
Marketing Department
Montclair State University
Montclair, NJ 07043
Phone: 973.655.5126
FAX: 973.655.7673
E-Mail: [email protected]
American Marketing Association / Winter 2005
Victoria L. Crittenden, Boston College, Chestnut Hill
Elizabeth J. Wilson, Suffolk University, Boston
Cameron Duffy, Boston College, Chestnut Hill
It has been 20 years since Behrman and Levin suggested that real-world business problems “do not yield to
a single-discipline solution” (1984, p. 142). During this
20-year period, there have been numerous calls for integration across college and university curriculums (cf.,
Association of American Colleges 1985; Boyer 1987) and
within colleges of business in particular (Porter and
McKibbin 1988). Schelfhaudt and Crittenden (2005) report, however, that while most MBA curricula have been
revised to accommodate the trend toward cross-functional integration, the curricula of undergraduate business
programs frequently fail to adapt to the changing needs of
modern organizations. To meet these needs, employees
must be skilled in organizational flexibility, teamwork,
and cross-functional communication and collaboration
(Smart and Barnum 2000; Sheth 2002). There is concern
as to whether undergraduate students will matriculate
with the people and technical skills needed in today’s
workplace (cf., Newman 1999; Parker 2003).
Marketing has been suggested as the broadest area in
business management and, as such, the boundary-spanning function with a company (Crittenden 2003). Academically, Barber et al. (2001, p. 240) suggested that the
marketing department in a college of business “is in a
powerful position to serve an important role in guiding
and binding together other areas” in the facilitation of
cross-functional teaching and learning. Following this
practitioner and academic line of logic, the study reported
here assesses the state of cross-functional management
education from the perspective of the chairs of marketing
departments in universities across the United States.
tions and teamwork that is facilitated and enhanced
by advances in technology.
Graduates with integrative academic experiences that
build on strong functional expertise have a competitive advantage in the job market and a greater chance
of long-term success.
Regarding the integration of marketing and other
functional areas, Crittenden (2003) and Barber et al.
(2001) suggest that the marketing function is in a boundary-spanning role in facilitating increased functional integration. It is not surprising, then, that many cross-functional, academic examples include interactions with marketing. As suggested by Alden et al. (1991), these examples cover a wide range of integration models, both
within and outside the business school. Additionally, the
functions included in the academic examples are consistent with the results of a 2002 study which found that
participation in new product development included marketing, quality, manufacturing, engineering, and purchasing (Goldense and Schwartz 2002).
Research Questions and Methodology
The current research addresses three major questions
with respect to the business school’s marketing department and its integration with other functional areas for
undergraduate management education:
Does integration occur between marketing and other
functional areas?
How is the integration accomplished?
Cross-Functional Education
What are the impediments to integration?
Several researchers have examined the need for crossfunctional integration in the business school curriculum
(e.g., Alden et al. 1991; DeMoranville, Aurand, and
Gordon 2000; Schelfhaudt and Crittenden 2005). Based
on these research findings, there are two major reasons for
integration within the business school program:
In the spring of 2004, a “Status of Cross-Functional
Business Education in the United States” survey was sent
to marketing department chairs at colleges and universities across the United States. The purpose of the survey
was to benchmark the state of cross-functional undergraduate marketing education by addressing the three
major research questions identified above. The survey
resulted in a 15 percent response rate, slightly below the
18 to 57 percent response rates found in previous studies
Cross-functional integration is the norm in business,
resulting in increased interdepartmental communica-
American Marketing Association / Winter 2005
utilizing academic directories as the sampling frame
(Andrus, Laughlin, and Norvell 1995).
It appears that marketing educators are participating
in some level of cross-functional education. Interestingly,
cross-functional education is more of a priority at private
schools than public schools. The majority of integration
takes place in Geiger and Dangerfield’s (1996) “integrating project curriculum” model. This level is more control-
lable by individual faculty members and less time-intensive than more comprehensive programs. In terms of
integration in the marketing classroom, respondents reported some difficulty at finding materials, agreed that
teaching experience is an important resource for effective
delivery of cross-functional content, and suggested that
industry experience is a plus in cross-functional teaching.
More importantly, educators may not be doing a good job
conveying the importance of cross-functional learning.
References available upon request
For further information contact:
Vicky Crittenden
Boston College
450 Fulton Hall
Chestnut Hill, MA 02467
Phone: 617.552.0430
FAX: 617.552.6677
E-Mail: [email protected]
American Marketing Association / Winter 2005
Alma Mintu-Wimsatt, Texas A&M University – Commerce, Commerce
Kendra Ingram, Texas A&M University – Commerce, Commerce
Mary Anne Milward, Texas A&M University – Commerce, Commerce
Courtney Russ, Texas A&M University – Commerce, Commerce
A recent conversation with several colleagues
prompted quite an animated discussion regarding various
modes of delivering business education and the role of
instructional technology. Some vehemently claimed that
the traditional face-to-face pedagogy is by far the most
effective means of teaching students. Others purported
that technology mediated distance learning modes are just
as effective. Interestingly enough, regardless of how each
colleague felt about various teaching pedagogies – ultimately, a consensus was reached. That is, the group
agreed that their teaching evaluations had “gone haywire”
with distance education classes despite the advances in
instructional technology. This consensus opinion prompted
us to investigate how teaching pedagogies affect students’
course evaluations. That is, does delivery method affect
how students evaluate their instructors?
The primary purpose of this study was to compare
MBA students’ evaluative perceptions of their professor
in three different classroom contexts: traditional, ITV and
Internet-Based Marketing Management course. This study
investigated how students’ evaluation of the instructor
was affected when different teaching pedagogies are
used. MBA students evaluated their instructor based on
five evaluation criteria: (1) teaching skills, (2) rapport
with students, (3) grading policies, (4) knowledge of
materials, and (5) presentation skills
MBA students enrolled in the Marketing Management course during their first year of the graduate program
served as the sample groups for this study. Most of the
students are in the 25–30 age range and have worked for
at least two years. The students were requested to complete a standardized University evaluation form. For the
Internet-based students, a second evaluation form was
utilized to assess online technology-related issues. Course
evaluation forms were distributed during the last week of
American Marketing Association / Winter 2005
The results suggest that the traditional students consistently ranked the professor the highest in all five
evaluative criteria. Looking at each of the evaluative
criteria, only the variable “grading policies” produced
slightly different results. That is, for “teaching skills,”
“rapport with students,” “knowledge of material,” and
“presentation skills” – the traditional class was significantly different (at p < .01) from ITV and Internet-based
methods. No statistical differences were found between
ITV and Internet-based groups on the said four variables.
Regarding the variable “grading policies,” ITV students ranked the professor the lowest. ITV result was
statistically different from traditional and Internet-based
at p < .01. Meanwhile, no statistical difference was found
in the “grading policies” between the traditional and
Internet-based classes.
This findings in this study compared how one seasoned professor’s evaluative rating [who has been recognized with several university teaching awards] was significantly affected by the mode of delivery. It appears that
instructors are rated better in the traditional face-to-face
context. However, it is noteworthy to mention that while
students rated both ITV and Internet-based modes lower,
the rating itself was still relatively favorable (i.e., means
of less than 2 in a scale of 1–5).
Given today’s student needs and university budgetary constraints, it is a foregone conclusion that instructional technology is here to stay. Unfortunately, while
technology can significantly improve teaching effectiveness [through the use of e-mails, power point presentations, web pages, etc.] it can also provide many challenges. Perhaps, there is none more intimidating to educators than the seemingly adverse impact it has on student
course evaluations. After all, most tenure and promotion
decisions hinge on students’ evaluative ratings of their
For further information contact:
Alma Mintu-Wimsatt
Department of Marketing & Management
Texas A&M University – Commerce
Commerce, TX 75429
Phone: 903.886.5698
FAX: 903.886.5702
E-Mail: [email protected]
American Marketing Association / Winter 2005
John R. Dickinson, University of Windsor, Ontario
This study conducts an assessment of the taxonomy
into which multiple-choice questions are classified in a
question bank accompanying a widely adopted consumer
behavior text (Solomon, Zaichkowsky, and Polegato [SZP]
2002). The study provides not only an assessment of that
particular question bank, but also a pro forma for similar
assessments of other question banks. Multiple-choice
questions are classified by SZP on two dimensions: question difficulty (easy, moderate, difficult) and “. . . the main
cognitive skill it is designed to test. . .” (Forrest 2002,
“Preface”) (applied, recall).
“The analysis of multiple-choice items typically begins with the computation of a difficulty and a discrimination index for every item.” (Aiken 1991, p. 78) In this
study question difficulty was operationalized as the percent of correct responses for a given question. The mean
percent was 55.7 percent, ranging from 2.4 percent to
100.0 percent. Discrimination was operationalized as the
point-biserial correlation between a student’s total exam
score (excluding the focal question) and the dichotomy of
whether the student answered the question correctly or
incorrectly. The mean point-biserial correlation was 0.218,
ranging from -0.364 to 0.669.
H1: The mean percent of correct answers is inversely
related to classified question difficulty.
H2: The mean percent of correct answers to questions
classified as recall is greater than the mean percent of
correct answers to questions classified as applied.
H3: There is a significant interaction between classified
question difficulty and classified question cognitive
skill on percent of correct answers.
H4: The mean point-biserial correlation of questions classified as moderate is greater than the mean pointbiserial correlation of questions classified as either
easy or difficult.
H5: The mean point-biserial correlation of questions classified as recall is not significantly different from the
mean point-biserial correlation of questions classified as applied.
H6: There is no significant interaction between classified
question difficulty and classified question cognitive
skill on discriminating ability.
Data were drawn from two midterm examinations
(40 and 42 students, respectively) covering chapters one
through eight and two noncumulative final examinations
(41 and 42 students, respectively) covering chapters nine
through seventeen. For each examination, six questions
were selected at random from each chapter on a systematic
basis, for a total of 204 questions.
Factorial Analysis of Variance Significance Levels
Classified Difficulty
Cognitive Skill
Difficulty x Cognitive Skill
Arc sine transformed
Fisher’s r to z transformed
American Marketing Association / Winter 2005
H1 through H3 and H4 through H6 were analyzed
using a 3 (difficulty levels) x 2 (cognitive skills) factorial
analysis of variance. Significance levels, i.e., p-values, for
all statistical tests are presented in Table 1. Mean values
for the respective criteria of percent answered correctly
and point-biserial correlation are presented in Table 2.
References available upon request.
Mean Criterion Values
Percent Correct
Point-Biserial Correlations
Factor Level
H1 and H2 were supported, H3 was not supported. H4 and H5 were not supported, H6 was supported.
John R. Dickinson
Odette School of Business
University of Windsor
Windsor, Ontario
Canada N9B 3P4
Phone: 519.243.4232, Ext. 3104
E-Mail: [email protected]
American Marketing Association / Winter 2005
Terry Daugherty, University of Texas, Austin
Harsha Gangadharbatla, University of Texas, Austin
Product placement is a form of advertising and promotion in which brands are placed in television shows,
movies, or other entertainment content to generate visibility and achieve audience exposure. Proponents of product
placement cite several potential advantages for embracing this method, such as a long shelf life, prominent
exposure, and enhanced realism. For example, even years
after a movie is released or a television show airs, advertisers are still able to receive some level of benefit from
DVD/video releases and television re-runs (Morton 2002).
Furthermore, product placement allows advertisers to
escape “commercial zapping” because consumers cannot
skip over products placed within media content. In fact,
television networks believe that by 2007, there will be
24.7 million DVR owners (Digital Video Recorders)
resulting in a loss of about $6.6 billion in advertising
revenue. However, there are common disadvantages associated with product placement, such as the lack of
control over how products are portrayed or incorporated
into a scene or storyline. Further, advertisers have no
influence over how successful media programming will
be, making it difficult to predict where to place brands for
maximum exposure. Nevertheless, advertisers continue
to spend as much as $20 million to have their products
appear in media content (Grover 2004).
While a considerable amount of research has explored the effects of product placement, key issues remain
for understanding this strategic tactic. For instance, much
of the research investigating product placement to date
has advocated or used memory-based tests (either recall or
recognition) to assess effectiveness (Brennan and Dubas
1999; Eddington 1991; Pracejus 1995; Russell 1998;
Weaver and Oliver 2000) with very little work done
comparing the effectiveness of product placement versus
traditional advertising. Therefore, the purpose of this
study is to explore consumer attitudes toward the various
forms of product placement (i.e., movies, television, video
games, music lyrics, etc.) and investigate how these differ
from traditional advertising.
According to the Elaboration Likelihood Model,
consumers process information through a central route
when they are highly involved or interested in content and
a peripheral route when involvement or interest is low
American Marketing Association / Winter 2005
(Petty and Cacioppo 1983). Thus, information is processed actively when deemed relevant and relegated to a
secondary status when relevance is perceived as low. For
the most part, product placement is more likely processed
through the peripheral route since the message is secondary to that of the media content. For instance, while
watching movies or television shows the likelihood that a
viewer is more focused on the placed product than on the
programming content is low. While elaboration of messages can vary depending consumer motivation, the implications for processing product placement is important
when measuring the effectiveness of this tactic given the
inherent differences between various types of media and
advertising. Gupta and Lord (1998) compared product
placement with traditional advertising and found that
prominent placements outperformed traditional advertising. However, this work does not lend itself toward
understanding product placement occurring in other media modalities, such as television, computer games and
music videos (Nelson 2002).
To explore these issues, five hundred adults were
randomly selected from an online panel and asked to
complete a thirty-item survey. Subsequently, a total of
227 completed questionnaires were collected resulting in
a response rate of 45.4 percent (227 out of 500). The
variables measured centralized around four categories:
opinions about advertising, opinions about multiple forms
of product placement, perceived advertising effectiveness, and perceived effectiveness of multiple forms of
product placement.
The findings suggest that in general product placement is less effective in generating brand awareness than
traditional advertising, but more effective in stimulating
interest and generating immediate or short-term product
purchase intentions. Further, while attitudes toward product placement in movies and television were elevated over
those in video games and music lyrics, more work is
needed in this area before any conclusions can be made
discounting these nontraditional alternatives.
Academic theorists are poised to expand our knowledge in this area as research exploring these issues has
both important industry and theoretical implications for
explaining the nature of product placement in media.
Empirical research is needed though to fully conceptual24
ize this tactic and identify exactly how product placement
impacts affective (attitude) responses rather than simply
cognitive (memory). The objective of this study was not
to suggest definitive attitudinal or behavioral preferences
over product placement or traditional advertising. Rather,
the goal was simply to expand this growing body of work
and lead to future research in this area. While advertisers
are continuing to search for alternative tactics to reach
their target audiences, media professionals need to be
cautious in how they approach these methods, as more
work is needed to extend our understanding of product
placement. References available upon request.
For further information contact:
Terry Daugherty
Department of Advertising
University of Texas at Austin
1 University Station A1200
Austin, TX 78712
Phone: 512.471.8917
FAX: 512.471.7018
E-Mail: [email protected]
American Marketing Association / Winter 2005
Yongjun Sung, The University of Georgia, Athens
Federico de Gregorio, The University of Georgia, Athens
Discussions of brand placement in the popular press
and academic literature tend to predominantly revolve
around film. However, recent content analytic work (e.g.,
de Gregorio and Sung 2004; Ferraro and Avery 2000;
Friedman 1991) demonstrate that brand appearances within
other media are prevalent and continue to increase in
incidence as time progresses. Brand placement in other
media is not a recent phenomenon. Advertisers produced
and sponsored television shows in the 1950s such as
Texaco Star Theater (McCarthy 2001), the Sega video
game company placed Marlboro ads in its early racing
games (Emery 2002), and a song from 1903 entitled
“Under the Anheuser-Busch” asked listeners to “Come,
come, drink some Budwise [sic] with me” (Agenda, Inc.
Although not voluminous, there has been a steady
stream of academic research since the late 1980s on the
strategy of brand placement. Although scholarly brand
placement research has been ongoing since the late 1980s
(Steortz 1987), it has largely focused on the context of
films, with a dearth of investigations of the practice in
other media. Some commonly investigated factors have
included: extent and type of placement (e,g., Devanathan
et al. 2002; Sapolsky and Kinney 1994), audience recall
and recognition of placed brands (e.g., Gupta and Lord
1998; Ong and Meri 1994), and qualitative explorations
of consumers assimilation and interpretation of the meaning of brands placed (DeLorme and Reid 1999).
In addition, a distinct sub-stream of the literature has
been devoted to the gauging of audience opinions about
and attitudes toward brand placements in films. While
numerous attitudinal studies of brand placement in films
exist, to the authors knowledge only a single, qualitative
study has yet examined attitudes toward brand placement
in multiple media (DeLorme 1998). This exploratory
study builds on and contributes to previous work by
serving as the first quantitative investigation of attitudinal
responses to brand placement in films, television shows,
popular songs, and video games. Its overall objectives are
to examine and compare the attitudes of college student
consumers with regards to brand placement across different media. In addition, this study also investigates two
potential antecedents of attitudes toward brand placement
American Marketing Association / Winter 2005
(attitude toward advertising in general and brand involvement).
Employing a convenience sample of college students
(n = 437), the results of this study reveal that opinions
regarding movie and TV show placements tend to be
rather similar and more positive (perhaps due to perceived
similarities of their characteristics) than those dealing
with music and video games. Respondents tend to perceive music and video game placements as: more inappropriate, less effective enhancers of content realism, inferior
sources of brand information, less influential in purchase
behavior, and more unethical and misleading.
As no previous study has looked at content genre
within the context of brand placement, our incorporation
throws further light on and expands the knowledge of
consumer perceptions of placement strategy. Finding of
the study indicates that film and television have more
genres considered appropriate for brand integrations than
music or video games. It is interesting to note that animated fare for both movies and television is considered
particularly inappropriate for brand placements by more
than 50 percent of respondents. It is also notable that genre
appropriateness for music tends to be split based on
“mainstream-ness” – country, rock, and hip hop being
considered appropriate (genres generally well represented
on the weekly mainstream music charts) and blues, jazz,
Christian, and classical/opera inappropriate (genres rarely
on the mainstream music charts). For video games, sports
is clearly the genre of choice among respondents (it is
possible that racing was considered a type of sport, thereby
explaining the closeness of percentages) and is also viewed
as especially appropriate for brand placement as a television genre. This would seem to point to an association of
sports with branding, which is of intuitive sense as sports
events tend to be brimming with sponsorships and advertisements.
In addition, the present study provides evidence that
those who are more positively disposed towards advertising in general are also likely to be more accepting of its
specific forms (in this case placed within media content).
Further, there exists a positive relationship between involvement with brands and positive perceptions of placement strategy. Thus, our results provide preliminary evidence that two ways advertisers can potentially segment
their brand placement audience is according to acceptance
of advertising in general and level of involvement with
brands. Greater research is needed, however, to develop
more detailed and precise points of segmentation for the
two criteria than our separation of high/low and more/less.
For further information contact:
Yongjun Sung
Department of Advertising and Public Relations
Grady College of Journalism and Mass Communication
The University of Georgia
Athens, GA 30602
Phone: 706.549.0988
FAX: 706.542.2183
E-Mail: [email protected]
American Marketing Association / Winter 2005
Andrew T. Stephen, University of Queensland, Australia
Leonard V. Coote, University of Queensland, Australia
Brand placement in mainstream media such as films,
television programs, computer and video games, and
music videos has become a common practice, and a
component of many integrated marketing communication
strategies. There are now countless examples of brand
placements in media, particularly in films and television
programs. Some recent placements in television programs
include General Motors’ products in CBS’s Survivor and
Bravo’s Queer Eye for the Straight Guy, Mitsubishi,
American Express, and Coors in NBC’s The Restaurant,
Coca-Cola in Fox’s American Idol, MSNBC in NBC’s
The West Wing, Dell Computer in Fox’s 24, and the
Trump corporate brand as the focus of NBC’s The Apprentice. Most commercial studio films feature brand
placements, such as Fox News in 20th Century Fox’s Day
After Tomorrow, and the suite of brands placed throughout the recent James Bond films (including Omega, BMW,
Aston Martin, Heineken, and Visa).
Past research on brand placement has focussed on
measuring the effectiveness of placements with respect to
consumer memory and recall and attitudes towards brands,
practitioners’ views on brand placement, and consumers’
attitudes towards the practice of brand placement with
respect to mostly ethical and moral considerations. Little
extant research has considered more enduring and fundamental processes or outcomes of brand placements. This
paper links brand placement with brand loyalty outcomes
through a process of consumer-brand identification. The
integration of consumer-brand identification with a nontraditional marketing communications strategy such as
brand placement is novel. Despite their prevalence in
marketing, the processes for leveraging brands to create
strategically valuable communication mechanisms and
highly loyal consumers is not yet fully understood. The
existing literature has built a detailed and thorough foundation for understanding brand placement and its potential benefits to advertisers and marketers, however it is yet
to consider the contributions brand placement makes to
developing strong social and emotional bonds between
consumers and their brands.
Brand placements are a unique form of marketing
communication in that they allow consumers to view
brands “in action.” When brands are placed in popular
mass media, this not only provides exposure to potential
American Marketing Association / Winter 2005
target consumers, but the placement also shows brands
being used or consumed in natural settings. This may be
more believable, since media characters with which consumers might relate to and identify with use the placed
brands. Social identity theory is thus relevant in this
context. A conceivable outcome of brand placements
putting brands in “action” in the eyes of consumers may
be the development of consumer-brand identification.
Identification literature has considered image-, knowledge-, and social-related antecedents of identification
(e.g., Bhattacharya and Sen 2003). Brand placements
showing brands in apparently realistic (yet contrived)
contexts may signal richer image, knowledge, and social
information about brands to potential consumers than
other forms of marketing communications due to the more
realistic medium. Examining brand placements and consumer-brand identification then helps not only to advance
knowledge of the effectiveness of this communication
device, but also to improve our understanding of how to
actualize deep-level bonds of identification between consumers and brands.
A conceptual framework advanced in this paper
proposes a process through which image-, knowledge-,
and social benefit-related characteristics of brand placements contribute to the development of identificationbased bonds between consumers and brands. Loyalty or
relational outcomes of identification are also considered
(i.e., brand loyalty, brand advocacy, and brand defence).
This process is thought to be moderated by characteristics
of a marketing communication strategy of which a given
placement is part, and characteristics of the focal brand.
Consumer characteristics with respect to (1) attitudes
towards brand placement (e.g., acceptance of the device),
and (2) personal relevance of the focal brand are also
posited as moderators of this process.
Implications for theory and practice are considered.
The main contribution of this paper is the integration of
social identity theory and consumer identification with
the brand placement literature. These theories provide
compelling justifications for brand placement as a marketing communication strategy because they explicate the
deeper connections that can form between consumers and
their brands, and the attitudinal and behavioral loyaltyrelated outcomes of these connections that are possible. In
terms of practical implications, this paper provides marketers and brand managers with a viable approach to
fostering consumer-brand identification. Bonds of identification between consumers and their brands are difficult
to break; a loyal customer base with a high level of
consumer-brand identification is strategically valuable
and a potential source of competitive advantage.
Although brand placement has been used in mass
media for many decades, its current growth and economic
value across a variety of media warrants a deeper examination of its effectiveness as an emerging “hybrid” communications strategy (cf., Balasubramanian 1994). This
paper considers placement from a different perspective by
examining its role in the process of consumers identifying
with brands and the outcomes of this process. The ability
of a brand placement to show a brand in “action” and to
personify a brand by associating it with media characters
in a realistic and believable manner makes it a unique
communication device, and one that is conducive to
fostering consumer identification with a brand. While
advertisers and marketers rightly perceive brand placement to be an effective communications and brand-building strategy, this paper considers the possibility that the
benefits advertisers can potentially enjoy from investing
in such a strategy may be more wide-reaching and valuable than previously thought. References available upon
For further information contact:
Andrew T. Stephen
UQ Business School
University of Queensland
Brisbane, Qld 4072
Phone: +61.7.3365.9721
FAX: +61.7.3365.6988
E-Mail: [email protected]
American Marketing Association / Winter 2005
Anna Shaojie Cui, Michigan State University, East Lansing
Roger J. Calantone, Michigan State University, East Lansing
To gain speed to market and to enable firms to address
markets otherwise inaccessible in the short run, marketing
alliances often form. The coexistance of cooperation and
competition between partners makes alliances a process
of cocompetition. The force of cooperation based on
common benefits holds an alliance together, while the
force of competition based on private benefits tears an
alliance apart. The two countervailing forces interact with
each other during the partnering process and influence the
stability of an alliance. Previous research has recognized
competition as a source of alliance instability, however,
largely due to the limitation of methodologies employed
in extant literature, few research has taken a dynamic view
and studied the cocompetition process overtime.
System dynamics modeling is a simulation method
that has been widely applied to model all kinds of complex
systems. This methodology provides a way to study
complex interactions and feedbacks overtime. Having not
been widely used in marketing, more specifically in
interfirm partnerships, this methodology has the potential
to improve our understanding of the interaction between
cooperation and competition and its influence on the
instability of an alliance.
In this study we build a system dynamics model in the
context of horizontal learning alliances (Figure 1). The
dyadic model captures the two partner firms’ learning,
increase in competitive advantage, dependence and willingness to continue the partnership, with “willingness to
continue the partnership” directly related to the stability of
an alliance. The model is symmetric between firm A and
B. For both firms, private learning increases individual
firm’s competitive advantage, while collective learning
increases the joint competitive advantage, which is shared
by the two firms; dependence increases with investment in
the partnership and unavailability of alternative partners;
American Marketing Association / Winter 2005
willingness to continue the partnership is based on the
firm dependence on the partner, satisfaction for past
cooperation, and the learning potential in the partnership.
Embedded in the model are positive loops capturing
the force of cooperation and negative loops capturing the
force of competition. Through the positive loops the
willingness to continue the partnership builds up itself.
For example, increasing with the willing to continue,
investment further enhances the firm’s dependence and
willingness to continue. Similarly, willingness to continue increases the cooperation effort and correspondingly the benefits generated from the partnership, which
in turn increases the willingness to continue. Through the
negative loops the willingness to continue the partnership
reduces itself. In respect to benefit sharing, disadvantage
in sharing benefits, increased by high dependence and
reduced bargaining power, decreases the firm’s satisfaction for the relative outcome and reduces its willingness to
continue. Related to partner availability, learning improves a firm competency and increases the availability of
alternative partners, which in turn decreases the firm’s
dependence and willingness to continue. Also, because of
opportunism, a firm dependence on the partner firm
decreases the partner firm cooperation effort, which reduces the focal firm learning and willingness to continue.
The model is run under a symmetric setting where all
parameters are set the same for the two firms and an
asymmetric setting where some parameters are set different for the two firms. The simulation results confirm that
when the force of competition overweighs the force of
cooperation, the propensity of instability is increased.
Further, when two firms are perfectly symmetric in learning capability, partner knowledge and intent of appropriation, the partnership is highly stable, while asymmetry in
these characteristics increases the propensity of instability.
A System Dynamics Model of Cocompetition in Learning Alliances
For further information contact:
Anna Shaojie Cui
Department of Marketing and Supply Chain Management
The Eli Broad College of Business
Michigan State University
N370 Business College Complex
East Lansing, MI 48824
Phone: 517.432.5535
E-Mail: [email protected]
American Marketing Association / Winter 2005
Neil A. Morgan, University of North Carolina at Chapel Hill
Anna Kaleka, Cardiff University, United Kingdom
Richard A. Gooner, Scott, Madden & Associates, Raleigh
Leveraging suppliers resources and capabilities via
category management has become the focus of widespread attention in the supermarket industry, as retailers
seek competitive advantage in the face of industry consolidation, globalization, and the rapid expansion of massmerchandisers into the grocery market (ACNielsen 1998;
Gruen and Shah 2000; Hopkins 2003). Category management concerns treating sets of complementary and/or
competing brands in retail settings as strategic business
units and allocating resources within these categories to
maximize planned outcomes (e.g., Blattberg and Fox
1995; Dhar, Hoch, and Kumar 2001; Zenor 1994). Category management therefore involves the analysis of
category-level data, setting goals for category performance, and the formulation and execution of category
plans, all of which might be undertaken with varying
degrees of involvement from suppliers (Basuroy, Mantrala,
and Walters 2001; Dussart 1998). However, analysts
suggest that retailers can enjoy significant performance
benefits if retailers allow a focal supplier to assume the
role of “category captain” where the supplier undertakes
or has significant input into the retailer’s category management (e.g., Blattberg and Fox 1995; Cannondale 1999;
Freedman, Reyner, and Tochtermann 1997). Despite this,
fear and/or experience of supplier opportunism means
that many retailers are either unconvinced or report having failed to make such category management relationships with focal suppliers work (e.g., Brandweek 1999;
Supermarket Business 1999).
The literature offers surprisingly little guidance to
retailer and supplier managers regarding this important
issue. There has been little empirical study of category
management generally, and no research focused on the
key issue of focal supplier opportunism at the categorylevel (Dhar et al. 2001; Gruen and Shah 2000). The
literature reveals a number of different theories relevant to
understanding buyer-supplier relationships (e.g., transaction cost analysis, relational exchange, resource dependence, etc.) and their impact on firm performance (resource-based view, industrial organization, etc.). However, many of these theories offer different viewpoints on
various aspects of supplier-retailer relationships in category management, and none provide a comprehensive
framework that permits the broad understanding of this
American Marketing Association / Winter 2005
complex issue required by retailers. For example, most
theory and empirical evidence regarding buyer-seller
relationships adopts a dyadic perspective, either focusing
on a single buyer-supplier relationship (e.g., Dyer and
Singh 1998; Jap 1999), or treating each supplier relationship with a common buyer separately (e.g., Subramani
and Venkatraman 2003). Yet, since retailers have more
than one supplier to almost all categories, and prescriptions advocate giving a key supplier significant influence
over retailer category management, the retailer-focal supplier relationship may affect relationships with other
suppliers to the category in ways that impact the retailer
performance. Since these conditions have not been addressed in previous theory development and empirical
research, the literature has little guidance to offer managers facing such situations.
This research contributes to theories of interfirm
relations and competitive advantage and offers guidance
for retailer and supplier managers by developing and
testing a model of opportunism among focal suppliers at
the category-level, its antecedents, and associated performance outcomes. Our research contributes to knowledge
in three areas. First, synthesizing insights gained from
qualitative fieldwork with those available in the literature,
we develop a conceptual model of important antecedents
and consequences of category-level focal supplier opportunism. Second, we test our model using data from 73
category managers representing six grocery retailers across
a representative set of 35 different product-categories to
provide new empirical insights into focal supplier opportunism and its impact on category-level performance. Our
data suggest that focal supplier opportunism decreases
retailer category performance. Consistent with retailer
fears, we find that focal suppliers with significant influence in retailers category management efforts are more
likely to engage in opportunistic behavior. However, our
data also reveal that retailer fears that being dependent on
a focal supplier will lead to greater supplier opportunism
are largely unfounded, while supplier dependence on the
retailer is also unrelated to focal supplier opportunism.
Finally, we find that retailers’ ability to monitor – but not
to punish – its focal suppliers is negatively related to
opportunistic behavior among focal suppliers. Third, our
findings illuminate the important but largely ignored case
in which a buyer relationship with a focal supplier puts
that supplier in a position to directly influence the buyer
relationships with other competing suppliers, who also
continue to supply products to the buyer. From this
perspective, we find that focal supplier opportunism increases militant behaviors among non-focal suppliers to
the category but that these militant behaviors do not
significantly negatively impact retailer category-level
For further information contact:
Neil A. Morgan
Kenan-Flagler Business School
CB# 3490, McColl Building
University of North Carolina at Chapel Hill
Chapel Hill, NC 27599–3490
Phone: 919.962.9835
FAX: 919.962.7186
E-Mail: [email protected]
American Marketing Association / Winter 2005
Andrew K.C. Wong, The Chinese University of Hong Kong, Hong Kong
Consumption experience is subjective, dynamic and
subject to external influences. Consumers may unconsciously color their judgments through the tinted glass of
a priori expectations. Imagine, when we take the first sip
of an award-winning Pauillac wine, or when the long
awaited sequel of an international blockbuster finally
opens, are we immune to the influence of expectations and
let the moment of truth tells the truth?
According to the Disconfirmation Paradigm (Olson
and Dover 1979), satisfaction is determined by the discrepancy between expectation and experience. Treating
and measuring expectation and experience as two independent entities, one can compute the discrepancy by
simple mathematics and determine the dis/satisfaction.
Accordingly the prediction is intuitively appealing: the
higher the expectation, the bigger the disappointment. But
what if the experiential perception is vulnerable to the
magnetic force of expectations? The focus of this paper is
to examine how prior expectations shape subsequence
consumption experience.
Affective Expectation Theory
Olson and Dover (1979) defined expectations as
pretrial beliefs about the product, and belief as a subjective probability of association between a product and an
attribute. Subsequent studies mostly focused on attributebased evaluation (e.g., Deighton 1984; Smith 1993).
While emphasis has long been given to the cognitive side,
the affective side of expectation is under explored.
Not until recently was the affective nature of expectations formally conceptualized and empirically tested.
Wilson and Klaaren (1992) defined affective expectations as “people’s predictions about how they will feel in
a particular situation or toward a specific stimulus” (p. 3).
In the context of consumption, advertising can induce not
only attribute-related expectations, but also the affective
expectations of how a consumer feels during and after
consumption. In accordance with the affective expectation theory, it is possible that even the actual consumption
experience objectively fails to meet a priori expectation,
consumers would still unconsciously surrender to their
own affective expectations such that the discrepancy
between expectation and experience is not noticed. As a
American Marketing Association / Winter 2005
result, disconfirmed experience tends to be assimilated to
the affective expectations, leading to satisfaction.
P1: Ad-induced affective expectations will lead to an
assimilation bias such that negatively disconfirmed
experience will be evaluated in the direction toward
the prior affective expectations, provided that the
discrepancy is not noticed.
Ambiguity Moderates the Effects of Affective Expectations
The assimilation bias of affective expectations is
contingent on the noticeability of the discrepancy (Wilson
et al. 1989). When facing an ambiguous experience,
which is open to multiple interpretations (Herr et al. 1983;
Hoch 2002), a consumer may have difficulty in recognizing the discrepancy, if any. Past research suggested that
ambiguous stimuli tended to be assimilated to contextual
stimuli (Herr et al. 1983; Hoch and Ha 1986; Martin et al.
1990; Schwarz and Bless 1992), providing tentative support to the notion. In the discussion of product attributes,
Hoch and Deighton (1989) related ambiguity to the search,
experience and credence qualities. Information in an ad
highlighting the experience or credence qualities of the
focal product is by default more ambiguous and likely to
induce greater assimilation to affective expectations.
P2: With the presence of affective expectations, an ad
highlighting experience or credence attributes of a
product or service will lead to greater assimilation
bias than does an ad highlighting search attributes.
Ambiguity can be reduced by the presence of a
comparison standard. It is not uncommon that past experience is recalled as a standard to resolve ambiguity. The
retrieval of past experience strongly suggests self-referencing, which occurs “when information is processed by
relating it to aspects of oneself, e.g., one’s own experience” (Burnkrant and Unnava 1995, p. 17). Phillips and
Baumgartner (2002) proposed that affective expectations
could be formed based either on the remembrances of
retrospective consumption-related emotions, or anticipatory visions of future emotions. These two types of selfreferencing attempt are in accordance with the retrospective and anticipatory self-referencing proposed by
Krishnamurthy and Sujan (1999). They defined retrospective self-referencing as anchoring the stimulus to
autobiographical experiences, and anticipatory self-referencing as referencing the stimulus to imagined future
Under retrospective self-referencing, the retrieved
details of a past consumption activated by an ad may serve
as a background against which the actual consumption is
evaluated. Discrepancies, particularly those negative ones
that fall short of the expectations, should be more noticeable and subsequently reduce the assimilation bias or even
lead to a contrast effect (Schwarz and Bless 1992). In the
case of anticipatory self-referencing, the interpretation of
the actual experience should be more “open” and more
likely to be assimilated to the affective expectations. In
summary, the temporal orientation of self-referencing
may either resolve (under retrospective self-referencing)
or enhance (under anticipatory self-referencing) the ambiguity of the experience, and thus moderates how affective expectations influence judgment.
P3: The assimilation bias of affective expectations is
reduced under retrospective self-referencing, but enhanced under anticipatory self-referencing.
For further information contact:
Andrew K.C. Wong
Department of Marketing
The Chinese University of Hong Kong
Shatin, N.T.
Hong Kong
Phone: 852.2609.7808
FAX: 852.2603.5473
E-Mail: [email protected]
American Marketing Association / Winter 2005
Stefânia Ordovás de Almeida, Pontifícia Universidade Católica do Rio Grande do Sul, Brazil
Walter Meucci Nique, Universidade Federal do Rio Grande do Sul, Brazil
The goal of this research is to propose and test a scale
that is suitable to measure the dimensions that compose
the customer delight construct, as well as its behavioral
consequences. Aiming that, three studies were used to
prove the existence of content and construct validity for
the proposed dimensions.
Customer delight can be defined as “an emotion,
characterized by high levels of joy and surprise, felt by a
customer towards a company or its offering (product/
service)” (Kumar 1996, p. 9). Thus, customer delight is
defined as a rather positive emotional state towards the
purchase/consumption experience, generally derived from
the surprisingly positive disconfirmation level of perceived performance (Oliver et al. 1997; Rust and Oliver
2000). Delight would be characterized as an emotion
made up of cognitive and affective aspects, including here
surprise (Kumar 1996). In this sense, Izard (1997) clarifies that even the cognitive concepts inherent in satisfaction and, consequently, in customer delight – such as need
and desire –, and its comparative standards are considered
affective by nature or, at least, as having an affective
Regardless of the great number of academic researches giving prominence to customer satisfaction, the
understanding of what happens to the customer when he/
she experiences something beyond satisfaction during the
post-consumption experience is still incipient. Going beyond satisfaction engenders a deeply positive emotional
state regarding the experience of buying or consuming,
which is known as customer delight. Considering this
scenario, this paper attempts to contribute to the Consumer Behavior literature by proposing a scale that is an
attempt to comprehend and measure the dimensions that
compose the customer delight construct, as well as its
behavioral consequences, and which is also suited to
evaluate different cases of buying or consuming experiences.
With this in mind an exploratory/qualitative research
was carried out, trying to understand the construct and
generate items for the construction of a measurement
scale. Subsequently, a quantitative/descriptive research
was conducted through three studies: the first two aimed
at the fine-tuning of the measures by successively applying the scale to distinctive samples; the third also aimed at
the validation of the scale through the criteria of model
adjustment, unidimensionality, reliability, convergent, and
discriminant validity properly attributed to the instrument. The content validity was a permanent concern
during the study.
Furthermore, this study consists of a theoretical review of the aspects that involve customer delight and the
description of the methodological procedures used in
field research. The explanation regarding the analyses
performed and results found has the purpose of describing
the research findings as a whole, giving a basis for the
discussion that encloses the study.
American Marketing Association / Winter 2005
Notwithstanding the fact that a delighted customer
should be at first satisfied, delight cannot be mistaken for
mere satisfaction. The differentiation basically occurs at
an arousal level of the positive emotional response: at a
low level there lies satisfaction; at a high level, delight
(Oliver and Westbrook 1993). In this sense, previous
studies also determined that pleasure and arousal are part
of intrinsic characteristics of either the goods or the
services experiences. Therefore, both dimensions are
viewed as complementary in the delight formation, considering that pleasure by itself is regarded as a positive
affect of moderate arousal (Mano and Oliver 1993).
Other evidence on the differentiation between satisfaction and delight can be found in the studies of Oliver
and Westbrook (1993). These studies showed that customers who experience high levels of joy and surprise
presented greater indexes of repurchase intention and a
high degree of expectations disconfirmation. Therefore,
the authors empirically confirmed the existence of a
delight state separated from satisfaction. Kumar (1996)
also attributed discriminant validity to the constructs and
concluded that the effects of delight on the repurchase
intentions of individuals are higher and go beyond those
of satisfaction. In this sense, it can be observed that the
differentiation between satisfaction and delight is not
present just at the level of surprisingly positive
disconfirmation experienced, but also at the level of the
positive affect felt by the consumer, including here arousal,
and in the post-consumption behavior generated.
The exploratory/qualitative phase of the scale development process was responsible for the construct domain
delimitation and creation of items. First a bibliographic
investigation was carried out through the analyses of
several studies in the marketing and psychology areas.
After this investigation, 30 consumers were questioned
concerning their highly satisfactory consumption experiences. Subsequently, 20 consumers whose illustrations fit
into the theoretical formulation of the theme were selected
to participate in the in-depth interviews.
The highly positive disconfirmation of expectations
was observed in all respondents’ descriptions as a fundamental point in delight formation. In this sense, surprising
consumption was experienced by all respondents interviewed and was always related to the positive affect. The
possibility of personalization of services as a way of
surprising consumers, as well as the product tailored to
one’s needs and desires, was a reason for the descriptions
of delightful experiences through personalization. Concerning the price perception, six respondents mentioned
this item directly and, often, the positive perception of
price was associated to the positive performance of the
product or service. The intention to buy again and the
tendency towards positive word of mouth were observed
among all respondents.
The measuring items for the scale construction come
from different sources. The ones responsible for the
positive surprise measurement were taken from the Differential Emotions Scale – DESII by Izard (1977). The
items used to measure the other dimensions were mainly
adapted from the studies of Kumar (1996), Oliver et al.
(1997) and Rust and Oliver (2000), with the grounding of
the in-depth interviews. These items were submitted to a
Portuguese version process. Once the version was finished, two marketing academics evaluated its comprehension. Therefore, three marketing experts analyzed the
items defined for the scale and suggested improvements.
Thus, 40 items formed the first version of the built scale
through five broad dimensions: cognitive aspects, affective aspects, positive surprise, price perception and postpurchase evaluation.
The descriptive phase of the delight scale development began with a pre-test of the instrument done with 10
people from the same study population. With the objective of testing, purifying and validating the scale, three
American Marketing Association / Winter 2005
different samples of the same population were used.
Undergraduates from business schools of three different
universities in Brazil formed the population. The first and
second samples, which were used only for scale finetuning, had 146 and 124 respondents respectively; the
third, which should also be submitted to validation, had
240 respondents. Regarding the samplings, it was verified
that a rate of 81 percent of the respondents in the first
study, 92 percent and 71 percent in the second and third
studies respectively, analyzed experiences with goods,
while the others did so with services.
The procedures used for testing and fine-tuning the
scale were based on the propositions made by DeVellis
(1991), in which the exploratory factorial analysis (EFA),
the communalities of the items – accepted at 0.5 (Evrard
2002); the measure of the reliability through Cronbach’s
Alpha – accepted at 0.6 (Evrad 2002); the item-item
correlation – minimum of 0.5 (Evrard 2002) and the itemtotal correlation – maximum of 0.80 (Kline 1998) were
taken into account, apart from the basic descriptive measurements. The software used here was SPSS 10.0. In
addition, following the recommendations of Hair et al.
(1998), unvaried outliers were examined through the Z
coefficient test and only in the third data collection the
necessity of withdrawing eight outliers from the sample
Data Collection and Measurement Scale
Data collection was carried out throughout March
and May/2003 by the researcher in the classrooms, and
respondents filled out the questionnaires by themselves.
The recommendation given to the participants when answering the questionnaire was to take into account a
highly satisfactory consumption experience that they had
gone through, considering the study focus. As a measurement scale, a 7-point Liket scale was used, where point
one represented the “totally disagree” assertive, and point
7 a “totally agree” assertive. Items indicating high agreement represented a higher tendency to delight.
Aiming at the proposed scale validation, two procedures were carried out: the content validity and construct
validity, both suggested by DeVellis (1991). The content
validity was achieved by logical analysis. The construct
validation was done using the AMOS 4.0. software.
Besides the validation process, the inexistence of multivariate outliers (measured by the Mahalanobis D² distance) was confirmed. Small problems of normality were
also verified and eliminated, according to the principles
suggested by Kline (1998). The results of the scale development process and its later validation are presented
The first scale version, applied to the first sample and
submitted to EFA, indicated nine factors responsible for
representing 67.32 percent of total variance explained.
The results of the EFA, after some gatherings were done
to regroup variables that were isolated or misallocated
based on their conceptual coherence and their factorial
loadings (Evrard 2002), are presented in Table 1 through
the factorial loadings of the items and their communalities.
With the reliability and correlation analyses done,
considering the EFA results, it was decided that some
variables needed to be removed. The variables and the
factor they belong to are: Factor 1: V4, V5, V10. Factor 2:
V18, V26. Factor 5: V6, V9, V36. Factor 6: V27. Since the
standardization measured through item V18 was not being well comprehended in its relation to delight, a new
item called “I received personalized service/good” was
inserted with the same variable code for the second study.
The Cronbach’s Alpha for the factors after the modifications were: Factor 1: 0,9303; Factor 2: 0.8542; Factor 3:
0.8125; Factor 4: 0.8343; Factors 5: no items left; Factor
6: only one item left; Factor 7: 0.5164. After all these
procedures, a new EFA was done and no items presented
values lower than 0.5.
The adjusted factorial composition of the second
study showed five dimensions and a total variance explained of 67.19 percent was presented, with a KMO
value of 0.861. Only one factor, represented by items V37,
V38, and V39, presented improper solutions in the analysis performed, with a Cronbach’s Alpha of 0.3848, and
improper correlations. In this way, variable V37 was
rewritten as “the price of this service/good spurred me to
buy,” and variable V38 was excluded for being prone to
dubious interpretations. Apart from that, no other changes
were made in the scale related to the previous study.
The third sampling pointed to a factorial structure
composed of six dimensions, responsible for a total variance explained of 64.52 percent and a KMO measure
value of 0.874. For the results analysis, the EFA was
initially conducted and its results were compared to those
from the internal consistency and item-item/item-total
correlation analysis, running all the procedures again each
time a variable was removed. Thus, at the end of all
analyses employed, the rejection of the following items
was performed: V40, V35, V17, V34, V13, and V16.
American Marketing Association / Winter 2005
The items related to the price perception measurement were not widely supported in the literature and they
were inserted in the analysis for their constant appearance
throughout the in-depth interviews. The observation of its
low adherence to the scale and, consequently, to the
studied construct, led us to the belief that price perception
was not correlated to the presence of delight. Consequently, the necessity of rewriting the statements on price
was brought up from the moment of the first data collection – along with the bad indexes that also indicated the
minor correlation of price factors with the construct.
Therefore, despite the fact that the final price factor
(variables V37 and V39) had presented in the latter study
a Cronbach’s Alpha of 0.6996 and an item-total correlation of 0.5381, the elimination of the factor was applied
for the theoretical motives explained above.
With the removal of the price perception factor, a new
EFA was run and the final factorial structure presented
five factors. Items V20 and V18 were presented alone
under one factor that was called personalization dimension. According to Kumar’s (1996) study personalization
is a feeling that can be associated both to satisfaction and
delight. Furthermore, he points out that this appraisal is
diagnostic and a significant predictor of delight. Personalization is, most of the time, related to unexpected extras
provided by the employees to tailor the offer to customer
needs. In this sense, higher levels of personalization make
the customer feel that the company cares about him,
leading to delight (Kumar 1996). The final factorial structure of the scale to be validated, covering a total variance
explained of 68.71 percent, followed by its communalities, means and standard deviations is presented in Table 2.
When analyzing the descriptive measures here presented, the existence of high standard deviations was
detected. The comprehension for those values came though
the employment of an ANOVA among consumers of
services and goods that corroborated the existence of
statistically significant differences in the groups’ means
for 16 of the 23 analyzed variables. In these cases, the
consumers of services always had the highest means.
Thus, the scale observed in Table 2 is the one presented for validation, being composed of 23 items, divided into five factors. The dimensions that compose
customer delight and its behavioral consequences are
described below, along with their respective Cronbach’s
Alpha values: Factor1 – Affective Aspects Dimension
(0.9179); Factor 2 – Cognitive Aspects Dimension
(0.8497); Factor 3 – Post-consumption Evaluation Dimension (0.7735); Factor 4 – Positive Surprise Dimension (0.7725) and Factor 5 – Personalization Dimension
(0.7830). As a result, the validation process of the proposed scale is demonstrated below.
First Study Initial Factorial Structure
Factor 1 – Items
This experience brought me happiness
This service/good transmitted positive feelings to me
This was a stimulating experience
This experience brought personal satisfaction to me
This was an irresistible experience to me
This experience brought me pleasure
This experience brought me joy
This experience was fascinating
I felt fulfilled with this consumption experience
This experience was attractive to me
This service/good made a dream come true
This experience made me feel special
I personally I identify myself with this service/good
This experience made me feel important
This consumption experience was one of the most important I have ever had
Factor 2 – Items
This service/good had an exceptional performance
This consumption experience completely satisfied my desires
This experience surpassed all my expectations
I received personalized assistance
The quality of the service/goods is superior to that of others
In this experience all the attributes that could be satisfactory were more than satisfactory
This service/good had great value to me
I received standard service/goods
I received more than is expected in this consumption experience
Factor 3 – Items
I was positively amazed with this experience of consumption
I was positively astounded with this consumption experience
I was positively surprised with this consumption experience
Factor 4 – Items
I intend to repurchase this service/good in the future
I would recommend this service/good to a friend
After this consumption experience I felt like complimenting the company/ employee
I am likely to make positive remarks about this service/good to other people
I am the most loyal customer after this experience
Factor 5 – Items
If I had not bought this service/good, I would have felt frustrated
I consider having a connection with the company whose service/goods I bought
This service/good was made to order for me
Factor 6 – Items Loa. Com.
The price was a decisive variable within the choice of this service/good
There was flexibility so as to assist my necessities in this consumption experience
Factor 7 – Items
Regarding my purchase potential, the price of this service/good is too high
The price of this service/good influenced my level of satisfaction towards the
consumption experience
I believe I have paid a fair price for this service/good.
Extraction Method: Principal Component Analysis with VARIMAX Rotation
Source: Data Collection
Kaiser-Meyer-Olkin Measure (KMO): 0.862
Bartlett’s Test of Sphericity 1911.087 – sig. = 0.000
American Marketing Association / Winter 2005
Third Study Final Factorial Structure
Factor 1 – Affective Aspects
This experience brought me joy
This was a stimulating experience
This service/good transmitted positive feelings to me
This experience brought me pleasure
This experience brought me happiness
I felt fulfilled with this consumption experience
This experience brought me personal satisfaction
This service/good had great value to me
This experience was fascinating
This experience made me feel important
Factor 2 – Cognitive Aspects
This service/good had an exceptional performance
The quality of the service/goods is superior to that of others
This consumption experience completely satisfied my desires
In this experience all the attributes that could be satisfactory
were more than satisfactory
This experience surpassed all my expectations
Factor 3 – Post-Consumption Evaluation
I would recommend this service/good to a friend
I intend to repurchase this service/good in the future
I am likely to make positive remarks about this service/good
to other people
Factor 4 – Positive Surprise
I was positively amazed with this experience of consumption
I was positively astounded with this consumption experience
I was positively surprised with this consumption experience
Factor 5 – Personalization
I received personalized assistance
I received personalized service/good
Extraction Method: Principal Component Analysis with VARIMAX Rotation
Source: Data Collection
Kaiser-Meyer-Olkin Measure (KMO): 0.887
Bartlett’s Test of Sphericity: 3105.668 – sig.= 0.000
Note: Although the load of V28 is rather low, it was decided that this variable should be maintained, since otherwise
we would have a factor with only two variables, which is not recommended in the validation process. Furthermore,
this three-item factor had already been proposed and validated by Izard (1977), as well as used in many studies before
this one, proving its reliability.
Since the content validity was already achieved
through the methodological accuracy employed in the
development phases and in the scale fine-tuning, clearly
specified in the study method, with the aim of verifying
the construct validity, the five-scale dimensions were
submitted as five different measurement models to the
confirmatory factor analysis (CFA). This method is widely
applied in marketing studies, as well as correlated fields,
in the search for the construct validity (Bagozzi et al.
American Marketing Association / Winter 2005
1991; Garver and Mentzer 1999; Jöreskog and Sörbom
1982; Steenkamp and Trijp 1991). In these circumstances,
these authors recommend the necessary procedures to
achieve construct validity as unidimensionality, reliability, convergent and discriminant validity, besides the
measurement models adjustment criterion. Table 3 shows
the CFA results for the five-scale dimensions.
Analyzing the fit-indexes, one can detect that most of
the measures are satisfactory. The χ2/df for the personalization dimension is higher than expected, but the probability of the qui-square being influenced by the sample
Results of CFA for the Five-Scale Dimensions
Chi-square (χ
Degrees of freedom (GL)
Chi-square/degrees of freedom (χ
Goodness-of-fit Index (GFI)
Adjusted Goodness-of-fit Index (AGFI)
Tucker-Lewis Index (TLI)
Comparative Fit Index (CFI)
Root Mean Square Error of
Approximation (RMSEA)
Estimation Method: Maximum Likelihood
size is well known and discussed in the literature (Hair
et al. 1998; Kline 1998). Therefore, Raykov and
Marcoulides (2000) recommend that other fit-indexes
should be analyzed, so that a real idea on the model
adjustment can be reached.
When analyzing the measures of the indexes GFI,
AGFI, TLI, and CFI, it can be noted that their values were
always higher than 0.90, which is in agreement with the
recommendations of Hair et al. (1998) and Kline (1998).
The adjustment measure RSMEA possesses acceptable
values ranging between 0.05 and 0.08 (Hair et al. 1998).
Analyzing the data mentioned in Table 3, one can observe
that the dimensions of post-purchase evaluation, positive
surprise and personalization presented values that exceeded the acceptability for the referred index. According
to Raykov and Marcoudiles (2000), this index shares the
same theoretical nature of the CFI. Thus, due to the high
values of the CFI obtained in the analysed dimensions,
these measures were considered validated as well.
After presenting the criteria that led to the conclusion
that all the dimensions of the proposed scale are fit and
validated, unidimensionality was pursued and achieved
through the examination of standardized residues proposed by Garver and Mentzer (1999), Jöreskog and Sörbom
(1988), and Steenkamp and Trijp (1991). According to the
authors, in order to present unidimensionality, a dimension should have all its standardized residuals lower than
2.58. The highest standardized residual score found in the
study was 2.049 in the personalization dimension, therefore, all dimensions may be considered unidimensional.
According to Garver and Mentzer (1999) a reliable
measurement model – in this case a reliable dimension –
should present a composite reliability (CR) over 0.7 and
American Marketing Association / Winter 2005
Cognition Post-Purchase Surprise
Source: Data Collection
an average variance extracted (AVE) over 0.5. By analyzing the reliability of the five dimensions, we could affirm
that all the measurement models are reliable. Thus, the
affective dimension presented CR = 0.9749 and AVE =
0.6880, the cognitive dimension presented CR = 0.9609
and AVE = 0.6296, the post-consumption evaluation
dimension presented CR = 0.9672 and AVE = 0.6887, the
positive surprise dimension presented CR = 0.9695 and
AVE = 0.7121, and the personalization dimension presented CR = 0.9648 and AVE = 0.6406.
For Garver and Mentzer (1999) and Bagozzi et al.
(1991), the convergent validity of a scale is given by the
quality of its fit-indexes. Besides all the scale dimensions
having been validated through the examination of their
fit-indexes, the factor regression coefficients were also
verified to certify the convergent validity. All the factor
regression coefficients were statistically significant, which,
according to Bagozzi et al. (1991), means that t-values are
higher than |2,00| for p < 0.05 (7.86 was the lowest t-value
found in the study). As a strong condition for convergent
validity, Steenkamp and Trijp (1991) suggest that all the
factor regression coefficients should exceed 0.5. This
condition was also achieved, since 0.591 was the lowest
value found.
As a final procedure, so as to infer construct validity,
the discriminant validity was verified through the method
proposed by Fornell and Larcker (1981). This method
proposes that the average variance extracted for each
dimension should be higher than the squared correlation
between this dimension and any other dimension, which
characterizes the shared variance. For the studied construct – customer delight and its behavioral consequences –
discriminant validity was detected among the dimensions.
This can be observed by the values of the average variance
extracted for these dimensions: 0.6880 for the affective
aspects, 0.6296 for the cognitive aspects, 0.6880 for the
post-purchase evaluation, 0.7122 for the positive surprise
and 0.6406 for the personalization dimension. These
values were by far higher than the highest value found for
the shared variances among dimensions (0.3600). The
following discussion comments all these results.
The scale construction and test practiced in this study
meet the demand of developing a greater theoretical
comprehension on customer delight. Within this context,
the first evidence on the study can be described as a
measure purification relevance, through a successive scale
reapplication; for only the empirical evidence can prove
that some items, or even entire dimensions, such as price
perception, did not belong to the construct. Hence, an
implication for the marketing academy is demonstrated in
the confirmation of the dimensions that compose the
customer delight construct and its behavioral consequences. This evidence was achieved through the favorable fit-indexes of the models and the confirmation of
unidimensionality, reliability and validity for the proposed scale in all analyzed dimensions, which confirms its
construct validity.
The content validity was also achieved, by logical
analysis, because of the quality of the scale measurement
items, accessed by the exploratory/qualitative research,
which was done before the scale construction, and also by
the successive fine-tunings. Yet, a scale application with
new contexts and another population is encouraged, supplying the deficiencies that might have come up in this
study, such as the employment of the students’ sample,
concerning the limitations of external validity that result
with this type of sampling.
It’s important to note that although discriminant
validity was established between the dimensions of the
scale proposed, this was not done between delight and its
close relatives, such as joy, as proposed by Oliver et al.
(1997), which suggested a more psychometric specification and differentiation between the called “positive affects.” Therefore, this can be a suggestion for future
studies. The discriminant validity between satisfaction
and delight was not the goal of this study either, as already
established by Kumar (1996). The peditive and nomological validity were not established either, since, to infer this,
it would be necessary to test the whole structural model.
Thus, it remains as a suggestion for the future.
When evaluating the research object used by the
respondents in the three studies, it is observed that the
citation of goods shows supremacy when compared to the
ones of services. Causes for this phenomenon were not yet
American Marketing Association / Winter 2005
found. However, the ANOVA realized in the third study
denotes the existence of statistically significant differences between the means of consumers of goods and
services: the latter group’s means are always statistically
higher. In these circumstances, the importance of the
insertion of a variety of services in goods that are generally standardized must be emphasized, considering the
necessity of variety when one is seeking to deliver an
unexpected pleasant performance (Oliver et al. 1997).
What could be observed from the consumption of goods
is that most of them were symbolic ones, so the need of
personalization was replaced, in these cases, by the congruency of the good with consumer self-concept. Besides
that, these differences are not relevant to the process of
scale development; neither do they show the need for
separated scales to evaluate the consumption of goods and
services. The difference between these consumers lies in
the kind of consumption experience and not in the dimensions analyzed, which pertain to both of them.
Another question to be regarded is the conclusion that
the price perception variables are not a customer delight
dimension. Thus, the perception of a low or fair price is
only part of customer delight when accompanied by other
attributes that also have the capacity of delighting (e.g.,
“these pants fit me perfectly and they were also cheap” –
respondents answered in one in-depth interview). The fact
of being only cheap is not enough to give the pants the
power of delight, it solely satisfies the bargain or equity
item. The presence of delight presumes that the experience possesses other components that might effectively
generate a positive affect and surprise. Therefore, still
maintaining the consideration of the need for new studies
so as to confirm the real accessory role of price in delight
formation, care must be taken when intending to use it as
a way of delighting customers. This observation is important for organizations to perceive that delight should occur
through their differentiated attributes rather than strategies that can be easily copied by their competitors, such as
price promotion (Rust and Oliver 2000).
All things considered, the inclusion of delight, through
the proposed scale, in theoretical models on the postconsumption evaluation process will allow a deeper understanding of the distinct impacts between satisfaction
and customer delight in following behavioral results. The
complete theoretical model test is another step to be taken
towards the comprehension of the existent relations among
the construct dimensions and the verification of which
dimensions have a higher impact on subsequent behaviors. Furthermore, other relations that search for a greater
comprehension of the role of customer delight in the postconsumption evaluation should be empirically verified,
pursuing a wider vision of customer delight as a highly
positive emotional result to the experience of consumption.
Bagozzi, Richard P., Youja Yi, and Lynn W. Philips
(1991), “Assessing Construct Validity in Organizational Research,” Administrative Science Quarterly,
36, 421–58.
Devellis, R.F. (1991), Scale Development: Theory and
Aplications. Newbury Park: Sage.
Evrard, Yves (2002), “Instrumentos de Pesquisa, Coleta
e Análise de Dados,” class material, Business School,
Federal University of Rio Grande do Sul/Brazil.
Fornell, Claes and David F. Larcker (1981), “Evaluating
Structural Equation Models with Unobservable Variables and Measurement Error,” Journal of Marketing
Research, 18 (February), 39–50.
Garver, Michael S. and John T. Mentzer (1999), “Logistics Research Methods: Employing Structural Equation Modeling to Test for Construct Validity,” Journal of Business Logistics, 20 (1), 33–57.
Hair, J.F.J., R.E. Anderson, R.L. Tatham, and W.C. Black
(1988), Multivariate Data Analysis. New Jersey,
EUA: Prentice Hall.
Izard, Carroll E. (1977), Human Emotions. New York:
Jöreskog, Karl G. and Dag Sörbom (1982), “Recent
Developments in Structural Equation Modeling,”
Journal of Marketing Research, 19 (November),
Kline, Rex B. (1998), Principles and Practice of Structural Equation Modeling. New York: The Guilford
Kumar, Anand (1996), Customer Delight: Creating and
Maintaining Competitive Advantage. Doctoral dissertation, Graduate Faculty, Indiana University.
Mano, Haim and Richard L. Oliver (1993), “Assessing the
Dimensionality and Structure of Consumption Experience: Evaluation, Feeling and Satisfaction,” Journal of Consumer Research, 20 (December), 451–66.
Oliver, Richard L. and Robert A. Westbrook (1993),
“Profiles of Consumer Emotions and Satisfaction in
Ownership and Usage,” Journal of Consumer Satisfaction, Dissatisfaction, and Complaining Behavior,
6, 12–27.
____________, Roland T. Rust, and Sajeev Varki (1997),
“Customer Delight: Foundations, Findings, and Managerial Insight,” Journal of Retailing, 73 (3), 311–36.
Raykov, Tenko and George A. Marcoulides (2000), A
First Course in Structural Equation Modeling. New
Jersey: Lawrence Erlbaum Associates.
Rust, Roland T. and Richard L. Oliver (2000), “Should
We Delight the Customer?” Journal of the Academy
of Marketing Science, 28 (1), 86–94.
Steenkamp, Jan-Benedict E.M. and Hans C.M. Trijp
(1991), “The Use of LISREL in Validating Marketing Constructs,” International Journal of Research
in Marketing, 8, 283–99.
For further information contact:
Stefânia Ordovás de Almeida
Faculdade dos Imigrantes/Pontifícia Universidade Católica do Rio Grande do Sul
Afonso Taunay 180/605
Porto Alegre/RS
Brazil 90520–540
E-Mail: [email protected]
American Marketing Association / Winter 2005
Vincent-Wayne Mitchell, City University of London, United Kingdom
Gianfranco Walsh, University of Strathclyde in Glasgow, United Kingdom
In 2004, the worldwide Internet population amounted
to 945 million and projections for 2005 put this at 1.1
billion ( 2004a). However, this growing number of consumers is presented with overwhelming amounts
of online information and websites and the pace of technological development is faster than some consumers can
adapt to. Recent authors have suggested that hyper-choice
confuses people, increases regret, is initially attractive but
ultimately unsatisfying and is psychologically draining
(Mick, Broniarczyk, and Haidt 2004). Such confusion can
affect attitudes toward online-shopping and make consumers; dissatisfied, less brand loyal, less trusting, postpone purchases, and shop offline (Walsh et al. 2002). It is
surprising then that so little research has addressed the
specific issue of consumer confusion on the Internet and
its effects on consumers. The aim of this research then is
to develop a conceptual model of e-confusion and to
explore some of its antecedents and consequences using a
cognitive, affective and behavioral framework.
Our framework extends that of Walsh et al. (2004)
who suggest confusion can be caused by too similar, too
many or unclear stimuli. Websites that look and feel
similar and give visual cues and/or brand appearance of a
“look-a-like” or “fake” website can cause consumers to
believe mistakenly, for example, that website A is the
same as website B. The website,,
offers many cases of Web design piracy. Consumers can
feel unclarity e-confusion when they encounter ambiguous, incongruous, misleading or inadequate Internet information. For example, Mobile phone sites (e.g., can make prices difficult to understand and workout. Overload e-confusion antecedents can
occur when consumers are confronted with more productrelated e-information than can be processed in the shortterm memory. A good example of e-information overload
is the often uncategorized results of search engines. Individual characteristics exert an influence on e-confusion
because they are often linked to the consumer’s ability to
rationalize and process stimuli. For example, age may
reduce e-confusion through an Internet experience framework or may increase e-confusion as processing competence decreases with the ageing process. Field independent individuals impose organization upon visual stimuli,
and are able to locate a sought-after component. The
American Marketing Association / Winter 2005
ability to better organize visual stimuli makes field independent consumers less likely to experience e-confusion
from overload and unclarity antecedents. Situational variables, such as using the Internet under time constraints,
can lead to rushed decision-making, shortened information-processing and inference-making time which is expected to increase e-confusion because of decreased processing time.
When e-confused, consumers attempt to understand
who they will attribute responsibility for the confusion
and can either blame themselves or others for the confusion. We suggest that attribution serves as a moderator of
the confusion-outcome link. We propose that the immediate effect of all e-confusion is indecisiveness and hesitation resulting in the consumer either doing nothing or
postponing their web activity. We conceptualize e-confusion as a temporary state of disorientation which has
feelings associated with it. These affective consequences
represent an individual’s feelings and emotions in relation
to their evaluation of the website such as frustration,
irritation, anxiety, or even anger. Cognitive consequences
refer to consumers’ knowledge and beliefs about a website.
Consumers may form erroneous beliefs about the website
which can affect trust, satisfaction and loyalty. Behavioral
consequences represent consumers’ behavioral intentions
or tendencies, or actual overt actions toward the website.
We divide behavioral consequences into two types; (1)
Generic, i.e., those which are generic to e-confusion and
(2) Specific, i.e., those which are specific to the antecedents causing e-confusion. E-companies need to learn how
to identify and eliminate sources of confusion on their
websites and could reduce confusion sources by doing a
confusion audit of their websites. From a regulation
perspective, more governmental and private monitoring
of the web might help to reduce the numbers of copycat
website and cyber squatting which will reduce sources of
similarity-induced e-confusion. Better e-mail filtering
systems will obviously help, but it may be time for the
establishment of a government sponsored e-mail preference service (EPS), to which all organizations should
subscribe. Our main contribution to theory lies in developing a model of consumer e-confusion. Future research
should include the development of a measurement instrument and subsequent testing of the conceptual model and
hypothesized relationships. References are available upon
For further information contact:
Vincent-Wayne Mitchell
Cass Business School
City University of London
106 Bunhill Row
Phone: +
FAX: +
E-Mail: [email protected]
American Marketing Association / Winter 2005
Frederick Hong-Kit Yim, Drexel University, Philadelphia
ers” is more strongly related to value perceived by consumers.
As a new paradigm in marketing, CRM is in need of
theoretical assistance (Gummesson 2002). Much, if not
most, of the research on CRM has tended to focus on its
favorable performance metrics such as sales growth.
There is scant research effort directed at examining the
differential impacts of CRM dimensions on delivering
consumer value. In particular, there is no attempt to look
into the mechanism of how customer loyalty can be
nurtured via value, satisfaction, and trust in CRM projects.
Notwithstanding some disappointing CRM results,
we believe that the early failures of CRM are not perennial
and CRM movements are not expected to terminate (Sheth
2002). A sharper theoretical understanding of CRM can
effectively advance future CRM endeavors and successfully breed outstanding firm performance. To avoid the
premature death of the CRM discipline (Fournier, Dobscha,
and Mick 1998), this study seeks to advance the CRM
literature by examining how the CRM dimensions differentially impact consumer value. In particular, CRM is
conceptualized to have four distinct behavioral dimensions, namely, (1) focusing on key customers, (2) organizing around CRM, (3) managing knowledge, and (4) leveraging information technology (Yim 2002). We posit that
when compared with other CRM dimensions of “organizing around CRM,” “managing knowledge,” and “leveraging information technology,” “focusing on key custom-
Moreover, drawing from the diverse research on
relational exchanges (e.g., Garbarino and Johnson 1999;
Nijssen et al. 2003; Sirdeshmukh, Singh, and Sabol 2002),
a comprehensive theoretical framework for understanding how consumer loyalty can be achieved through value,
satisfaction, and trust in the CRM context is developed.
Specifically, we postulate that value perceived by consumers is positively related to satisfaction with the service
firm, which, in turn, is positively related to trust in the
service firm. We further posit that trust in the service firm
is positively related to loyalty to the service firm.
In conclusion, in response to the call for more theoretical assistance for CRM (Gummesson 2002), our research contributes to the marketing discipline both theoretically and managerially. Theoretically, it advances the
CRM literature by explicating how a number of exchange-relevant constructs are related, and sheds light on
how organizational CRM efforts differentially impact
value perceived by consumers in a service setting. As far
as managerial implications are concerned, managers are
afforded the broad picture of how loyalty can be grown via
a number of consumer response constructs, and therefore
inculcated the effective way to direct their CRM efforts in
terms of delivering value to their key consumers.
For further information contact:
Frederick Hong-Kit Yim
Bennett S. LeBow College of Business
Drexel University
32nd and Chestnut Streets
Philadelphia, PA 19104
Phone: 215.990.9129 or 215.895.2145
FAX: 215.895.6975
E-Mail: [email protected]
American Marketing Association / Winter 2005
Christopher P. Blocker, University of Tennessee, Knoxville1
Evidence shows relational strategies can prove successful in some cases but are costly and ineffective in
others. Yet, understanding favorable conditions for a
relational over an arm’s length approach is still emerging.
One area that holds promise for shedding light on this
issue is buyer-seller mismatches, as they occur when firms
strive for dissimilar goals and relate in incompatible ways.
This paper draws focus to this concept by integrating the
literature and exploring the complexity of buyer-seller
Building strategic buyer-seller relationships that are
marked by long-term, close dealings has captured the
attention of firms and researchers alike (Day 2000). Given
the substantial resources firms invest to make relationships work, it is unsettling to find a significant number of
relationships end in failure (Das and Teng 2000; Wathne,
Biong, and Heide 2001). One leading scholar posits that
“some firms lose half or more of their customers every
three years, and the worst is still to come” (Day 2000,
p. 25). These are difficult realities considering the abundance of research performed in relationship marketing
over the past two decades.
In view of these realities, research in business-tobusiness relationships shows a noticeable movement from
enthusiasm that included declarations of a new paradigm
(Gronroos 1994) and a fundamental re-shaping of the
field (Webster 1992), to a dampened realization that
relationship strategies are not universally applicable or
painless to implement (Day 2000). For example, many
firms make significant investments in technologies (e.g.,
CRM) promising greater customer retention and loyalty,
but the large majority fail to realize the anticipated return
(Newell 2003). Additionally, researchers historically have
argued for suppliers to shift customer interaction from a
transactional mode to a relationship building mode (Kotler 1991; Webster 1992). Regrettably, this approach has
influenced some firms to attempt partnering initiatives
without respect to the other party’s fit or desire (Day 2000;
Garbarino and Johnson 1999).
Recently, researchers have urged firms to pull back
the reins on relationship strategies, in favor of plural
strategies blending relational and transactional approach-
American Marketing Association / Winter 2005
es relative to the situation (Coviello et al. 2002). However,
research is still seeking to build theory that can prescribe
targeted relationship strategies to firms as they interact
with diverse sets of customers in various situations
(Siguaw, Baker, and Simpson 2003). Existing efforts to
address this issue take several approaches, including:
identifying relationship-relevant dimensions on a continuum (Anderson and Narus 1991; Webster 1992), mapping product market types to relational strategies (Coviello et al. 2002), analyzing relationships with ROI (Gummesson 2004), and identifying profitable customers (Reinartz and Kumar 2003). For the most part, these approaches take a seller’s one-sided viewpoint. Unfortunately, key questions of whether the other party desires a
relationship – or perhaps more important – whether a
“close relationship” means the same thing to both parties
are largely left unaddressed.
Additionally, some have used the concept of buyerseller mismatches – specified as a mismatch in relationship goals – to provide greater explanation into why
relationships might succeed or fail (Gronroos 1997; Pels,
Coviello, and Brodie 2000). This approach has at least two
key advantages. First, assessing mismatches requires a
dyadic perspective. Knowing only one party’s intentions
and goals is not enough. Second, mismatch considerations give priority not only to stable characteristics of
each party but also to situations that might significantly
influence relationship outcomes. If firms can understand
possible mismatches up front, before investing significant
resources, there is potential to drive down the rate of
relationship failure, and thus, risks associated with sunk
costs and missed opportunities elsewhere.
Use of buyer-seller mismatches as a specified construct in relationship research is infrequent. However, the
concept is inherent in much of the literature that, for
example, discusses mismatches in relationship values,
social mismatches leading to relationship failure, and
relationship dysfunctions, to name a few. In general,
research questioning the appropriateness of relationships
in light of potential incompatibilities supports the idea of
mismatches (Colgate and Danaher 2000). However, mismatch research thus far oversimplifies the phenomenon.
Existing research points solely to a single match or mismatch from a global view of the relationship. At this
aggregate level, there is little appreciation for the complexity of business exchanges, wherein a variety of mismatched goals might occur at different levels of the
relationship. This leads to several questions such as: What
types of mismatches are common across various ongoing
exchanges? Which ones significantly impact the relationship as a whole? When should a mismatch be overlooked
versus deemed insurmountable? Given these questions
and current difficulties that business relationships face, a
deeper look is warranted.
A more granular understanding of the buyer-seller
mismatch phenomenon could provide additional insight
into understanding why relationships succeed or fail.
Thus, a primary question needing further development is
this: how might a deeper look into the nature of mismatches expand upon previous conceptions of relationship incompatibility and provide a clearer window into
the true complexity of buyer-seller relationships?
Developing buyer-seller relationships has been recognized by firms as an integral component to overall
strategy for many years (Cannon and Perreault 1999).
Specifically, firms now see customer retention and management of relationships as a key to fending off rivals,
who constantly seek to attract customers away (Day
2000). From a financial perspective, managers covet the
performance gains that research suggests can be achieved
through retention (Noordewier, John, and Nevin 1990).
Furthermore, market drivers such as elimination of middlemen, global competition, technological innovation, and
supply-chain coordination provide both the motive and
means for fostering close relations (Sheth and Parvatiyar
Alongside the flurry of relationship activity in the
business community, a rich tradition of research has
supported the surge of interest in buyer-seller relationships. Early works observed business relationships diverging from transactional models towards long-term
associations (Arndt 1979). Research streams have since
examined traits like trust and commitment (Gundlach,
Achrol, and Mentzer 1995), dependence (Heide and John
1990), and potential performance outcomes (Kalwani and
Narayandas 1995). Generally, one could argue that the
most significant progress thus far has been exploring a
wide selection of relationship-relevant constructs. These
constructs serve as key variables in the process of developing and maintaining relationships.
Upon examining the development of buyer-seller
relationships, at least three themes emerge. First, an overwhelming bulk of research has sought to explain how
good relationships are built. Second, researchers have
given a great deal of attention to linking relationships to
positive outcomes such as lower costs (Noordewier, John,
and Nevin 1990), greater control (Dwyer, Schurr, and Oh
American Marketing Association / Winter 2005
1987), satisfaction (Berry and Parasuraman 1991), and
profitability (Kalwani and Narayandas 1995). The main
thrust of research to date generally assumes that firms
should be in the process of shifting from arm’s length
dealings to building close relationships (Colgate and
Danaher 2000). Finally, research generally takes a seller’s
“push” perspective in attempting to retain customers,
erect switching barriers, and build profitability.
Despite substantial attention directed towards developing buyer-seller relationships, current signs point to
instability in relationships, continued customer attrition,
and termination of partnerships (Wathne, Biong, and
Heide 2001). Blatant drawbacks to the relationship approach have drawn criticism including potential for: hidden costs, negative return on investment (Gummesson
1997), and other negative outcomes. Further, despite the
popularity of relationship strategies, many firms continue
to rely on competitive, transactional dealings (Cannon
and Perreault 1999). One key learning from this discussion is the realization that, prior to embarking upon
relationship strategies, greater consideration should be
given to the resources needed and potential risks. Doing
so might prevent wasted resources, and ultimately, messy
relationship failures. So, while the potential benefits of
relationships are clear, the net recommendation is for
firms to pursue plural strategies that employ both transactional and relational approaches relative to varying situations, customers, and environments (Frazier 1999;
Garbarino and Johnson 1999).
However, this shift is not easily accomplished. Many
agree that existing theory is not sensitive to situational
factors (Wilson 2000). Beyond this, it rarely allows for a
much needed dyadic perspective. Though a supplier might
see a particular customer as ripe for relationship building,
the customer may not be responsive. Even more complex,
both parties might agree in principle but simply view
relationships in different ways. A supplier may believe a
strong relationship is one that is exclusive. Yet, the respective customer might feel it is simply good business
practice to keep suppliers “on their toes” by engaging
competitors. The next evolution, then, of buyer-seller
theory should adequately address these variations and
develop theory around the issue of with whom firms
should build relationships in given situations.
The term mismatch in business relationships was first
used by Pels, Coviello, and Brodie (2000), who sought to
integrate transactional and relational strategies into a
plural approach. They posit that buyers and sellers often
operate under mismatched exchange orientations. Exchange orientations, they theorize, are overarching ways
of dealing with another party and arise from specific
relationship needs. In other words, relationship needs
give rise to a party’s pursuit of either transactional or
relational dealings. Thus, a mismatch of exchange orientation occurs when one party elects a transactional mode
and the other operates under a relational mode.
Similarly, Gronroos (1997) asserted that customers
operate in one of three modes: a transactional mode, a
passive relational mode, or an active relational mode.
Mapping these customer modes to a seller’s relational or
transactional approach, he argues that dollars spent by
sellers in relationships where modes do not match are
wasted efforts. These two perspectives provide a baseline
understanding of buyer-seller mismatches and are illustratively condensed into Figure 1. This figure serves as an
overarching picture of the phenomenon, yet does not
distinguish the reality that many mismatches can occur at
different levels in a relationship. One other comparable
example to note is the work of Gassenheimer, Houston,
and Davis (1998), who introduce the notion of relative
relational distance. They theorize that social and economic value discrepancies between parties create relational distance. The result of this distance is that parties
evaluate social and economic value discrepancies by a
comparison of alternatives and subsequently decide to
tolerate the differences or exit the relationship. While this
perspective is dyadic, relational distance is modeled as a
“summary disposition” (p. 335) and does not attend to the
specific discrepancies that occur across a variety of ongoing exchanges.
In addition to these examples, the concept of buyerseller mismatches can be traced from a variety of sources
such as mismatches in relationship values, mismatches of
relationship desire, behavioral and social mismatches
leading to relationship failures, and relationship dysfunctions, to name a few (Table 1). In reviewing this literature,
several concepts emerge. For one, the discussion on
mismatches and related topics has occurred as an afterthought to the excitement around building relationships.
This might be attributed to a realization in the last decade
that many relationships fail because of relationship mismatches. Additionally, up to this point, research addressing mismatches has limited itself to high-level descriptions of the phenomenon and has not explored integrative
connections to the extant literature on relationships.
Although the concept of mismatches has been discussed both explicitly and implicitly in relationship literature, no formal definition has been offered. This work
seeks to expand upon previous perspectives (Gronroos
1997; Pels, Coviello, and Brodie 2000) of buyer-seller
mismatches and integrate ideas from literature that speaks
Buyer-Seller Mismatches
Buyer Exchange Paradigm
Seller Exchange
American Marketing Association / Winter 2005
American Marketing Association / Winter 2005
The Concept of Mismatches in Relationship Literature
Topic As It Relates to Mismatch
What Is Specifically Mismatched?
Illustrative Author(s)
1. Mismatch of Exchange Orientation
– Seller’s Exchange Orientation vs. Buyer's Exchange Orientation
– Seller’s Offer and Buyer's Need
– Gronoos 1997; Pels, Coviello, and Brodie 2000
2. Mismatch of Desire for Relationship
– Seller’s Motivation for Relationship vs. Buyer's Motivation for Relationship
– Barnes 1997; Day 1994;Garbarino and Johnson 1999;
Sollner 1999
3. Mismatch of Relationship Values
– Seller’s Values vs. Buyer’s Values
– Gassenheimer, Houston, and DAvis 1998
4. Behavioral or Social Mismatch
Leading to Relationship Failure
Seller’s Relationship Investment vs. Buyer’s Relationship Investment
Seller’s Time Orientation vs. Buyer's Time Orientation
Seller’s Collaborative Orientation vs. Buyer’s Collaborative Orientation
Seller’s Level of Dependence vs. Buyer’s Level of Dependence
Krapfel, Salmond, and Spekman 1991
Garbarino and Johnson 1999
Garbarino and Johnson 1999
Gundlach and Cadotte 1994; Keep, Hollander, and
Dickinson 1998; Kumar, Scheer, and Steenkamp 1995
– Seller’s Levelof Information Sharing vs. Buyer’s Level of Information Sharing
– Kumar, Scheer, and Steenkamp 1996; Sirdeshmulch,
Sinah, and Sabol 2002
– Keep, Hollander, and Dickinson 1998
5. Mismatch of Marketing Tools
– Seller’s Marketing Tools vs. Buyer’s Exchange Orientation
– Jackson 1985
6. Unexpected Costs Leading to
Relationship Failure
– Seller’s Expectations vs. Relationships Ability to Meet Financial Goals
– Cannon and Homburg 2001; Cannon and Narayandas
2000; Dwyer, Schurr, and Oh 1987; Gummeon 1997;
Jackson 1985
7. Relationship Disfunctions
– Buyer Seller Expectations vs. Inherent Drawbacks of relationships
– Wilkinson and Young 1998; Hakansson and
Senhota 1995; Colgate and Danaher 2000; Walter,
Ritter, and Gurmenden 2001
8. Prerequisites for Relational Strategy
– Seller Expectations vs. Actual Readiness for Relationship Strategy
– Berry 1995; Bitner 1995; Colgate and Danaher 2000;
Gordon McKeage, and Fox 1998; Gronroos 1995;
Payne and Ballantyne 1991; Pine, Peppers, and
Rogers 1995; Sheth and Parvatiyar 1995
– Seller’s Level of Trust vs. Buyer’s Level of Trust
to mismatches (Table 1). As such, the following serves as
an initial definition for buyer-seller mismatches:
Buyer-Seller mismatches are composed of active or
latent differences in parties’ perceived needs and wants
from a business relationship, as shaped by situational
factors and dissimilar goals, that are ultimately reflected
in incompatible interfirm relations.
Variety of Mismatches: Inherent in this conceptualization is the idea that a variety of mismatches can occur
in relationships. Business relationships can be complex
because a range of exchanges may take place. This complexity allows for multiple layers of interaction across
product/service exchanges, partnership investments (Rokkan, Heide, and Wathne 2003), information exchange
(Anderson and Weitz 1992), social norms (Cannon, Achrol, and Gundlach 2000), operational linkages, and many
others. So, while an overall mismatch of transactional
versus relational exchange orientations might exist, a
variety of mismatches can occur that may or may not
significantly impact the relationship as a whole. This
represents a departure from previous notions of a solitary
overarching match or mismatch.
Perceived Needs and Wants
Consistent with theory applied to relationships (e.g.
resource dependence, TCA, social exchange), parties
enter relationships with the expectation that doing so will
be rewarding (Berry and Parasuraman 1991). Buyers and
sellers pursue a range of needs and wants from the other
party. Within the context of mismatches, buyers and
sellers can strive for needs that the other party is ultimately
unable or unwilling to provide. Mismatched needs can
occur across (1) homogenous relationship dimensions
(i.e., common to both parties) or (2) heterogeneous relationship dimensions, such as supplier dependability in
exchange for an exclusive relationship. Finally, research
suggests that desired needs and wants can be latent or
active as the situations change (Gronroos 1997).
Shaped by Situations and Goals
Several authors acknowledge that relationship theory
has been generally insensitive to situational factors that
shape relationships (Coviello et al. 2002). Mismatches
provide a framework for including them. For example, a
multitude of situational conditions in the macro and task
environment and firm characteristics can shape buyerseller mismatches such as: environmental factors (Keep,
Hollander, and Dickinson 1998), product-market characteristics (Crosby and Evans 1990), firm strategy (Wilson
2000), and risk orientation. Relationship goals also shape
buyer-seller needs and wants. Firms enter relationships
for the purpose of fulfilling strategic goals like entering
new markets and serving customer needs to name a few
American Marketing Association / Winter 2005
(Sheth and Parvatiyar 2000). These goals play an active
role in shaping relationship needs. When buyers and
sellers have incompatible relationship goals, they result in
Reflected in Incompatible Interfirm Relations
Borrowing from the Nordic school of relationship
theory, mismatches are reflected in ongoing interaction
between buyers and sellers (Gronroos 1997). Mismatches
become manifest in actions that buyers and sellers take or
fail to take towards each other, resulting in an unsatisfied
need or want across a particular relationship dimension.
These differences can be assessed at a high level (like in
previous research) as one firm’s general desire for relational dealings versus the other party’s general desire for
transactional dealings (see Figure 1). It is suggested here,
however, that desired needs and wants from the relationship drive the exchange orientation. Thus, mismatched
exchange orientations serve as a proxy for a variety of
underlying mismatched needs and wants. Ultimately,
mismatches become salient, take shape, and result in
incompatible dealings.
To illustrate, buyers can be confronted with a seller
who constantly attempts to raise the bar on the commitment of the relationship, when in fact, the buyer senses no
return on this investment. While this seller might see
potential growth in getting “deeper” into the customer
relationship, they are met with buyer apathy. Alternatively, buyers can be frustrated in relationships where they
continually vie for attention from a seller who is “busy
with other opportunities.” These differences in perceived
needs and wants are played out and result in mismatches.
To further explore the connection between mismatched
needs and wants within exchange orientations, the following discusses buyer-seller tradeoffs associated with transactional and relational dealings.
Organizations, for the most part, make intentional
decisions to establish relationships and have particular
goals in mind (Oliver 1990). Furthermore, they do so in
ways that maximize rewards from these relationships
(Frazier 1983). Many have explored various goals and
tradeoffs for suppliers and customers arising from a
transactional or relational exchange. For example, many
posit that relationship strategies can lead to competitive
advantage (Day 2000), yet others suggest maintaining
close relationships can also prove very costly (Sharma
and Tzokas 1999). An integrated review of these benefits
and sacrifices as they map to both a transactional and
relational orientation is presented in Table 2. It is suggested that understanding these factors presents insight
into why buyers and sellers might pursue incompatible
needs and wants from relationships.
American Marketing Association / Winter 2005
Buyer-Seller Exchange Tradeoffs
Buyer – Transactional Orientation
Buyer – Relational Orientation
Benefits Gained / Sacrifices Avoided Associated with Transactional Orientation
Benefits Gained / Sacrifices Avoided Associated with Relational Orientation
* Avoidance of Switching Costs, Sunk Costs e,f,m,p
High Avilability of Alternatives a,g,p‘
* High Leverage (Low Vulnerability) with Suppliers, l,p,ac,ah,ak
Less Hassle / Low Commitment j,aa
* Low Price through Adversarial Bidding a,g,p,aj
Access to Technology g,p,ag
Access to Value-Added Services h,d
Conflict Resolution More Manageable p
* Cost Reduction through Synergies b,g,p,r,z,ag,ak
Efficiency / Effectiveness for Value Chain p,ak
Greater Customization of Products/Services e,d,ad,ag
Higher Control of Direction of the Relationship ag
* Higher Relationship Satisfaction c,k,n,x,ab,ab,ac,ah
Greater, Specialized Service Levels h,w,ad
Leads to Economies of Scale s
Leads to Opportunities for Competitive Advantage ad
Outsourcing Benefits, Ability to Focus Energies Elsewhere d
Reducation of Choices / Efficient Decision Making d,ad
Risk Reduction in Crisis Situations s
Shortened New Product Development Time g,p
Seller – Transactional Orientation
Seller – Relational Orientation
Benefits Gained / Sacrifices Avoided Associated with Transactional Orientation
Benefits Gained / Sacrifices Avoided Associated with Relational Orientation
* Avoidance of High Service Costs, Investments, Adaptation n,o,t,v,aa,ac
Avoidance of Overdependence, Relationship Burdens p,r,ae
Greater Ability to Focus on Acquiring New Customers j,i
Less Hassle / Low Commitment j,o,aa
Cost Reduction through Synergies p,r,u,ac,ag
Customer Learning p,ag
* Customer Retention, Satisfaction, Loyalty c,k,n,x,y,ac,ah
Optimized Focus of Resources, Retention j,
Leads to Economies of Scale s
* Leads to Opportunities for Competitive Advantage j,u,ad,ai
Greater Price Stability p,ac
Risk Reduction / Higher Leverage with Buyers ae
Sales / Profitability Outcomes j,ac,af
* Items have received greated attention in Relationship Literature
amihud 1976
Anderson 1995
Berry and Parasuraman 1991
Bitner, Gwinner, and Gremler 1998
Brennan and Turnbull 1999
Burnham, Frels, and Mahajan 2003
Cannon and Homburg 2001
Cannon and Narayandas 2000
Child and Dennis 1995
Day 2000
k Garbarino and Johnson 1999
l Gasseheimer, Houston, and Davis 1998
m Billiland and BEllo 2002
n Golicic, Foggin, and Mentzner 2003
o Gronroos 1997
p Han and Wilson 1993
q Helper and Levine 1992
r Kalwani and Narayandas 1995
s Keep, Hollander, Dickinson 1998
t Krapfel 1991
Krapfel, Salmond, and Spekman 1991
LaBahn and Krapfel 2000
Lambert, Emmelhainz, and Gardner 2000
Leuthesser and Kohli 1995
Morgan and Hunt 1994
Noordeweier, John, and Nevin 1990
Pels, Coviello, and Brodie 2000
Sharma and Grewal 1995
Sharma and Tzokas 1999
Sheth and Sharma 1997
Sollner 1999
Spekman 1988
Sriram, Krapfel, and Spekman 1992
Webster 1992
Weitz and Jap 2000
Williamson 1985
An economic mismatch could include conflict over
preferred discounts or length of contract. A social
mismatch might arise from asymmetrical levels of
trust. Form also explains whether the mismatch occurs across a homogenous relationship dimension
(e.g., frequency of interaction) or a heterogeneous
one (e.g., buyer’s need for reliability vs. seller’s push
for exclusivity).
Given the newness of the concepts presented in this
paper, the model (Figure 2) is a framework to guide theory
development and testing of buyer-seller mismatches.
Situational Conditions
The model assumes a context shaped by situational
conditions that emanate from the macro and task environment, as well as both party’s characteristics. This elevation of situational conditions lends greater understanding
to the types of relationships that can feasibly form in a
given context. Conditions act to motivate, as well constrain relationship development due to incentives and
deterrents arising from the context. In the model, situations shape buyer-seller goals, needs and wants from
relationships; mismatches that take place; comparison
level of alternatives; and resulting outcomes.
Buyer and Seller Relationship Goals, Needs, and Wants
Salience: This refers to whether the mismatch is
latent or active for either party.
Priority: Mismatches relative to goals, needs, and
wants can be assigned a certain priority, which could
be perceived differently by the parties. A high priority mismatch could be a shift in strategic direction that
significantly alters the relationship structure. A low
priority mismatch might be a personality conflict
between two boundary personnel.
Extensiveness: The extensiveness of a mismatch
describes the degree to which incompatibilities exist
at an individual level or organization. A seller may
determine that a blocked need for closer interaction
within a customer’s firm is localized around a particular gatekeeper. Buyers might see the overall seller’s
offer (organization) falling short of its needs.
Magnitude: Mismatches take on relative magnitudes
based on the perceived gap size.
Temporal Nature: Parties to a relationship may learn
to cope with certain mismatches over a long period of
time, while others require immediate action.
These components shape what is sought in a relationship and are where mismatches of needs and wants occur.
A disproportionate focus in the literature has discussed
buyer needs and wants from a relationship, however, it is
asserted that inclusion of seller’s needs and wants provides a more holistic picture.
Buyer and Seller Exchange Orientations
The assumption here is that exchange orientations
arise out of need structures (Pels, Coviello, and Brodie
2000). Changes in need structure might drive changes in
exchange orientation. If a seller sees a need to retain a
customer whose past interaction has remained arm’s length,
that seller might begin utilizing relationship tactics, thus
altering the exchange orientation. A buyer who desires
“less hassle” in a relationship might enact a transactional
orientation to ward off unnecessary use of time. Thus, it is
suggested firms do not adopt some degree of transactional
or relational orientation for its own sake. Rather, orientations arise as a perceived means for achieving desired
needs and wants from the relationship.
Buyer-Seller Mismatches
When considering the host of mismatches that can
occur within a relationship, understanding their traits adds
insight towards classification of the phenomenon. The
following traits within the model are considered an initial
set of aspects to define a mismatch. It is not assumed that
this list is exhaustive, as further inquiry will likely refine
and/or add to this set.
Form: Mismatches can take different forms. A simple
typology might include economic and social needs.
American Marketing Association / Winter 2005
Perceived Mismatches and Comparison Level of Alternatives (CL alt)
The model proposes two basic outcomes of mismatches. First, it suggests that, parties perceive mismatches relative to their situation, goals, needs, and wants.
Second, they judge these mismatches against a comparison level of alternatives, hereafter CL alt (Thibaut and
Kelly 1959). A significant stream of research has used the
concept of CL alt to study relationships (Wilson 2000),
i.e., parties continually evaluate outcomes against desired
needs and wants. CL alt is the lowest level of outcomes
that a party will accept in light of other available alternatives. This standard serves as the deciding factor for
whether the party will cope with the outcomes or seek
alternatives (Thibaut and Kelley 1959).
Given the instability of many relationships, research
recommends buyers and sellers move toward plural approaches that blend relational and transactional strategies.
American Marketing Association / Winter 2005
Buyer-Seller Mismatch and Mismatch Outcomes
Situational Conditions (Macro and Task Environment, Firm Characteristics)
Set of Buyer-Seller
Goals, Needs, and Wants
from Relationship
Goals, Needs, and Wants
from Relationship
Temporal Nature
Buyer Exchange Orientation
Seller Exchange Orientation
Perceived Mismatches
Seek Alternatives
Below Comparison
Level of Alternatives
(CL alt)?
Below Comparison
Level of Alternatives
(CL alt)?
Seek Alternatives
Yet, making this move is not easy. Firms struggle with
determining strategies for particular situations and answering the question of with whom close or arm’s length
relationships make sense. On one side, firms might miss
the benefits of a close relationship. Conversely, some
firms dive into relational strategies and waste significant
resources when relationships do not pan out. Further,
many agree that existing research does not adequately
account for diverse situations and customers (Cannon and
Perreault 1999; Coviello et al. 2002; Wilson 2000).
Understanding relationship incompatibility from the
perspective of mismatches, casts a wider net that allows
for a more comprehensive view of both parties’ desires
and a deeper look at situations that influence success or
failure. Key contributions offered from this discussion are
threefold. First, a brief review of relationship literature
identifies the need for theory to offer a dyadic perspective
and greater sensitivity to situational factors. Current research is largely limited to a single firm perspective and
oversimplifies the concept of incompatibility. This paper
puts forth the first known attempt to integrate the mismatch concept to directly address these issues. Second, a
detailed definition, with discussion of relevant variables
and refinement of existing discussion on mismatches is
offered. This work builds on previous studies to theorize
that incompatible needs and wants lie at the core of
mismatches. Finally, a model of buyer-seller mismatches
is proposed, including antecedents, aspects of the phenomenon, and potential consequences around mismatch
Managers are urged to appreciate the concept of
mismatches as they occur in relationships. The concept of
mismatches forces managers to look deeper at both sides
of the equation. This might help firms both avoid wasted
resources and optimize relationship investments. Within
existing relationships, mismatches could guide sellers in
The author thanks Dr. John T. Mentzer for his valuable
comments on a previous version of this paper.
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American Marketing Association / Winter 2005
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Buyers might utilize mismatch information as input into
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American Marketing Association / Winter 2005
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304 Stokely Management Center
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E-Mail: [email protected]
American Marketing Association / Winter 2005
Devon Johnson, Northeastern University, Boston
Although web-based self-service technology delivers convenience benefits to customers and transaction
cost savings to firms, it also heightens consumers’ concerns about the privacy of personal identity and contact
information. These concerns are perhaps salient due to the
absence of tangible and verifiable cues regarding a seller’s
intentions and capabilities (Balasubramanian, Konana,
and Menon 2003). Information security and technology
concerns have been recognized as essential to consumer
evaluations of a Web a site’s trustworthiness. Trust in a
web site is therefore regarded as critical to web site
success and a key focus of competitive differentiation
(Urban, Sultan, and Qualls 2000).
This article addresses a gap in the literature by proposing two new facets of consumer trust in a technologybased service firm: trust in technology and perceived
commitment of the firm to privacy protection. The study
proposes a model that demonstrates the importance and
role of these two constructs in the wider nomological
network of consumer-multi-channel service firm relationship. Affective commitment, operational benevolence,
and problem solving orientation are modeled as antecedents of trust in technology and commitment to privacy
protection. Trust in the firm, frequency of transactions,
and customer-company identity are examined as consequences of the two trust norms. The model is evaluated
using combined survey and transaction data from 834
personal computer (PC) banking customers of credit
The results reveal that trust in technology and perceived commitment to privacy protection play an essential mediating role between the aforementioned antecedent and consequence variables. Interestingly, overall trust
in the firm does not mediate the impact of these trust
norms on the consequence variables, i.e., commitment to
privacy and trust in technology directly impact customercompany identity and frequency of transaction, respectively. The findings indicate that managers and researchers need to consider cross-channel effects of consumer
evaluation of other firm channels in evaluating the trustworthiness of a web site. Managers also need to explore
ways of demonstrating and reinforcing firm identity ideals in technology-based service delivery. Finally, the
study suggests that rather than regard service delivery
technology as a generic invisible black box, managers
should communicate the capabilities and integrity of its
service delivery technology to customers.
For further information contact:
Devon Johnson
Northeastern University
Boston, MA 02115–5000
Phone: 617.373.3549
FAX: 617.373.8366
E-Mail: [email protected]
American Marketing Association / Winter 2005
William O. Bearden, University of South Carolina, Columbia
R. Bruce Money, Brigham Young University, Provo
Jennifer L. Nevins, University of South Carolina, Columbia
Time orientation exists as a ubiquitous influence that
permeates many aspects of life for every individual,
whether in a personal or business-related context. As
such, marketing researchers have long been interested in
how time is valued by consumers and decision makers in
business settings. Measures of long- versus short-term
time orientations have been the subject of recent inquiry
regarding their conceptualization, measurement and levels of analysis. The research reported here involves an
assessment and validation of a multi-factor set of items
designed to measure long-term orientation at the individual level using data from a study involving 592 American and Japanese adult respondents. In addition, two
application studies investigate the predictive validity of
the long-term orientation measures in consumer and managerial decision contexts.
Time Orientation Use and Measurement
Hofstede’s (1980) work on national cultural values
has generated numerous citations and discussion, as well
as criticism (Oyserman et al. 2002; Spector et al. 2001,
2002). Specifically, Long-Term Orientation (LTO), or
Confucian Dynamism, as Hofstede’s fifth dimension was
originally called, has been the subject of recent inquiry
regarding the conceptualization, measurement, and levels
of analysis this dimension was designed to capture (Fang
2003). The lack of clarity regarding the underlying values,
as well as confusion surrounding the dimensionality and
polarity of the LTO construct has contributed to increasing scrutiny of this cultural dimension.
Hofstede’s fifth dimension has come to be used as a
measure of time orientation. Indeed, attitudes toward time
have been shown to vary systematically among consumers (Prelec and Loewenstein 1998), business/marketing
managers (Kim and Oh 2002) and national cultures (Graham 1981). The concept of LTO has been used in a
number of international marketing studies (Nakata and
Sivakumar 1996), with many indicating the need for
improved measurement. Some of these studies either
empirically or conceptually correlated Hofstede index
scores for the countries involved, but could have benefitted from better individual-level measurement. In an effort
American Marketing Association / Winter 2005
to address the shortcomings of extant measures, Bearden
et al. (2003) developed a measure of long-term orientation
composed of eight items in two subscales of four items
each designed to address tradition and planning aspects of
LTO. In the current research we evaluate this two-factor
LTO scale with data collected from two samples of U.S.
(n = 339) and Japanese (n = 253) adults (study 1).
Validation and Equivalence
From the U.S. and Japanese data, a uni-dimensional
model in which all eight items loaded on one factor, a twofactor uncorrelated model, and a two-factor correlated
model, in which the two sets of four items loaded on their
respective tradition and planning factors, were estimated.
Comparisons of these models (cf., Anderson and Gerbing
1988) across both country analyses revealed that the twofactor correlated model provided the best representation
of the data. Overall, these results provide evidence of
discriminant validity for the separate factor LTO subscales
(tradition and planning) and are consistent with the previous results reported by Bearden et al. (2003). Additionally, we examined the measurement equivalence of the
data following the procedures outlined by Singh (1995)
and Steenkamp and Baumgartner (1998), who recommend tests of configural equivalence and metric equivalence, both of which exhibited satisfactory levels of fit.
These results support the cross-cultural applicability of
the LTO scale.
Additional Evidence
Responses from the U.S. and Japan were also collected for the eight-item consumer frugality scale of
Lastovicka et al. (1999), a four-item measure of personal
ethics (Vitell, Rallapalli, and Singhapakdi 1993), and a
twelve-item consumer compulsive buying scale (Valence,
d’Astous, and Fortier 1988). It was hypothesized that
individuals scoring high in the tradition and planning
facets of long-term orientation would score higher in
terms of consumer frugality, and ethics, and lower in
compulsive buying tendencies. In addition to these other
constructs, single item convergent validity items for both
of the proposed LTO scales were also assessed using the
procedures recommended by Bagozzi (1993). A series of
consistently significant (p < .01) and generally strong
estimates between the two tradition and planning subscales
and these additional measures provided supportive evidence of validity for the proposed LTO measures.
Application Studies
In addition to study 1 assessments of equivalence and
validity, two additional studies were conducted to investigate the extent to which the proposed LTO measures are
correlated as expected with important consumer outcomes (study 2) as well as managerial decision making
(study 3). In study 2, data were collected from 54 undergraduate business students under the ruse of a study of
consumer credit use among college students. Two measures of credit involvement were obtained: total average
monthly credit card balance and the total number of credit
cards owned. Although the correlations between the credit
measures and planning and tradition were mixed, both the
simple correlations, as well partial correlation estimates,
for the total eight-item LTO scale and both of the credit
measures were significant (p < .10). We also found
evidence of the ability of our measures to moderate the
negative relationship between Lastovicka et al.’s (1999)
consumer frugality scale and the two credit outcome
variables described above.
In study 3, seventy-three MBA students first reacted
to a choice scenario involving selection of a pricing
strategy that varied in terms of long-term versus short-
term outcomes related to firm profits and market share.
Following completion of the choice task, respondents
then replied to an item designed to elicit their confidence
in their decision, as well as the tradition and planning LTO
measures. While the correlations between the tradition
and planning measures and the dichotomous choice variable were modest, the estimates are positive and significant as expected and provide additional support for the
proposed scales in terms of predictive validity.
Conclusions and Implications
The results reported in this article are generally
supportive of the bi-dimensional measure of long-term
orientation proposed by Bearden et al. (2003). A replication and application of the proposed LTO measure yielded
evidence of convergent, discriminant, and predictive validity, dimensionality, and nomological validity. The implications of our research are important to business academics for several reasons. Our study adds to the body of
knowledge regarding culture, and LTO in particular, and
supports a valuable tool for studying an important aspect
of culture. Rather than merely assign index scores as
reflective of whole groups, researchers using new scales
such as the LTO scale described in the current research,
will be able to investigate outcome phenomena dependent
directly on the individual values of subjects in various
countries. Citation information available upon request.
For further information contact:
William O. Bearden
The Moore School of Business
University of South Carolina
Columbia, SC 29208
FAX: 803.777.6876
E-Mail: [email protected]
American Marketing Association / Winter 2005
Alfred Y. Sit, Chinese University of Hong Kong, Hong Kong
Haksin Chan, Chinese University of Hong Kong, Hong Kong
Third culture kids (TCKs, children raised outside
their passport countries) are a growing segment of global
significance. We conducted an in-depth, qualitative study
on consumer socialization of adolescent TCKs (ATCKs),
and the data suggest that the unique cross-cultural experiences of ATCKs are conducive to self-socialization, a
phenomenon that has largely been neglected in the marketing literature. Our findings highlight ATCKs’ flexible
use of socialization agents, as well as the influence of
ATCKs’ own motives and values.
Contrary to much of previous research, the adolescent consumer is not a passive recipient but rather an
active agent in the consumer socialization process. Straddling the home (i.e., first) and host (i.e., second) cultures,
ATCKs are naturally exposed to a wide range of market
information, but they are at the same time quite purposive
as they “pick and choose” from a variety of potential
consumer socialization agents. Notably, ATCKs’ motives
and values play a significant role in the consumer socialization process, as they negotiate the multi-cultural terrain
of global markets. From a self-development perspective,
ATCKs strategically engage in selective exposure to
socialization agents and actively construct their own shopping and consumption scripts.
To conduct a discovery-oriented study addressing
complex and dynamic issues of consumer socialization,
we adopted phenomenological interviewing as the method
for data collection. Textual data were generated by means
of in-depth interviews with 13 English-speaking female
ATCKs (ages 15 to 17) in a cosmopolitan city. The data
were analyzed using a modified meaning condensation
technique. After establishing an internal structure through
an iterative process, we generated meaning categories via
collective coding. Finally, inter-relationships among the
categories were established in keeping with the overarching
theme of consumer socialization.
The ATCKs in our study have very strong ties to the
immediate family. In contrast to previous findings of
waning parental influence during adolescence, parents
American Marketing Association / Winter 2005
have largely maintained their socializing influence on our
ATCK participants. Often deprived of an extensive network of social support as they frequently relocate, many
ATCKs have developed an unusually strong bond with
the immediate family.
The consensus in the literature is that peer influence
is negatively correlated with parental influence. Given
ATCKs’ strong family ties, one would expect their peers
to assume a smaller role. Indeed, the strength of peer
group influence does appear weaker for ATCKs. However, the diminished peer group influence may also be
attributable to the mobility of ATCKs. Their nomadic
lifestyle apparently attenuates peer group influence.
School is the place where adolescents spend most of
their time awake. Interestingly, extant consumer socialization research has produced little evidence of school
influence. Note that school life extends far beyond the
classroom, and extracurricular activities are an important
part of school life for many ATCKs. One interesting
finding is that extracurricular activities afford special
shopping and consumption opportunities that otherwise
would not be available to the adolescent consumer.
Previous research has suggested that TV is a potent
force shaping consumer values. This is, however, not the
case for the ATCKs in our study. Our participants opt for
the Internet and teen magazines to enrich their marketplace knowledge of the first culture, even though the firstculture marketplace is thousands of miles away. Broadly
speaking, these media are selected because they enable
the ATCKs to stay connected to their cultural roots.
Contrary to past research which suggests that adolescents from higher-income families are more materialistic,
the well-off ATCKs in our study generally do not consider
themselves to be brand-conscious. Situated in a heterogeneous brand environment in the diverse expatriate community, ATCKs appear to be less vulnerable to the hegemony of leading global brands.
Unlike much of the empirical research on consumer
socialization, our ATCK study has brought the cultural
context to the forefront. In light of the encouraging
findings of this study, the door is wide open for follow-up
studies on consumer socialization of ATCKs, and for
investigations into the impacts of global marketing on the
socialization of consumers in different cultures. A concerted effort in cross-cultural research on consumer socialization would contribute to our understanding of international consumer behavior and the broader impacts of
Some have envisaged a homogeneous youth market.
The socializing influence of global marketing, however,
is mediated by socialization agents. There are hints of
unyielding local differentiation, given that young consumers are active participants in the socialization process.
Many ATCKs in our study long for a connection to
their cultural roots while adapting to the second culture.
Notably, previous research has found that expatriate executives, ATCKs’ adult counterparts, also share this sentiment. This has important implications for global marketers targeting the growing expatriate communities around
the world. Arguably, the marketing and public policy
implications apply to immigrant communities as well.
For further information contact:
Haksin Chan
Department of Marketing
The Chinese University of Hong Kong
Shatin, Hong Kong
Phone: 852.2609.7637
FAX: 852.2603.5473
E-Mail: [email protected]
American Marketing Association / Winter 2005
Heiner Evanschitzky, University of Muenster (MCM), Germany
Florian V. Wangenheim, Universität Dortmund, Germany
International marketing researchers have for long
been concerned with determining whether consumers are
predisposed towards a preference for domestic as opposed to foreign products. Empirical studies have consistently confirmed the existence of such as “domesticcountry bias” (DCB), which is manifested in stronger
product preferences and buying intentions for homemade products (for an overview, see Verlegh and
Steenkamp 1999). DCB has typically been explained by
an individually varying, trait like property named “consumer ethnocentrism” (CE; Shimp and Sharma 1987). In
brief, the more ethnocentric consumers are, the stronger
the DCB, and consequently, their predisposition to prefer
domestic over foreign products.
In a recent study, Balabanis and Diamantopoulos
(2004) identify a number of weaknesses of prior research
linking CE to DCB. First, earlier research had typically
been restricted to one product category, thereby not allowing researchers to investigate potential variation of DCB
across product categories. Second, previous studies had
focused on a very limited number of countries of origin
(COO) of the researched product categories, which in turn
prevented findings regarding varying degrees of DCB for
different COOs included in the study. Since there are
some indications that the effect of CE on DCB depends on
the specific configuration of COO and product category,
it is important to consider both aspects jointly. In sum,
there are reasons to believe that the effect of consumer
ethnocentrism on domestic country bias is likely to differ
both across countries and product categories, but prior
research has not been designed to test this assumption.
termed consumer cosmocentrism (CC), which we introduce due to the specific circumstances surrounding etnocenstrism in Germany is able to explain DCB better than
the CE construct.
In a German context, we examine the relationship
between CE and CC on consumer preferences and investigate whether competitiveness and cultural similarity can
help explain the varying strength of CE effects. The
inclusion of a new construct, CC, adds little explanatory
power to our models. It seems important to verify that CE
does in fact explain consumer preferences better than its
counterpart, even in a culture which is likely to be biased
towards the formulation of the CE scale.
In general, it seems that preference rankings can be
better explained by the combination of demographic
variables and CE for Germany than for Britain. The
highest R 2 -value in the study by Balabanis and
Diamantopoulos (2004) is .14 (Cars/Britain), while the
highest explained variation in the present study is .18
(Shoes/Germany). Taken together, the fact that the highest R2-value in both studies is obtained for the home
country suggests that CE is better suited for explaining
domestic rather than foreign-country bias. Still, the level
of explained variance is far from satisfactory. Since the
CC construct has not yielded satisfactory results, one
implication from this study is that further research is
needed to understand more clearly how preference judgments for domestic versus foreign products are formed.
Based on those weaknesses, Balabanis and
Diamantopoulos (2004) investigate the effect of CE on
DCB for one domestic (Britain) and five foreign countries
of origin in eight product categories, and find initial
support for the assumption that this effect varies across
product categories and COOs.
The effect of CE on domestic product preference is a
consistent finding in both Balabanis and Diamantopoulos
(2004) and the present study. Domestic firms in Germany
can well rely on a “safeguarding” effect when marketing
their products to consumers high in CE. At the same time,
managers from foreign countries cannot rely on CE as a
reliable indicator of the inclination of consumers to downgrade their products.
Replicating and extending Balabanis and Diamantopoulos (2004), we contribute to the literature by (1)
conducting a similar study using a larger sample of German consumers, (2) investigating a total number of 14
product categories (including the eight categories researched by Balabanis and Diamantopoulos 2004) and (3)
testing whether the addition of an alternative construct,
The findings of the study confirm that CE effects are
product- and country-specific, which confirms Balabanis
and Diamantopoulos’ (2004) findings. However, the results of the study contradict Balabanis and Diamantopoulos
(2004) somewhat, in that at least economic competitiveness of the country-of-origin plays a role in determining
respondents’ judgments. One explanation for this finding
American Marketing Association / Winter 2005
may be that Germans are higher in uncertainty avoidance
than Britons. Therefore, Germans tend to choose products
that they believe to be superior rather than to “experiment” with home country products when competitively
better offers are available. This finding is also important
from a managerial perspective, as Balabanis and
Diamantopoulos (2004) concluded that in Britain, managers from economically strong countries cannot count on
a country-of-origin effect in their favor, due to economic
competitiveness. For the German market, however, that
seems to be the case: American and British firms are not
negatively affected by CE effects, and in a few cases it
even seems that CE is positively related to preference for
When further examining the structure of effects of
CE on preferences, we are able to generate some explor-
atory insights that could help shape further research
questions. First, it seems that CE affects preference ratings for the home country negatively in product categories
(a) that are perceived as being strong drivers of the
economy (in Germany: cars, TV sets, electronics) and/or
buying from foreign firms may endanger employment in
the home economy (fashion wear, toys). Consequently,
CE exhibits the expected effects in product-country configurations that are likely to be perceived as threats for the
home economy (e.g., French food products, Italian fashion wear and shoes, Japanese electronic products and TV
sets). From that perspective, it may be concluded that
German ethnocentrist view British and American products as good and competitive, but not as harmful for the
German economy, and therefore do not discount them in
their preference ratings. References and tables with results available upon request.
For further information contact:
Heiner Evanschitzky
Marketing Center Muenster
Am Stadtgraben 13–15
D-48143 Muenster
Phone: +
FAX: +
E-Mail: [email protected]
American Marketing Association / Winter 2005
Morris K. George, University of Connecticut, Storrs
Girish N. Punj, University of Connecticut, Storrs
We propose an index (labeled as Search Pattern
Index) that can be used to capture distinctive patterns of
consumers in an online store setting. A sensitivity analysis
reveals that the proposed index can capture a variety of
search sequences, thereby enabling a better understanding of underlying online behavior.
However, based on previous research on information
source usage in traditional settings (Bruner 1986;
Westbrook and Fornell 1979) it is possible to hypothesize
likely influences on search in a web environment. These
may be broadly classified as Consumer Characteristics
and Product and Situational Factors and are briefly described next.
Consumer Characteristics
The internet has become a dominant source of information about products and services. The information
search sequences used during consideration set formation
stage may vary across consumers depending on several
consumer, product and situational influences. The observed search sequences are an external (and measurable)
manifestation of what the consumer is perhaps thinking
while evaluating a particular brand for inclusion in a
consideration set. Buried in the search sequences are
insights into the behavior of consumers in an online store
The purpose of this study is to propose a methodology by which distinct search sequences can be measured
and classified. Specifically we seek to develop a Search
Pattern Index (SPI) that can be used to capture the distinctiveness of common search sequences used by consumers
in accessing web-based product information.
Consumers are likely to use the web as an information
source during the early phases of the consumer decision
making process. Later, this information is likely to be
supplemented by (and integrated with) information gathered through a mix of traditional sources such as personal
(friends, family, etc.), neutral (books, magazine articles,
etc), and marketer-dominated (advertisement, etc.) Search
sequences in these environments, while also important,
are much more difficult to capture. But, by then the
purchase decision has already been framed by the information initially gathered on the web. Hence, it is important to understand the search sequences used by consumers during this important initial phase.
There is relatively little research on the factors that
may determine search patterns in an online store setting.
American Marketing Association / Winter 2005
Domain expertise is defined as the ability of consumers to navigate through a website to access relevant
information. Consumers construct navigational maps,
consisting of places or “landmarks” (Hodkinson et al.
2000). Landmarks are “features of the online environment
which are relatively stable and conspicuous” (Dillion
et al. 1993, p. 173), such as known websites. Domain
expertise can be expected to be an important influence on
search patterns.
System Expertise: Is the ability of an individual to
use the web and it includes skills such as being able to
navigate through menus, plan and execute an online
search, and the ability to manipulate and interact with a
search engine or decision aid. System expertise can also
be expected to be an influence on search patterns
(Hodkinson et al. 2000).
Demographic Characteristics: Such as education,
occupation and income can also be expected to influence
consumer search patterns. Education is assumed to increase the buyer’s need for information relating to the
purchase decision. Occupation and income are also important influences because of their effect on search costs
(Westbrook and Fornell 1979).
Attitude Towards the Web: Can be expected to
influence search patterns because of consumers varying
beliefs of the credibility and reliability of information
posted on the web. Consumers may be skeptical of marketer-dominated information and may perform unneeded
search solely to establish the credibility of such information.
Brand Preference: Consumers with a strong brand
preference normally limit their search to information
about their preferred brand. A consumer who has decided
to buy a particular brand will primarily be interested in
comparing prices for the selected model and choosing the
best store/outlet. Hence, search patterns are likely to focus
few attributes.
Price and Non-Sensory Attributes: The search attributes can be categorized into (1) brand name, (2) price,
(3) searchable sensory attributes, and (4) non-sensory
attributes (Degeratu et al. 2000). Non-sensory attributes
form an important evaluative criterion in a web-based
store environment. The importance given to price and
other non-sensory attributes as an evaluative criterion by
a consumer depends on the price sensitivity and utilitarian
needs of the consumer.
Product and Situational Factors
Nature of the Product: The complexity and value of
the product and the consumer’s prior experience are likely
to influence search patterns. For a complex, high value
product, consumers are likely to access more information
about product attributes and product reviews or ratings.
For low value products, information search is likely to be
limited to brand and/or price comparisons.
Shopping Strategies: Are likely to be an important
influence on consumer search patterns because of their
relationship to two important goals, namely, the urgency
of the purchase and the motivation for the website visit
(Moe and Fader 2001). A taxonomy based on these two
dimensions suggests four shopping strategies: directed
purchase visits, search/deliberation visits, hedonic browsing visits, and knowledge building visits.
Directed Purchase Visits: Since an immediate purchase is planned, consumer search will be product specific
and of the “drill-down” type (Lynch and Ariely 2000). In
other words, consumers will visit few sites, but examine
more pages at a visited website. Another phenomenon
consumers are likely to display is referred to as “harking
back” (Green and Jackson 1976), which refers to frequently going back to pages visited earlier.
Search/Deliberation Visits: The search patterns will
be similar to those in a directed purchase visit, except that
there will be less “harking back” due to the diminished
urgency for the purchase. Also, consumers are likely to
visit more websites, and examine fewer pages at a visited
Hedonic Browsing Visit: The search patterns are
likely to be more random, since an immediate purchase is
not planned and neither is there a sense of purpose.
Consequently, consumers are more likely to be susceptible to the effects of “flow” (Hoffman and Novak 1996).
They are likely to visit many websites, but only access a
few pages at a visited site.
American Marketing Association / Winter 2005
Knowledge Building Visit: The search patterns are
likely to be similar to those in a hedonic browsing visit but
with more structure to them. They are less likely to be
affected by “flow.” Fewer websites are likely to be visited
with more pages being accessed at a visited site.
Web-Design Features: The amount of information
stored on a website and the navigational tools or decisions
aids that facilitate search between and within web pages
that are linked to that site have an important influence on
search patterns. These design features determine to a great
extent the total number of pages visited, the frequency
with which pages are visited more than once and the
sequence of page visits. There are at least two different
approaches that can be used to understand how consumers
navigate across the webpages linked to a website.
According to the economics of information perspective, there is a likely negative relationship between search
cost and extent of search (Stigler 1961). Search cost in a
web-based environment is closely related to the time or
effort required to execute the search (Johnson et al. 1999).
Web-design can play an important role to reduce the time
or effort required for search by providing readily identifiable links to related attribute information on other pages.
According to the information foraging framework,
information resides in “patches” and consumers allocate
time to searching between-patches versus within-patch
search, such that they optimize the rate of information
gain per unit cost (Pirolli and Card 1999). In an online
store setting, consumers will allocate time to within-page
versus between-page search in order to maximize information gain. The easier it is to access information across
web pages, the more within-page search there will be.
To summarize, information search patterns in a webbased environment are likely to be influenced by the
Consumer Characteristics and Product and Situational
Factors as discussed above. The manner in which these
factors interact to influence search patterns is depicted in
Figures 1 and 2.
Figure 1 shows the factors influencing the search
activity of a consumer. Regardless of the product, consumers have certain inherent consumer characteristics
such as demographic, domain and system expertise and
attitude toward web, brand preference, etc. that they bring
to the search task. Once web-based search is initiated,
purchase related product and situational factors, such as
shopping strategy (e.g., directed search vs. hedonic browsing), web-design features, especially amount of information and the organization of information in different
webpages, will either facilitate or distract the consumers
in their search for information. Taken together, the abovementioned factors determine the information search patterns of consumers in an online store setting.
Factors Influencing the Information Search Pattern in a Web-Based Environment
• Domain expertise
• System expertise
• Demographic
• Attitude towards web
• Brand preference
• Price & non-sensory
Web Search
Product &
Situational Factors
• Nature of the product
• Shopping strategy
Web-design features
• Amount of information
• Navigational tools’
HedonicBrowsing visit
KnowledgeBuilding visit
decision aids
Figure 2 shows the different paths consumers may
take in a web-based information search depending on the
influence of the above factors at different stages of the
search process. Each of these paths reflects different
patterns of information search. For example, a consumer
in a directed search visit (immediate planned purchase)
who has decided the brand to buy will directly access any
known website to search for evaluative information. On
the other hand, a consumer without a pre-search decision
about brand and with less product knowledge will first try
to access product information through a search engine or
decision aid (depending upon domain and system expertise). At this stage too, the amount of information accessed
varies from consumer to consumer depending on the
motivation to acquire information. In both the above
cases, the number of sites visited (inter-site search) and
number of pages visited per site (intra-site search), links
taken from a site and the type of sites visited depend to a
great extent on the design of the web-sites.
American Marketing Association / Winter 2005
Search patterns are important for designing websites
for different kinds of products. A manager is interested in
understanding specific search patterns consumers display
for their product. The formation of a consideration set is
often an outcome of a web-based search. It is therefore
important for the manager to understand the search patterns used in the formation of a consideration set. Many
websites of electronic stores or retail chains are designed
in such a way that a consumer can search for alternatives
in a product category using certain attributes or attribute
values as search criteria. Depending upon customers’
preferences, these alternatives can also be sorted based on
price, consumer ratings, or best-selling brands.
In developing a Search Pattern Index, it is important
to understand the underlying search behavior of consum67
Flow Chart of Web-Based Information Search for a Directed Purchase Visit
Brand loyalty
Prior search
Domain and
system expertise
Brand site
Purchase visit
Brand price
Specific site
address known?
Shop bots
Search enginekeyword search
Search enginekeyword search
Prior Search
Shop bots
knowledge about
product category?
Involvement of
Shop bots
Brand site
Consumer reports
ers. Consumers start their search with the “ultimate, all
singing, all dancing version of the product rather than with
a straightforward replacement” (Smith 2000). In other
words consumers search for a product which scores high
on all their important evaluative criteria (attributes). This
gives them an opportunity to know what is available in the
market and at what price. But very often this ideal product
will be a high priced premium product and not what the
consumer wants. Consumers then “trade down” (Smith
2000) to evaluate more realistic brands for the purpose of
forming a consideration set. Since information search is
associated with search cost in terms of time (and cognitive
effort), customers attempt to arrive at the consideration set
with minimum number of searches. They select criteria
which, according to them, will reduce the number of
searches required for the formation of consideration set.
In order to achieve this goal, consumers may engage in
attribute (alternative) based search. Some of the earlier
studies have focused on developing a search index, which
reflects this kind of search pattern in a web based decisionmaking environment. Payne (1976) proposed Search Index as:
American Marketing Association / Winter 2005
Visit estores
Product &
Siturational Factors
Search Index = Alternative transitions – Attribute transitions
Alternative transitions + Attribute transitions
where alternative (attribute) transitions represent the number of instances in which the ith +1 piece of information
accessed was of the same alternative (attribute) as the ith.
This will give an indication whether it is an alternativebased search or attribute-based search depending on
whether search index is positive or negative. This index
captures the consumers’ search pattern in cases where the
information accessed can be segregated as attribute based
or alternative based.
However, in most searches, a combination of attributes and attribute values are used as search criteria and
this makes it difficult to use this index. The general search
pattern indicates that instead of accessing information
about an attribute, consumers use attribute-values as search
criteria to arrive at a set of alternatives. This brings up the
need for a new search index, which captures the search
pattern described above.
It is evident from the general pattern of search that (1)
consumers use attribute-values as search criteria (2) the
number of attributes used in a search and attribute-values
differ across searches (3) consumers try to minimize the
number of searches in arriving at a desired set of alternatives. They use attributes and attribute-values in such a
way that it helps to reduce the number of searches. An
ideal situation would be one in which the consideration set
is arrived at in one search using the correct number of
attributes and the right attribute-values. But in reality,
consumers tend to over calibrate or under calibrate, or, in
other words, they start with more stringent or less stringent criteria for selection. In subsequent searches, this
over/under calibration is corrected by relaxing/tightening
the criteria. For an index to reflect the search pattern, it
should capture this over/under calibration and transitions
in consecutive searches, i.e., from under calibration to
over calibration or vice versa.
Measuring Over/Under Calibration
As discussed above, attributes and attribute-values
are used as criteria in searches. Therefore, the number of
attributes and attribute-values used in a search gives us an
indication of how stringent the criterion is. Since this
varies with consumers and searches, the index of search
pattern should include the following variables to represent over/under calibration:
attributes selected remains the same, (b) the attribute
value remains the same, but the number of attributes
change, and (c) both the attribute value and the number of
attributes change.
Here, we are ignoring the scenario where both attribute values and numbers of attributes remain unchanged
because, in such cases, the alternatives selected will be the
same and it would not be an effective search. In most
cases, the attribute value, which has the maximum impact
on selection, is price range. Hence, we are considering
only price range as the attribute value.
In the three cases mentioned earlier, identifying transition is easy in the first two cases. In the first case, when
the number of attributes remains unchanged, narrower/
wider price range will indicate more/less stringent criteria
for selection, and hence becomes a case of transition to
over/under calibration. In the second case, when attribute
values remain unchanged, more/less number of attributes
in the second search indicates more/less stringent criteria
and thus is transition to over/under calibration. However,
in the third case, it is very difficult to identify transitions.
To identify transition, one can follow a general rule of
thumb like the one mentioned below:
When the number of attributes is less and the price
range is more, in the second search, it is a case of
under calibration.
When the number of attributes is less and the price
range smaller, it is over calibration.
Number of attributes used in the first search, A1
Number of attributes used in the last search, AL
Total number of attributes, NA
When the price range is larger and the number of
attributes more, it is under calibration.
The attribute value: in most cases, the price range, in
the first search, R1
When the price range is smaller and the number of
attributes less, it is considered over calibration.
Price range in the last search, RL
Maximum price range, RMAX.
In addition to the above variables, we need to measure the transitions- under calibration transitions, NU, and
over calibration transitions, NO. In two consecutive
searches, if the search criteria are more stringent in the
second search than in the first, it is a case of transition to
over calibration and NO is taken as 1. Similarly in the
second search, if the search criteria are less stringent
compared to the first, it is considered as transition to under
calibration and NU is taken as 1.
Identifying Over/Under Calibration Transitions
In consecutive searches, the following scenarios are
probable: (a) the attribute value changes, while number of
American Marketing Association / Winter 2005
In (3) and (4) it is assumed that when the price range
is smaller, the selection criteria becomes stricter even
though the number of attributes is less and is treated as
transition to over calibration. Similarly, larger price range
indicates less strict selection criteria and the transition is
treated as under calibration transition.
Using the above parameters, an index of search
pattern can be expressed as:
SPI = 100 {(A1 – AL)/2NA + (RL – R1)/2RMAX} NU/NT
number of attributes in the first search
number of attributes in the last search
total number of attributes in the search
price range in the first search
price range in the last search
RMAX = maximum price range
NU = number of transitions to under calibration
NT = total number of transitions
The term, NU/NT is a measure of consumers’ willingness to correct his/her initial over calibration in the subsequent searches. Together with the first term, this indicates
the magnitude of over/under calibration.
The term, {(A1 – AL)/2NA + (RL – R1) / 2RMAX} is a
measure of over all under/over calibration. Theoretically,
the most extreme values for this term are -1 and +1. Here,
we are interested in the sign of the expression. The
following scenarios are possible with respect to the sign of
The index, we proposed allows for range specification only in price. However, in reality, the websites allow
for range specification in more number of attributes. In
order to capture the search patterns in such cases, one can
modify SPI by adding terms, similar to (A1 – AL)/2NA,
representing the over/under calibration with respect to the
range specification of different attributes. However, by
doing so the interpretation of SPI becomes more complex.
Since we thought price is a surrogate measure in many
cases for product features and performance, only price
range is included in our search pattern index.
Positive Sign: This can happen in the following
Customer specifies relatively stringent criteria on the
attributes as well as the price range (i.e both (A1– AL)
and (RL – R1) are positive) in the initial search. This is
a simple case of over calibration. The customer
searches for the ideal or dream product in the first
search itself.
Other conditions, in which SPI is positive, are not so
straightforward. Customer may over calibrate in one
criterion but under calibrate in the other. In this case,
SPI will be positive only when the under calibration
in attributes/price range is canceled out by the over
calibration in price range/attributes. For example, if
a customer specified 4 attributes initially and 8 attributes in the final search, and if NA=10, then under
calibration by the customer in attributes is -0.2 (i.e.,
(A1 – AL)/2NA). However, if the same customer had
specified a price range of 100 initially, 700 in the last
search, and if RMAX is 1000, then the over calibration
in price range, (RL – R1) / 2RMAX) is 0.3. Hence, the
overall over calibration in this case is 0.1.
The Search Pattern Index is tested using data from an
experiment involving apartment search in a web-based
environment. A total of 19 attributes (NA = 19) of the
apartment like location of the apartment, availability of
heat/hot water, facilities such as swimming pool, fitness
room in the complex are used as search criteria. Along
with these attributes, participants specified maximum and
minimum monthly rent for the apartment as other search
criteria. The maximum monthly rent that can be entered
for search was $1300 and minimum was $400. Hence the
maximum price range, Rmax is 900 (i.e., 1300 – 400).
Participants used a combination of these search criteria in
a number of searches to arrive at a list of apartments,
which they consider for renting. The participants’ choice
of attributes and the price range specified in each of the
searches was captured in log files. The experiment was
conducted in severe to slight pressure and few alternatives
vs. many alternatives (2 x 2 experiments).
SPI will be negative in the following conditions:
Customer specifies relatively less stringent criteria
on the attributes as well as the price range (i.e both
(A1 – AL) and (RL – R1) are negative) in the initial
search. This is a simple case of under calibration. The
customer searches for what is available in the market
and then goes toward the product which best suits his/
her needs. Another explanation may be that a customer who under calibrates may not have sufficient
knowledge about the product.
Other necessary condition for a negative sign for SPI
is the overall under calibration by the customer,
similar to the second condition explained in the case
of positive sign. Here, for SPI to be negative, the over
calibration in attributes/price range has to be cancelled out by under calibration in price range/attributes.
American Marketing Association / Winter 2005
The search histories of eight participants who display
different search patterns are studied. The search parameters A1, AL, R1, RL, NO, and NU, are calculated from the log
files and used to arrive at the Search Pattern Index. The
SPI, calculated for different combination of search parameters are given in Table 1.
The search histories selected show great amount of
variability. The number of attributes used in the first
search varies from 13 to 4 and that in the last search ranges
from 1 to 8. Similarly the price range selected varies from
200 to 900. In all these cases, the Search Pattern Index
(SPI) captures the underlying aspect of search pattern.
The sign of SPI indicates whether it is overall over/under
calibration and magnitude represents the extent of over/
under calibration. The index is positive with higher magnitudes when stricter criteria (over calibration) are used in
Search Pattern Index in a Web-Based Information Search
Maximum price range, RMAX = 900
Total No. of Attributes, NA = 19
Sl. No
Search Parameters
the first search compared to the last search, in terms of
both the number of attributes and price range (cases 1, 2,
and 8 in Table 1). When less stringent criteria are used in
the first search, in terms of both the number of attributes
and price range, the index is always negative (case 3).
However in cases where participants used more attributes
but wider price range, the sign and magnitude of the index
depends on the extent of overall over/under calibration
specified by both price range and number of attributes
used in the search. In cases 4, 5, and 6, the under calibration in terms of price range was large enough in order to
nullify the over calibration specified in terms of A1 and AL
and therefore the overall index is negative. But in case 7,
the over calibration specified in terms of A1 and AL is
sufficient to nullify the under calibration expressed in
terms of price range and hence the search index is positive.
This illustrates the SPI’s ability to capture the search
pattern in terms of overall over/under calibration in different searches.
more efficiently. One way of customization, which many
companies do, is to make the search more interactive and
prompt customers to visit more appropriate sites. This is
done by tracking the sites and pages visited by the consumers in their search. Identification of search pattern and
more importantly making inferences about the consumers
from the search pattern will help to customize the search
for individual consumer. In this paper we identified certain factors that influence search patterns. These factors
have varying influence on consumers’ search activity at
different stages of their search. Also, in order to reflect the
individual search pattern, especially in the search for
formation of consideration set, a Search Pattern Index is
developed. This can be used as a dependent measure in
future researches to understand and predict consumers’
search pattern in a web-based environment. The index can
be easily modified to suit websites of different e-stores
because the basic nature of search remains the same- i.e.,
searching for alternatives using attributes and attribute
values as criteria.
Emergence of web as an important source of information has necessitated the identification of search patterns.
More and more e-businesses are trying to customize their
web sites to help the consumers search for information
American Marketing Association / Winter 2005
We developed a uni-dimensional index to represent
search pattern, which is a multi-dimensional activity.
Future research can focus on developing a multi-dimensional index without sacrificing the ease of interpretability.
Bruner, C. Gordon (1986), “Problem Recognition Styles
and Search Patterns: An Empirical Investigation,”
Journal of Retailing, 62 (3), (Fall) 281–97.
Degeratu, Alexandru M., Arvind Rangaswamy, and Jianan
Wu (2000), “Consumer Choice Behavior In Online
and Traditional Supermarkets: The Effects of Brand
Name, Price, and Other Search Attributes,” International Journal of Research in Marketing, 17, 55–78.
Smith, Gerald E. (2000), “Search at Different Price Levels: The Impact of Knowledge and Search Cost,” The
Journal of Product and Brand Management, 9 (3),
Green, T.R. and P.R. Jackson (1976), “Hark-Back: A
Simple Measure of Search Patterns,” British Journal
of Mathematical and Statistical Psychology, 29 (1),
(May), 103–13.
Hodkinson, Chris, Geoffrey Kiel, and Janet R. McCollKennedy (2000), “Consumer Web Search Behaviour: Diagrammatic Illustration of Wayfinding on the
Web,” International Journal of Human-Computer
Studies, 52, 805–30.
Johnson, J. Eric, Gerald L. Lohse, and Naomi Mandel
(1999), “Designing Marketplaces of the Artificial:
Four Approaches to Understanding Consumer Behavior in Electronic Environments,” INFORMS Conference “Marketing and the Internet.”
Moe, W. Wendy and Peter S. Fader (2001), “Uncovering
Patterns in Cybershopping,” California Management
Review, 43 (4), (Summer), 106–17.
Payne, J. Stephen, Andrew Howes, and William R. Reader (2001), “Adaptively Distributing Cognition: A
Decision-Making Perspective on Human – Computer Interaction,” Behaviour & Information Technology, 20 (5), 339–46.
Pirolli, Peter and Stuart Card (1999), “Information Foraging,” Psychological Review, 106 (4), 643–75.
Westbrook, Robert A. and Claes Fornell (1979), “Patterns
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For further information contact:
Morris K. George
Department of Marketing
University of Connecticut
2100 Hillside Road
Storrs, CT 06269
Phone: 860.486.1102
FAX: 860.486.5246
E-Mail: [email protected]
American Marketing Association / Winter 2005
Tanawat Hirunyawipada, University of North Texas, Denton
Mohammadali Zolfagharian, University of North Texas, Denton
Consumer innovativeness is a central element in the
studies of diffusion of innovation (Midgley and Dowling
1978), and it identifies early adopters from general consumers (Roehrich 2002). Finding early adopters can accelerate the diffusion of innovation and minimize the
chances of new product failure (Robertson 1971, pp. 112–
113). Consumer innovativeness studies generally seem to
focus on arousal and novelty seeking as the underlying
reasons for consumers to seek novel products (Hirschman
1980). However, new products also inherently encompass an element of risks associated with resistance to
adoption (Ram and Sheth 1989). This study examines: (1)
consumer innovativeness is the trait that engenders the
adoption of innovation; (2) new products encompass
resistance to adoption. We hypothesize that perceived
risk, which is a highly salient, influential attribute of
innovation resistance (Bettman 1973; Dholakia 2000),
moderates the relationship between consumer innovativeness and new product adoption.
Reviewing consumer innovativeness literature (e.g.,
Midgley and Dowling 1978, 1993; Hirschman 1980;
Roger 1983; Venkatraman and Price 1990), we delineate
the consumer innovativeness hierarchy, which includes
the three different aspects: global innovativeness (GI),
domain-specific innovativeness (DSI), and actualized
innovativeness (AI). GI is defined as the degree to which
an individual is receptive to new ideas and independently
adopts the ideas through various forms of new products.
GI is also disaggregated into cognitive innovativeness
(CGI) and sensory innovativeness (SNI). DSI is considered an individual’s innovativeness predisposition toward generic product class. AI is defined as the degree to
which consumers are relatively earlier in adopting new
products than other members of their societies. We suggest that AI be disintegrated into the adoption of actual
products (Adoptive innovativeness, ADI) and the acquisition of novel information about products (Vicarious
innovativeness, VCI).
This study also proposes that perceived risk, i.e.,
instigating resistance to the adoption of innovation, moderates the relation between consumer innovativeness and
innovation adoption. Perceived risk is a multidimensional
American Marketing Association / Winter 2005
construct containing common dimensions across product
categories as well as category-specific dimensions. Since
this study focuses on high-tech products, network externalities is introduced as a category-specific risk while
financial, performance, physical, time, social, and psychological risks are included as perceived risk dimensions
generally found across categories. The seven dimensions
of perceived risk are collectively tested to explore the
effect of innovation-resistance on the consumer innovativeness hierarchy.
Data collected from 746 graduate and undergraduate
students at a major public university in Southwestern U.S.
show strong supports for all 12 hypotheses. The positive
relation between CGI and ADI suggests that CGI is a
propensity to enjoy cognitive process that needs practical
and pragmatic activities and that can be obtained through
using products. This trait can drive consumers toward the
actual innovation adoption. The positive relation between
SNI and VCI shows that SNI trait relates to consumers’
tendency to seek fantasy and arousal for optimizing their
level of stimulation. This arousal is achieved by the mere
adoption of stimulus information. SNI is therefore a trait
in consumers with positive propensity toward VCI. The
positive relation between DSI and AI (both ADI and VCI
dimensions) may suggest that consumer innovativeness
becomes stronger within specific product categories. DSI
encompasses consumers’ interests in specific categories
and constitutes higher propensity to adopt innovations.
The results confirm the moderating effect of perceived risk, that is, consumers with high overall perceived
risk typically score high on VCI (the higher perceived
risk, the higher VCI). This is a key answer to the ongoing
dispute concerning the proneness of globally innovative
consumers (GI) toward new product adoption. The resistance to innovation adoption, represented by perceived
risk associated with new products, clearly counteracts the
influence of the CGI trait. It is only the SNI trait that
significantly influences the adoption behavior of innovative consumers with high concern about risk. This effect
causes innovative consumers to reject new products but
still acquire and enjoy products’ novel information. Perceived risk changes the innovators from “doers” to “dreamers.” However, perceived risk has insignificant impact on
the relation between DSI and AI (both ADI and VCI). DSI
consumers’ interests and knowledge in certain product
categories may mitigate perceived risk from his/her adoption.
The result implies that marketing managers should
first target DSI consumers as early adopters for high-tech
products. GI consumers make up the second best potential
adopters. To achieve this objective, managers should
manipulate the market mix so that both groups of consumers are targeted. Promotional messages, while stressing
CGI and SNI, should ensure consumers that they can
overcome the risk associated with innovation adoption.
Product demonstration, product trials, and appropriate
warranty programs are among considerable activities to
mitigate consumers’ perceived risk.
Future study should consider more diversified product categories. By doing so, the other dimensions of
perceived risk might be identified, and the external validity of the model might be increased. Additionally, the
hierarchy of consumer innovativeness needs further theorization, especially on other moderating variables that can
significantly influence AI. The dimensions of perceived
risk, which may be salient in different aspects of consumer
innovativeness, are another interesting avenue for future
For further information contact:
Tanawat Hirunyawipada
University of North Texas
P.O. Box 311396
Denton, TX 76203
Phone: 940.565.3120
FAX: 940.565.3837
E-Mail: [email protected]
American Marketing Association / Winter 2005
Joseph W. Chang, University of Regina, Regina
Yung-Chien Lou, National Cheng-Chi University, Taiwan
Research in family brand evaluations uncovers that
the reciprocal effects of brand extensions on family brands
are moderated by the categorical similarity of brand
extensions (e.g., Chang 2001; Loken and John 1993;
John, Loken, and Joiner 1998) and the accessibility and
diagnosticity of brand extension information (e.g.,
Ahluwalia and Gurhan-Canli 2000; Chang 2002). When
the accessibility of extension information is high, consumers engage in piecemeal or systematic processing on
brand evaluations, where detailed brand extension information is processed for the impression formation of family brands. Under the circumstances, the valence of highly
accessible extension information is more diagnostic than
the contextual factor of categorical similarity on family
brand evaluations. The images of family brands are weakened by negative extension information and are enhanced
by positive extension information, regardless of the categorical similarity of brand extensions.
Most recently, a considerable amount of attentions in
the research of social cognition has been given to the
influences of new group members on the impression
formation of social groups with high and low perceived
entitativity (e.g., Crawford, Sherman, and Hamilton 2002;
Lickel, Hamilton, Wieczorkowska, Lewis, Sherman, and
Uhles 2000; McConnell, Sherman, and Hamilton 1997).
A social aggregate is perceived as having “the nature of an
entity, of having real existence” (Campbell 1958, p. 17;
McConnell et al. 1997, p. 750), whereas perceived
entitativity is defined as the degree to which a collection
of persons is perceived as being bonded together in a
coherent unit (Campbell 1958; Lickel et al. 2000, p. 224).
The concept of perceived entitativity emphasizes the
interactive coherence among group members (Gaertner
and Schopler 1998). Expected variability discusses the
similarity among existing group members in a more static
fashion, such as race, gender, and quality, whereas perceived entitativity emphasizes the relationship among
group members on the dynamic perspective of interactive
coherence (Gaertner and Schopler 1998; Hamilton,
Sherman, and Rodgers 2003; Lickel et al. 2000). Low
variable groups with same ethnicity or gender, such as
American Marketing Association / Winter 2005
Jews, women, may be perceived as low or moderate
entitative groups with insignificant coherent interactions.
Social groups with coherent interaction among group
members, such as task or intimacy groups, are normally
perceived as high entitative and strongly valued (Lickel
et al. 2000). Social groups with different perceived
entitativity activate different psychological processes and
lead to different subsequent impression formation (or
judgments) of groups. Moreover, Crawford et al. (2002)
find that the abstracted traits of the individual behaviours
of high entitative groups are more likely to be applied to
revise group stereotypes than those of low entitative
groups, which suggests that new individual members of
high entitative groups are more influential than those of
low entitative groups on group impression formation. The
findings suggest that, except for similarity and information accessibility-diagnosticity, group impression formation is moderated by the perceived entitativity of groups.
For brand evaluation research, the results may also imply
that the new extension information of high entitative
family brands is more influential than that of low entitative
family brands on family brand evaluations.
Based on group impression formation and accessibility-diagnosticity theories, experimental hypotheses are
developed to examine the intermediating roles of perceived entitativity, information valence, and categorical
similarity on family brand evaluations with laboratory
experiments under high accessibility situations. Both high
and low entitative family brands are enhanced and diluted
by positive and negative extension information respectively, regardless of the categorical similarity of brand
extensions and the perceived entitativity of family brands.
The polarization effect of perceived entitativity on the
quality judgements of family brands is also observed.
High entitative family brands are more favorably evaluated than low entitative family brands. The polarization
effect then serves as a mediator on reciprocal extension
effects and leads to the results that high entitative family
brands are more significantly diluted by negative extension information and low entitative family brands are
more significantly enhanced by positive extension information. References available upon request.
For further information contact:
Joseph W. Chang
University of Regina
1320C Grace Street
Regina, SK S4T 5M8
Phone: 306.949.9523
FAX: 310.356.4934
E-Mail: [email protected]
American Marketing Association / Winter 2005
David A. Griffith, Michigan State University, East Lansing
Stephanie M. Noble, The University of Mississippi, University
Qimei Chen, University of Hawaii, Honolulu
Despite the growing interest among scholars and
practitioners, there is a lack of research on and a need to
improve our understanding of the process of implementing a knowledge management strategy. This article addresses this area and contributes to our understanding by
providing insights into both synergistic knowledge resource effects and the environmental influences on knowledge management strategy implementation effectiveness.
Specifically, we investigate the synergistic effect of combining knowledge of customers, industry, and firm practices to develop the capability of ability to meet customer
needs and the influence of the capability of ability to meet
customer needs on performance. Further, as our focus is
resource conversion into the capability of ability to meet
customer needs, we examine the moderation effect of two
environmental conditions i.e., competitive intensity and
market dynamism, on the conversion effectiveness.
Method and Analysis
We tested the hypotheses using data collected in the
retail industry. Trained market researchers were then sent
into the field to conduct 320 pre-arranged in-office interviews with retailers systematically selected from a directory. A total of 293 usable responses were received,
yielding a 60 percent response rate (when taking the
replacement sample into account). Retail sectors in the
sample consisted of airlines, major household appliance,
automobile dealers, banks, beauty salons and services,
clothing retail, computer dealers, convenience stores,
copy and duplication service, cosmetics retail, department stores, electronic appliances, florists retail, furniture
retail, gift shops, golf, grocer, hotels, insurance, jewelers,
pet shops, pharmacies, photo finishing, pizza, real estate
agent, restaurants, sporting goods, toys, and travel agencies.
The fit of the measurement model was assessed by
examining factor loadings from latent variables to indicator variables, the chi-squared test, and fit indices. All
factor loadings were significant at the p < .001 level and
American Marketing Association / Winter 2005
all standardized factor loadings were well above .40, a
minimum threshold of acceptability (Hair et al. 1998).
The measurement model produced a chi-square value of
399 with 216 degrees of freedom, a chi-squared/df ratio of
1.85, GFI of .90, IFI of .943, and CFI of .942, indicating
that the model provides a good overall fit.
Results and Discussion
This study makes several important contributions to
the literature. First, researchers have yet to fully explore
the synergistic effects of knowledge resources in their
conversion into capabilities. Day (1994) identifies capabilities and skills related to “market-sensing” and “customer-linking,” as critical to a firm’s competitive advantage. Our results build on this and indicate that when the
firm’s knowledge resources (i.e., knowledge of a firm’s
customers, its industry and the firm’s practice) are developed and implemented in conjunction with one another
the firm is able to establish more well developed capabilities in relation to meeting customer needs.
The findings of this study also demonstrate the influence of environmental conditions on resource conversion.
The results indicate that competitive intensity does not
diminish the conversion of knowledge resources into the
capability of ability to meet customer needs. In fact, the
conversion of knowledge resources had a positive influence on the ability to meet customer needs even in highly
competitive markets. These finding are encouraging as
they indicate that even in markets stronger in competitive
intensity, synergistically combining knowledge resources
can result in the development of the capability of ability to
meet customer needs.
Further, the results pertaining to the influence of
market dynamism on resource conversion indicated that
market dynamism did in fact influence a firm’s knowledge resource conversion. Specifically, the results indicated that firms who were able to synergistically combine
knowledge resources operating in highly dynamic markets were less effective at developing the capability of
ability to meet customer needs when compared to firms
operating in less dynamic markets. As theorized, dynamic
markets are characterized by ever changing consumer
demands and as such even firms who are able to synergistically combine resources are faced with unique market
challenges. This is not to indicate that firms that were able
to synergistically combine resources were not able to
develop the capability of ability to meet customer needs,
for the results clearly indicate that there was a strong
relationship between these two elements in markets characterized by high and low market dynamism, but rather
that the market environment itself hampered the firm from
fully capitalizing on its ability to synergistically combine
knowledge resources.
In addition, most studies of knowledge resources
have focused almost exclusively on direct performance
implications, thus neglecting the importance of resource
conversion into viable capabilities. The importance of
knowledge resources to a firm is often viewed in terms of
its performance outcomes, without careful consideration
of its intervening firm capabilities, such as the ability to
meet customer needs. As such, the findings of this study
underscores, and provides empirical support for, the theoretical precepts put forth in the capabilities literature, i.e.,
that resources are necessary yet insufficient for the establishment of enhanced performance. Here, the findings
demonstrate that it is through the conversion of knowledge resources into capabilities that a firm is able to
develop a unique market position allowing for enhanced
performance. As such, this study extends the literature on
knowledge resources and the RBV of the firm by exploring the employment of knowledge resources under a
capabilities perspective. References available upon request
For further information contact:
David A. Griffith
Department of Marketing and Supply Chain Management
The Eli Broad College of Business
Michigan State University
East Lansing, MI 48824–1122
Phone: 517.432.5535, Ext. 260
FAX: 517.432.1112
E-Mail: [email protected]
American Marketing Association / Winter 2005
Danielle A. Chmielewski, The University of Melbourne, Australia
Bryan A. Lukas, The University of Melbourne, Australia
Robert E. Widing II, The University of Melbourne, Australia
This study empirically investigates the impact of
competitive intensity, market turbulence and market
growth potential on a firm’s order-of-brand entry decision. The results indicate that the greater the competitive
intensity and market growth potential, the earlier the
brand entry. Directions for future research are discussed.
Order-of-brand entry refers to the sequence of entry
of brands into a market (Schoenecker and Cooper 1998).
The issue of when to introduce a new brand into a market
is a complex one, because as Schnaars (1986) asserts,
different entry strategies are optimal for different firms as
well as for different market conditions. Whilst earlier
entry into a market can lead to the development of a firstmover advantage (see Lambkin 1988; Robinson 1988;
Robinson and Fornell 1985), there are also risks and costs
associated with introducing a brand earlier into the market. Development and particularly promotion costs of the
brand are high, and the risk of failure is considerable, as
demand uncertainty exists (Lambkin 1988; Urban et al.
1986). In a new market, it can also be difficult to accurately forecast the size of the market and the optimal
positioning of the new brand (Sullivan 1991). Entering a
brand later into the market can allow a firm to benefit from
a late-mover advantage (see Sullivan 1991; Shankar,
Carpenter, and Krishnamurthi 1998), although later entry
also has its risks, because the brand is entering a more
competitive marketplace. Therefore, by understanding
the factors affecting the order-of-entry decision for a
brand, a firm is better placed to enter a brand into a market
in such a way as to balance the risks of entering too early
with the problems of missing opportunities by entering
too late (Lilien and Yoon 1990).
The strategic marketing and management literature
has long argued that a firm’s environment affects a firm’s
strategy (e.g., Miller 1987; Tan and Litschert 1994). A
firm’s external environment can be a source of information uncertainty (Rajagopalan and Spreitzer 1996). Conducting an analysis of the competitive environment enables a firm to better understand and measure “the attractiveness of industries for long-term profitability and the
factors that determine it” (Porter 1985, p. 1). Given the
American Marketing Association / Winter 2005
highly competitive nature of the consumer goods industries, it is important for firms to better understand the
impact of market factors on its order-of-entry strategy.
This will help ensure that a firm’s order-of-entry decision
for a brand reflects the conditions it faces in the market it
is choosing to enter.
Against this background, the purpose of this study is
to empirically examine the impact of key characteristics
of the market, namely competitive intensity, market turbulence and market growth potential, on a firm’s order-ofbrand entry strategy in a range of consumer goods industries. These three characteristics affect the attractiveness
of the market into which a firm wishes to enter. This is a
very important and managerially relevant issue, because
it suggests that different market characteristics require
different order of entry decisions. It has been argued that
the order-of-entry of a product into a market is a key
determinant of the success or failure of the product
(Fuentelsaz, Gomez, and Polo 2002). Understanding the
interplay between the market and order of entry strategy
will allow firms to make a more informed decision about
the most appropriate entry strategy to employ, given the
market conditions.
The paper is structured as follows. First, we present
the conceptual model and put forth our hypotheses by
providing a brief review of the relevant literature. Then,
we identify the methodology employed in this empirical
study, before presenting our results. In the final section,
we provide a discussion of the results and some future
research avenues.
Figure 1 is a conceptual framework for the discussion
that follows. We now discuss each of the proposed relationships and develop hypotheses based on existing literature.
An attractive market is defined as one “where the
average competitor consistently earns a return above its
cost of capital, i.e., it is creating value for shareholders”
(Doyle 2000, p. 157). Market attractiveness is a function
of the structure of the market in which a firm competes,
and the extent to which the market is turbulent influences
Order-of-Brand Entry Strategy: A Conceptual Model
Market Attractiveness
(a) Competitive Intensity
(b) Market Turbulence
(c) Market Growth Potential
the attractiveness of that market (Glazer 1991). A turbulent, dynamic market requires a firm to be responsive and
adapt to changes in its environment (Rajagopalan and
Spreitzer 1996). A number of factors influence the attractiveness of the market, including customer turbulence,
competitive intensity, technological intensity, buyer power,
and supplier power (Doyle 2000; Jaworski and Kohli
1993; Miller 1987; Porter 1980). This study will focus on
three key factors; competitive intensity, market turbulence, and market growth potential (Doyle 2001). We now
turn to a brief discussion of each of these factors.
Competitive Intensity
Competitive intensity refers to the extent to which the
composition of the market and competitive actions change
over time (Gatignon and Xuereb 1997; Kohli and Jaworski
1990; Slater and Narver 1994). According to Fuentelsaz,
Gomez, and Polo (2002, p. 250), “competition stems from
firms interacting and striving in the same environments
and for the same resources.” Competitive intensity addresses the breadth and aggressiveness of a competitor’s
actions (Slater and Narver 1994). Day (1994) asserts that
the intensity of competition within a market determines
the profit potential of that market.
According to Porter (1980, p. 17), competitive intensity in a market occurs “because one or more competitors
either feels the pressure or sees the opportunity to improve
position.” Rivalry can take the form of price competition,
aggressive advertising and marketing tactics, product
introductions, and increased levels of customer service or
A firm achieves superior performance by choosing to
enter an attractive market, where it can defend its position
against competitors. An increased level of competitive
intensity decreases the attractiveness of the market, in that
it can result in the erection of barriers to entry such as
economies of scale and strong brand name recognition
(Urban and Hauser 1993). Entry barriers provide early
American Marketing Association / Winter 2005
Order-of-Brand Entry
entrants with a “head start,” because they increase the
lead-time between early-movers and late-movers.
Barney (1991) argues that early entrants can develop
an advantage over late entrants, because they have the
opportunity to develop solid relationships with suppliers,
establish strong brand awareness, and obtain a large share
of the market. Consequently, they are able to lock in
suppliers and customers and create barriers to entry, thus
making entry more difficult for subsequent entrants. If
firms know that their industry will be characterised by
intense competition, they have an incentive to make a preemptive move by entering earlier and erecting barriers to
entry, rather than entering later and facing barriers to
entry. On this basis, we put forth the following hypothesis:
Hypothesis 1: The greater the competitive intensity in
a market, the earlier the brand entry.
Market Turbulence
Market turbulence is defined as the extent to which
the composition of customers and their preferences change
over time (Han, Kim, and Srivastava 1998; Kohli and
Jaworski 1990). Market turbulence is similar to “environmental heterogeneity,” which refers to “the change in
diversity of production methods and marketing tactics
required to cater to customers’ needs” (Miller 1987,
p. 62).
Customers are an important component of an industry. They can influence the nature of competition within
an industry (and hence industry profitability) by forcing
prices down, demanding higher quality or more services,
and playing competitors against each other (Porter 1980).
A market that is characterised by high levels of
turbulence implies that a firm must constantly modify its
portfolio of brands or develop new brands in order to
continuously meet customers’ changing preferences or
latent needs (Jaworski and Kohli 1993). This makes a
market quite unattractive, because brand preferences are
frequently changing. In addition, in turbulent markets,
increased customer pressure puts profit margins under
threat (Doyle 2000). Thus market turbulence makes it
difficult for firms to accurately forecast the demand potential for their brand, as well as to develop an appropriate
positioning strategy for their brand (Sullivan 1991). Where
market turbulence is present, later brand entry may be the
best option for a firm. The reason for this is as follows.
Entering earlier into a market requires high set up costs,
such as R&D, advertising, and market development costs.
A market that is turbulent is not particularly attractive,
therefore in order to maximise its return, a firm should
engage in a strategy that is cost-effective and less risky.
Later entry allows a firm to free-ride on the investments
made by earlier entrants, hence reducing the costs associated with entry and increasing the profitability of the
brand entry (Sullivan 1991). Lowest-cost entrants are
most likely to generate profitability for their new brand
(Doyle 2000). In light of this, we hypothesize the following:
Hypothesis 2: The greater the market turbulence, the
later the brand entry.
Market Growth Potential
Market growth potential refers to the level of potential and demand growth of the market at the time of entry
of the brand strategy (Fuentelsaz, Gomez, and Polo 2002).
According to Lilien and Yoon (1990), a firm’s order of
entry decision depends on the market potential and demand growth of a market. A higher growth and demand
potential increase the attractiveness of the market, because it is easier for a brand to be successful if the market
into which a firm is entering is growing (Doyle 2000).
According to Doyle (2000), “growth markets are nonzero-sum: all the competitors can grow, which acts to
reduce destructive price competition and margin erosion”
(p. 158). However, in order to capitalise on the growth
potential of the market and capture early-mover advantages, high market growth potential is most likely to lead
to early brand entry. Therefore:
Hypothesis 3: The greater the market growth potential, the earlier the brand entry.
Industry Selection
To be consistent with previous research (e.g., Golder
and Tellis 1993; Kalyanaram and Urban 1992; Schoenecker
and Cooper 1998; Sullivan 1991; Urban et al. 1986), our
unit of analysis is the strategic business unit (SBU) of
firms operating in a range of consumers goods industries.
These industries include beverages, clothing and footAmerican Marketing Association / Winter 2005
wear, food, household products, motor vehicles, personal
care products, and computers. Respondents were asked to
complete the survey with respect to a new brand that their
SBU had introduced into the market at least one year ago.
Data Collection
The sampling frame for this research comprised 2894
consumer goods manufacturers in Australia and New
Zealand. The mailing list was obtained from a public
mailing list company. T-tests found that there were no
significant differences between the Australian and New
Zealand responses. The study employed direct mail data
collection in the form of an on-line survey. An on-line
survey was chosen because past research has found that an
on-line survey generally “produces an acceptable response rate at a lower cost per returned questionnaire than
mail” (Tse 1998, p. 353).
E-mail invitations containing a hyperlink leading to
a web-site with the on-line survey were sent to marketing
executives, brand managers, or general managers of strategic business units in our sample firms. The initial e-mail
was followed by two subsequent follow-up e-mails. The
response rate, after taking into account a number of
ineligible and/or unreachable respondents, was six percent, with 149 useable surveys completed. Whilst the
response rate is low, it is not unusual. Alreck and Settle
(1995) note that it is not uncommon for direct mail data
collection response rates to fall within the range of five to
ten percent. Indeed, our response rate (6%) was consistent
with the response rate obtained by Tse (1998) (7%) in his
study comparing response rates when using e-mail versus
mail data collection methods. Low e-mail response rates
may be attributed to the sharp increase in junk e-mails in
recent years, and increasingly effective anti-spam software blocking unsolicited e-mails (Tse 1998).
For the purposes of this study, a high internal validity
was more important than external validity, which is consistent with the view put forth by Wittink (2004) in his
recent Editorial Statement of the Journal of Marketing
Research. We nonetheless controlled for a possible nonresponse bias in three ways. First, in the spirit of Armstrong
and Overton (1977), we tested for differences between
early and late respondents by dividing the data into thirds
using the three response waves as the grouping variable.
The t-tests between mean responses of first-wave and
second-wave, first-wave and third-wave, and secondwave and third-wave responses indicated no statistically
significant differences (p < .05) across market turbulence,
competitive intensity, market growth potential, order of
entry, and business unit size. Second, we conducted a oneway between-groups analysis of variance to explore the
impact of response wave on market turbulence, competitive intensity, market growth potential, order-of-brand
entry, and size of business unit. Respondents were divided
into three groups according to the response wave. There
were no statistically significant differences (p < .05) in the
mean scores of first-wave, second-wave, and third-wave
responses. Third, we used the Mann-Whitney U Test to
compare the median responses between first-wave and
second-wave, first-wave and third-wave, and secondwave and third-wave responses across market turbulence,
competitive intensity, market growth potential, order-ofbrand entry, and size of business unit. No statistically
significant differences (p < .05) were found. These findings indicate that non-response bias was not a problem in
this study.
using exploratory factor analysis (EFA) run with SPSS
11.5 and confirmatory factor analysis (CFA) run with
LISREL 8.5. EFA identifies the structure of the factors to
be tested (Gerbing and Anderson 1988). Market turbulence, competitive intensity and market growth potential
were subjected to EFA using principal components extraction method with oblique rotation in order to allow the
factors to correlate with each other (Tabachnick and
Fidell 2001). Factors with eigenvalues greater than 1.0
were retained, and items with low loadings (less than
0.40) were deleted (Hair, Anderson, Tatham, and Black
1998). The results supported both discriminant and convergent validity for all three constructs.
The Measures
This study used a combination of existing scales and
new scales.
Order of Brand Entry: The scale was adopted from
Green, Barclay, and Ryans (1995) and Schoenecker and
Cooper (1998), and comprised a single item, “how many
brands were in the market prior to entry of your brand?”
The item was scored using a 7-point Likert-type scale,
were 1 = 7, 2 = 6, 3 = 5, 4 = 4, 5 = 3, 6 = 2, and 7 = 1 brands.
Competitive Intensity: We adopted the 7-point scale
used by Jaworski and Kohli (1993) to assess competitive
intensity. The scale consisted of six items, where 1 =
strongly disagree, and 7 = strongly agree.
Market Turbulence. We adopted the 7-point scale
used by Jaworski and Kohli (1993) measure market turbulence. The scale consisted of six items, where 1 = strongly
disagree, and 7 = strongly agree.
Market Growth Potential: A new scale was developed for this construct in this study. The scale for market
growth potential comprised 4 items: (i) the market for our
brand did not grow as fast as expected, (ii) the untapped
dollar value of our market was not as large as expected,
(iii) our market did not provide the expected sales potential for the brand, and (iv) our market was not as profitable
as expected. These were assessed using a 7-point scale,
where 1 = strongly agree, and 7 = strongly disagree.
Control Variables: Consistent with prior research
studies on new brands and order of entry (see Fuentelsaz,
Gomez, and Polo 2002; Lilien and Yoon 1990; Robinson
and Fornell 1985; Smith and Park 1992), this study
employed brand development time, quality of the brand,
degree of similarity of new brand with existing brands,
and business unit size as control variables.
Assessment of Measures
A pretest was first conducted to determine face validity. We then assessed measure reliability and validity
American Marketing Association / Winter 2005
After conducting EFA, we subjected market turbulence, competitive intensity and market growth potential
to CFA to test the underlying structure identified in the
EFA (Gerbing and Anderson 1988). The chi-square of the
measurement model was statistically significant (χ2 =
96.84, p = 0.04, df = 74). The goodness-of-fit index (GFI),
adjusted goodness-of-fit index (AGFI), root mean square
error of approximation (RMSEA), parsimonious normed
fit index (PNFI), comparative fit index (CFI) and normed
incremental fit index (NFI) indicate an acceptable fit with
the hypothesised measurement model (GFI = 0.86, AGFI =
0.81, RMSEA = 0.06, PNFI = 0.59, CFI = 0.88, and NFI =
0.72), and meet the benchmarks suggested by the literature (Baumgartner and Homburg 1996).
Reliability of the three constructs was measured by
looking at the composite reliability and cronbach alpha.
Convergent validity was assessed by examining the parameter estimates, t-values and average variance extracted
(AVE). Discriminant validity was assessed by comparing
the squared correlations for all pairs of constructs in the
measurement model with the AVE for each construct
(Fornell and Larcker 1981).
The three constructs exhibited acceptable reliability
levels, with the cronbach alphas ranging from 0.70 to 0.82
(exceeding the recommended level of 0.70) (Churchill
1979), and the composite reliability ranging from 0.69 to
0.83 (exceeding the recommended threshold of 0.60)
(Churchill 1979; Fornell and Larcker 1981). All of the
parameter estimates were significant, with the t-values
ranging from 3.70 to 7.79. All the t-values were significant (p < 0.01) (Hair et al. 1998). Moreover, nearly all
parameter estimates met or exceeded the threshold of 0.60
recommended by Bagozzi (1981), providing evidence of
convergence validity. The AVE ranged from 0.33 (for
customer turbulence), 0.50 (for competitor intensity), and
0.40 (for market growth potential). Whilst two of the
constructs had AVE values that did not meet the recommended threshold of 0.50 (Fornell and Larcker 1981),
they exhibited acceptable levels of reliability and face
validity. There was also evidence of discriminant validity
between the constructs. Looking at the correlations in
Table 1, it can be seen that the squared correlation between any pair of the three constructs does not exceed
either of the construct’s AVE.
Regression analysis was conducted to test the hypothesized relationships. Table 2 provides a summary of
the results.
Hypothesis 1 predicted that the greater the competitive intensity, the earlier the brand entry. Order of brand
entry is significantly and positively related to competitive
intensity (ß = 0.715, p < 0.01). Hypothesis 1 was supported.
Hypothesis 2 predicted that the greater the market
turbulence, the later the brand entry. Order of brand entry
is negatively and marginally significantly related to market turbulence (ß = -0.206, p < 0.10). While Hypothesis
2 could not be supported, it was marginally significant and
thus warrants future research. This will be discussed later.
Hypothesis 3 predicted that the greater the market
growth potential, the earlier the brand entry. Order of
brand entry is significantly and positively related to market growth potential (ß = 0.691, p < 0.01). Hypothesis 3
was supported.
Two of the four control variables were significant.
The results show a significant and negative relationship
Pearson Correlations and Descriptive Statistics
Order of Brand Entry
Competitive Intensity
Market Turbulence
Market Growth Potential
* p ≤ .01 (two-tailed test)
Regression Analysis: Standardized Regression Coefficients
Dependent Variable
Independent Variables
Order of Brand Entry
Control Variables
Brand development time
Quality of brand
Degree of similarity of brand
Business unit size
Direct Effects
Competitive Intensity
Market Turbulence
Market Growth Potential
Adjusted R2
* p ≤ .01; ** p ≤ .05; *** p ≤ .10 (one-tailed test)
American Marketing Association / Winter 2005
between brand development time and order of brand entry
(ß = -0.421, p < 0.05), and a significant and negative
relationship between quality of the brand and order of
brand entry (ß = -0.435, p < 0.05). These two significant
results will be discussed briefly later.
The purpose of the study was to empirically test
several hypotheses grounded in the literature regarding
some possible antecedents of order-of-brand entry strategy. The findings support our hypothesis that the attractiveness of the market influences a firm’s order-of-brand
entry strategy.
The study suggests several factors as important determinants of a firm’s order-of-brand entry strategy. First,
competitive intensity in a market appears to be an important determinant of early brand entry. In competitively
intense markets, a firm must be strategically aware that
their competitors are likely to enter earlier rather than
later, so this should be factored into a firm’s entry decision. A firm should recognize that entering such a market
earlier helps a firm generate switching costs and establish
barriers to entry through the development of strong brand
awareness and strong relationships with buyers and suppliers (Barney 1991). In addition, as Mueller (1997)
states, early-movers face lower costs than late entrants,
because they can disregard these sunk costs when making
strategic decisions, whereas later entrants must incur both
the sunk costs and any other costs in order to compete on
the same level as the early-movers.
Second, as market turbulence had only a marginally
significant impact on later brand entry, this warrants
further investigation. To the degree that future research
supports market turbulence as being an important determinant of order-of-brand entry, this suggests that a firm
should factor market turbulence into its entry decision.
Market turbulence reduces the attractiveness of a market
and increases the risks of entry for a new brand, in that it
becomes more difficult to accurately forecast the demand
potential for a brand (Sullivan 1991). Entering later in the
market allows a firm to free-ride on the investments made
by established competitors in the market, hence reducing
the financial risks of entry into such an unstable market
(Doyle 2000). Again, in this study, the marginally significant result should be interpreted with caution.
Finally, the results indicate that the growth potential
of the market is also an important determinant of early
brand entry. In markets with strong growth potential, a
firm must be aware of the likelihood of its competitors
entering earlier rather than later, thus indicating that a firm
must factor the market growth potential into its entry
American Marketing Association / Winter 2005
decision. A strong market growth potential denotes a
more favourable, attractive market, because it reduces the
risks of entry and increases the likelihood of a firm
capturing an early-mover advantage (Doyle 2000).
In sum, our results, taken together, suggest that market characteristics are indeed important drivers of orderof-brand entry. Therefore, a thorough knowledge of the
market is necessary to make an informed entry decision.
Importantly, these market characteristics will enable decision-makers to have a more complete understanding of
competitor reaction by enhancing the likelihood of correctly predicting their competitors’ entry decisions (Porter 1980). This knowledge may subsequently influence a
firm’s decision to enter earlier or later.
Two control variables, brand development time and
brand quality, were significantly and negatively related to
order-of-brand entry, thus indicating that both these variables are also important determinants of later brand entry.
Future research needs to be conducted in order to further
our understanding of the impact of these two variables on
order-of-brand entry.
There are some other possible avenues for future
research that would help to develop a more comprehensive understanding of the market attractiveness – orderof-brand entry relationship. Market turbulence was negatively and marginally significantly related to order-ofbrand entry. Further investigation of this relationship is
necessary to more fully understand the impact (if at all)
that market turbulence has on a firm’s order-of-entry
decision for a brand.
In addition, it seems desirable to include performance
indicators (such as return on investment, return on sales,
and market growth) in the model in order to empirically
determine the performance of the order-of-brand entry
strategies given a market’s competitive intensity, market
turbulence and market growth potential.
Also, by looking only at market attractiveness in this
study, this research has focused on the opportunities and
threats (i.e., external environment) that influence a firm’s
order-of-brand entry strategy. Including a firm’s resources
and capabilities in the conceptual model would help to
empirically determine how a firm’s strengths and weaknesses (i.e., its internal environment) affects the order-ofentry decision for a brand.
Finally, it would also be interesting to replicate this
study in the industrial goods industries to see whether the
attractiveness of a market plays an important role in
determining a firm’s order-of-entry decision for a brand in
these industries.
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American Marketing Association / Winter 2005
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Danielle A. Chmielewski
Department of Management (Marketing Program)
Alan Gilbert Building
The University of Melbourne
Parkville Vic 3010
Phone: +61.3.8344.1886
FAX: + 61.3.9348.1921
E-Mail: [email protected]
American Marketing Association / Winter 2005
Artur Baldauf, University of Bern, Switzerland
David W. Cravens, Texas Christian University, Fort Worth
Christian Bischof, University of Bern, Switzerland
Research attention has been given in several studies
to organizational culture, market orientation, innovation,
and organizational performance. Dimensions of culture
are potential antecedents to market-driven positional advantage which is expected to impact organizational performance consequences. Nonetheless, only limited research has considered the simultaneous antecedent and
consequence relationships. In the focal construct we view
positional advantage as a multi-dimensional construct
consisting of market intelligence, innovativeness, and
learning and development. The proposed organizational
culture antecedent dimensions are market focus, participative decision making, support and collaboration, and
power sharing. We also relate the focal construct to
desired consequences and argue that a market-driven
positional advantage positively impacts market performance, profitability, and sales growth.
The organizational culture, positional advantages,
and performance conceptualization adds to prior cultural,
market orientation, and performance research in the following ways: (1) cultural and process perspectives of
market orientation are considered in an antecedent consequence context; (2) positional advantage which could be
termed as a receptivity to innovate is conceptualized as a
three dimensional construct consisting of market intelligence, innovativeness, and learning and development;
and (3) a multi-dimensional view of organizational performance is examined in terms of culture and innovation
We view organizational culture in terms of widely
shared and strongly held values and belief systems and
consider the higher level construct as a source of competitive advantage. Our market-driven positional advantage
dimensions are proposed to capture relevant dimensions
of the capacity to innovate, and represent a more comprehensive reflection of innovative behavior than is considered in prior research. Based on our conceptual logic we
specifically interested in examining the following cultural
and positional advantage hypotheses:
American Marketing Association / Winter 2005
Hypothesis 1: There is a positive relationship between (a) market focus, (b) participative decision
making, (c) support and collaboration, (d) power
sharing and market intelligence.
Hypothesis 2: There is a positive relationship between (a) market focus, (b) participative decision
making, (c) support and collaboration, (d) power
sharing and innovativeness.
Hypothesis 3: There is a positive relationship between (a) market focus, (b) participative decision
making, (c) support and collaboration, (d) power
sharing and learning and development.
Market intelligence, innovativeness, and development and learning positional advantages are expected to
have a positive impact on the market and financial performance of the business unit. We offer the following hypothesis:
Hypothesis 4: There is a positive relationship between (a) market intelligence, (b) innovativeness,
and (c) learning and development and market and
financial performance of the business unit.
The data for examining the hypotheses were collected from senior managers employed by companies in a
German-speaking business environment. The sampling
objective was to include a wide range of larger firms in a
wide range of different businesses. A judgment sampling
procedure was applied to identify candidate companies.
We utilized a standardized questionnaire which was pretested for wording and understanding before final mail
distribution. After several follow-up activities we received 204 usable questionnaires were returned reflecting
a response rate of 21 percent. Established multiple item
measures were used for the ten construct measures which
we purified applying state-of-the art methodologies. Acceptable reliability and validity of the scales was indicated. Besides investigating the above stated direct relationships we also controlled in our path models for potential effects of customer type and company size on the
organizational culture and positional advantage relationships. In addition, market turbulence, competitive intensity, and technological turbulence were included as moderators for the positional advantage and performance
relationships. Regression analysis was used to test the
The results for H1, H2, and H3 are encouraging but
mixed. Market focus and participative decision making
are strong predictors of market intelligence, innovativeness,
and learning and development. Power sharing is only a
predictor of learning and development; support and col-
laboration has no significant impact on the positional
advantage dimension.
Higher market intelligence activities result in higher
market, profitability, and growth performance. Innovativeness positively impacts profitability but not market
and growth performance. Learning and development positively impacts all three performance consequences. Hence
we find partial support for H4a and H4c and mixed
support for H4b. The moderating effects of the environment constructs are not supported.
For further information contact:
Artur Baldauf
Management Department
University of Bern
Engehaldenstrasse 4, 3012 Bern
Phone: +41.31.631.5331
FAX: +41.31.631.5332
E-Mail: [email protected]
American Marketing Association / Winter 2005
Christian Homburg, University of Mannheim, Germany
Andreas Fürst, University of Mannheim, Germany
Despite substantial benefits of an effective complaint
management, there is ample evidence that many organizations do not handle customer complaints appropriately.
Instead, organizational members often exhibit an apparently irrational and dysfunctional defensive behavior towards complaints. This paper aims at providing a theoretical explanation for this phenomenon. Furthermore, based
on a dyadic data set, it analyzes antecedents and consequences of the prevalence of defensive organizational
behavior towards complaints (DOB).
Conceptualization of DOB
Based on individual psychology and organizational
theory as well as in line with literature on organizational
behavior and complaint management, we argue that individuals in organizations perceive customer complaints as
a source of actual or potential threat to self-esteem,
reputation, autonomy, resources, or job security. Thus, in
order to protect themselves against this threat, they exhibit
different types of DOB.
Overall, we identify seven types of DOB that can be
assigned to one of the three following categories: complaint acquisition (i.e., isolation from complaints, hostile
behavior towards complainants), complaint transmission
(i.e., no/biased transmission of complaints to complaint
managers, no/biased transmission of complaints to senior
managers), and complaint utilization (i.e., no/inadequate
handling of complaints, no/inadequate analysis of complaints, and no/inadequate use of complaint information
in decision making).
Our data analysis is based on 110 dyads. Each dyad
consists of a managerial assessment of the antecedents
(i.e., customer orientation of human resource management (HRM), customer orientation of corporate culture,
prevalence of negative attitudes towards complaints) and
types of DOB in the focal company and five customer
assessments related to their post-complaint responses
(i.e., complaint satisfaction, overall customer satisfaction, perceived complaint-based improvements, future
American Marketing Association / Winter 2005
complaint intention), representing the consequences of
With respect to the (direct and indirect) antecedents
of the prevalence of DOB, the results of our study support
the prediction that the prevalence of negative attitudes
towards complaints is negatively affected by customer
orientation of HRM and customer orientation of corporate
culture, respectively (p < .01). Moreover, as suggested,
the prevalence of negative attitudes towards complaints,
in turn, has a positive effect on the prevalence of DOB (p <
.01). In addition, our results provide evidence for the
prediction that the prevalence of DOB is also (directly)
negatively affected by customer orientation of HRM (p <
.01). However, we fail to find statistical support for our
assumption that the prevalence of DOB is too (directly)
negatively influenced by customer orientation of corporate culture (p > .10).
Furthermore, all hypotheses related to the consequences of the prevalence of DOB are confirmed by the
data. More specifically, the prevalence of DOB is found
to have a negative effect on complaint satisfaction as well
as on perceived complaint-based improvements (p < .01).
Moreover, we observe that complaint satisfaction positively influences overall customer satisfaction and future
complaint intention, respectively (p < .01). In addition,
our findings confirm a positive impact of perceived complaint-based improvements on overall customer satisfaction as well as on future complaint intention (p < .01).
Research Issues
First, drawing upon individual psychology and organizational theory, we provide a theoretical explanation for
the phenomenon of DOB.
Second, our study provides evidence for the high
relevance of this phenomenon. More specifically, we
show that the presence of DOB has a significant negative
impact on customers’ complaint satisfaction and on the
ability of the firm to learn from complaints (i.e., the
implementation of complaint-based improvements).
Third, our research provides an understanding of the
forces within an organization that can influence DOB. A
particularly strong influence on the prevalence of DOB
comes from the customer orientation of HRM.
Managerial Implications
Our research also provides guidance for managers on
how to improve a firm’s complaint management. More
specifically, the findings of our study suggest that managers should strive to reduce the prevalence of DOB in their
company. This can be done in two ways:
First, managers can work directly on this phenomenon. Our conceptualization of DOB (i.e., the identification of seven different types) provides managers with a
checklist type of structure. Based on this structure, they
can analyze the prevalence of DOB in their company and,
in turn, initiate activities to reduce this behavior.
Second, managers may also work on the antecedents
of the prevalence of DOB. In this context, the customer
orientation of a firm’s HRM is particularly important.
For further information contact:
Christian Homburg
Marketing Department I
University of Mannheim
L 5-1
68131 Mannheim
Phone: +49.621.181.1555
FAX: +49.621.181.1556
E-Mail: [email protected]
American Marketing Association / Winter 2005
Clay M. Voorhees, Florida State University, Tallahassee
Michael K. Brady, Florida State University, Tallahassee
David M. Horowitz., Florida State University, Tallahassee
While most service recovery strategies have focused
on customers that actively complain to the firm, it has been
suggested that these customers represent only the “tip of
the iceberg” (Diener and Greyser 1978, p. 22). This means
that the majority customers that experience poor service
simply exit the encounter and managers receive no opportunity to recover. Davidow (2003) suggests that in order
to fully understand customer behavior in failed encounters a study must be forwarded that investigates the
responses of the consumers that do not register complaints.
In an effort to address this critical gap in the literature,
the current study conducts a comprehensive comparison
of groups of customers that opted not to complain and
those that registered a complaint to the firm. The comparisons are made across repeat purchase intentions and a
number of negative outcome variables. It is hypothesized
that consumers that end a failed encounter with a satisfactory recovery are most likely to return to the service
provider. Moreover, consumers that simply exit a failed
encounter may demonstrate more favorable intentions
toward the firm than those that opt to complain and
experience poor recovery efforts.
The analysis reveals significant differences between
the different consumer groups with respect to their repeat
purchase intentions and several negative outcomes variables. Specifically, the results confirm the hypotheses and
demonstrate that consumers that receive a satisfactory
recovery effort have the most favorable intentions toward
a firm. Following this, noncomplainers demonstrate the
next most favorable intentions. Finally, consumers that
complain but receive a dissatisfactory recovery effort are
least likely to return to do business with a service provider.
Ultimately, the findings offer significant implications for both service researchers and managers. In particular, the results provide further justification for research on service recovery strategies as it appears that
poor recovery efforts can be costly to a firm. References
are available upon request.
For further information contact:
Clay M. Voorhees
Department of Marketing
Florida State University
Tallahassee, FL 32306–1110
Phone: 850.645.1519
FAX: 850.644.4098
E-Mail: [email protected]
American Marketing Association / Winter 2005
Felix T. Tang, The Chinese University of Hong Kong, Hong Kong
Consider a dinning scenario in which your server has
completely forgotten your order. How do you feel? This
is an outcome failure and the extant literature predicts that
you will become dissatisfied, and you may also engage in
negative word-of-mouth and exit behaviors. What if your
server collapses into tears in front of you after finding out
that he/she has completely forgotten your order? Would
you feel sympathetic towards the server despite of the
service failure? Would you abandon your resentment
towards the service provider? In such situation, consumers might feel empathetic and behave in a merciful way
towards the server even if there has not been a word of
apology or compensation.
Although this scenario may be pushing the limits, it
exemplifies a boundary condition where the concepts of
justice, equity, fairness, disconfirmation, and attribution
are not adequate to explain all consumer behaviors. The
traditional view downplayed consumers’ ability to selfrestore satisfaction, ignored consumers’ consideration for
other’s welfare, and overlooked the effect of positive
emotions on post-recovery evaluation.
Prosocial Behavior and Forgiveness
Prosocial behavior research in psychology suggests
consumers may look beyond their own well being (Batson
et al. 1995). Prosocial behavior is broadly defined as
“social behaviors oriented to benefit another, regardless
of potential outcomes for oneself” (Miller, Kozu, and
Davis 2001). Such behavior includes but not limited to
donating, forgiving, helping, sharing and volunteering.
Philosophers, such as Hume (1949), considered prosocial
behavior as moral actions of human instinct. Of the
various prosocial behaviors, forgiveness is one of the
most relevant concepts in the service marketing context.
Modern philosophers, such as North (1987), agreed that
the central theme in forgiveness involves replacing resentment with beneficence. Using McCullough, Pargament, and Thoresen’s (2000) definition, forgiveness is an
intraindividual and prosocial change toward a perceived
The most proximal determinant of forgiving of forgiveness is empathy (McCullough et al. 1998). Empathy
American Marketing Association / Winter 2005
reflects a concern for others and incorporates the concepts
of sympathy, compassion, and tenderness (Batson 1990).
When people feel empathy towards the transgressor, they
are more likely to forgive him/her (McCullough et al.
1997, 1998). Such evidences have been found across
demographics variables, across cultures, and across contexts (Eisenberg and Miller 1987). Thus, consumers are
capable of displaying prosocial behavior, even if such
behaviors may not be directly beneficial. The concept of
empathy has also been discussed by Parasuraman et al.
(1988), Tax et al. (1998), but the conceptualization is
quite different in this paper. While Parasuraman et al.
(1988) and Tax et al. (1998) saw consumers as recipients
of empathy, this paper advocates the possibility for consumers to be givers of empathy.
Observational set and perceived similarity are the
two most relevant antecedents in the service recovery
context. Observational set is the focal of one’s attention
and it can be instructed or cued. When people focus on the
needy other’s emotional state or perspective, they are
more likely to feel empathetic towards those who are in
need than when people focus on the facts (Eisenberg and
Miller 1987). Perceived similarity concerns one’s perception of the resemblance between oneself and a comparison
object. In their meta-analysis of sixteen studies, Miller
et al. (2001) concluded that perceived similarity with
another was associated with or led to feelings of empathy
or sympathy.
Forgiveness as Consumer Behavior
What marketers are doing during service recovery
are essentially wooing for consumer forgiveness with
compensation and apology, asking consumer to replace
resentment (e.g., dissatisfaction) with beneficence (e.g.,
satisfaction). The two consequents of forgiveness, lower
avoidance and lower revenge, are also strikingly similar to
the marketing consequents of successful service recovery
(e.g., increase repatronage and lower negative word-ofmouth activity). Thus, forgiveness is a valid, alternative
perspective of service recovery.
Based on insights from prosocial behavior research,
six hypotheses are postulated and are summarized in
Figure 1. Due to space constraint, the hypotheses and their
development are not discussed here. The Figure should be
An Empathy-Forgiveness Model in the Context of Service Failure
Negative WOM
self-explanatory (the positive and negative signs indicate
the predicted directions of relationship) and the logics
flow from the discussion above.
our ability to explaining consumer behavior; (3) postulate
a new perspective by seeing service recovery efforts as
attempts to seek consumers forgiveness.
No doubt, the concept of justice, equity, fairness,
disconfirmation, and attribution remain the cornerstones
of our understanding on consumer behavior in the recovery process. However, let us not blindly rely only on these
concepts for they do not give us a complete picture of
consumer behavior. References available upon request.
This paper aims to (1) call for attention to the limitations of the current views and theories on service recovery; (2) introduce the concepts of prosocial behavior,
empathy, and forgiveness into service recovery to broaden
For further information contact:
Felix Tang
Department of Marketing
The Chinese University of Hong Kong
Hong Kong
Phone: 852.9678.5958
FAX: 852.2603.5473
E-Mail: [email protected]
American Marketing Association / Winter 2005
Sengun Yeniyurt, Michigan State University, East Lansing
Janell D. Townsend, Michigan State University, East Lansing
Erin Cavusgil, Michigan State University, East Lansing
Collaborative ventures are an indispensable tool for
executives in the quest for achieving a sustained competitive advantage in the marketplace. The significance of this
instrument is evidenced by a marked increase in the use of
cooperative arrangements as a business form, and the
variety of studies related to this phenomenon. The boundaries of what define the marketplace, however, have
evolved in ways previously unimaginable. The world has
become more integrated in terms of infrastructure and
dependence; the drivers of these global trends leave few
industries untouched by the increased velocity and intensity of competition for resources and customers (Wolf
2000). In this domain, collaboration has become an indispensable means through which firms are able to respond
to environmental turbulence (Achrol 1991), effectively
extending the reach and resources they would not have
otherwise. The use of alliances in marketing and international contexts is inextricably linked.
This complex phenomenon encompasses dynamic
aspects of the competitive environment and various perspectives of firm behavior. As firms collaborate to compete (Ohmae 1989a), the relative population of potential
partner firms remains somewhat static over time, eventually leading to competition for collaboration in an industry. What remains to be discerned is the nature of the
competition for alliance partners, particularly in light of
the increased environmental turbulence and diversity
established by the globalization of industries (Achrol
1991). Additionally, experiential learning is posited to be
fundamental to a firm’s ability to accumulate knowledge
(Huber 1991; Sinkula 1994) and conduct international
operations (Cavusgil 1980; Johanson and Vahlne 1977);
yet, empirical findings supporting this position remains
sparse. While the literature generally proposes cultural
distance as a significant factor in the internationalization
process (Johanson and Vahlne 1977; Johanson and
Weidersheim-Paul 1975; Kogut and Singh 1988), recent
findings do not support this proposition with respect to
international market entry timing (Mitra and Golder 2002).
The question remains as to whether the diversity of
cumulative culture distance experiences affects an
organization’s inclination toward future international collaborative ventures. This study contributes to the literature through the reconciliation of these perspectives by
American Marketing Association / Winter 2005
uncovering the effects of competition for collaboration,
experiential learning and culture distance on the propensity to engage in a specific mode of entry: international
marketing alliances.
A co-evolutionary dynamic framework is introduced
as a means to understand the complex phenomena involved in forming international marketing alliances. The
advantages derived from international marketing alliances are first explored based on the concepts of resource
complementarities and extension. In order to reveal the
consequences of the intensity of collaboration and company experience on international collaborative venture
formation in the global marketplace, we draw on the
organizational ecology perspective. Further, we employ
the concepts of organizational learning and the assumptions of the internationalization process to delineate the
effects of experience and culture on international collaborative ventures.
The hypotheses are tested through the analysis of the
global marketing alliance activity announced by U.S.
pharmaceutical firms from 1984 to 2003; this includes
792 international marketing alliance formations engaged
by 317 firms. An event history was constructed for each
U.S. pharmaceutical company starting with the date of its
first international marketing alliance. The data were arranged into yearly spells updated when an event occurred
and at the end of each year to account for the changes in
variables. A continuous time event history analysis with
time varying covariates was employed in order to estimate
the effects of the independent variables on the probability
of a company engaging in a new international alliance.
The findings of a Cox hazard rate model support the
hypothesized effects of legitimation and competition,
sustaining the assumptions of organizational ecology,
extending the theory to the global context of inter-firm
relationships. Particularly important to the literature is
that companies are eager to follow their competitors in the
early stages of industry level internationalization utilizing
marketing alliances as a mode of entry; yet once a critical
mass of international marketing alliances is attained in the
industry, the propensity to engage in alliances declines.
Our results provide strong support for the proposition that
companies learn from their international alliance formations. Cultural distance is a significant factor in interna94
tional marketing alliance engagement, as the cumulative
cultural distance of previous alliances increases the likelihood that a company will engage in a future international
marketing alliance. Previous studies have only considered the effect of culture distance experience in specific
markets, as opposed to the impact of the diversity of
cumulative cultural distance experiences on an organization’s inclination toward future actions. Finally, organizational size has a positive effect on the propensity to engage
in a new international marketing alliance. References are
available upon request.
For further information contact:
Sengun Yeniyurt
Department of Marketing and Supply Chain Management
The Eli Broad Graduate School of Management
Michigan State University
N370 Business College Complex
East Lansing, MI 48824
Phone: 517.353.6381
FAX: 517.432.4322
E-Mail: [email protected]
American Marketing Association / Winter 2005
Patrick Lentz, University of Dortmund, Germany
Deepak Sirdeshmukh, North Carolina State University, Raleigh
Ed Nijssen, Radboud University, The Netherlands
Hartmut H. Holzmüller, University of Dortmund, Germany
Jagdip Singh, Case Western Reserve University, Cleveland
Broadly, two fundamental mechanisms are relevant
for understanding the dynamics that promote or impede
consumer-firm market exchanges in a global society of
networked economies. One fundamental mechanism focuses on the ongoing exchanges between individual consumers and sellers, and involves understanding the motivations for each party to enter into, consummate and
continue market exchanges, from here on referred to as
micro mechanism (e.g., Nicholson, Compeau, and Sethi
2001). A second fundamental mechanism focuses on the
embeddedness of market exchanges and involves understanding the social and market context that provides an
arena for individual consumer-firm exchanges to occur,
referred to as macro mechanism (e.g., Shapiro 1987;
Zucker 1986). Few if any studies have focused on the
macro mechanisms of individual consumer-firm exchanges, which is particularly troubling since different
markets around the globe are likely to vary both in terms
of their micro and macro mechanisms.
Conceptual Background and Research Hypotheses
We draw from extant literature to develop a micro
model of Satisfaction-Trustworthiness-Trust-Value-Loyalty (ST 2VL) relationships (e.g., Liu, Furrer, and
Sudharshan 2001; Sirdeshmukh, Singh, and Sabol 2002).
Regarding the larger context in which exchanges occur,
we draw from sociology (Shapiro 1987; Zucker 1986) and
economics (Hirschman 1970; Nooteboom, Berger, and
Noorderhaven 1997) to define market milieus. These
involve consumers’ and sellers’ expectations regarding
the norms governing customer-firm interactions in a given
market. Market milieus thus refer to the dominant and
shared normative structure that forms the context for
consummating exchanges between providers and their
customers. As Kramer (1999) notes, in the absence of
specific knowledge about each other, consumers and
firms can revert to formal rules at one end of a continuum
to mutual relationships at the other end, to solve their
problem or uncertainty. We thus define two dominant
configurations of market milieus, that is, rule-based (characterized by contracts, detailed legal environments, and
American Marketing Association / Winter 2005
other control mechanisms) and relationship-based (characterized by reciprocity, fairness, and personal exchange
processes) market milieus. We propose hypotheses regarding the effects of market milieus on micro relationships, mainly drawing from Granovetter (1985), Kollock
(1994), and Zucker (1986):
H1: Consumers’ perceptions of exchange value and satisfaction will be significantly higher in rule based
market milieus, relative to relationship based market
H2: Consumers’ judgments of trust will be significantly
higher in relationship based market milieus, relative
to rule based market milieus.
H3: Consumers’ loyalty intention judgments will not
vary significantly for different configurations of
market milieus.
H4: Relative to relationship based market milieus, the
influence of consumers’ satisfaction and value judgments on loyalty will be significantly higher in rule
based market milieus.
H5: Relative to rule based market milieus, the influence
of consumers’ trust judgments on loyalty will be
significantly higher in relationship based market milieus.
Research Design
Two different samples were used to test the hypotheses. First, we collected a consumer sample regarding the
individual-level dynamics between satisfaction, trustworthiness, trust, value, and loyalty with their insurance
company (n = 365, 504, and 316 for the U.S., Germany,
and the Netherlands, respectively). Second, a separate
consumer sample was used to evaluate the macro environment, i.e., the market milieus at the industry level in the
same three countries (n = 18, 30, and 31 for the U.S.,
Germany, and the Netherlands, respectively), which helped
circumvent method bias. To test our hypotheses, the two
types of data were joint in an hierarchical type of analysis
using both mean analyses and multiple-group SEM, with
the three countries as separate groups. Items for analyzing
the micro environment have been adapted from existing
literature, whereas items capturing the level of rules and
relationships have been developed for the purpose of this
study, and pretested using “think aloud” exercises with
small convenience samples. The measurement model
evidenced good levels of reliability and validity.
and partial support for H1, since only value shows higher
levels in rule based relative to relationship based market
milieus; however, H2 cannot be supported. Third, turning
to the moderating effects of market milieus, we find
partial support for H4 and H5. While both satisfaction and
trust in frontline employees differ in their influence on
loyalty according to our hypotheses, trust in management
policies and practices as well as value do not.
Our analysis revealed substantial and statistically
significant differences across the three market milieus at
the macro level. We found that the U.S. insurance market
milieu is more relationship based, the German insurance
market is rule based, and the milieu of the Dutch insurance
market is located between the two extreme positions.
Although additional differences were found in the micro
model relationships between countries, the more interesting result is related to the influence of market milieus.
First, the macro level variables add significantly to model
fit. Second, regarding direct effects of market milieus on
exchange-specific constructs, we find full support for H3
Our study results demonstrate that examining consumer-firm relationships in situ is a promising approach
for better understanding exchange relationships, particularly when considering markets in different countries.
This extends contemporary understanding of the exchange
dynamics and thus provides both theoretical and managerial relevance. The results clearly reveal that an isolated
investigation of micro mechanisms is inappropriate, especially in cross-cultural settings. We believe that our work
enhances the knowledge of macro effects on micro mechanisms by conceptualizing and empirically demonstrating
the different effects. References available upon request.
For further information contact:
Patrick Lentz
Department of Marketing
University of Dortmund
Otto-Hahn-Str. 6
D-44227 Dortmund
Phone: +49.231.755.3277
FAX: +49.231.755.3271
E-Mail: [email protected]
American Marketing Association / Winter 2005
Stephen J. Grove, Clemson University, Clemson
Les Carlson, Clemson University, Clemson
Michael J. Dorsch, Clemson University, Clemson
Christopher D. Hopkins, Clemson University, Clemson
Since its inception, Integrated Marketing Communication (IMC) has been viewed as a valuable concept by
marketing practitioners (McArther and Griffith 1997).
IMC has been characterized as the coordination of communication tools (e.g., advertising, publicity, sales promotion, etc.), for a brand. A review of this phenomenon in
practice uncovers three broad categories including IMC
as “integrated communication,” IMC as “one voice” communication and IMC as a “coordinated marketing communication campaign.” This study focuses on the integrated communication approach because it appears to be
the one most often used in practice. Relative to services,
it is argued that advertising in this area should be characterized by a greater presence of IMC than the advertising
of physical goods. This is largely do the fact that IMC may
provide a mechanism that addresses some of the problems
associated with marketing a product the customer has
difficulty comprehending clearly and thus, may alleviated
a degree of perceived risk.
This study empirically investigates the utilization of
IMC across product type and over time. It is expected that
there is greater usage of IMC among sellers of services
than among sellers of goods. It is also expected that the
usage of IMC has grown over the years, reflecting its
increased emphasis in the marketing discipline. To measure the nature and incidence of IMC, the study focuses on
its manifestation at the tactical level.
A research design was employed to compare services
print advertisements and goods print advertisements on
their degree of integration and the trend towards integration over time. First, a sample of services and goods print
advertisements was generated to obtain a wide range of
advertising messages over three different time periods.
Next, a data collection process was established for extracting data from each print advertisement. The data
extraction process consisted of two steps. During the first
step, content analysis of each print advertisement was
conducted in order to profile it in terms of the communication tools that it employed. During the second step, the
profiled print ads were re-examined to determine the
extent to which they were integrated. This two-step process produced a data set consisting of count data. Once the
data set was created, the data were examined using both
inferential and descriptive analyses.
Results indicate that while IMC is a reality among
both services and physical goods advertisements, IMC
was found to exist in services advertising to a greater
extent relative to goods advertising. Moreover, the incidence of IMC at the advertisement level, regardless of the
product type that is being advertised, has not increased
significantly over recent years. As a result, there appears
to be much room for further and more enlightened adoption of IMC principles. References available upon request.
For further information contact:
Christopher D. Hopkins
Department of Marketing
College of Business and Behavioral Science
Clemson University
233 Sirrine Hall, Box 341325
Clemson SC, 29634–1325
Phone: 864.656.3952
FAX: 864.656.0138
E-Mail: [email protected]
American Marketing Association / Winter 2005
Dafina Rexha, The University of Western Australia, Australia
Katherine Mizerski, Edith Cowan University, Australia
Richard Mizerski, The University of Western Australia, Australia
Childhood obesity has tripled in the U.S., U.K., and
Australia in the past decade with one in four children now
being classified as overweight or obese (Azhar 2004; de
Brito and Segal 2002). These children are more likely to
develop health problems such as diabetes, asthma, cardiovascular disease, joint problems, back pain, and psychological problems (Anthony, Patterson, and Kemp 2002;
Cameron et al. 2003).
There are a number of factors thought to contribute to
the “obesity epidemic” (Time 2004) with increased consumption of energy-dense foods and decreased levels of
physical activity, receiving most of the blame (Waters and
Baur 2003). Advertisers of these energy-dense foods and
fast foods have come under scrutiny and are accused of
targeting their products directly to children. This targeting
has led for a call to ban food advertising during children’s
programmes in a number of countries (Canning 2004) and
has forced manufacturers to re-evaluate their offerings.
Recently, a new culprit has been identified as a
contributor to childhood obesity. It has been suggested
that schools, that routinely educate children about good
nutrition in the classroom, have failed to send the right
messages from their school canteens. A study by Which?
Magazine (2003) found that school canteen offerings read
more like fast food menus and contributed less than one
portion of fruit and vegetables to a child’s daily intake.
This has led to criticism being levelled at schools for
failing to fulfil their duty of care towards students by
providing “unhealthy” food choices (Stanton 2002; Wallis
With one third of all children’s meals coming from
outside the home and more than half (52%) of these being
consumed at school, many food preferences and food
acceptance patterns are developed in schools (Birch 1999;
Story 2002). Schools are also a critical component of the
child’s social environment and play a significant role in
shaping children’s food preferences and eating behaviours
(Baxter 1998). Not only are children reinforced through
their own choices at school, they are also affected by the
choices of their peers (Kubik et al. 2003). This peer
American Marketing Association / Winter 2005
influence and socialisation can have a significant impact
on children’s first purchasing decisions.
School canteens are one of the first places where
children are faced with the decision of what food to
purchase by themselves. Usually parents give their children money to purchase from the school canteen. The
parents, however, are not present at the time the purchase
decision is made.
Many suggest that an immediate change in the school
food and nutrition environment needs to occur (Stitzel
2003; Wallis 2004) so that schools are healthy environments where the food related policy of the canteen allows
children the opportunity to make healthy choices (Baxter
1998; Conento et al. 1995). O’Dea (2003), in her research
into children’s eating practices, identified convenience,
taste and social factors as barriers to healthy eating. The
children in the study noted, however, that they would eat
what was available and “allowed.” This would suggest
that if healthy food were available for children to purchase
and eat at school, they would do so. There is a lack of
research, however, on how to create this change and how
to encourage children to eat healthier. The current study
attempts to fill this gap and provides the results of a
multiple observation period experiment undertaken at a
primary school canteen in Australia. The experiment was
designed to determine the effects of sampling, subtle
promotion, and availability of healthy food in children’s
preferences and purchases of canteen food.
The sample consisted of 166 children in grades one to
four. Each child who purchased food from the canteen
during recess was observed and their food choices recorded. After obtaining a baseline of existing product
sales, Smoothies, a healthy food choice consisting of
strawberries, skim milk, and orange juice, were made
available as a new option. This new option was supported
with point of purchase promotion in the form of a large
poster at each window. In addition, two of the classes were
provided with samples prior to recess.
The results support previous research into the effect
of advertising on children’s preferences but go beyond
this to look at the effect of alternative promotional tools on
actual purchase. While the point-of-purchase ad did have
the effect of increasing sales, sampling, an often used tool
in adult food purchases (e.g., Fazio 1986; Smith and
Swinyard 1980), was not as effective. Although more
children who had sampled ultimately purchased, the differences were not significant.
Evidence from the study suggests that the availability
and promotion of a healthy food product can reduce the
purchase and consumption of other “less healthy” options. This effect, however, was short-lived. The rebound
of these less healthy options in the absence of promotional
tools may provide a strategy for long-term behavioural
change. If schools are serious about encouraging good
eating habits, and joining the fight to reduce childhood
obesity, perhaps they need to consider the use of “promotional” materials. Given that most schools provide infor-
mation in class on nutrition, these promotional tools could
serve as reinforcement for the educational message.
Although the findings of the current study are based
on children’s choice behaviour in a school canteen setting, the findings may be generalizable to a broader venue.
As canteens are one of the first places where children can
make independent food choices, the results of this study
can be used by other outlets where children make choices
(i.e., fast food outlets). The results can provide valuable
information for managers of food outlets that target children and for producers of food targeted at children. By
providing information on healthier options, food advertisers may be able to circumvent restrictions on advertising
during children’s programs. References available upon
For further information contact:
Katherine Mizerski
Edith Cowan University
Pearson St.
Churchlands 6018
Western Australia
E-Mail: [email protected]
American Marketing Association / Winter 2005
Claire Lambert, University of Western Australia, Australia
Richard Mizerski, University of Western Australia, Australia
The Fast Food Industry has come under extensive
criticism for its “junk food” content and its aggressive
marketing to children (Sieders and Petty 2003). The use of
extensive advertising to children and toys as premiums are
alleged to cause young consumers to develop poor eating
habits, become overweight or obese, and labor under
long-term health problems due to a diet of too much Fast
Food (Dore, Harris, and Whittaker 2002; WHO 2003;
McKimmie 2004).
New restrictions, including warning labels on fast
food meal packaging, the banning of advertising to children, and eliminating promotions that involve toys as
premiums, are being studied by some Australian States
and their Federal Government in order to tackle rising
obesity in young Australian children (Cumming 2002).
Similar sentiments have been expressed in the United
States and the United Kingdom, where there are initiatives
to restrict or ban fast food advertising and promotion
aimed at young consumers (Banzhaf 2003; Barboza 2003;
House of Commons 2004). There are present bans on
“junk food” advertising during children’s television programs and restrictions concerning the type of premiums
used in five other countries (Lambert and Mizerski 2003).
The success of premium based promotions appears
rare for many product categories, with consumer participation rates often reported as one percent or less of a
brand’s buyers (Schultz, Robinson, and Peterson 1993).
However, the experience of fast food retailers is quite
different (Taylor 2001). McDonalds, Burger King, and
Wendy’s lead all other companies in the use of premiums
in their promotions. Most of their premiums appear to be
aimed at children, with some Fast Food retailers beginning their targeting to three years olds (AFA 2001).
Critics of the Fast Food Industry (Schlosser 2001;
WHO 2003; McKimmie 2004) charge that the special
allure of toy type premiums, and the sheer volume of their
use, may train young and naïve children into repeatedly
requesting or purchasing Fast Food meal items. The
promotion of these meals frequently feature cartoon character premiums tied into television programs or movies in
their advertising and sales promotion (Spethmann 2002).
The repeated use of heavily promoted premiums is assumed to build Fast-Food brand and category loyalties
American Marketing Association / Winter 2005
among children. However, few of the three to seven year
old consumers that are targeted actually purchase the
premiums. Because independent visits to Fast Food restaurants appear rare before the age of eight, the vast
majority of toy premiums are bought by adults. It is
assumed that adults purchase Fast Food premiums after
being “pestered” by the child to obtain the items
(McKimmie 2004).
The most effective time for a child to request a Fast
Food toy premium would appear to be at the Fast Food
restaurant, where the decision is made and the retail
environment showcases the product. One would expect
that meal buyers accompanied by a child to a Fast Food
facility, would have a greater probability of purchasing a
cartoon toy premium aimed at that child than a buyer
without a child with them (AFA 2001). Fast Food and
brand past purchase frequency and perceived value of the
premium were also tested for an effect in the premium’s
The research was conducted using a field experiment
at a major Fast Food brand’s retail facility located in the
Perth, Australia metropolitan area. The promotion was a
four-week long continuity premium promotion that offered 16 versions of a Snoopy plush toy. The campaign
included local media advertising that almost exclusively
aired on children’s television, as well as point-of-purchase material meant to generate awareness and intentions to visit the fast food retail operations.
The study used a cross-section sample of meal buyers
that were personally interviewed over three time periods
to investigate the effect of the Snoopy premium on consumer decision-making and purchase in this category. A
total of 50 surveys were completed per day (n = 100 per
weekend) over three periods, and sampled meal buyers
that visited the Fast Food facility in-store, during the
weekend lunch period.
It was found that the accompaniment of children with
the meal buyer was not a significant effect in the purchase
of a Snoopy cartoon toy premium, nor for the number of
Snoopy premiums reported purchased in the past. Buyers
of the premium provided a significantly higher mean
value of the Snoopy premium than non-buyers of the
premium, but these values were significantly lower if the
buyer was accompanied by a child or children. However,
there were no differences in the groups’ perceived value
of the Snoopy premium if pre-campaign respondents’
mean estimation of the premium’s value was included in
The effect of previous purchase of the Snoopy premium, not purchase of the brand of Fast Food, was a
significant effect in buying the Snoopy premium on the
visit that was surveyed. In addition, the reported purchase
of the premium reflected a distribution not significantly
different from the Negative Binomial Distribution often
observed with fast moving consumer package goods and
gambling products (Mizerski et al. 2004). This suggests
that purchase of the continuity premium may have become habitual. This apparently habitual component was a
significant effect in repurchase of that premium, and
potentially more influential than the respondent’s perceived value of the premium.
The study’s results provide an insight into the effectiveness of children’s requests for Fast Food toy premiums targeted at them. The claims that cartoon-based
premiums necessarily lure children to a Fast Food restau-
rant should be re-evaluated as it appears they may tend to
primarily lure adults. These results suggest that potential
Public Policy interventions need to be aimed at the parents
and caretakers that largely make the purchase decisions
for what children eat. The need for bans on the use of
cartoon–based premiums targeted to the children’s market (cf., Sieders and Petty 2003; McKimmie 2004), needs
more evidence before causality can be assumed. Of course,
it may be that simple possession of a premium is enough
as reported by Pierce et al. (1998), but rejected by Lee
et al. (2004), in regard to finding of an effect of Tobacco
premiums in smoking initiation.
Researchers that have looked into the stochastic
pattern for fast moving consumer package goods have
argued (cf., Ehrenberg 1969) for there generally being
little or no effect of information processing or attitudinal
precursors in frequent choice behavior. Information-based
programs and remedies may be expected to be less effective than if the buyer of the premium was more cognitively
involved in the decision. Clearly, more research needs to
be conducted to see if these early findings can be replicated and explained. References available upon request.
For further information contact:
Richard (Dick) Mizerski
School of Economics and Commerce M261
The University of Western Australia
35 Stirling Highway, WA 6009
Phone: +618.6488.7210
FAX: +619.6488.1055
E-Mail: [email protected]
American Marketing Association / Winter 2005
Sweta Chaturvedi Thota, James Madison University, Harrisonburg
This paper identifies the factors that moderate the
relationship between multimarket contact and mutual
forbearance observed by firms that operate in multimarkets.
A framework is developed that identifies the market
factors that moderate the relationship between multimarket
contact and mutual forbearance. Specifically, the paper
discusses the moderating effects of factors, which arise
mainly due to the presence of dominant local players, on
the levels of mutual forbearance observed by firms. It is
proposed in this paper that the suggested moderating
factors would reduce the level of mutual forbearance
observed by firms when firms operate in multimarkets.
Multimarket competition is defined as a situation
where firms compete with each other simultaneously in
several markets (Karnani and Wernerfeldt 1985). This
situation is present in multiproduct industries or industries
with different geographic markets (Fernandez and Marin
1998). A better understanding of multimarket competition is of great importance to marketing strategy research
and practice because of the central nature of the issue of
interfirm rivalry to marketing strategy issues. Thus, it is of
extreme importance to firms that compete in multiple
markets to develop an understanding of the behavior of
other firms that operate in these markets. Further, in
formulating a strategy for multimarket competition, it is
important to consider the impact of various factors that
affect the level of competition between firms. Despite
attempts by past research to explore issues revolving
around multimarket competition, there is a dearth of
research that explores the roles of the various moderating
variables on the relationship between firms that engage in
multimarket competition.
Strategy researchers and industrial economists have
examined whether firms that engage in multimarket competition would compete aggressively against each other or
observe mutual forbearance (i.e., tacitly collude). Mutual
forbearance is a form of tacit collusion in which firms
avoid competitive attacks against the rivals they meet in
multiple markets (Jayachandran, Gimeno, and Vardarajan
1999). Interestingly, past research has argued both for and
against whether mutual forbearance is a deterministic
outcome of multimarket contact.
It is stressed here that although the relationship between multimarket contact and mutual forbearance has
been examined in prior research, the factors that moderate
American Marketing Association / Winter 2005
the relationship between multimarket contact and mutual
forbearance have not received adequate attention in extant literature. In this paper, the factors that moderate the
relationship between multimarket contact and mutual
forbearance are identified. The paper draws from gametheoretic propositions and hypercompetition literatures
and develops a framework that identifies the market
factors that moderate the relationship between multimarket
contact and mutual forbearance. It is proposed that the
various moderating variables would reduce the level of
mutual forbearance observed by firms when firms operate
in multimarkets. In this paper, primary market factors that
moderate the relationship between multimarket contact
and mutual forbearance are identified, which would help
in understanding and determining the relationship between multimarket contact and the mutual forbearance
observed by firms.
The paper discusses the moderating effects of factors
that arise mainly due to the presence of single-market
firms or dominant local players on the levels of mutual
forbearance observed between firms. The factors identified are the presence of single-market firms or dominant
local players, the level of competition triggered by dominant local players, and resource similarity between the
single-market firms and the firms operating in multimarkets.
The discussion in this paper, that describes the process through which multimarket competition influences
the intensity of competition and leads to reduced mutual
forbearance, has been represented in a framework. The
framework, demonstrates the role of moderating variables
that reduce mutual forbearance and heighten the intensity
of competition when firms operate in multimarkets.
The framework and propositions in this paper have
several research implications for managers and researchers. The impact of the several moderating variables on the
level mutual forbearance and, consequently, on the level
of competition between firms that operate in multimarkets
has been examined in this paper. The reduced levels of
mutual forbearance and the increased intensity of competition may have serious implications on the success of
multimarket firms and on the level of competition that
multimarket firms may face from a single-market firm or
a dominant local player operating in that market. This
study will help shed light on how managers of multimarket
firms should mentally map their market and determine
their rivals.
For further information contact:
Sweta Chaturvedi Thota
Department of Marketing
College of Business MSC 0205
James Madison University
Harrisonburg, VA 22807
Phone: 540.568.6817
FAX: 540.568.3587
E-Mail: [email protected]
American Marketing Association / Winter 2005
Pilsik Choi, University of Illinois, Champaign
Interfirm interactions have been extensively studied
in economics, marketing, strategic management, and organization theory. Over the last two decades, research on
interfirm interactions has evolved into two research
streams: one based on firms’ competitive behavior and the
other on firms’ cooperative behavior. Before the mid
1980’s, interfirm interactions were analyzed with great
emphasis on firms’ competitive behavior. This stream of
research was influenced by economic theory, which generally embraces intense competition. In the mid and late
1980’s, while other researchers dwell on the tradition of
firms’ competitive behavior, a number of researchers
turned their attention to the cooperative aspects of interfirm interactions. Since then, they have identified various
types of interfirm cooperation, e.g., symbiotic marketing,
co-marketing, strategic alliances, etc. All of these concepts emphasize cooperation between firms.
In the early 1990’s, sharing the similar background to
that of the concepts emphasizing cooperation, a new
concept, “co-opetition,” was created. Unlike the other
concepts, co-opetition (blend of cooperation and competition) focuses on both cooperation and competition at the
same time. The book, Co-opetition, by Brandenburger
and Nalebuff (1996) ignited the popularity of the concept.
The book has generated tremendous interest among practitioners and researchers. In light of the amount of interests in co-opetition, however, it is surprising that academic publication on co-opetition is very limited thus far.
Addressing this issue in the literature, this paper
attempts to investigate the nature of co-opetition. The
purpose of this paper is to review the literature related to
co-opetition and examine its antecedents and consequences. Specifically, this study attempts to address the
following questions: (1) What is co-opetition? (2) How
can it be classified? (3) Which firm characteristics cause
co-opetition? (antecedents), and (4) What benefits does
co-opetition generate for firms that adopt the concept?
Co-opetition is defined as the situation where a group
of competitors cooperate in activities associated with
creating mutual benefits while at the same time they
compete with each other in activities associated with
dividing up the benefits. Co-opetition is different from
symbiotic marketing, co-marketing, and strategic alli-
American Marketing Association / Winter 2005
ances mainly because it focuses on both cooperation and
competition with competitors simultaneously while the
other three focus only on cooperation with suppliers,
customers, competitors, and/or noncompeting firms. Competitors in this paper are defined as direct competitors who
are competing in the same market(s).
Co-opetition is categorized into channel co-opetition,
marketing co-opetition, and R&D co-opetition. Channel
co-opetition denotes a situation where one competitor
becomes the other competitor’s buyer or supplier or a
situation where one competitor uses the other’s distribution channels or production facilities while they compete
with each other in a final goods market. Marketing coopetition is a situation where direct competitors cooperate
for joint marketing efforts (e.g., brand alliances, joint
promotion, bundling, etc.) while they compete with each
other in the same market. R&D co-opetition occurs when
direct competitors join forces in research and development or other similar activities (e.g., joint new technology
development, joint industry standard development, etc.)
while they compete in other activities.
Drawing upon the literature on co-opetition, strategic
alliances, co-marketing, and symbiotic marketing, I identify complementarity, compatibility, managerial ability,
and competition level as antecedents of co-opetition.
Complementarity occurs when the pooled skills and resources can create excess value relative to their value
before the pooling. Since the cooperation part of coopetition requires mutual benefits, one partner should
have certain skills or resources that the other partner needs
in order for such cooperation to be formed. Thus, a high
level of complementarity between competitors will likely
lead them to enter into co-opetition. In this process,
technological change moderates the influence of
complementarity on co-opetition. Compatibility, which is
characterized as similarities in management style and
company culture, is another important factor for the
cooperation part of co-opetition. Although competitors
are complementary with each other, if they are not compatible in the areas where they cooperate, it is difficult for
them to cooperate with each other in those areas. Hence,
a high degree of compatibility between competitors will
likely lead them to engage in co-opetition. Management
ability is also an important factor for co-opetition formation. Management that has the ability to recognize skills
and resources it needs and seek those skills and resources
from other companies will more likely identify co-opetition
opportunities with other competitors that can provide
such skills and resources. Therefore, competitors with
such management ability will likely forge a co-opetitive
relationship. Finally, competition level can influence coopetition formation as well. When two companies compete fiercely in a market, they likely perceive each other
as an enemy to defeat and have less willingness to collaborate, even if they have complementary skills and resources. Thus, it is proposed that a high level of competition between competitors will decrease the possibility of
formation of a co-opetitive relationship.
In terms of consequences, co-opetition brings better
competitiveness and efficiency to participating competitors. Since competitors outside the co-opetitive relationship do not possess all the skills and resources that are
available to the firms in the co-opetitive relationship, their
products and services are not likely to match those from
the firms in the co-opetitive relationship. Thus, the firms
in the co-opetitive relationship gain a competitive edge
over competitors outside the relationship, which increase
competitiveness. In addition to increased competitiveness, co-opetition also provide the participating firms
with efficiency because they do not need to develop skills
and resources they need internally.
The most important contribution of this paper is that,
to my knowledge, this study is the first study that formally
defines co-opetition and examines both its antecedents
and consequences. Given the fact that research on coopetition is at its early stage, this study provides groundwork on which future research on co-opetition can build.
For further information contact:
Pilsik Choi
Department of Business Administration
339 Wohlers Hall
University of Illinois at Urbana–Champaign
1206 South Sixth Street
Champaign, IL 61820
Phone: 217.333.4240
FAX: 217.244.7969
E-Mail: [email protected]
American Marketing Association / Winter 2005
Lewis K.S. Lim, Indiana University, Bloomington
Rebecca J. Slotegraaf, Indiana University, Bloomington
Rockney G. Walters, Indiana University, Bloomington
A growing number of studies in marketing and strategic management are concerned with the notion of pricing capabilities. Within this emerging literature, two
schools of thought dominate the intellectual discourse.
The “technological” school, reflected mainly in industryoriented and business practice writings, emphasizes computational precision, and objectivity as prerequisites to
effective pricing. Accordingly, it views pricing capabilities as driven by the installation of information systems
and the procurement of pricing engineering expertise. In
contrast, the “people” school, espoused largely by scholars subscribing to an organizational capabilities or organizational learning perspective, sees market sensing and
concerted organizational action as the fundamental mediators of effective pricing. Focusing on such higherorder people-dependent processes, this school advocates
the development of coordination mechanisms, tacit knowledge, and routines over time to improve pricing effectiveness.
Noting the divergent viewpoints, we construct two
“implied” models of pricing capability development in
order to bring to light the mediating processes and driving
mechanisms assumed by proponents of the respective
schools of thought. In the technological model of pricing
capability development, we depict the availability of
accurate and timely information on cost and revenue
flows, the acquisition of pricing engineering knowledge,
and the customization of data display in information
systems as antecedents, and pricing precision and objectivity as mediators, of pricing astuteness. In the people
model on the other hand, we suggested collective task
experience in developing the pricing process, a shared/
dominant logic about the marketplace, and interfunctional
goal alignment within the organization as antecedents,
and market sensing and concerted organizational action
as mediators, of pricing astuteness.
By juxtaposing the two alternative models, we are
able to draw differential implications of each school.
Evidently, each school suggests a different set of resource
American Marketing Association / Winter 2005
investment priorities for firms. Specifically, the technological school would place a greater priority on the external acquisition of material, tangible resources such as
software and consultancy services, whereas the people
school would prescribe the internal development of abstract, intangible resources such as tacit market knowledge, and interfunctional conflict resolution mechanisms.
Each school inherently emphasizes resource acquisition
from a different kind of factor market and may be suited
for adoption in a different type of organizational environment. These issues call for linking the study of pricing
capabilities to the broader theories of management, such
as the resource-based view, transaction cost theory, and
contingency theory.
In exploring these two schools of thought, this paper
contributes to marketing knowledge in a number of ways.
First, the current state of understanding concerning pricing capabilities is put into proper perspective, with the
delineation of two possible alternative positions scholars,
consultants, and practitioners alike might hold toward the
topic. Certain implicit theories or otherwise unstated
premises on either side are thereby illuminated. Second,
within each school of thought, the notion of a pricing
capability itself is further clarified with the identification
of the key enabling skills and resources. Third, the alternative processes of improving pricing effectiveness are
explicated, thus allowing us to understand how different
compositions of resources influence the effectiveness of
price decision making.
As an agenda for future research, we outline two
primary directions in which the framework proposed in
this paper could be extended. For a start, investigations
could be carried out into the managerial-perceptual and
organization-specific factors that lead a firm to adopt
either the technological or the people model of pricing
capability development. Thereafter, research could focus
on determining the contingent deployment of different
pricing capabilities to suit the organizational decision
environment. More definite conclusions could then be
drawn about the role of pricing capabilities in influencing
firm performance.
For further information contact:
Lewis K.S. Lim
Kelley School of Business
Indiana University
1309 East Tenth Street
Bloomington, IN 47405
Phone: 812.855.1116
FAX: 812.855.6440
E-Mail: [email protected]
American Marketing Association / Winter 2005
Mohammadali Zolfagharian, University of North Texas, Denton
Rajasree K. Rajamma, University of North Texas, Denton
Research in the last two decades identifies relational
exchange as the key underlying factor driving business
performance. However, the theoretical foundation of relational exchange is far from clear. Relational exchange
has been operationalized using over 37 different dimensions, many of which overlapping and interrelated
(Gundlach et al. 1995). This might be due to the contextual
and methodological differences of the studies. The contribution of our meta-analysis is twofold: (1) to establish
whether an overall positive association exists between
relational exchange and its purported outcome variables
and (2) to identify the contextual, methodological and
measurement peculiarities that instigate variation in findings reported by different researchers. Hence, our first
proposition is that there is an overall positive relationship
between relational exchange and its outcomes.
The database for meta-analysis was constituted of 34
studies, altogether contributing 37 dimensions of relational exchange and 13 outcome variables. After collapsing dimensions with similar definitions and eliminating
those that have less than 10 correlations, our database
consisted of 19 studies (55%) providing 89 usable correlations. These correlations were associated with five relational exchange dimensions: solidarity, durability, flexibility, information exchange and mutuality, and three
outcome variables: satisfaction, performance, and commitment. These dimensions and outcomes were categorized into (1) instrumental/concrete including flexibility,
information exchange (two dimensions) and performance
(one outcome) and (2) abstract including solidarity, durability, mutuality (three dimensions), satisfaction and commitment (two outcomes). We hypothesized that the instrumental dimensions and outcomes of relational exchange
would have significant, positive relationship with the
effect size.
Differences across correlations in meta-analyses are
often attributed to four broad categories of characteristics:
measurement method, research context, estimation procedure, and model estimation (Sultan et al. 1990). As our
analysis focused on correlations, model estimation procedure and model specification (i.e., omitted variable bias)
were not considerable issues for this study (Henard and
Szymanski 2001). Therefore, two contextual and two
American Marketing Association / Winter 2005
methodological moderators below were identified and
used in our analysis.
Contextual Moderators:
1.1 The country from which data was collected (U.S.
vs. other countries).
1.2 Whether the data was collected from a single
industry; and two.
Methodological moderators:
2.1 Whether upstream or downstream firm in the
relationship responded to the survey.
2.2. Respondent’s status in the firm (whether the
respondent was a top executive or not).
We hypothesized that relational exchange dimensions have a stronger impact on its outcome variables (a)
when the sample is drawn from within the U.S. (b) when
it is drawn from a single industry (c) when the upstream
partner is the respondent in the study and (d) when the
respondent has a high rank in the firm.
Analysis was done using the multiple regression
technique with dummy coded variables (0/1). The ztransformed correlations formed the criterion variable
and the five dimensions of relational exchange, the three
outcome variables and the four moderator variables formed
the predictor variables in the regression equation. All the
data, except the effect size, were dummy-coded.
The findings offer insights to researchers as well as
practitioners. We could not find any significant overall
relationship between relational exchange and its outcome
variables. The results also partially support our argument
that instrumental dimensions (flexibility) as well as instrumental outcomes (performance) of relational exchange
are more salient than abstract dimensions. Further, significant moderators of the relationship were found to be
sampled industry (studies that collected data from a single
industry had stronger positive effect sizes) and the
respondent’s rank in the firm. Responding firm’s position
in the relationship was found to marginally moderate the
relationship. By far, it was seen that, sampled industry is
the strongest moderating factor of the relationship.
In sum, the findings indicate that the association
between relational exchange and outcome variables is
highly dependent on three factors: (1) how relational
exchange is operationally defined, (2) who evaluates the
relationship (upstream firm versus downstream firm and
high-status employee versus low-status employee within
the organizational hierarchy), and (3) the data source
(single- vs. multiple-industry).
One major limitation of our findings stems from the
small number of empirical studies that are available and
that explore the relationship between relational exchange
and its outcomes. This calls for more studies in the area.
Moreover, we found that other meaningful dimensions of
relational exchange such as trust, harmonization of conflict have received barely any attention from the researchers. Hence, this is an avenue for further research on the
subject. Future research should also include the views of
all the parties involved in the relationship in order to get
a more comprehensive view of what is happening within
a given relationship.
For further information contact
Rajasree K. Rajamma
College of Business
University of North Texas
P.O. Box 311396
Denton, TX 76203–7231
Phone: 940.565.4787
FAX: 940.381.2374
E-Mail: [email protected]
American Marketing Association / Winter 2005
Sudha Mani, University of Western Ontario, London
Kersi D. Antia, University of Western Ontario, London
Aric Rindfleisch, University of Wisconsin – Madison
Entering a foreign market is an expensive, risky, and
daunting task comprised of multiple decisions. Among
the most important of these decisions is the governance
arrangement of a new subsidiary. Firms entering foreign
markets must first select a mode of entry (e.g., a whollyowned subsidiary versus a joint venture with a local
partner). For joint ventures, the entering firm must also
decide upon its level of equity investment. Although these
two governance decisions are strategically inter-related,
the extant FDI literature has examined them in isolation.
The bivariate model in this paper addresses the problem
associated with the correlated nature of these two decisions.
The key theoretical perspectives explaining entry
mode and level equity have been the transactional cost and
experience perspective. Prior studies have typically assumed common antecedents of transaction cost analysis
(TCA) and experience for both aspects of governance,
and little is known about their specific effects on each
aspect of governance. TCA emphasizes capability protection, while the experience perspective considers governance with a view to capability enhancement. Despite
recent research examining these dual objectives (Delios
and Henisz 2000; Lu 2002; Madhok 1997), the relative
predictive ability of these two theoretical perspectives
across both aspects of FDI governance is unknown, as
there has been no simultaneous estimation of their influence. Our paper addresses this lacuna by simultaneously
estimating both mode and level of FDI governance via the
lens of both the TCA and experience perspectives. Our
inclusion of these dual viewpoints allows us to assess their
relative theoretical merit upon both aspects of FDI decisions.
Using a rich dataset of 4,459 subsidiaries of 858
Japanese firms across 38 countries over a nine-year period, we specify a cross-classified, multilevel, bivariate
model of FDI governance. This model enables simultaneous estimation of entry mode and level of equity decisions and integrates theoretical viewpoints from both the
TCA and experience perspective.
The results from the bivariate multilevel analysis
suggest a need to integrate the TCA and experience
perspective. Our findings reveal that TCA factors have a
greater significant impact on choice of entry mode than it
does on the level of equity participation. In contrast,
experience considerations significantly determine both
aspects of governance. The much larger effect sizes obtained for entry mode and host country experience, relative to that of advertising intensity lend support to the
assertion that models of FDI activity that focus solely on
TCA-related concerns are underspecified (Blodgett 1991;
Brouthers 2002). Further, our analysis reveals that although experience exerts a powerful influence on FDI
governance, the direction of its effects is dependent upon
the type of experience in question.
This research was supported by a grant from the
Social Sciences and Humanities Research Council of
Canada (#411-98-0393) at the University of Western
Ontario. References available upon request.
For further information contact:
Kersi D. Antia
Richard Ivey School of Business
University of Western Ontario
1151 N. Richmond Street
London, Ontario N6A 3K7
Phone: 519.661.4231
FAX: 519.661.3959
E-Mail: [email protected]
American Marketing Association / Winter 2005
Andrew T. Stephen, University of Queensland, Australia
Leonard V. Coote, University of Queensland, Australia
The governance of interfirm relationships in marketing channels is complex. Much extant literature has considered relationship governance from the perspective of
discrete, isolated dyadic relationships (e.g., a single buyer
and a single supplier). In reality, relationships in marketing channels, supply chains, and distribution networks
combine to form relationship networks that are inherently
complex and can have high levels of uncertainty. The
governance of relationships in these networks is likely to
vary significantly from the governance of the single
dyadic relationships that have been the focus of many
previous studies. An emerging stream of literature considers the governance of multiple, linked relationships in
network-type structures (e.g., Heide 2003; Mishra, Heide,
and Cort 1998; Wathne and Heide 2004). While it is
understood that complex systems of interfirm relationships exist and are relatively commonplace in practice
(cf., Anderson et al. 1994), research into the governance
of these networks of relationships is needed.
Continuing in the tradition of this emerging stream of
literature, and seeking to extend previous, more descriptive conceptualizations of relationship networks in marketing, this paper advances a more general conceptualization of governance in relationship networks. The paper
focuses specifically on how governance system choices
are made and what factors influence these decisions, and
the performance-related outcomes of systems of governance. An important element of the conceptual discussion
in this paper is the notion that governance choices for one
level in a network are strongly influenced by a firm’s
assessments and evaluations of conditions of uncertainty
and relationship characteristics at other levels in the same
network. The authors present an extended conceptual
discussion and formal propositions in an attempt to advance thought towards a more general framework of
network governance.
A central issue considered in the conceptual framework relates to the use of plural forms, or plural governance, in managing multiple, linked relationships in net-
American Marketing Association / Winter 2005
works (cf., Bradach and Eccles 1989; Heide 1994, 2003).
Plural governance is intended to afford firms in networks
with greater flexibility to adapt to changing conditions in
their environments or channels. This notion is applied to
more general considerations of how uncertainty can be
dealt with in relationship networks through governance
mechanisms. The discussion then turns to introducing the
notion of governance system compatibility; that is, optimal configurations or combinations of governance modes
under plural governance must be compatible across levels
or branches of relationship networks. The most efficient
governance systems or plural forms of governance are
those that provide sufficient flexibility and greater certainty, and that are compatible across levels. The conceptual framework builds on these foundations and advances
propositions that predict (1) how downstream channel
conditions can influence upstream channel governance
choices, and (2) when plural governance is required based
on prevailing conditions elsewhere in a network.
The concepts and propositions discussed in this paper
have a number of implications for theory and practice.
Studying relationship networks and how they might be
efficiently governed in order to increase flexibility and
certainty for firms in these networks is of importance to
academic and practitioner audiences. At a theoretical
level, the framework proposed in this paper is novel in the
sense that it considers contingent effects across levels of
networks (e.g., upstream vs. downstream) in determining
the most appropriate systems of governance that are
compatible with each other. This builds on recent work by
Mishra et al. (1998) and Wathne and Heide (2004).
Including plural governance in these conceptualizations
adds to the depth and richness of the framework. For
practitioners, this paper offers suggestions for how to
make optimal and efficient governance system choices
under conditions of uncertainty and complexity in a
relationship network context. The conceptualizations provide guidelines for what practitioners should consider and
evaluate as part of the process of designing the most
appropriate governance systems for their needs. References available upon request.
For further information contact:
Andrew T. Stephen or Leonard V. Coote
UQ Business School
University of Queensland
Brisbane, Qld 4072
Phone: +61.7.3365.9721
FAX: +61.7.3365.6988
E-Mail: [email protected]
American Marketing Association / Winter 2005
Helder J. Sebastiao, University of Oregon, Eugene
Firms that launch radical product and process innovations are market driving: creating, shaping, and accelerating markets for their radical innovations and redefining customer expectations, value propositions, and business processes. Successful market driving is dependent on
developing, growing, and strategically leveraging networks of alliances and key customers, and relationship
marketing plays a critical role in fostering collaboration.
This suggests a fundamental shift in marketing focus from
targeting and communicating with prospective customers
towards the cultivation, management, and leveraging of
multiple collaborative relationship ties. Thus initial relationship marketing efforts should be concentrated on
establishing strong alliance network ties and conducting
frequent and intensive mutual learning-oriented communications with initial customers.
Contrasting Being Market Driven with Market Driving
Market Driven Firms Are Responsive: Market driven
relationship marketing strategies emphasize responsiveness to both channel member and existing customer needs.
When a firm is market driven its primary objectives are to
gain full channel member support of a product launch and
to leverage existing customers in adopting an incremental
innovation, often through the use of product/service migration strategies. The result of a successful market driven
strategy should be expanded market share or share of
wallet/budget, reinforced brand loyalty, and enhanced
existing customer satisfaction. While firms can maintain
competitive advantage by being market driven in existing
markets, they become vulnerable to firms pursuing a
market driving strategy.
Market Driving Firms Are Opportunistic and Collaborative: Market driving firms are generally new entrants who revolutionize an industry by delivering a
substantial leap in customer value through either a breakthrough technology or marketing system made possible
by a unique business process (Kumar, Scheer, and Kotler
2000). The most successful radical innovations produce
what Arthur (1990) refers to as a market in lock-out,
where a technology or technology-based business process
becomes an industry standard that is extremely difficult to
dislodge. Examples include and EBay being perceived as the standards for conducting e-com-
American Marketing Association / Winter 2005
merce, and Dell driving the standard for modular computer manufacturing processes (Kumar, Scheer, and Kotler
The market driving entrepreneur typically creates
and enters new markets through alliances and similar
cooperative strategies rather than competitive positioning
(Sarasvathy 2001). Success is dependent on leveraging
and building upon who they know: industry contacts,
funding sources, supporters, suppliers, and customers
(Sarasvathy 2001). This emphasis on alliances and collaboration is the most significant influence on the selection of relationship marketing objectives and strategies.
Alliances facilitate widespread industry adoption and
provide access to markets and customers that otherwise
may not be available to the entrepreneurial firm. Initial
customers provide feedback and the input that drives
successive product iterations and service enhancements
(Gatignon and Xuereb 1997; Hill 1997).
Market driving firms both drive the formation of
expectations and use an iterative approach to refining new
products and services to meet customer and alliance
partner expectations that evolve through successive interaction with their networks. Due to limited resources
entrepreneurs must achieve this incremental learning within
a relatively short timeframe. Interaction with the firm’s
networks must also reinforce strategically important relationships.
Market Driving Creates an Innovation Network
A collaboration-oriented relationship marketing strategy should result in lower product launch costs, reduced
time for market acceptance, and reduced market uncertainty. Embedded relationships provide an additional barrier against competitive threats and help reduce overall
marketing costs. The strategic leveraging of these relationships leads to ongoing product, service, and market
opportunities as the network expands and becomes increasingly interconnected to other alliance and customer
networks. The desired end state is status as an industry
standard and possession of a highly embedded network of
relationships contributing to future innovations based on
joint value creation. This is a natural evolution for the
initial customer relationships in which the seeds of collaboration were planted. This environment of shared risk
and reward fosters greater learning between the firm and
the customer, which in turn can lead to improved efficien-
cies, higher quality, and faster turnaround times (Prahalad
and Ramaswamy 2000).
Table 1 summarizes the differences between market
driving and being market driven.
Market Driving Versus Market Driven Relationship Marketing
Market Driving
Market Driven
Type of Innovation
Radical product and/or process innovation
Incremental product / service
Firm Situation
Typically entrepreneurial; new product to new markets
New product/service to existing
Basic marketing
Essentially proactive, iterative, and committed to
creating technology standards and markets
Essentially reactive/responsive to
market demand
Basic strategic
Strategy evolves from an iterative process, testing as
many alternatives as possible by leveraging
♦ Firm technical, functional, market expertise
♦ Emerging networks of prospective customers/alliances
♦ Collaboration
Select an optimal strategy among
alternatives based upon expected
returns, using
♦ Pre-specified criteria
♦ Pre-determined goals
♦ Research and projections
♦ Knowledge of existing channels
and customers
Involvement of
target customer
in the innovation
Initial target customer input is integral to the iterative
process of product/service and segment refinement;
Dialog is continuous, and network of potential
customer/collaborators continually expands
Possible contact via context of NPD
Leverage existing relationships for
potential migration
Key Relationship
Mktg Strategies
Identifying, recruiting and forming networks of
alliances and customers
Building commitment to the technology as a standard
Joint value creation via embedded network relationships
Customer adoption/migration to new
Full channel cooperation
Customer as input to future product
Customer as referral source
Key Relationship
Mktg Goals
(1) Well defined market
(2) Standards as an effective barrier to entry
(3) Access to additional markets and opportunities
(1) Expand market share
(2) Expand share of wallet/budget
(3) Reinforce brand loyalty
Key Mktg-Based
Assets from
RM Activities
(1) Industry standard technology or process
(2) Embedded product innovation network
acceptance time
(1) Expanded cash flow from
incremental sales
(2) Enhanced cash flow from
reduced market
Traditional relationship marketing models for established, market driven firms do not adequately account for
the characteristics and challenges of entrepreneurial market driving firms. These firms redefine markets with
radical innovations that trigger dramatic changes in customer expectations, value propositions, and business pro-
American Marketing Association / Winter 2005
cesses. Successful market driving is dependent on developing, growing, and strategically leveraging networks of
alliances and key customers. Relationship marketing plays
a critical role in market driving and ultimate radical
innovation launch success, particularly in fostering collaboration with alliances and customers. References are
available upon request.
For further information contact:
Helder J. Sebastiao
University of Oregon
Lillis Business Complex
1208 University of Oregon
Eugene, OR 97403–1208
Phone: 541.346.4179
FAX: 541.346.3341
E-Mail: [email protected]
American Marketing Association / Winter 2005
Audhesh K. Paswan, University of North Texas, Denton
Lisa C. Troy, University of North Texas, Denton
The objective of this paper is to enhance our understanding of key perceptual dimensions influencing consumers’ intentions to adopt radical and incremental new
products. We do so by investigating five key perceptual
factors as antecedents to intention to adopt (or purchase)
a radical new product (RNP) or an incremental new
product (INP): perceived knowledge about the RNP and
INP, perceived complexity of the RNP and INP, perceived
financial risk and perceived performance assurance (opposite of risk) associated with the RNP and INP, and
perceived comfort associated with purchase of the INP or
RNP. Our investigation of whether these perceptual factors vary across radical versus incremental new products,
and whether they influence the adoption of radical versus
incremental new products similarly differs from existing
literature which typically focuses on consumer innovativeness as a trait or a behavior and which often lumps
consumers together into radical versus incremental groups
despite the fact that consumers may actually adopt incremental products some of the time and radical products in
other situations.
The respondents for the study were composed partly
of senior and graduate students at a major university in a
suburban campus and partly of non-students contacted
personally through student interviewers from two market
research classes. The scale items for measuring the five
perceptual factors were adapted from existing studies.
The same scale items were repeated in two separate
sections of the survey – one for Incrementally New
Products (INPs) and another for Radical New Products
(RNPs) in the context of consumer electronics. A total of
609 surveys were first analyzed for reliability and validity
(convergent and discriminant) using Cronbach’s Alpha
and inter-item correlations. The results indicate acceptable levels of reliability and validity. We next tested the
hypotheses using pair wise t-tests and multiple regressions to test the hypotheses of interest. Separate models
were run using purchase intention towards the RNP and
the INP, and for both models the multi-collinearity estimates were well within acceptable limits.
Findings from the study indeed indicate that the very
same consumer can have similar adoption intentions for
different types of products (i.e., radical versus incremental), possibly desiring to adopt both a radical and an
incremental new product within the same broad category
of consumer electronics. Additional findings suggest that
consumers seem to differ in the way they perceive the two
types of innovative products (radical versus incremental)
along perceptual dimensions such as complexity, financial risk and performance assurance dimensions but do
not differ (in our sample) across product types in their
perceptions of perceived knowledge or perceived comfort
with the purchase process. Finally, we find that the influence of key perceptual factors on adoption intentions may
be similar for radical versus incremental new products.
Our findings are important for marketers who have
historically sought to lump consumers into innovative
categories with the assumption that these would hold
across products. Furthermore, consumers seem to differ in
the way they perceive the two types of innovative products along perceptual dimensions such as complexity,
financial risk, and performance assurance dimensions but
do not differ (in our sample) across product types in their
perceptions of perceived knowledge or perceived comfort
with the purchase process. These findings are also important to marketers as they seek to design marketing plans to
address consumer’s perceptions.
For further information contact:
Audhesh K. Paswan
Department of Marketing and Logistics
College of Business Administration
University of North Texas
P.O. Box 311396
Denton, TX 76203–1396
Phone: 940.565.3121
FAX: 940.565.3837
E-Mail: [email protected]
American Marketing Association / Winter 2005
Yun Ye, The University of Arizona, Tucson
This paper identifies an implicit potential resource
that can generate sustained competitive advantage for
firms that produce innovative products: consumer pioneers. Examining the mechanism of consumer learning
and organizational learning, this paper emphasizes the
mediating role of higher-level organizational learning and
the dynamics how consumer pioneers generate sustained
competitive advantage.
Identifying resources that can generate sustained
competitive advantage has been an important area of
study in strategic management. In the existing literature,
some unique resources, such as strategic planning, information processing systems and positive reputations, are
considered to be able to generate sustained competitive
advantage for firms (Barney 1991), but resources which
can generate sustained competitive advantage have become more implicit and limited today. As environmental
uncertainty is growing faster in this technology era, it has
become more crucial to exploit new resources to serve as
sustained competitive advantages for firms, especially for
those firms whose products are highly innovative and
need to be upgraded constantly, such as digital product
industry (e.g., computer, digital camera, PDA, etc.)
Thus, the purpose of this study is to address another
implicit and important potential resource that can generate sustained competitive advantage for firms that produce innovative products: consumer pioneers. Defined as
lead consumers with high learning capability and low
learning costs, consumer pioneers as a resource have four
empirical indicators of the potential to generate sustained
competitive advantage: value, rareness, imperfect imitability, and non-substitutability (Barney 1991). The underlying idea is learning transfer. That is, firms can generate
consumer pioneers to sustained competitive advantage by
learning from what consumer pioneers have learned. Prior
studies have considered working with lead customers to
recognize strong needs before the rest of the market and to
find solutions to those needs as a salient strategy for firms
to gain competitive advantage (Slater and Narver 1995).
But what is the underlying mechanism that such a resource generates sustained competitive advantage? Under what conditions does this resource become crucial to
firms, and to what kind of firms? This article provides
answers to the above questions by examining the relevant
American Marketing Association / Winter 2005
literature and developing a mediation model. The model
indicates that the resource of consumer pioneers can
generate sustained competitive advantage through the
mediator of higher-level organizational learning, especially under high-level environmental uncertainty for
firms that produce high-level innovative products.
In the next section, I will discuss the concept of
consumer pioneers from a consumer learning perspective,
followed by a discussion of why the resource of consumer
pioneers could be a potential sustained competitive advantage by addressing its four attributes. Then I will
discuss the mediating role of higher-level organizational
learning. Finally, a conceptual framework and some additional propositions are presented to build a comprehensive mediation model incorporating consumer pioneers,
organizational learning and sustained competitive advantage.
Consumer Learning
Consumers learn, but their learning varies. The basic
definition of learning, which refers to the relatively enduring changes in the response to stimuli (Rogers 1962),
already points out the key issue: change. But how do
changes happen? How are they different from consumer
to consumer? And what does the difference mean to
researchers and marketers? These are the major issues I
will address here. Consumer learning occurs not only
through exposure to external information sources such as
advertising and word-of-mouth, but also through a process of internal knowledge transfer from familiar to novel
domains (Gregan-Paxton and John 1997). Employing the
internal knowledge transfer view, this study focuses on
the endogenous mechanism of consumer learning. Two
popular views that apply to the endogenous mechanism of
consumer learning are the hierarchical connections between stored pieces of information (Miller 1956) and the
model of Consumer Learning by Analogy (Gregan-Paxton
and John 1997). According to the hierarchical connection
theory, the information previously stored in consumers’
memory will associate their learning when they encounter
similar information. Similarly, the model of Consumer
Learning by Analogy predicts that previously acquired
knowledge is transferred by analogy in the process of
consumer learning. These two views reveal that learning
is a relatively harder task to consumers when they encoun118
ter an innovative or a new product and use the product for
the first time, as they may not be able to refer to similar
previous experience. Thus, firms that have innovative
products face harder tasks of consumer learning than
those firms that don’t.
Innovation Adoption and Diffusion
As Rogers (1962) stated, the process by which innovations are adopted by consumers is a special example of
consumer learning. There are five stages in the adoption
process: awareness, interest, evaluation, trial and adoption. Depending on the degree of innovativeness, different consumers belong to different categories of the diffusion curve: innovators, early adopters, early majority, late
majority, and laggards. Consumer innovation adoption
and diffusion are especially important to firms entering
the market with innovative products because consumers’
learning costs are usually high for such products. Just as
Mistri (2002) indicated, “the consumer’s learning behavior presupposes that he is in a situation of bounded
rationality and must proceed with a progressively more
and more refined classification of a product or group of
products, and that he is seeking a strategy that enable him
to classify the goods with a minimum research effort”
(p. 310). Thus, the main barrier for consumers to adopt an
innovative product is the relatively high learning cost.
Learning Costs
Since most of the time consumers do not have complete information of the product, they are more likely to
learn inaccurately and misperceive product quality. Perfect learning only occurs when consumers can accurately
evaluate product quality (Goering 1985). Not all consumers can perform perfect learning for all products.
Gabszewicz, Pepall, and Thisse (1992) explained “as with
most new products, consumers need to learn how to use
the new good, and consumers differ in their ability to
learn, or in their willingness to adapt to something new”
(p. 399). Thus, the combination of consumers’ willingness and ability to learn can be seen as their learning
capability. As Gabszewicz, Pepall, and Thisse (1992)
stated, a consumer with low learning capability has a high
learning cost, and is predicted to dislike trying new
products. Meanwhile, a consumer with high learning
capability has a low learning cost and will enjoy trying
innovative products. Thus, I refer to consumers with high
learning capability and low learning costs as consumer
pioneers, and I refer to those with low learning capability
and high learning costs as average consumers.
Consumer Pioneers
As we can see, for an innovative product, there are
always various groups of consumers who have different
learning capabilities and adoption actions, and they are
American Marketing Association / Winter 2005
located on different positions of the diffusion curve.
Among them there exists such a group that enjoys learning, trying and sometimes adopting new products, especially high technological products such as digital cameras, MP3 players, new models of computer, and hybrid
electric vehicles. These consumer pioneers are active and
effective learners compared to average consumers. Their
learning usually does not stop at adoption, or even at
rejection of a product. Unlike average consumers, these
pioneers will extend their learning beyond adoption or
rejection with high interest and enthusiasm. For example,
after adoption, when they find what they like or dislike
about the product, they will express their satisfaction,
dissatisfaction, or further demands to the marketers. On
the other hand, if they reject the product, they clearly
know why they rejected the product and what needs to be
improved in the future. In both cases, they are willing to
deliver their perceptions (e.g., satisfaction, expectations,
and demands) to others (other consumers or the firm). In
the beginning, when they are interested in the product,
they can be very passionate and highly motivated. Later,
when they evaluate the product, they can be very rational
and professional.
In this article I use the term “consumer pioneers”
rather than “consumer experts” or “innovators/early adopters” because these three groups are from different consumer behavior perspectives. Precisely, consumer experts emphasize expertise and knowledge (consumer behavior status) and early adopters emphasize adoption
(consumer behavior consequence), while consumer pioneers emphasize learning (consumer behavior process).
Consumer experts are “people whose prior knowledge is
well developed, in part because they have had a lot of
experience, knowledge, and familiarity with an object or
a task” (Hoyer and MacInnis 1997, p. 101). Thus, these
consumers may have high expertise in necessary choice
and purchase, but may not be willing to learn and try new
products. Some firms use consumer experts in test marketing because of their expertise. However, since they are
not necessarily interested in new products in the first
place, their opinions may not be that reliable to represent
average consumers in the real market, and may cause
firms to overestimate the market. In contrast, consumer
pioneers may not have as much expertise as experts, but
they have more enthusiasm to learn and try new products
as well as communicate with marketers and other consumers. Additionally, since their actions are more spontaneous, firms could lower consumers’ learning costs by
studying consumer pioneers’ learning processes. This
may not only help the firm to explore flaws of their
products, but also to accelerate the diffusion process.
Also, a consumer pioneer can be a member of either the
first two categories of adopters: innovators and early
adopters. The reason it is not necessary to distinguish
consumer pioneers from innovators or early adopters is
that this article focuses on the process of consumers’
choice (learning) rather than the consequence of choice
(adoption). It’s not important whether a consumer pioneer
eventually adopts the product, but he/she engages in the
learning process with high learning capability during the
Nowadays, it is common to see numerous online
communities in which people communicate with each
other about their experiences with certain products and
brands. Consumer pioneers often are active members,
though not necessarily opinion leaders (Rogers 1962).
One salient characteristic of them is their high willingness
to communicate with other consumers and also with
marketers. Unlike consumer experts, who are usually
located by firms to ask for opinions, consumer pioneers
voluntarily locate firms to provide suggestions. Such
activities include writing online reviews, providing feedback cards, e-mailing to technology support departments,
and so on. The underlying motivation could be their needs
for self-esteem and self-fulfillment, which needs further
research. But at least one thing is clear: such communication between the marketers and consumers as well as that
among consumers is crucial to innovation adoption and
diffusion processes (Schiffman and Kanuk 2000).
The definition of sustained competitive advantage
that Barney (1991) provided is “a firm is said to have a
sustained competitive advantage when it is implementing
a value creating strategy not simultaneously being implemented by any current or potential competitors, and when
these other firms are unable to duplicate the benefits of
this strategy” (p. 102). Also according to Barney (1991),
to have the potential of sustained competitive advantage,
the resource must have four attributes: value, rareness,
imperfect imitability, and non-substitutability. To argue
that consumer pioneers are a potential source of sustained
competitive advantage, I first examine whether it has
these attributes.
A firm’s resource is considered valuable if it exploits
opportunities in a firm’s environment. Consumer pioneers are such a valuable resource in two ways. First, as
mentioned above, consumer pioneers are willing to provide valuable evaluations and suggestions for products,
especially new products, to firms. These evaluations and
suggestions help firms accurately estimate their product
and market and plan future strategy. Since the comments
from consumer pioneers are representative of average
consumers to a certain degree, firms may identify what
American Marketing Association / Winter 2005
consumers and market really expect from the product and
exploit new opportunities. Second, as mentioned earlier,
since high learning cost is a main barrier for average
consumers to adopt new products, firms may exploit the
strategy that can lower consumers’ learning costs through
consumer pioneers’ experience. For example, firms could
find how to improve consumers’ willingness to try a new
product by stimulating their interest, which can be discovered from consumer pioneers’ experience. Learning from
consumer pioneers’ experience, firms can also improve
consumers’ learning ability by designing education programs and upgrading products. Thus, the above argument
indicates that consumer pioneers can be considered a
valuable source that can help firms to exploit new opportunities in the market, and finally generate sustained
competitive advantage.
Just as not all firms can have sustained competitive
advantage, not all consumers can be consumer pioneers.
Only those active and effective learners with high learning willingness and ability can be consumer pioneers. A
few factors put constraints on consumers’ learning willingness and ability, such as interest, financial support,
education level, time, and so on. For example, a consumer
with a tight schedule may not have time to try new
products even though he may be interested in them. A
consumer with limited financial support also will not try
new products because he will not risk his money at all
(Rogers 1962). A consumer with limited education may
have difficulty understanding a high technology product
and may be unable to provide insightful comments even
after he has adopted it. Thus, for certain product categories, there is a limited amount of consumer pioneers, and
they compose a rare resource for firms to perform competition.
Imperfect Imitability
To be a potential source of sustained competitive
advantage, the source must be imperfectly imitable. That
is, firms that do not possess it cannot obtain it. Barney
(1991) proposed how firm resources can be imperfect
imitable. One possibility is that the resource is socially
complex. Are consumer pioneers such a socially complex
resource? The answer is positive if a firm can create longterm and stable relationships with them. However, it is not
an easy task. It requires unique pursuing strategies for the
firm to hold a pool of its own loyal consumer pioneers, and
this complex relationship is hard to be mimicked by other
firms. Moreover, if a firm can create the reputation among
consumer pioneers that it is a superior relationship holder,
this imperfect imitability will be durable.
A potential resource of sustained competitive advantage cannot be strategically substituted. The substitutes
for this resource may be valuable but are neither rare nor
imperfectly imitable. As to consumer pioneers, as long as
the firm can maintain a stable relationship with them, they
are non-substitutable. One reason is that consumer pioneers are mobile and time-effective. For a particular brand
the consumer pioneer pool is unique and willing to serve
the firm who locate them first. Moreover, even competitors can locate them later, often the optimal timing (e.g.,
introductory period) has passed, and the consumer pioneer pool is no longer effective for the product. Of course,
this argument is based on some assumptions. That is,
consumer pioneers usually have limited effort and are
easier to obtain brand loyalty for the firm that cares them
most. For example, a consumer pioneer who serves
Microsoft may be hard to serve Macintosh simultaneously,
not only due to his preference for Microsoft but also due
to his limited time or expertise.
In summary, possessing these four attributes – value,
rareness, imperfect imitability, and non-substitutability –
consumer pioneers can be considered a potential resource
of sustained competitive advantage. Thus, the first hypothesis is,
H1: Consumer pioneers are a potential resource of sustained competitive advantage for firms.
But this poses another question: how can this resource generate sustained competitive advantage? Does
every firm have the ability to generate this resource to
sustained competitive advantage? The answer lies on
organizational learning. As Cravens (2000) addressed,
firms can benefit from organizational learning which
helps them quickly respond to opportunities and threats,
reduce time to develop new products, improve existing
products and services, and accelerate new product adoption. In the next section, I will examine the mediating role
of organizational learning in the relationship between
consumer pioneers and sustained competitive advantage.
Organizational Learning
Foil and Lyles (1985) defined organizational learning as “the development of insights, knowledge, and
associations between past actions, the effectiveness of
those actions, and future actions” and adaptation as “the
ability to make incremental adjustments as a result of
environmental changes, goal structure changes, or other
changes” (p. 811). They also classified organizational
learning into two levels: lower- and higher-level learning.
American Marketing Association / Winter 2005
Lower-level learning, also called adaptive learning (Senge
1990) or single-loop learning (Argyris 1977), occurs
within a given organizational structure when organizational contexts are well understood and reflect the
organization’s assumptions about its environment and
itself. In contrast, higher-level learning, also called generative learning (Senge 1990) or double-loop learning
(Argyris 1977), tries to adjust overall rules and norms
rather than specific activities or behaviors. This type of
learning is a more cognitive process and the associations
resulting from it have long-term effects and impacts on the
organization as a whole. Obviously, learning from consumer pioneers is such a higher-level learning. In the
three-stage process of learning that includes information
acquisition, information dissemination, and shared interpretation (Slater and Narver 1995), learning from consumer pioneers is crucial in the stage of information
acquisition for innovative firms. When organizations perform this kind of learning from consumer pioneers, they
should not only focus on the openness to such external
“learning partners” (Slater and Narver 1995), but also
create an effective interface and long-term relationship
with them, thus establishing a superior organizational
culture and reputation among customers. This type of
higher-level learning can be considered market-based
organizational learning.
Market-Based Organizational Learning and MarketBased Absorptive Capacity
As Sinkula (1994) stated, market-based organizational learning is different from other types of learning in
five ways. First, it focuses on external information (e.g.,
customers and suppliers) and it is not as explicit as most
internally focused organizational learning. Second, it
results in the fundamental bases of competitive advantage. Third, it pays more attention to the observation of
competitors. Fourth, the information it acquires and stores
in organizational memory is difficult to access. Finally,
market-information is equivocal. From these five attributes, we can see that learning from consumer pioneers
is such a market-based organizational learning. Consumer pioneers provide “access to a greater number of
information sources, force the development of mechanisms that facilitate the sharing of information, and offer
alternative perspectives to the meaning of critical information that could lead to generative learning” (Slater and
Narver 1995, p. 70). Furthermore, this kind of “information-driven” (Goldstein and Zack 1989) and “marketdriven” (Jaworski, Kohli, and Sahay 2000) learning is
especially important to innovative firms because they face
barriers of high learning costs for average consumers in
their innovation adoption. Two dimensions underlying
innovation – technology and market – suggest that developing new products needs not only technology that is
different from prior technology, but also fulfilling key
customer needs better than existing products (Chandy and
Tellis 1998). Thus, even though the primary goal of the
innovative firms is to drive the market to a new direction,
identifying which direction is most likely to be successful
based on consumers’ needs is at least as, if not more,
critical as new technology development. How does one
identify the right direction? In this article, the answer lies
in market-based absorptive capacity from consumer pioneers.
Absorptive capacity, also called innovative capability, is defined as the ability of a firm to recognize the value
of new, external information, assimilate it, and apply it to
commercial ends (Cohen and Levinthal 1990). As Cohen
and Levinthal (1990) addressed, “absorptive capacity
refers not only to the acquisition or assimilation of information by an organization but also to the organization’s
ability to exploit it” (p. 131). Thus, the ability to exploit
market-based knowledge and information can be seen as
market-based absorptive capacity, which is a special form
of higher-level organizational learning. This exploration
ability, which will eventually determine the firm’s innovative capability, is crucial to the firm’s success. An
organization’s market-based absorptive capacity depends
mostly on its direct interface with the external environment (e.g., customers, suppliers, competitors). Since innovative firms face more barriers of high learning costs
from consumers than non-innovative firms, they especially benefit from working with consumer pioneers to
discover effective ways to lower learning costs for average consumers when develop new products (e.g., radical
product innovation) or upgrade existing products (e.g.,
incremental innovation). As average consumers usually
experience difficulties in innovation learning (Engelland
and Alford 2000), the information provided by consumer
pioneers will help the firm match average consumers’
expectations to increase their willingness to learn, make
product quality or features less ambiguous, and finally
lower their learning costs and diminish the entry barriers.
Thus, I argue that higher-level organizational learning,
i.e., market-based organizational learning and absorptive
capacity, serves as a mediator in the relationship between
consumer pioneers and sustained competitive advantage.
H2: The resource of consumer pioneers can generate
sustained competitive advantage by the firm’s higherlevel organizational learning (i.e., market-based organizational learning and market-based absorptive
Employing the knowledge transfer theory, the conceptual model illustrates the knowledge transfer mechanism which emphasizes that firms learn from what consumer pioneers learn and generate the tacit knowledge to
sustained competitive advantage (Figure 1).
There are two moderators in the model. One is environmental uncertainty, including market and technology
uncertainty. Prior research shows that under high environmental uncertainty, customer orientation has a positive
influence on firms’ innovation because the development
of a new product in a highly uncertain environment
Conceptual Framework of Relationship Among Consumer Pioneers, Higher-Level
Organizational Learning, and Sustained Competitive Advantage
American Marketing Association / Winter 2005
creates the need for more market scanning and networking with users to identify customer needs (Gatignon and
Xuereb 1997). Thus the third hypothesis is:
H3: The higher the environmental uncertainty, the more
the likelihood that the resource of consumer pioneers
can generate sustained competitive advantage for the
firm via higher-level organizational learning.
Another moderator is the innovative level of the
product. As I stated before, consumers’ learning costs are
higher for radical products than for incremental products
(Chandy and Tellis 1998). Therefore, it is especially
important for firms that produce radical products to remain close with their customers, lower their learning costs
and increase their adoption rates via consumer pioneers.
So the final hypothesis is:
Argyris, Chris (1977), “Double Loop Learning in Organizations,” Harvard Business Review, 55, 115–25.
Barney, Jay (1991), “Firm Resources and Sustained Competitive Advantage,” Journal of Management, 17,
Chandy, Rajesh K. and Gerard J. Tellis (1998), “Organizing for Radical Product Innovation: The Overlooked
Role of Willingness to Cannibalize,” Journal of
Marketing Research, 35, 474–87.
Cohen, Wesley M. and Daniel A. Levinthal (1990), “Absorptive Capacity: A New Perspective on Learning
and Innovation,” Administrative Science Quarterly,
35, 128–52.
Cravens, David W. (2000), Strategic Marketing. Boston:
Irwin McGraw-Hill.
Engelland, Brain T. and Bruce L. Alford (2000), “Consumer Learning and The Creation of Primacy Advantages for Followers,” Journal of Business Strategies,
17, 145–62.
Foil, C. Marlene and Marjorie A. Lyles (1985), “Organizational Learning,” The Academy of Management
Review, 10, 803–13.
Gabszewicz, Jean, Lynne Pepall, and Jacques-Francois
Thisse (1992), “Sequential Entry with Brand Loyalty
Caused by Consumer Learning-by-Using,” Journal
of Industrial Economics, 40, 397–416.
Gatignon, Hubert and Jean-Marc Xuereb (1997), “Strategic Orientation of the Firm and New Product Performance,” Journal of Marketing Research, 34, 77–90.
Goering, Patricia A. (1985), “Effects of Product Trial on
Consumer Expectations, Demand, and Prices,” Jour-
American Marketing Association / Winter 2005
H4: The higher the innovative level of the product, the
more the likelihood that the resource of consumer
pioneers can generate sustained competitive advantage for the firm via higher-level organizational learning.
The possible method will be a survey among key
informants in innovative product industries. These informants include firms’ gatekeepers or knowledge managers, who monitor the environment and translate external
information into understandable internal knowledge to
the research group (Cohen and Levinthal 1990). Another
survey will be conducted using relevant industry databases to examine the performance of these firms’ R&D.
nal of Consumer Research, 12, 74–82.
Goldstein, David K. and Michael H. Zack (1989), “The
Impact of Marketing Information Supply on Product
Managers: An Organizational Processing Perspective,” Information Technology & People, 4, 313–36.
Gregan-Paxton, Jennifer and Deborah R. John (1997),
“Consumer Learning by Analogy: A Model of Internal Knowledge Transfer,” Journal of Consumer Research, 24, 266–84.
Hoyer, Wayne D. and Deborah J. MacInnis (1997), Consumer Behavior. Boston: Houghton Mifflin.
Jaworski, Bernard, Ajay K. Kohli, and Arvind Sahay
(2000), “Market-Driven versus Driving Markets,”
Academy of Marketing Science, 28, 45–54.
Miller, George A. (1956), “The Magical Number Seven,
Plus or Minus Two: Some Limits on Our Capacity to
Process Information,” Psychological Review, 63, 81–
Mistri, Maurizio (2002), “Consumer Learning, Connectionism and Hayek’s Theoretical Legacy,” Eastern
Economic Journal, 28, 301–17.
Rogers, Everett M. (1963), Diffusion of Innovation. New
York: The Free Press.
Schiffman, Leon G. and Leslie L.Kanuk (2000), Consumer Behavior. Upper Saddle River: Prentice Hall.
Senge, Peter M. (1990), The Fifth Discipline. New York:
Sinkula, James M. (1994), “Market Information Processing and Organizational Learning,” Journal of Marketing, 58, 35–45.
Slater, Stanley F. and John C. Narver (1995), “Market
Orientation and the Learning Organization,” Journal
of Marketing, 59, 63–74.
For further information contact:
Yun (Serah) Ye
The University of Arizona
320 McClelland Hall
1130 E. Helen
P.O. Box 210108
Tucson, AZ 85721
Phone: 520.621.9179
FAX: 520.621.7483
E-Mail: [email protected]
American Marketing Association / Winter 2005
Yinlong Zhang, The University of Texas at San Antonio, San Antonio
Lawrence Feick, University of Pittsburgh, Pittsburgh
Vikas Mittal, University of Pittsburgh, Pittsburgh
Globalization is becoming the buzzword of this century. Business executives and marketing academics are
discussing this term to explore the profound changes that
will happen in marketing practice. Many marketers nowadays face decisions on whether to market their products
globally or locally. One aspect of this global versus local
decision is whether to emphasize their market brands as
global or local ones. For example, a recent trade article
(Marketing News 2004) reported that many new soft
drink companies are making decisions on whether to
stress their brands as global, like Pepsi or Coke, or as local
based on what can be proven to better their chances for
success in markets that are both increasingly globalized
and localized.
From a theoretical perspective, this decision asks
whether emphasizing a brand as global or local will
induce positive responses from consumers. Marketing
literature offers contradictory empirical answers for this
question. For example, Steenkamp, Batra, and Alden
(2003) found that labeling a brand global instead of local
can increase its appeal to customers even if the objective
product quality is the same. While Zambuni (1993) found
the opposite: consumers like it more when a brand is
emphasized as a local one than when it is emphasized as
a global one. Along the same line, De Mooij (1998)
argued that localization strategy seems to be more attractive than the globalization strategy for consumer products. These inconsistent findings on global versus local
suggest that some boundary conditions moderate the main
effect of global or local on consumer preference. In other
words, being global can induce better responses from
consumers sometimes, but being local can induce better
responses in other situations.
Three experiments were proposed to investigate the
effect of accessibility of global versus local identity construct in consumer preference between global and local
brands. Study one manipulates the relative accessibility of
global versus local identity, inducing effects in consumer
preference for global or local brands. Study two measures
the relative accessibility of the consumer’s global and
local identity, and obtains the same pattern of results as
Study one on consumer preference. The first two studies
offer convergent evidence supporting our hypothesis:
When a global identity is activated, consumers tend to
value the global brands more highly than the local brands;
when the local identity is activated, consumers tend to
value the local brands better than the global brands. Study
three manipulates the differential versus integration modes
to replicate the results similar to the one manipulating the
accessibility of local versus global identity. This will, in
turn offer the initial evidence that the effect of global
versus local identity on consumer preferences runs through
the differential versus integration ways of thinking. Implications from these three studies on globalization and
accessibility-diagnosticity are discussed. Through these
studies we make a key theoretical contribution to the
literature of globalization, since we offer a powerful
theoretical explanation for the inconsistent findings in
past studies. Our results are consistent with the recent
development in the literature of cross-cultural psychology. Our studies are also consistent with the recent development in the accessibility diagnosticity framework.
For further information contact:
Yinlong “Allen” Zhang
The University of Texas at San Antonio
6900 North Loop 1604 West
San Antonio, TX 78249
Phone: 210.458.6331
FAX: 210.458.6335
E-Mail: [email protected]
American Marketing Association / Winter 2005
Annie H. Liu, Loyola Marymount University, Los Angeles
Mark P. Leach, Loyola Marymount University, Los Angeles
Robert D. Winsor, Loyola Marymount University, Los Angeles
In the face of competition for limited vacation and
leisure time, meeting planners and membership associations have traditionally been interested in how to attract
new members and enhance attendance at organizational
conferences. This study empirically investigates members’ intentions to attend organizational conferences using an accessibility-diagnosticity framework. Findings
suggest that post-attendance attitudes are the most important factors predicting intentions to (1) attend a future
conference and (2) recommend the conference to others.
Furthermore, what one has heard about the conference
(i.e., the buzz) and one’s perceived congruence with the
values of the organization are also found to be important
when predicting attendance intentions.
Purpose of the Research and Hypotheses
The purpose of this research is to investigate members of professional organizations regarding their intentions to attend conferences. Toward this goal, we examine
three types of information that might be relevant to the
formation of conference intentions. These are: (1) the
member’s attitude toward the conference, (2) information
acquired through word-of-mouth (i.e., the conference
buzz), and (3) the member’s perceived congruence with
the values of the organization. We further utilize the
accessibility-diagnosticity framework to provide a theoretical rationale for why the relative importance of these
three information types might differ between attendees
(i.e., those members who have previously experienced
one or more of the organization’s conferences) and nonattendees. Specifically, it is hypothesized that for attendees, attitudes toward the conference will be more diagnostic with regard to intentions to attend future conferences.
For non-attendees, conversely, their attitudes will be less
diagnostic, and therefore other information sources will
be accessed and utilized.
In addition, it is hypothesized that for non-attendees,
attitudes will be formed primarily based on what they have
heard about the conference, and from their general feelings about the organization. For attendees, attitudes will
instead be formed upon more elaborative judgments (e.g.,
American Marketing Association / Winter 2005
a cost-benefit analysis [perceived value assessment], or
an analysis of how well expectations were met [perceived
satisfaction assessment]). Underlying these hypotheses is
our premise that the high degree of elaboration associated
with these assessments makes attitudes more easily accessible and highly diagnostic.
We were further interested in members’ intentions to
recommend a conference to others. By evaluating the
relationship between attitudes regarding a conference and
referral intentions for past attendees, and the relationship
between word-of-mouth information and attendance intentions for non-attendees, this study will provide an
empirical test of whether or not a reinforcing feedback
cycle exists for conference attendance.
Model, Methodology, and Results
Our base model incorporates three antecedent variables predicting attendance: perceived organizational
congruence, word-of-mouth information, and attitude toward the conference. In addition, this model includes
relationships between perceived organizational congruence and attitude, and word-of-mouth information and
attitude. An expanded model includes intentions to recommend, and adds three direct relationships between
perceived organizational congruence and referral intentions, word-of-mouth information and referral intentions,
and attitude toward the conference and referral intentions.
A sample of 800 members of an organization for
retired employees of a government agency was randomly
drawn from the population of approximately 8,000 organizational members, and mailed a questionnaire. The total
number of useful and complete responses obtained was
448, representing a 58 percent response rate.
Structural equation methodology was used to test the
hypothesized relationships. Results indicated that for the
sub-sample that had attended a recent conference, intention to attend a future conference was directly related only
to one’s attitude toward the conference. In addition,
attendees’ attitudes toward the conference were found to
be related to perceived organizational congruence and to
information they received from word-of-mouth. The direct relationship between one’s perceived organizational
congruence and intention to attend was not found to be
statistically different from zero. Neither was the relationship between word-of-mouth information and intention to
attend. Thus, for those who have attended, the effects of
perceived congruence and word-of-mouth information
appear to be fully mediated by one’s attitude.
For the sub-sample without a recent conference experience, intention to attend a conference was directly related to one’s perceived congruence with the organiza-
tion, and their attitude toward the conference. In addition,
one’s perceived organizational congruence and the information acquired through word-of-mouth were found to be
related to one’s attitude toward the conference. Again, the
direct relationship between the word-of-mouth information and intention to attend was not found to be significant,
suggesting that this relationship is fully mediated by one’s
attitude toward the conference.
For further information contact:
Annie H. Liu
College of Business Administration
Loyola Marymount University
One LMU Drive
Los Angeles, CA 90045
Phone: 310.338.3039
FAX: 310.338.3000
E-Mail: [email protected]
American Marketing Association / Winter 2005
E. Deanne Brocato, The University of Texas at Arlington, Arlington
Susan B. Kleiser, The University of Texas at Arlington, Arlington
Services literature has recognized the role customers
play as an integral part of the service environment (Baker
1987; Bitner 1992; Grove and Fisk 1997). Other customers in many instances can be viewed as part of the service
environment (Martin and Pranter 1989), since they are
often required to share the same facility (Baker 1987).
Drawing on inference theory (Huber and McCann 1982),
other customers within a service environment provide
cues, which in turn are used by consumers to make
assessments of quality (Baker, Parasuraman, Grewal, and
Voss 2002). “The appearance, behavior, and number of
other customers and contact personnel can clearly affect
the way consumers perceive the service firm” (Baker
1987, p. 79). The importance of service personnel has
been documented in several studies (Parasuraman,
Zeithaml, Berry 1988; Bitner 1992; Baker 2002), but
there appears to be a gap in the extant literature concerning
the influence of other customers on the perceptions of
service facility quality and ultimately on service evaluations, such as satisfaction. The lack of attention devoted to
the influence of other customers is surprising since many
times “the number and duration of such c-c [customer to
customer] encounters exceed that of employee-customer
encounters by an order of magnitude” (Martin and Clark
1996, p. 347). Furthermore, the presence of other customers in a service environment may influence, albeit directly
or indirectly, one’s satisfaction (Martin and Pranter 1989).
In addition, frequent interactions among customers can
lead to either a more favorable or less favorable service
experience depending on the type of interaction (e.g.,
friendly patrons, crying children, cursing, etc.). This paper sets forth to create the Other Customer Influence
(OCI) scale to measure the influence that other customers
have on one’s evaluation of facility quality and ultimately
on satisfaction with the service experience.
Dimensions of Other Customer Influence
Drawing on services literature (Martin and Pranter
1989; Grove and Fisk 1997; Martin and Clark 1996;
McGrath and Otnes 1995; Baker 1987; Baker et al. 2002)
three dimensions of the Other Customer Influence (OCI)
construct are posited. These dimensions are compatibility, visual cues and behavior. We define compatibility as:
capable of existing or performing in harmonious, agreeable, or congenial combination with another or others.
Martin and Pranter (1989) address the need for managers
American Marketing Association / Winter 2005
to create service environments where the customers that
enter the environment are compatible. It makes intuitive
sense that customers will “gravitate toward those service
environments with which they are most compatible” (Martin and Pranter 1989, p. 7). In line with compatibility, the
visual characteristics (appearance, dress, gender, ethnicity)
of other customers can have an influence on the service
environment. Age, income, and social class have been
suggested as characteristics that should influence perceptions of the environment (Baker 1987). Other patrons’
behaviors can have profound effects on customers. Grove
and Fisk (1997) found in an exploratory study at a theme
park, behaviors of other customers affected consumer
both positively and negatively. For example, other customers cutting in line and shoving during waiting for
service created dissatisfying service encounters and waiting in line with polite patrons led to satisfying encounters.
In another exploratory study by Martin (1996), general
factors of behaviors were found to influence patrons’
evaluations of service satisfaction.
Scale Development
Scale items for the dimensions of compatibility,
visual cues and behavior were generated drawing from
services literature that has explored customer-to-customer
interactions (Martin and Pranter 1989; McGrath and Otnes
1995; Grove and Fisk 1997). Forty-one (41) items were
developed in order to capture the full conceptual domain
of the construct. After item purification 11 items remained
in the model representing the three dimensions. Evidence
was found for convergent and discriminant validities.
Also, all Cronbach’s alpha reliability coefficients exceeded the .7 lower limit (Hair et al. 1998) with the
dimension reliability estimates ranging from .74 to .83.
Nomological validity was assessed by investigating
the hypothesized paths between the three dimensions of
OCI and the facility quality construct. The model fit was
assessed and found to be sufficient: (GFI .90; AGFI .86;
CFI = .98; RMSEA = .065). The chi-square value was
significant (χ2 = 278.40, 128 df, p < .00), however this was
expected due to the sample size (Marsh, Balla, and
McDonald 1988). Positive links between compatibility
and behavior to facility were found to be significant (p <
.05) as indicated by the positive gamma (γ) parameters.
The parameter linking visual cues and facility quality was
not found to be significant. Finally, the path from facility
quality to satisfaction was significant.
Discussion, Limitations, and Future Research
One study cannot provide sufficient evidence of a
valid measure. However, this study lays the foundation
for the continuing process of construct validation. The
evidence provided indicates the OCI scale is a valid
measure. This measure provides marketers with the ability to determine how other patrons’ social factors influence evaluations of facility quality and service satisfaction. The recognition of other customers as an integral part
of the service environment provides the justification for
this new measure. This measure is a starting point for
future investigations into the construct of OCI. Each
dimension should be investigated and expanded as more
empirical evidence is gathered. Continual refinement is
needed for all measures and this measure is no different.
The complexity of the construct necessitates the need for
future research and investigation. References available
upon request.
For further information contact:
E. Deanne Brocato
The University of Texas at Arlington
Box 19469
Arlington, TX 76019–0469
Phone: 817.272.6765
FAX: 817.272.2854
E-Mail: [email protected]
American Marketing Association / Winter 2005
Elten Briggs, University of Oklahoma, Norman
Tim Landry, University of Oklahoma, Norman
Charles Wood, University of Tulsa, Tulsa
Todd Arnold, Oklahoma State University, Stillwater
Young people represent a strong and growing source
of volunteers for not-for-profit organizations (NPO), and
represent an important focus for NPO marketing efforts.
Therefore, it is in the long-term interests of NPOs that they
develop a better understanding of teenage volunteerism.
Despite the importance of the topic, research concerning
the volunteer sector in the marketing literature has been
scant historically (Bendapudi, Singh, and Bendapudi 1996;
Fisher and Acherman 1998; Wymer and Starnes 2001),
and no marketing studies have focused on the challenges
faced by charitable organizations in their efforts to attract
and solicit quality help from youth volunteers.
The present study attempts to bridge this gap by
examining the determinants of helping behavior in a
sample of youth volunteers involved in a task requiring
significant self sacrifice. We hypothesize that attitudes
toward this task will mediate the effect of other individual
variables on the quality of the helping behavior received
by the NPO. Based on the conceptualization of helping
behavior forwarded by Bendapudi, Singh, and Bendapudi
(1996), we consider two distinct dimensions of helping
behavior – help vs. no help and token help vs. serious help.
The first of these dimensions is captured by the variable
participation, which indicates whether or not the respondent chose to take part in the fast; and the second of these
dimensions is captured by the variable goal-setting, which
indicates whether or not the individual set a fundraising
goal. We examine three primary independent variables of
interest that have been theorized to play key roles in
determining volunteer behavior and that should be especially relevant for better understanding teens’ charitable
participation: (1) their attitudes towards the organization,
(2) their level of self-esteem, and (3) their level of materialism. Our hypotheses are as follows:
H1a: The relationship between attitude towards the organization and the decision to volunteer is mediated by attitude towards the task.
H1b: The relationship between attitude towards the organization and goal setting is the mediated by
attitude towards the task.
American Marketing Association / Winter 2005
H2a: The negative relationship between materialism
and the decision to volunteer is mediated by attitude towards the task.
H2b: The negative relationship between materialism
and goal setting is the mediated by attitude towards
the task.
H3a: The relationship between self-esteem and the decision to volunteer is mediated by attitude towards
the task.
H3b: The relationship between self-esteem and goal
setting is the mediated by attitude towards the task.
Questionnaires were administered by mail to a national sample of youth who had received marketing materials asking them to participate in a fundraising effort for
an international relief organization that involved fasting –
i.e., not eating solid food for 30 hours. The respondents’
attitudes towards the organization and towards the
fundraising task were measured by instructing the respondent to “Please mark an “X” on the space that best
describes your honest attitudes or feelings about each of
the following.” The fasting task and the name of the
organization were each followed by a five-point scale
anchored by “negative” and “positive.” Materialism
(MAT) and Self-Esteem (SES) were both measured using
established scales. In order to test our hypotheses we
followed the procedure outlined by Barron and Kenney
(1986) for testing mediation. This test entails three steps:
(1) regress the independent variable on the mediator, (2)
regress the independent variable on the dependent variable, and (3) regress both the independent and mediator on
the dependent variable. Four of the six anticipated relationships were supported: H1a, H1b, H2a, and H3b. A
task was consistently a significant predictor of both helping behavior dependent variables.
Our findings indicate that for NPOs marketing to
youth for involvement in volunteer projects, even if teens
think highly of an organization, the choice of the task is
crucial to their participation and their commitment to
fundraising. For NPOs recruiting teens that are likely to be
higher in materialism, the nature of the task or activity
needs to be interesting and compelling enough to get them
to join in. However, once they have joined the activity,
attitudes toward the fundraising task do not appear to be
enough for them to follow-through with actual fundraising
activities. Finally, our results seem to imply that the
relationship between helping behavior quality and selfesteem becomes more pronounced upon the decision to
participate in a volunteer task, but in our context, selfesteem was not predictive of the initial decision to volunteer.
For further information contact:
Elten Briggs
University of Oklahoma
307 West Brooks, Room 10A
Norman, OK 73019
Phone: 405.325.4675
FAX: 405.325.7688
E-Mail: [email protected]
American Marketing Association / Winter 2005
William Kilbourne, Clemson University, Clemson
Marko Grünhagen, Southern Illinois University at Edwardsville, Edwardsville
Janice Foley, University of Regina, Regina
Interest in materialism and its implications is apparent as far back as the early Greek philosophers. Pythagoras, for example, required that students relinquish their
personal possessions before entering his school. Rudmin
and Kilbourne (1996) provide an historical view of different attitudes toward materialism from the ancient world to
the modern. Marketing scholars recently returned to an
assessment of materialism in contemporary societies.
While some studies have remained critical of consumption practices, referring to materialism as a “dark side”
variable (Mick 1996), others have suggested that materialism might have positive aspects as well (Holt 1997).
Despite the many examinations of materialism, it remains
unclear how it relates to other aspects of life.
Burroughs and Rindfleisch (2002) argue that the
nature of materialism needs to be clarified, and that more
researchers are beginning to examine it in the context of
other life goals and values. While there have been many
definitions of materialism, what they have in common is
that they reflect the use of consumption to acquire more
than instrumental or use value in the things purchased.
Collectively, the definitions suggest that the individual
seeks a relationship with objects through which she or he
is enhanced in some way.
Moschis and Chruchill (1978) and Richins (1987)
have measured materialism as an attitude structure focusing on the meaning of possessions to the individual. The
model developed here depicts materialism as an attitude
structure that is influenced by the individual values of
self-enhancement and self-transcendence as used by
Schwartz (1994).
The sample for the study consisted of university
students from Canada, Germany and the U.S. There were
168, 139, and 97 respondents respectively from the three
countries. Canadian students completed and returned the
questionnaire in class, and U.S. and German students
completed the questionnaire outside of class and returned
it the next week. All participation was voluntary and no
American Marketing Association / Winter 2005
incentives were given. The final sample was 46 percent
female and 54 percent male.
Following Roberts, Manolis, and Tanner (2003),
materialism is represented as a second order factor model
with success, centrality, and happiness as first order latent
constructs. Second, the model suggests that self-transcendence values will be inversely related to materialism, and
self-enhancement values will be positively related to
materialism. The model will be tested across three cultures, Germany, Canada, and the U.S., using the procedures suggested by Steenkamp and Baumgartner (1998).
Both the measurement model and the structural model were tested for invariance across the samples. In these
tests, five statistics were used with standard cutoff criteria
as suggested by Hair et al. (1998). In addition, successively constrained models were subjected to sequential Chi
square difference tests to determine if the constrained
model fit the data as well as the baseline model.
The analysis required that the structural model proposed be tested. This was done as suggested by Byrne
(1999), maintaining the invariances established in the
measurement models in the initial structural model. Because the measurement model for materialism was invariant, it was included as a fully constrained measurement
model across the three countries. The values measurement
model was fully invariant except for the covariances that
were partially invariant with the German sample left free
to vary. The final structural model was tested first for
overall fit across countries and satisfied all criteria used.
In addition, the sequential Chi Square Difference Test
yielded a p-value of 0.74 indicating that the constrained
model predicted as well as the original model. We concluded that the structural model was invariant across
countries as predicted.
The path coefficients for the structural model were
consistent with the hypotheses established. The coefficient from self-transcendence to materialism was -0.21
(p < 0.01) indicating the negative relationship hypothesized. The result was consistent across the three countries.
The coefficient from self-enhancement to materialism
was 0.70 (p < 0.01) demonstrating the positive relationship hypothesized. This result also held across the three
There are two main conclusions to be drawn from the
study. The results of the analysis indicate that the reduced
form of the materialism scale produces a valid second
order factor model of materialism. The latent constructs
are happiness, centrality, and success and the model was
shown to be invariant across countries.
The second objective or the study was to determine
the causal sequence for values and materialism assuming
that the materialism scale is a measure of attitudes toward
consumption rather than a true value labeled as materialism. The hypothesized causal sequence was individual
values having an effect on attitudes toward materialism.
The results indicated that the proposed causal model had
an acceptable fit on all criteria. In addition to this, the
causal model was demonstrated to be invariant across all
three countries. The relationship between self-transcendent values and materialism was negative, and the relationship between self-enhancement values and materialism was positive as hypothesized.
For further information contact:
William Kilbourne
Department of Marketing
Clemson University
Clemson, SC 29634
Phone: 864.656.5296
FAX: 864.656.0138
E-Mail: [email protected]
American Marketing Association / Winter 2005
Kenneth W. Bates, University of Arkansas, Fayetteville
Kyle A. Huggins, University of Arkansas, Fayetteville
Obesity has become a major health concern for many
citizens in the United States, and it is an issue, that
according to the CDC, has reached epidemic proportion
(Manson and Bassuk 2003). It has been projected by the
United States Department of Health and Human Services
that obesity will soon overtake tobacco as the leading
cause of preventable death in the United States and will
offset many of the medical advancements made in diseases such as cancer, diabetes, and heart disease (U.S.
DHHS 2001; Manson and Bassuk 2003). Due to these
recent developments many policy makers, public-interest
groups, and concerned citizens have turned their focus
upon the restaurant industry. In the last thirty years, the
amount of money spent on food purchases outside-thehome has risen 20 percent and accounts for almost half of
American’s total yearly expenditures on food (Lin, Frazão,
and Guthrie 1999). The correlation between increases in
restaurant patronage and obesity has created concern
about the healthiness of restaurant menu items, and propositions have been made that Congress should extend the
Nutrition Labeling and Education Act (NLEA) to include
restaurant menu items. The Menu Education and Labeling
Act (MEAL) of 2003 in Congress requires restaurant
chains with twenty or more outlets to list key nutrition
information (DeLauro 2003), and the FDA has initiated
preliminary discussions about possible national standards
for the provision of nutrition information for restaurant
foods (Mathews and Leung 2003). Any ruling that mandates the provision of nutrition information at restaurants
will have profound financial, tactical, and strategic implications for retailers in the restaurant industry.
Given the importance of this issue to public policy
makers and restaurant industry managers, our research
extends recent findings related to nutrition disclosure in
table service restaurants to the fast food industry. Burton
et al. (2004) found that consumers significantly underestimate the nutritional content of items that are higher in
calories, fat, and sodium while estimations of relatively
healthier items were far closer to actual nutrient levels.
When item nutrition levels were actually provided, respondents significantly decreased in their purchase intention for items inconsistent with nutrient estimates (relatively unhealthier items) and either showed no effect or
increased purchase intention for items consistent with
nutrition estimates (relatively healthier items). Results
American Marketing Association / Winter 2005
show that consumers may be able to distinguish differences between relatively healthy and non-healthy items,
but they are generally unaware of the large degree to
which many items are unhealthy. This, in conjunction
with the decline in purchase intention for unhealthy items
when nutrition information is provided, suggests benefits
from nutritional disclosure in dinner house restaurants.
While these are important findings for dinner house
restaurants, we believe the fast food industry is an equally
important arena for exploration. The National Restaurant
Association projects that $123.9 billion will be spent on
quick service dining in 2004 (National Restaurant Association 2004). While Burton and his colleagues (2004)
assessed the effect of nutrition disclosure on purchase
intention and choice, we propose that significant gender
differences will be found within fast food item evaluations and choice.
There has been a substantial amount of research
stressing the importance of physical appearance and attractiveness, especially the importance that it holds for
females (e.g., Cash, Winstead, and Janada 1986; Bar-Tal
and Saxe 1976; Richins 1991). According to Hirschman
(1987), women’s personal value is much more likely to be
determined by physical attractiveness while males will be
evaluated on a wider range of attributes. In 1992, Myers
and Biocca found that watching only 30 minutes of
television programming and advertising can alter a young
woman’s perception of her body. Empirical studies have
also found that women are more concerned about their
physical appearance than men (Burton, Netemeyer, and
Lichtenstein 1995); young women frequently compare
themselves with idealized advertisement models, and the
amount of comparison is negatively correlated with satisfaction of one’s physical appearance (Richins 1991).
Therefore, in light of this stream of literature, it seems
appropriate to investigate gender effects within the patronage of quick service restaurants.
Overall, fast food results model that of dinner house
restaurants as respondents’ estimations of calorie, fat, and
sodium levels in fast food items are generally inconsistent
with actual levels. As items become higher in unhealthy
attributes, consumers significantly underestimate objective nutrient levels. Of concern to the MEAL proposition,
consumers are also unable to predict, with any increased
accuracy, the levels of fat or sodium in an item when
caloric content alone is provided. While consumers may
know that higher calories are positively related to higher
saturated fat and sodium levels, they do not appear to
make accurate predictions of these levels from calories
Findings also indicate that males generally visit fast
food establishments more often than females, have more
positive attitude towards unhealthy items, and choose
them more frequently. As expected, when no nutrition
information is provided, males select unhealthy items
nearly 70 percent of the time as opposed to women at only
a quarter of the time. However, under the full nutrition
condition (provided information on calories, fat, and
sodium), males and females both significantly decrease
their frequency of choosing these items. Although males
still choose the unhealthy items 47 percent of the time
compared to women at only 5 percent, this provides
empirical support for requiring nutrition disclosure. Due
to the preference exhibited by males for unhealthier items
and the significant effect of nutrition condition on item
content favorability and purchase intentions, the level of
nutritional disclosure could potentially have a large impact upon the male gender. References available upon
For further information contact:
Kenneth W. Bates
Marketing and Logistics Department
Sam M. Walton College of Business, 302 BADM
University of Arkansas
Fayetteville, AR 72701
Phone: 479.575.4055
FAX: 479.575.8407
E-Mail: [email protected]
American Marketing Association / Winter 2005
Thorsten Hennig-Thurau, Bauhaus-University of Weimar, Germany
Peter C. Honebein, University of Nevada, Reno
Benoit Aubert, Grenoble Ecole de Management, France
Vargo and Lusch (2004) argue that it is the customer
who eventually determines the value of a product by using
it, not the producer by manufacturing and distributing it.
Specifically, the customer “must learn to use, maintain,
repair, and adapt the appliance to his or her unique needs,
usage situation, and behaviors” (Vargo and Lusch 2004,
p. 11). The question we address in this research is derived
directly from this shifting of the focus of value production
from the producer to the customer: How can the producer
ensure that there is not only value potential embedded in
its goods, but also that this value potential will be unlocked appropriately by the customer during product
the product’s consumption and, ultimately, its disposal.
The overall customer value of a product is the totality of
values realized across these different stages.
Second, the customer value delivered by a product
over the different phases is the result of a joint effort of the
producer and the consumer. Both parties’ actions and
competence are indispensable for generating customer
value in each phase. In the joint value creation framework,
manifest products carry the potential for a certain level of
customer value, with this potential being innovated and
implemented by the producer in its laboratories and factories, respectively. The level of value production can be
increased by an active role of the customer in these phases.
Customer Education Model
In this research, by drawing upon the literature of
customer-as-coproducer from service research, we present
the idea of a joint value creation process between producers and consumers for the context of consumer goods. We
then illustrate how the use of customer education, referred
to as a company’s measures and actions that are targeted
at the development of post-purchase related customer
knowledge and skills, can impact key company outcomes,
such as customer satisfaction, trust, and loyalty.
Joint Value Creation
Organizations should endeavor to increase the competence of customers that is needed by the customer to
stimulate full use of a product during consumption. We
suggest a joint value creation framework should serve as
the theoretical basis for the customer education concept
since it demonstrates how customer value is created.
The framework is founded on two basic axioms.
First, it is presumed that the generation of customer value
represents a multi-stage process, which starts with the
generation of the product idea, continues with the development and production of the product, and finalizes with
American Marketing Association / Winter 2005
As illustrated in the joint value creation framework,
customers hold the key to unlocking post-purchase value
through the preparation, use, and disposition of products.
To aid the customer, companies offer supporting activities, such as customer education, which ensure customers
have the necessary skills to perform key value-driven
tasks. We offer a conceptual model that predicts the
effects of unlocking value through customer education on
product satisfaction, company satisfaction, customer trust
in the firm, and customer loyalty (see Figure).
From a conceptual standpoint, our research suggests
that customer education can be a catalyst for increasing
customer loyalty. Through the acquisition of skills, we
expect customers to use products more intensely, which
leads to greater product performance and increased product satisfaction. Additionally, we believe customer education also influences the customer’s satisfaction and trust
with the company. The combination of customer satisfaction, company satisfaction, and company trust is what
ultimately leads to customer loyalty. Future research
should examine the link between customer education and
customer loyalty.
For further information contact:
Thorsten Hennig-Thurau
Department of Marketing and Media Research
Bauhaus-University of Weimar
Bauhausstr. 11
99423 Weimar
Phone: +49.3643.58.3822
FAX: +49.3643.58.3791
E-Mail: [email protected]
American Marketing Association / Winter 2005
Linda M. Foley, University of Mississippi, University
Douglas W. Vorhies, University of Mississippi, University
Victoria D. Bush, University of Mississippi, University
Increasingly, the dynamic capabilities view is being
utilized as a favored approach to understanding a firm’s
competitive advantage. The dynamic capabilities view
builds on the previous resource based view of the firm by
supplementing its strengths while simultaneously recognizing its weaknesses (Priem and Butler 2001; Eisenhardt
and Martin 2000; Teece, Pisano, and Schuen 1997). This
emerging capabilities literature realizes that the possession of rare, imperfectly imitable, and valuable resources
is an important step to build competitive advantage.
However, dynamic capabilities also address the development and deployment of these resources and how resources are integrated together within a firm (Barney, Wright,
and Ketchen 2001; Day 1994). The dynamic capabilities
“view recognizes that the deployment of resources through
these organizational processes may better explain firm
performance variations than absolute resource levels in
driving firm performance” (Ray, Barney, and Muhanna
Due to its inherent advantage, researchers have studied this important concept (e.g., Teece, Pisano, and Schuen
1997; Day 1994). However, despite all the recent attention, little research has been conducted with specific
regard to dynamic capabilities and marketing. Since marketing processes are constantly undergoing adaptations
that parallel the changes in consumer preferences and the
environment as a whole, it is extremely important to
understand marketing processes in a dynamic context.
A better understanding of marketing capabilities may
lead to the ability to answer some fundamental questions
Barney, Jay, Mike Wright, and David J. Ketchen, Jr.
(2001), “The Resource-Based View of the Firm: Ten
Years After 1991,” Journal of Management, 27,
Day, George S. and Prakash Nedungadi (1994), “Mana-
American Marketing Association / Winter 2005
to both academics and practitioners. For example, why are
some firms better at adapting to change than others? What
business processes and routines must be in place to allow
firms to adequately adjust to modifications in consumer
preferences, economic, or other environmental conditions? How do firms generate continual and successful
innovative thinking? How does this internal reconfiguration to adapt to external changes affect overall business
performance, from both a perspective of financial outcomes and positions of advantage? And, finally, how do
specific marketing functions such as customer relationship and brand management play into outcomes like
customer satisfaction and brand equity from a dynamic
capabilities perspective?
This paper attempts to answer the above questions by
integrating dynamic capabilities into a single unified
framework. In order to do so, we classify and subdivide
the various levels of organizational routines and processes into lower and higher order capabilities constructs.
Since the addition of the word “dynamic” to the term
“dynamic capabilities” implies learning through reconfiguration, development, and integration, it was necessary
to integrate the organizational learning literature into the
framework presented here.
This paper contributes to academia by tying marketing capabilities to the financial performance of the firm,
which is a topic which has had numerous calls for research
(e.g., Srivastiva, Shervani, and Fahey 1998) including a
recent edition of the Journal of Marketing devoted to
understanding this relationship. Additionally, the framework was also developed based on qualitative interviews
with key informants in marketing organizations.
gerial Representations of Competitive Advantage,”
Journal of Marketing, 58 (April), 31–44.
Eisenhardt, Kathleen M. and Jeffrey A. Martin (2000),
“Dynamic Capabilities: What Are They?” Strategic
Management Journal, 21, 1105–21.
Priem, Richard L. and John E. Butler (2000), “Is the
Resource-Based ‘View’ a Useful Perspective for
Strategic Management Research?” Academy of Management Review, 26 (1), 22–40.
Ray, Gautam, Jay B. Barney, and Waleed A. Muhanna
(2004), “Capabilities, Business Processes, and Competitive Advantage: Choosing the Dependent Variable in Empirical Tests of the Resource-Based View,”
Strategic Management Journal, 25 (1), 23–38.
Srivastava, Rajendra K., Tasadduq A. Shervani, and Liam
Fahey (1998), “Market-Based Assets and Shareholder Value: A Framework for Analysis,” Journal of
Marketing, 62 (1), 2–18.
Teece, David J., Gary Pisano, and Amy Shuen (1997),
“Dynamic Capabilities and Strategic Management,”
Strategic Management Journal, 18 (7), 509–33.
For further information contact:
Linda M. Foley
Department of Marketing
School of Business Administration
University of Mississippi
University, MS 38677
Phone: 412.401.2662
FAX: 412.481.3160
E-Mail: [email protected]
American Marketing Association / Winter 2005
Gilbert N. Nyaga, Michigan State University, East Lansing
Roger J. Calantone, Michigan State University, East Lansing
Thomas J. Page, Michigan State University, East Lansing
This paper explores the mediating role of manager’s
attitude, subjective norms, and perceived behavioral control in the adoption of RFID technology. Moderating
variables are also examined. Strategic and theoretical
implications are discussed. The examined antecedents are
posited to have significant influence on RFID adoption.
Advances in technology have made the need for
companies to implement new systems that improve business process performance a continuous imperative. However, decision makers in organizations are not always
willing to implement or adopt new technologies or to do
so early. This unwillingness maybe due to shortage of
funds, lack of appreciation of the technology’s potential,
or even outright negative attitude toward new technology.
This study seeks to understand how managers’ attitude
toward a new technology, radio-frequency identification
(RFID), influences their decisions to implement, delay, or
reject its adoption. RFID is the latest technology byword
in supply chain management. Manufacturers, wholesalers, retailers, and third party firms are seeking to leverage
the advantages brought about by the RFID technology.
Yet, there are marked differences in the deployment of the
technology among firms, especially with respect to the
attitude of managers mandated to evaluate and implement
RFID adoption.
There exists a significant body of research on the
reasons why people accept or reject new technological
systems (Davis et al. 1989). Most studies are premised on
theories and models borrowed from social psychology
(Davis 1986; Swanson 1987). In this study, the theory of
reasoned action (TRA) and its two variants, the theory of
planned behavior (TPB) and the technology adoption
model (TAM) are used. Extant literature shows that stipulations of these theories have been applied, directly or
indirectly, in examining the impact of an individual’s
attitude on behavioral intention, and subsequently observed behavior (Eagly and Chaiken 1993). Most studies
on technology adoption tend to focus on end users (Davis
et al. 1989) while ignoring the role of manager’s involved
in implementation of those technologies. This study seeks
American Marketing Association / Winter 2005
to address this gap by underscoring the importance of
managers’ attitude toward RFID adoption.
Radio-Frequency Identification (RFID) Technology
RFID consists of a passive radio-frequency tag with
a printed antenna and a radio-frequency (RF) emitter/
reader. The tag emits a signal using energy derived from
the RF emitter/reader. The tag stores detailed product
information and is attached to a product or pallet, with
each tag specifying a unique product identification code
(Rutner et al. 2004). Currently the RFID signal range is a
few meters, but with continued advances in technology,
the range is likely to increase tremendously. Use of RFID
enables more accurate inventory management, fewer stockouts, and less product loss throughout the supply chain.
As a result, most retailers including Wal-Mart, Target,
and Albertsons as well as the Department of Defense have
imposed deadlines for their suppliers to begin shipping
RFID-tagged pallets and cases (Bednarz 2004).
RFID can be deployed in anything that can be tagged,
which means that RFID can be used in very diverse
industries and data management systems. For instance, in
the tire industry, RFID chips that are smaller than the size
of a rice grain can be embedded into new tires, which
enables association of the tire with a specific vehicle, store
a 12-character coding for a number required by the U.S.
Department of Transportation, and indicate when and
where the tire was manufactured (Faber 2002). Both big
and small firms are implementing RFID technology. For
example, a fairly small company, Beaver Street Fisheries
is using RFID to track cases and pallets of fish and more
exotic fare-including alligator and turtle meat at the company’s seafood-processing and packing plant (Sullivan
In spite of the demonstrable benefits, some managers
are less than enthusiastic about implementing RFID technology. One of the reasons is that it is a costly investment.
Generally, the cost of implementing RFID ranges from
$100,000 to several millions (Sullivan 2004). A market
study by The Aberdeen Group shows that most of the
polled company officials believe that deploying RFID
will add costs and significantly erode their profit margins
(Cooke 2002). Other concerns include lack of RFID
standardization and security/privacy issues. Managers are
concerned that some RFID deployments may not be
compatible with those of supply chain partners. Indeed,
big firms such as Kimberly-Clark, Target, and Wal-Mart
have been pressing for adoption of standards on what is
included in RFID chip and how readers and tags communicate (Bacheldor and Sullivan 2004).
individual’s belief about the extent of difficulty or ease of
performing the behavior (i.e., implementing RFID). It is
a measure of a person’s perception of his or her control
over factors necessary to carry out the behavior (Hill et al.
1996), and is expected to reflect past experiences as well
as anticipated impediments and obstacles (Doll and Ajzen
1992). Examining managers’ perceived behavioral control as an antecedent of intention to adopt new technology
can help better understand RFID adoption.
TAM is an adaptation of TRA, which aims at providing a basis for tracing the impact of external factors on
internal beliefs, attitudes, and intentions (Davis et al.
1989) and is specifically tailored for modeling user acceptance of information systems (Phillips et al. 1994). According to TAM, the key determinants of acceptance
behavior are perceived usefulness and perceived ease of
use. Perceived usefulness refers to the prospective user’s
subjective probability that using a specific application
system will increase his/her job performance in an organizational context. Perceived ease of use (EOU) reflects
the potential difficulties in transferring and utilizing the
new technology both by the adopting firm and individuals
expected to use it (Phillips et al. 1994). TAM stipulates
that people form intentions to perform behaviors that they
have positive affect. For instance, people form intentions
toward using computer systems based largely on their
cognitive appraisal of how the computer system will
improve their performance. TAM offers a base for examining antecedents of managers’ attitude toward deploying
The theory of reasoned action (TRA) (Ajzen and
Fishbein 1980) is a very general model that has been
subjected to several adaptations. These include Davis’
(1986) technology adoption model (TAM) and the theory
of planned behavior (TPB) (Ajzen 1980). These theories
have been shown to provide a robust analysis of the
attitude-behavior intention relationship. In this study,
antecedents of attitude toward technology adoption postulated in TAM, and antecedents of behavioral intention
posited in TRA and TPB are integrated to develop a model
of RFID adoption.
TRA stipulates that an individual’s performance of a
behavior is determined by his or her behavioral intention
(BI) to perform the behavior, and that BI is jointly determined by the person’s attitude and subjective norms
concerning the behavior in question (Ajzen and Fishbein
1980; Davis et al. 1989). BI is a measure of strength of
ones intentions to perform a specified behavior while
attitude refers to the degree to which a person has favorable or unfavorable evaluation of the behavior in question. Subjective norm (SN) is a person’s perception that
people who are important to him/her think that he/she
should or should not perform the behavior (Ajzen and
Fishbein 1980; Hill et al. 1996). Extant literature on
adoption identifies several salient referents including top
management, supervisors, the organization’s MIS department, technology experts, and peers. Attitude toward a
behavior is determined by an individual’s salient beliefs
about consequences of performing the behavior (i.e.,
adopting RFID technology) multiplied by the subjective
values or evaluations of those consequences (i.e., impact
of RFID technology). Beliefs refer to an individual’s
subjective probability that performing the target behavior, in this case deploying the RFID technology, will result
in a given consequence. TRA has been applied widely and
provides a useful framework for this study.
TPB is an extension of TRA, which seeks to address
limitations in TRA with respect to behaviors over which
people have incomplete volitional control (Ajzen 1985;
Doll and Ajzen 1992). TPB stipulates that besides attitude
and subjective norms (as stipulated in TRA), another
factor, perceived behavior control is predictive of behavioral intentions. Perceived behavioral control refers to an
American Marketing Association / Winter 2005
The preceding literature review highlights several
variables that have a bearing on a manager’s attitude and
behavioral intention with respect to implementing RFID
in their organizations. Each of the three models, TRA,
TPB, and TAM, provides some bases for understanding
technology adoption. Thus, this study integrates stipulations of the three models to develop the model shown in
Figure 1.
As argued in TAM, perceived usefulness and perceived ease of use are stipulated to influence managers’
attitude toward RFID technology adoption (Davis et al.
1989; Adams et al. 1992; Phillips et al. 1994). In the case
of RFID adoption, perceived usefulness refers to perceived RFID utilities for the organization. It is conceptualized in terms of costs and benefits of RFID technology
compared to current technology (i.e., technology in use
that is to be replaced). For instance, if a firm has bar coding
technology in place and wishes to adopt RFID, the manager will compare the costs of implementing RFID (actual, purchase cost, installation costs, employee training
costs, etc.) and expected benefits (i.e., asset management,
error reduction, supply chain collaboration, etc.) against
Conceptual Model
Perceived usefulness
Perceived ease of use
and implementation
Normative beliefs and
motivation to comply
with referent
Manager’s attitude
toward adopting RFID
Manager’s subjective
norms toward adopting
Manager’s perceived
behavioral control on
adopting RFID
Behavioral intention
about adopting
♦ Manager’s experience
♦ Firm size
the costs and benefits of bar coding. If the gap between
these is significantly large (i.e., RFID is more effective
than bar coding), then the manager can justifiably seek
RFID implementation. Whether a firm adopts RFID technology or not is likely to be influenced by the manager’s
cognitive evaluation of the gains from the implementation. Thus, it is hypothesize that:
H1: Perceived usefulness has a direct and positive effect
on the manager’s attitude toward RFID adoption.
Perceived ease of use is conceptualized in terms of
extent of difficulty, time, and learning costs associated
with changing from the current system to RFID technology. If RFID deployment is perceived to be cumbersome
and difficult, or inconveniencing to supply chain partners,
then it is expected that managers might be hesitant to
implement it. However, if the deployment is perceived to
be less involving, then managers might be inclined to
readily implement it. Moreover, the cost of training employees on how to use RFID can be high and time
consuming. Learning costs can also include the negative
performance implications of technology changeover and
potential losses in the process of replacing the current
system with RFID. These costs could influence managers’ attitude toward RFID adoption. Thus, it is hypothesized that:
H2: Perceived ease of use has a direct and positive effect
on the manager’s attitude toward adopting RFID.
American Marketing Association / Winter 2005
Managers’ normative beliefs and motivation to comply with referents are stipulated to influence subjective
norms and subsequently behavior intention (Ajzen and
Fishbein 1980; Davis et al. 1989). Referents expected to
exert influence on managers adopting RFID include supply chain partners, senior managers, consultants, etc. For
instance, recommendations by highly reputed consultants
as well as advice by experienced executives held in high
esteem by a manager may motivate the manager to undertake a specific business function, in this case, deploying
RFID technology. Furthermore, if supply chain partners
and competitors are deploying RFID, then managers will
most likely follow suit. Thus, it is hypothesized that:
H3: Manager’s normative beliefs and motivation to comply with a referent have direct effects on his/her
subjective norms toward RFID adoption.
The manager’s attitude toward implementation of
RFID is posited to be a major determinant of whether or
not he/she executes RFID deployment. Attitudes develop
from beliefs that people hold about the object of the
attitude (Doll and Ajzen 1992). It is expected that if
managers strongly believe that implementing RFID in
their organization will culminate in improved process
performance and better coordination with supply chain
partners, they are likely to develop favorable attitudes
toward RFID. However, if their RFID evaluation is negative, then we expect that their attitude toward RFID
implementation will be negative. This is expected to
impact on their behavioral intentions and subsequently
decisions to either implement or not implement the RFID.
Thus, it is hypothesized that:
H4: Manager’s attitude toward RFID technology has a
direct and positive effect on intentions to adopt RFID.
Subjective norms have been shown to influence behavioral intention (Ajzen and Fishbein 1980; Hill et al.
1996; Karahanna et al. 1999). In the case of RFID adoption, it is expected that manager’s subjective norms as
determined by normative beliefs and motivation to comply with referents will have a strong influence on technology deployment. These norms may arise from available
information (i.e., trade journals, business magazines, consultant reports, etc.) or desire to conform to expectations
of senior managers, experts, and/or supply chain partners.
Thus, it is hypothesized that:
H5: Manager’s subjective norm toward RFID has a direct
and positive effect on intention to adopt RFID.
Perceived behavior control, according to Ajzen
(1991), can influence whether people choose to pursue an
outcome, their degree of preparation, the effort they
expend, their perseverance, as well as the thoughts and
emotions experienced during the task. Thus, the extent to
which manager’s view themselves as capable of implementing RFID, both in terms of mandate to oversee RFID
implementation and possession of requisite skills, will
influence their behavioral intention. Moreover, as Doll
and Ajzen (1992) state, beliefs dealing with presence or
absence of required resources and opportunities to perform a specific behavior are perceived to dictate perceived behavioral control. It is expected that the more
resources and opportunities a manager has, the greater
should be their perceived behavioral control over RFID
adoption. Consequently, greater perceived behavioral
control is expected to lead to greater intention to adopt
RFID. Thus, it is hypothesized that:
H6: Manager’s perceived behavioral control on RFID
deployment has a direct effect on intention to adopt
experience with a practice differentially affects their attitudinal and normative beliefs, which in turn influences
their intention to continue or introduce a practice. Doll and
Ajzen (1992) concluded that experience with behavior
increased the overall predictiveness of attitude, subjective
norm, and perceived behavioral control on behavior intention.
Firm size has also been stipulated as a moderator. In
their international study of attitudes toward adoption,
Bunker and McGregor (2002) suggest that contextual
variables such as firm size and business type are the most
influential factors. Indeed, they report that skill-based
(experience) factors have lesser influence on adoption
than contextual factors (i.e., firm size, business type).
Sillence et al. (1998) also reported size of business as an
influential factor in adopting e-commerce. In small firms
faced with resource constraints, RFID implementation
may not be the highest priority project. However, in large
firms with greater resource endowment, RFID implementation may be easily accomplished. Moreover, the influence of trading partners may be more intense (i.e., WalMart’s requirement that its top 100 suppliers adopt RFID).
From these studies, it can be argued that managers’
past experience in implementing new technology and firm
size will increase the predictive power of antecedents of
behavioral intention (attitude, subjective norm, and perceived behavior control). In other words, the three antecedents will more strongly predict intention to implement
RFID among managers with experience in implementing
new technologies than those with no prior experience, and
in bigger firms than in small firms. Thus, it is hypothesized
H7: The influence of (i) attitude, (ii) subjective norms,
and (iii) perceived behavioral control on intention to
adopt RFID technology increases with:
Increases in manager’s experience in new technology adoption
Increases in firm size
Moderators of Attitude-Behavior Relationship
Past studies employing TPB have shown that situational and personal factors moderate the relationship
between attitude, subjective norm, perceived behavioral
control, and behavior intention (Doll and Ajzen 1992; Hill
et al. 1996; Ajzen 2001). For instance, in a study of
competitive benchmarking intentions among managers,
Hill et al. (1996) found out that attitude has stronger effect
for more experienced managers than less experienced
managers. They posit that managers’ experience or lack of
American Marketing Association / Winter 2005
To test the proposed model, data can be collected
using a survey questionnaire directed to senior logistics
officials involved in the new technology implementation
process. The study sample can be selected from member
list of appropriate industry associations such as the Council of Logistics Management. Mail surveys can be effective in collecting required data. To measure the constructs
stipulated in the study, tested and validated measures in
extant literature could be adapted. For perceived usefulness and perceived ease of use of RFID, Davis’ (1989)
technology acceptance scale could be adapted with modifications to make them relevant to RFID deployment.
Measures of attitude and subjective norms could be adapted from TRA scale (Ajzen and Fishbein 1980) while
perceived behavioral control construct measures could be
adapted from Ajzen’s (1985) TPB scale. Behavioral intention construct measures have been developed in all
three theories (Ajzen and Fishbein 1980; Ajzen 1985;
Davis 1989). The scales entail asking the respondents to
indicate the extent to which they agree or disagree with
statements concerning the subject of interest on a sevenpoint Likert scale anchored with 1 = “Strongly Disagree”
and 7 = “Strongly Agree” (Ajzen and Fishbein 1980;
Ajzen 1985; Davis 1989). Measures of moderator variables include information about the respondent such as
number of years as a manager (experience) and company
information such as annual revenue, number of employees, etc (firm size). Firms could also be grouped as small,
medium, or large in size.
To analyze the data, structural equation modeling
(SEM) approach could be used. SEM is a comprehensive
statistical approach to testing hypotheses about relations
among observed and latent variables, and combines aspects of multiple regression and factor analysis to estimate
a series of interrelated dependence relationships simultaneously (Hair et al. 1998). SEM provides a robust way of
addressing the relations between constructs and subsequently enables a better understanding of issues in question.
RFID’s implementation is expected to attract inputs from
diverse quarters including industry pundits, supply chain
partners, managers’ peers, and top echelons of firm’s
management hierarchy. However, extant literature has
not given much attention to this fact. This study therefore
raises an issue of practical and theoretical import, which
calls for further investigation.
Third, the study implicitly extends the theory of
reasoned action to supply chain research. In examining an
issue that has widespread impact on the supply chain, the
study serves to open new frontiers for TRA, TAM, and
TPB applications and research. Future research is likely to
add great value by investigating organizational and supply chain issues within the framework of expectancy
models. Moreover, the study takes into account all three
theories, thereby developing a more comprehensive assessment of attitude-intention linkage within the context
of new technology adoption. Such an integrative view of
expectancy models is likely to give better insights to
future research.
Fourth, the study raises the issue of factors moderating the impact of manager’s attitudes toward new technology adoption on behavioral intentions. Firm size and
manager’s experience are only a start. There could be
other moderating variables that future research can explore. For instance, how does centralization versus decentralization mediate the attitude-intention relationship? By
understanding the moderating effects of different variables, researchers and practitioners alike will be able to
identify conditions in which specific actions are most
appropriate. This in turn will have both managerial and
theoretical implications.
There are several strategic and theoretical implications from the preceding arguments. First, the study raises
the issue of manager’s attitude toward RFID application,
and by extension technology adoption for firms engaged
in supply chain relationships. Past studies have tended to
ignore the role of manager’s attitude, yet, in the final
analysis, the manager in charge of new technology deployment must be convinced that RFID implementation is
appropriate, feasible within a given timeframe, and urgent. This is an issue of great importance especially with
the expanding deployment of RFID in supply chain operations. By examining the role of managers’ attitude,
greater insights are likely to emerge that could enable a
better understanding of not only RFID adoption, but also
other new technology adoption situations. This could
result in better planning of marketing efforts.
Scholars and practitioners alike concur that new
technology adoption is a process characterized by many
challenges for both the users and implementers. The study
shows that the role of managers involved in technology
adoption ought to be given greater consideration when
examining technology adoption. In addition, the study
shows that an integrative assessment of propositions from
various expectancy models greatly help in the understanding of technology adoption process. Moreover, as
Davis et al. (1989) suggest, conditions under which attitudes mediate the belief-intention link ought to be investigated further. This study is a positive step in responding
to Davis et al.’s challenge.
Secondly, the study reinforces the role of normative
beliefs in technology adoption. RFID deployment has
strategic and operational implications on firm’s partners
in the supply chain. Furthermore, being a recent development in supply chain collaboration and management,
The issues raised in this study have important implications for academics and researchers. For academicians,
the study raises important questions about the mediating
role of manager’s attitude in technology adoption. Indeed,
the study’s focus on technology adoption from the point
American Marketing Association / Winter 2005
of view of the manager’s attitude will be of interest to
consumer behavior researchers. For practitioners, the
issues raised offer an opportunity for a better assessment
and planning of new technology implementation and
marketing programs. The study has implications on how
to design new technology adoption programs and measures to increase usage (i.e., number of companies adopting RFID).
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Intention and Behavior: An Introduction to Theory
and Research. Reading, MA: Addison-Wesley.
Hair, Joseph F., Rolph E. Anderson, Ronald L. Tatham,
and William C. Black (1998), Multivariate Data
Analysis, 5th ed. Upper Saddle River, NJ: Prentice
Hill, Matt, Leon Mann, and Alexander J. Wearing (1996),
“The Effects of Attitude, Subjective Norm, and SelfEfficacy on Intention to Benchmark: A Comparison
Between Managers with Experience and No Experience in Benchmarking,” Journal of Organizational
Behavior, 17, 313–27.
Karahanna, Elena, Detmar W. Straub, and Norman L.
Chervany (1999), “Information Technology Adoption Across Time: A Cross-Sectional Comparison of
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Phillips, Lisa A., Roger Calantone, and Ming-Tung Lee
(1994), “Intentional Technology Adoption: Behavior Structure, Demand Uncertainty, and Culture,”
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Hulland (2001), “Intermediating Technologies and
Multi-Group Adoption: A Comparison of Consumer
and Merchant Adoption Intentions Toward a New
Electronic Payment System,” Journal of Product
Innovation Management, 18, 65–81.
Rutner, Stephen, Mathew A. Waller, and John T. Mentzer
(2004), “A Practical Look at RFID,” Supply Chain
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(1988), “The Theory of Reasoned Action: A MetaAnalysis of Past Research with Recommendations
for Modifications and Future Research,” Journal of
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American Marketing Association / Winter 2005
For further information contact:
Gilbert N. Nyaga
Michigan State University
N370 Business College Complex
East Lansing, MI 48824
Phone: 517.353.6381
FAX: 517.432.1112
E-Mail: [email protected]
American Marketing Association / Winter 2005
Russell Adams, University of Texas – Pan American, Edinburg
For decades researchers have ascribed to Rogers’ and
Porter’s contention that new products are one of the
strategic keys for a company’s survival (Porter 1980;
Rogers 1962), much research has been conducted in this
field which is well summarized by Mahajan, Muller, and
Bass (1990). Companies are continually developing new
products to remain competitive in their markets. Given the
substantial investment involved and the relatively low
success rates of new product introduction, fifty percent of
new product introductions fail within the first year (Zirger
and Mandique 1990), and given that new products can
count for a third of a firms profits (Booz et al. 1982)
research that discovers ways to increase this success rate
is critically important. Several aspects of successful New
Product Development (NPD) and adoption have been
studied independently, such as diffusion, strategic partnerships, Word-of-Mouth (WOM), and installed user
base as well as the effects of marketing, but these factors
have not been modeled in conjunction.
The goal of this paper is not to create a definitive
model for guaranteeing the success of new product launches, but to shift the theoretical lens to allow researchers to
pursue avenues that have yet to be studied. By combining
the different aspects of product success into one model it
will be easier to recognize the critical factors of success
and facilitate the focus of future research on these aspects.
The paper also explains the appropriateness of using
percolation (Weisbuch and Solomon 2000) as an alternate
view of diffusion theory that reflects what occurs in
consumer markets.
The model views product success, measured by diffusion, as the intersection of two important paths; production, and marketing. From the production side, network
effects are created by both installed user base and licensing relationships, this then expands the content value of
the hardware leading to greater diffusion. The marketing
side involves the human or consumer element. With
appropriate marketing and the positive attitude (which
can also be derived from the installed user base), positive
WOM will synergistically combine with the network to
result in product diffusion (percolation). The comprehensive model is then applied to the current platform wars for
computer gaming. Currently Sony, Microsoft, and Nintendo are vying for dominance in the console game market
with Sony’s Playstation 2 the current leader. The value of
the model becomes apparent as the factors of success for
Sony reflect the synergies that are developed in the model.
References available upon request.
For further information contact:
Russell Adams
University of Texas – Brownsville
80 Fort Brown
Brownsville, TX 78520
FAX: 956.983.7558
E-Mail: [email protected]
American Marketing Association / Winter 2005
Min Lu, University of British Columbia, Vancouver
Yanbin Tu, University of Connecticut, Storrs
This paper investigates the income elasticity of household’s demand for communication and IT (CIT) products
in twenty-three OECD countries during 1989 to 2001. We
find that CIT products are luxury goods to the households
in these countries. We discuss the marketing implications
of our findings, and provide some marketing recommendation.
Business firms engaged in the manufacturing and
sales of communication and IT products are facing a
dynamic and challenging marketplace. In such an environment, the capacity to attract and retain consumers, and
maintain reasonable profit margins, is critical to the business success. The idea and practice of differentiating and
segmenting customers are quite common in the technology sector. Some communication and IT products vendors
such as Dell divide their customers into categories of
home, small business, and large business. Other vendors
such as Amazon target the markets in different countries.
However, these differentiations and segmentations are
typically based on differences in the type of product or
service each segment desires. Theoretically or empirically, we need to offer additional information that can be
used to support and refine their differentiating and segmenting strategy. One perspective is to measure whether
one commodity is necessary or luxury to different groups
of customers. This represents an important research topic,
because understanding the nature of income demand
elasticity is very useful to developing effective pricing
and versioning strategies for communication and IT products vendors. According to economic theory, the income
elasticity of demand is used to describe how many percentage points the demand for an item will change when
income adjusts by one percent. An income elasticity of
demand greater than one suggests that the good is luxury
to the consumer. An income elasticity of demand between
zero and one implies a necessary good to him, while a
value less than zero suggests that the good is an inferior
good to him.
The objective of this research is to determine whether
communication and IT products are considered luxury
American Marketing Association / Winter 2005
goods or necessary goods by households, who exhibit
different demand patterns from other categories of consumers such as private firms and government agencies.
We investigate the income elasticity of household’s demand for communication and IT products in the OECD
countries ranging from 1989 to 2002, and find that communication and IT products are luxury goods to households in OECD countries. We also discuss the marketing
implications of our findings in the paper.
The rest of the paper is organized as follows: Brief
Literature Review; Hypothesis and Testing Results; A
Discussion of our Findings; and Concludes the paper with
Limitations of this work.
For a given product, income elasticity and price
elasticity of demand are expected to change over time as
the product moves through its life cycle. Early marketing
researchers about product life cycle theory including
Clifford (1965), Levitt (1965), Cox (1967), Polli and
Cook (1969), and Scheuing (1969) describe in detail the
four major stages in a product’s life cycle: introduction,
growth, maturity, and decline. New products diffusion
models that incorporate price changes have been developed by Robinson and Lakhani (1975), Bass (1980),
Jeuland (1981), and Kalish (1985). From this literature,
price elasticity is expected to increase as a product moves
through its life cycle. Two reasons are for this result. First,
consumers will collect more information about the product, especially regarding availability, deals, prices. and
promotions, in the later stages of the life cycle (Tellis
1988; Tellis et al. 1988). Second, the “early adopters”
during the introduction stage tend to have higher incomes
and are more likely to exhibit lower price elasticities,
accordingly lower income elasticities, than late adopters
(Onkvisit et al. 1989; Nagle 1987; Simon 1979). So, we
can say that price elasticity of demand is likely to be more
negative in the later stages of the product life cycle.
A better understanding of income elasticity and/or
price elasticity of demand in combination with the product
life-cycle theory can enable more effective marketing
strategies. For instance, if a product is necessary to some
consumers, they are more likely to be early adopters and
more likely to purchase the product during the introduction and growth stages of the product life cycle. In addition, these consumers are less price-sensitive so a price
premium can be charged. Luxurious users, on the contrary, do not tend to have an “urgent” need for the product,
and are more likely to buy the product during the growth
or maturation stages. Luxurious users are also more sensitive to prices, that is, lower prices likely to spur demand
and higher prices likely to discourage demand.
Economics and marketing scholars have conducted
some empirical research on the income elasticities of a
number of goods and services, such as energy (Bohi
1981), agricultural products (Klonaris and Hallam 2003;
Mdafri and Brorsen 1993) healthcare (Matteo and Matteo
1998; Getzen 2000; Freeman 2003) and information goods
(Bakos and Brynjolfsson 1999, 2000). Lu et al. (2004)
measure whether computers and packaged software are
necessary or luxury to private firms, households and
government agencies in USA. They find that such IT
products are necessary goods to private firms, luxury
goods to households and inferior goods to government
agencies. This paper is related to Lu et al.’s research.
However, the difference of this study form theirs is as
follows: (1) we investigate communication and IT products, a broader range of commodities, which include
computers and packaged software; (2) we conduct a
global measurement of income elasticity of communication and IT products across twenty-three countries, which
provide more robust testing results; (3) this study only
focuses on the households.
The demand for a commodity is said to be normal if
demand does not fall when income rises, and inferior if
demand falls when income rises. We define the income
elasticity of demand for x as η = (cx / cM) where M is the
income of consumer. η is interpreted as the percentage by
which the demand for good x changes when income
changes by one percent. A commodity, say x, is a luxury
good if η < 1, a necessary good if 0 < η < 1, or an inferior
good if η < 0.
While some parts of communication and IT products
will be necessary goods to private firms (see Brynjolfsson
and Yang 1996; Dewan and Min 1996; Lu et al. 2004), we
expect that overall communication and IT products will be
considered luxury goods by households, since the main
function of such products are entertainment, and communication, and rarely critical computing to households.
Following this reasoning process that private firms will
tend to be early adopters of communication and IT products, as their income elasticity of demand is quite low, we
expect that households, on the other hand, will tend to be
later adopters of communication and IT products, as their
American Marketing Association / Winter 2005
income elasticity of demand is higher. We set up the
following hypothesis.
Hypothesis (H): Communication and IT products are
luxury goods to households.
In order to measure the income elasticity of demand,
empirically we perform the following regression: In Q =
α + β In M + ε where Q is the quantity of good, M is income
or expenditure and ε is the error term. Taking the derivative with respect to M, we obtain β = (cQ / cM)
(M / Q)which is the estimated value of the income elasticity of demand for Q.
We collect the data of annual household final consumption expenditure, annual expenditure on communication products and annual expenditure on audio-visual
photographic and information processing equipment
(called IT products) which are all at 1995 prices, from
1989 to 2001 in OECD countries (OECD 2002). We
conduct regressions for communication products and IT
products respectively. Table 1 shows the regression results for communication products in twenty-three OECD
countries. From the table, we clearly see that the estimated
coefficient for each country is greater than one (from the
highest 8.686 for Japan to the lowest 1.577 for Iceland),
which suggest communication products are luxury goods
to the households in these countries. The t-values for these
estimated coefficients indicate that they are significant at
one percent level. Most important, the R-squares for most
of countries (17 out of 23) are over 0.90 (the average Rsquare is 0.927), which means that, generally, the regressions have a high level of goodness-of-fit.
Table 2 presents the regression results for IT products
in seventeen OECD countries. Except for Germany, all
the estimated coefficients for other countries are greater
than 1 (from the highest 6.221 for Demark to the lowest
1.576 for Korean), which also indicate that IT products are
luxury goods to the households in these countries. All the
estimated coefficients, except for Germany and Greece,
are significant at one percent level. The R-squares for 13
out of 17 countries are over 0.90, and the average Rsquare is 0.906, which mean that the regressions for IT
products have a high level of goodness-of-fit as well.
German, the outlier in the sample, has the income elasticity of 0.8141, which suggests IT products are necessary
goods to German households. But, the testing for it is not
significant below three percent level.
The testing results for both communication and IT
products support the hypothesis (H) in the study, that is,
that overall communication and IT products are luxury
goods to the households in OECD countries. Since most
of OECD countries are developed countries, we can
generalize our conclusion to that communication and IT
products are luxury goods to the households globally. The
Regression Results for Communication Products
# of
2.25 x10-8
Regression Results for IT Products
# of
American Marketing Association / Winter 2005
underlying reason is that if such products are considered
as luxury goods by the households in developed countries,
they must be perceived as luxury goods by the households
in developing countries as well since the developing
countries have a low GDP per capital and an associated
living standard.
Why are communication and IT products luxury
goods to the households? Unlike private firms, who use
communication and IT products for the purposes of computing function and competitive advantage, households
usually use such products for entertainment, communication and convenience. It is common to state that game
software, digital camera, audio or video systems are
luxury goods to households. For other IT products such as
computers, households need them to function these “luxury” goods. Therefore, computers and associated application software are the extension of such luxury goods to the
households. Figure 1 shows the percentage of households
with access to a home computer in OECD countries in
2000. The percentage varies from 11.1 for Mexico to 65
for Demark. For U.S., 51 percent households use computer at home in 2000. Figure 2 shows that more and more
people buy and use personal computers in USA during
1997 to 2001, which tells us that even in USA, not every
household processes a computer. Intuitively, these two
figures further demonstrate that computers are luxury
goods to households in OECD countries.
This study provides some interesting insights into
communication and IT products markets. We find evidence in the global setting to suggest that communication
and IT products are luxury goods to households. Vendors
of communication and IT products can take advantage of
these findings by strategically setting prices for the household. Vendors should set low prices of communication
and IT products for households for two reasons. First, as
these products are considered to be luxury goods, a high
price will result in a sharp drop in demand.
Second, as growth in the household sector is a precursor to growth in the overall market, a drop in current
demand will also entail a reduction in future sales (see Lu
et al. 2004). As Lu et al. (2004) point out that during the
introductory stage of the product life cycle for computers
and packaged software the consumer base will tend to be
comprised predominantly of private firms, and once the
growth stage begins, marketing and advertising efforts
should shift to cultivate demand within the household
sector. Our findings in the global setting further confirm
that vendors of communication and IT products should
make more marketing efforts towards the household markets when their products evolve into the growth stage. As
Households With Access to a Home Computer in 2000
Turkey (4)
Belgium (3)
Finland (1)
Beginning of 2002; 2March 2001–April 2002 (financial year) instead of 2001; 31999 instead of 2000;
Households in urban areas only; 5For 1999, households in urban areas with more than 15,000 inhabitants
American Marketing Association / Winter 2005
Personal Computers in USA (Per 1000 People)
the life cycle of communication and IT products become
shorter and shorter, this recommendation is significant to
the communication and IT industry.
This paper investigates the income elasticity of household’s demand for communication and IT products in 23
OECD countries during 1989 to 2001. We find that
communication and IT products are luxury goods to
households in these countries, which suggests that such
products are luxury goods to the households globally. We
also discuss the marketing implications of our findings
and provide communication and IT products vendors with
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American Marketing Association / Winter 2005
some marketing recommendation of using price discrimination to households and switching their market target to
households as their products evolve to the growth stage of
product life cycle.
The work presented here is not without limitations.
We use aggregate data in our analytical framework. The
conclusions reached in this paper may not be valid across
all types of communication and IT products. Some parts
of communication and IT products, taken cell phone as an
example, might be necessary goods to the households in
some countries. Therefore, using micro-data to investigate these types of nuances is a worthwhile area for future
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For further information contact:
Yanbin Tu
Department of Operations and Information Management
Business School
University of Connecticut
Storrs, CT 06269
Phone: 860.486.6485
FAX: 860.486.4839
E-Mail: [email protected]
American Marketing Association / Winter 2005
William J. Jones, University of Kentucky, Lexington
Devon S. DelVecchio, University of Kentucky, Lexington
Terry L. Childers, University of Kentucky, Lexington
Economic choice models originally conceived consumers as rational agents making optimal choices. Later,
consumer researchers would present evidence of a consumer who is rational within the bounds set by the desire
to maximize outcomes given an acceptable level of mental
effort (e.g., Payne, Bettman, and Johnson 1993; Simon
1978). In such a “satisficing” mode, consumers rely on
heuristics to reduce processing demands. One of the most
widely cited heuristics is anchoring and adjustment. Anchoring and adjustment has often been used to explain the
integration of price information (e.g., Morwitz, Greenleaf,
and Johnson 1998; Yadav and Seiders 1998). This may be
a popular heuristic among consumers since it requires
little mental effort. However, anchoring and adjustment
typically fails to provide highly accurate estimates (e.g.,
Jacowitz and Kahneman 1995).
In this study we introduce computational estimation
as an alternative explanation to consumers’ use of partitioned prices. Dowker et al. (1996) define computational
estimation as a procedure in which elements of simple
computation and approximation skills are combined to
devise strategies for manipulating numbers. The strategies in computational estimation include, but are not
limited to, rounding, using known numbers (e.g., transforming $106 X .23 to $100 X .25), distributing one
number into two or more (e.g., 15% is broken into 10% +
5%), and use of fractions (e.g., 80 X 25 = 80 X ¼ X 100).
Thus, computational estimation procedures enable consumers to evaluate price information in a more sophisticated manner than other heuristics, but without investing
the large amount of mental energy needed to perform
exact calculations.
This research addresses three key questions examined via three studies. First, what varieties of computational estimation strategies are consumers likely to employ when revising a discounted price? Second, given
computational estimation strategies how do interactions
between the numerical value of the price and discount
influence consumer choice? Specifically, we examine
situations in which price and discount combinations suggest a particular computational estimation strategy and
how the effort expended in using this strategy affects
choice share. Third, does the affect generated from employing more or less effortful computational estimation
procedures increase or decrease choice share for the
brand. In or initial study, we examine strategies that
consumers use when estimating the value of a discount for
144 price-discount combinations. Study 2 examines choice
behavior for a discounted brand and how price-discount
combination s favoring particular computational estimation strategies increase or decrease share for the brand
relative to other brands. Study 3 largely replicates Study 2,
but measures affect and confidence generated through the
estimation process.
Because of its higher accuracy, lower effort niche, we
expect that consumers employ computational estimation
strategies in a variety of situations. Thus, our point-ofview is consistent with a bounded rationality view of
consumer decision-making, but one that supposes greater
mental effort and accuracy than the predominant heuristic. This view is supported by results that differ from those
that would be predicted by anchoring and adjustment.
However, additional studies that directly contrast anchoring and adjustment and computational estimation in terms
of consumers’ price estimates and choice are warranted.
For further information contact:
William J. Jones
Gatton School of Business and Economics
University of Kentucky
Lexington, KY 40507
Phone: 859.275.2962
FAX: 859.257.3577
E-Mail: [email protected]
American Marketing Association / Winter 2005
Keith S. Coulter, Clark University, Worcester
Robin A. Coulter, University of Connecticut, Storrs
Research has demonstrated that consumers often rely
on the non-conscious, automatic processing of price information when choosing among brands. The numerical
cognition literature suggests that one way in which numerical stimuli (and hence prices) may be non-consciously
represented and encoded in memory is in terms of magnitude representations. Magnitude representations are judgments of relative “size” arrayed in analog format along a
left-to-right oriented mental number line, and may reflect
either the exact value (e.g., 8), or an approximation of the
exact value (e.g., “large”) of a number (Dehaene 1992).
Research further suggests that the magnitude representation that sustains the processing of numeric value may be
highly related to the underlying magnitude code that
sustains the processing of physical stimuli (Dehaene and
Akhavein 1995). Thus, interference may ensue if the
magnitude representation associated with the numeric
value of a number (e.g., large) is inconsistent with the
magnitude representation associated with the physical
size or appearance of that number (e.g., small).
Consider, then, a set of price lists containing comparatively high (standard) and low (sale) prices for several
items within a particular product category. The lower
prices are all displayed in either smaller font, such that the
numerical value and physical size dimensions are congruent (e.g., $12–10), or larger font such that the numerical
value and physical size dimensions are incongruent (e.g.,
$12–10). In the case of the incongruent lists, we hypothesize that the non-corresponding magnitude representations should interfere with consumers’ ability to encode
the sale prices as lower or smaller than the standard high
prices. As a result, the differences between the standard
high prices and the low sale prices should be perceived as
less, and the more favorable price and/or value assessments typically associated with the comparatively low
sale prices should be weakened or reduced. The reduced
value assessments should lead to a decrease in demand for
each of the low-priced items. The opposite effects are
expected in the case of the congruent physical-size/numeric value lists.
Research has also shown that the order in which
buyers are exposed to multiple prices (i.e., in list format)
American Marketing Association / Winter 2005
affects their perceptions (Monroe 2003). Because consumers typically examine the items in a list from top to
bottom, prices at the top of the list become externallysupplied reference prices that influence the perceptions of
prices that occur lower on the list. Buyers who initially see
high prices perceive subsequent lower prices as less
expensive (and hence of greater value) than they would if
they initially see low prices (Slonim and Garbarino 1999).
Thus, in the case of the aforementioned price lists
consisting of standard/sale prices in different size fonts,
we also consider that these prices may occur in either
descending (e.g., $20–18, 16–14,12–10) or ascending
(e.g., $4–2, 8–6,12–10) series. Thus, relative to a particular target item that appears at the bottom of the lists and
hence is typically examined last (i.e., the item priced at
$12–10 in the example above), initial reference prices
would be higher in the descending series, and lower in the
ascending series.
In the case of the descending order series, both
standard and sale initial reference prices would be greater
than a target sale price appearing at the bottom of the list.
Thus we hypothesize that a (small) congruent physical
size magnitude representation associated with that target
sale price should reinforce the perception that the target
price is actually lower or smaller (and hence a better buy)
than the higher reference price(s). Both size/value congruence and price-order effects are expected to occur.
Conversely, a (large) incongruent physical size magnitude representation associated with the target sale price is
expected to interfere with the perception that the target
price is lower or smaller than the higher reference price(s).
Therefore in this latter instance, price-order effects should
be diminished.
Hypotheses were tested in a 2 (congruent/incongruent) x 2 (ascending/descending order) experiment (N =
120). Subjects were shown a list of (6) brands in table
format containing high (standard) and low (sale) prices
and brief product descriptions. In the congruent (incongruent) conditions the higher standard prices appeared in
larger (smaller) font than the lower sale prices. Brands
were listed in either ascending or descending order of
price, with a fictitious target brand always appearing at the
bottom of the list. After viewing the stimulus price list,
subjects were exposed to a brief “filler” infomercial. They
then completed a paper and pencil questionnaire.
Findings indicated that congruent magnitude representations result in more favorable value perceptions,
lower price judgments, and increased purchase likelihood. Findings also demonstrated that numerical size/
value congruency interacts with price-presentation order
such that price-order effects are eliminated under incongruent magnitude representation conditions. Processing
check results supported our contention that subjects’
processing of price information was implicit, automatic,
and non-conscious, rather than explicit, conscious, and/or
inferential. Results also indicated that differing degrees of
attention caused by the size of the larger/smaller fonts
could not have accounted for dependent variable results.
References available upon request.
For further information contact:
Keith S. Coulter
Clark University GSOM
950 Main Street
Worcester, MA 01610–1477
Phone: 508.793.7749
FAX: 508.793.8822
E-Mail: [email protected]
American Marketing Association / Winter 2005
Jay P. Carlson, The Graduate College of Union University, Schenectady
William O. Bearden, University of South Carolina, Columbia
David M. Hardesty, University of Miami, Coral Gables
An array of pricing-related selling tactics (i.e., tactics
used by sellers to generate favorable price perceptions
regarding their brands, stores, and/or offerings) exists in
the marketplace. Prior research examining pricing-related
selling tactics has focused on assessing consumer response to individual tactics (e.g., partitioned pricing –
Morwitz, Greenleaf, and Johnson 1998; pennies-a-day –
Gourville 1998; price bundling – Yadav and Monroe
1993). Research that has studied consumer price knowledge has done so in the context of individual prices (e.g.,
Dickson and Sawyer 1990; Mazumdar and Monroe 1992;
Monroe and Lee 1999; Vanhuele and Dreze 2002). Also,
consumer persuasion knowledge, as advanced by Friestad
and Wright (1994), has been investigated in the domains
of advertising (Boush, Friestad, and Rose 1994) and
personal selling (Campbell and Kirmani 2000). However,
consumer persuasion knowledge in the domain of pricing,
more specifically, for marketer pricing-related selling
tactics, has not been examined.
Alba and Hutchinson’s (2000) review of knowledge
calibration supports the contentions of prior researchers
(e.g., Brucks 1985; Park, Mothersbaugh, and Feick 1994)
that objective and subjective knowledge are two important but distinct knowledge constructs that differentially
impact information search and consumer evaluations.
Moreover, prior research examining the relationship between objective and subjective knowledge has not always
found consistent results, and researchers argue that a
better understanding of the relationship is needed (Cowley and Mitchell 2003). The current research examined
both objective knowledge and self-perceived knowledge
regarding the persuasive aspects of marketer pricingrelated selling tactics in order to better understand the
relationship between the two knowledge constructs.
The objective then of the current research was to
identify and test a set of hypothesized factors that influence two knowledge constructs as they relate to knowledge regarding the persuasive aspects of marketer pricing-related selling tactics (cf., Park et al. 1994; Radecki
and Jaccard 1995). The first of these constructs was
objective knowledge or accurate information stored in
long-term memory. The second construct was subjective
American Marketing Association / Winter 2005
knowledge or self-assessed perceptions regarding what
consumers think they know. To this point, no research has
attempted to investigate directly influences on objective
and subjective knowledge or any moderators of the relationship between objective and subjective knowledge
regarding consumer persuasion knowledge of marketer
pricing-related selling tactics. To address this objective,
the present paper describes the results of a study that
investigated issues related to both objective and subjective knowledge of the persuasive aspects of pricingrelated selling tactics.
Hypothesized Relationships
Preference for numerical information (Viswanathan
1993), need for cognition (Cacioppo and Petty 1982), and
experience with pricing-related selling tactics were all
predicted to be positively related with objective knowledge. The personal relevance of pricing-related selling
tactics, frame of reference (i.e., the beliefs about the
knowledge possessed by significant others in an individual’s life – Radecki and Jaccard 1995), experience with
pricing-related selling tactics, and objective knowledge
were all hypothesized to be positively related with subjective knowledge. Lastly, experience was predicted to moderate the relationship between objective knowledge and
subjective knowledge such that this relationship would be
weaker when experience was high relative to when experience was low.
Study Overview
The eight hypotheses were tested from data collected
in a survey research study involving a sample of 191
undergraduate students. The data were collected in two
time periods, separated by one week. Measures of objective knowledge, subjective knowledge, and experience
were collected in phase one, with preference for numerical information, need for cognition, personal relevance,
and frame of reference collected in phase two.
Results and Discussion
Briefly, the results provided support for several hypothesized antecedents of both objective and subjective
knowledge and suggest that experience is a key moderator
of the objective knowledge – subjective knowledge relationship in the domain of pricing-related selling tactics.
Specifically, need for cognition and experience with pricing-related selling tactics were positively and significantly related with objective knowledge, while the relationship between preference for numerical information and
objective knowledge received mixed support. In addition,
personal relevance, experience, and objective knowledge
were positively and significantly related with subjective
knowledge, while the relationship between frame of reference and subjective knowledge received mixed support.
Lastly, the relationship between objective knowledge and
subjective knowledge was found to be positive and significant when experience was low, but was non-significant
when experience was high. This result suggests that
consumers might be susceptible to overconfidence when
experience is high but objective knowledge is low. References available upon request.
For further information contact:
Jay Carlson
The Graduate College of Union University
Schenectady, NY 12308
Phone: (518) 388.6738
FAX: (518) 388.6754
E-Mail: [email protected]
American Marketing Association / Winter 2005
Brian D. Till, Saint Louis University, St. Louis
Daniel W. Baack, Saint Louis University, St. Louis
Creativity is a very important component of advertising. With the industry focus on creative advertising, there
is surprisingly little research looking directly at the effectiveness of award-winning advertising. There are only a
handful of studies that focus specifically on this topic.
First, the research by Kover et al. (1995) investigated the
link creative advertising and consumers’ responses to that
advertising. They found that student defined “creative”
advertisements were linked to higher purchase intent. The
second study, Ang and Low (2000), investigated the
relationship between advertising creativity and subjects’
affective responses. The authors found that creative ads
were consistently perceived as more favorable, and, to a
lesser degree, resulted in a more favorable view of the
brand and increased purchase intent. The third study,
Stone et al. (2000), attempted to link creative commercials
to likeability. The study found that liked commercials
were more often judged as creative. Two recent studies,
Till and Baack (2004a) and Till and Baack (2004b)
explore the effectiveness of creative advertisements by
linking exposure to creative advertising (measured as
winning an advertising award) to increased unaided recall
of both the brand advertised and the features of the
commercial. Till and Baack (2004a) finds that creative
advertisements led to greater unaided brand and feature
recall. Till and Baack (2004b) replicated their first study,
but used a one-week delay measure of recall. They found
that brand names and commercial features are better
recalled for creative commercials, but only in the unaided
recall task.
All of the above studies, while significant, leave
some issues for further investigation. First, for most of the
studies, the grouping of advertisements into creative and
non-creative groups was based on student ratings. Students may not be the most appropriate judges of the
creativity of an advertisement (White and Smith 2001;
Kover et al. 1995). This potential problem with student
raters cast particular doubt on studies of the affective
effectiveness of creativity advertising. To further investigate this issue, this study explores the link between
creative advertising and brand attitude and purchase intent, but uses professionals, not students, to rate creativity.
Specifically, the following hypotheses are investigated:
American Marketing Association / Winter 2005
H1: Creative advertising will lead to higher levels of
purchase intent for the advertised brands.
H2: Creative advertising will lead to more positive attitudes for the advertised brands.
For the creative commercials, we used Communication Arts award winners. Communication Arts bases its
awards primarily on ad creativity as assessed by a panel of
distinguished advertising professionals. Forty advertisements were randomly selected from a pool of winners
from three recent years to form the sample. To create the
pool of control advertisements, advertisements were sampled during prime time television during four randomly
selected days of the week. From this pool, forty were
randomly selected. We inserted the commercials selected
into two television programs (Dream Living and Ground
Forces). We used two programs embedded with a different set of 20 commercials (½ creative, ½ control) for intrastudy replicability. Therefore, our study used four two and
a half minute pods with five thirty second commercials
each. This resulted in a total of ten minutes of advertising
(twenty commercials) per program. Subjects were 69
undergraduate students enrolled in business courses at a
Midwestern university. Three weeks before watching the
television program, subjects complete a questionnaire
measuring the attitude and purchase intentions regarding
the brands advertised. After watching the television program, the subjects filled out the same questionnaire previously completed. To measure purchase intent and brand
attitude, subjects were asked to rate on a seven-point,
bipolar adjective scale purchase intent and brand attitude.
Both of these measures were based on previous studies
(e.g., Chapman and Aylesworth 1999; Till and Busler
Results and Discussion
The unit of measure for the analysis is the change in
purchase intent and brand attitude between pre and post
advertisement exposure (statistics available upon request).
For both programs, a paired t-test analysis revealed no
significant differences between control and creative advertisements for brand attitude and purchase intent.
This research focused on the effect of creativity on
both purchase intent and attitude toward the brand. The
results find suggest that creative advertisements, at least
with limited viewing, do not appear to affect purchase
intent or attitude toward the brand. These results cast
doubt on past studies finding that creative advertising led
to increased affective effectiveness (Ang and Low 2000;
Kover et al. 1995; Stone et al. 2000). It is possible that
these results reflect the difficulty in affecting consumer
brand attitude and intent to purchase with one commercial
exposure. Unlike measures of recall, as used in Till and
Baack (2004a) and Till and Baack (2004b), brand attitude
and purchase intent of known brands is likely more solidly
ingrained and less influenced by a single ad exposure. It
also possible that differences in findings between this and
previous research is due differences in the types of judges
used to evaluate advertising as creative. While past studies have found creative advertisements to be effective
using similar measures (e.g., Ang and Low 2000; Kover
et al. 1995; Stone et al. 2000), they used students to assess
creativity. We feel that the use of professionals to judge
the advertising is a far more valid measure of “creativity”
and may account for the different results of the present
research versus earlier studies. References available upon
For further information contact:
Daniel Baack
Saint Louis University
3674 Lindell Boulevard
St. Louis, MO 63108–3397
Phone: 314.977.3810
FAX: 314.977.3897
E-Mail: [email protected]
American Marketing Association / Winter 2005
Arjun Chaudhuri, Fairfield University, Fairfield
A natural viewing situation is used to examine the
efficacies of three scales that purport to account for
emotional and rational responses to advertising. With
attitude to the ad as the dependent variable, the three scales
are tested using a large number of subjects, a random and
large number of ads and a sufficiently large number of
independent observations (each subject was exposed to a
single ad only). The results indicate differences in the
prediction of attitude to the ad among the three scales.
Surprisingly, the most parsimonious of the three scales
achieves the greatest predictive ability.
The purpose of this study is straightforward. Can a
short scale for assessing the emotional and rational reactions to advertisements predict the attitude to these ads as
well or better than two scales that are well known but are
considerably longer in length? If so, the implications of
the study for practical purposes of data collection are also
obvious. Respondent fatigue will be lowered and better
quality of responses may be expected with a substantially
smaller scale that also addresses the multidimensional
properties of responses to advertising.
Accordingly, this study compared the “feelings” scale
(53 items) developed by Edell and Burke (1987) and the
“judgments” scale [25 items taken from the Reaction
Profile for TV commercials (Wells, Leavitt, and McConville 1971)] also used by these authors (Burke and Edell
1989; Edell and Burke 1987; Burke and Edell 1986) with
the relatively short (16 items) CASC (Communication
Analytic and Syncretic Cognition) scale developed by
Chaudhuri and Buck (1995a, 1995b, 1998). The three
scales were examined in terms of their ability to predict
attitude to the ad.
Affect has been operationalized in different ways in
consumer research and advertising studies. One way has
been to view affect as an overall, global reaction such as
“liking” for an ad (Haley and Baldinger 1991; Herr and
Page 2004; Mitchell and Olson 1981). Another way has
been to assess affect as an amalgam of a set of qualitatively
different types of affects that may be evoked by an ad. This
has been prompted by evidence (Chaudhuri and Buck
1995a; Edell and Burke 1987) that different dimensions of
affect can have strikingly different effects on liking for the
American Marketing Association / Winter 2005
ad. For instance, Chaudhuri and Buck (1995a; see also
Chaudhuri 2004) showed that reptilian affects are not
related to liking for the ad while prosocial affects are
positively, strongly and significantly related. Burke and
Edell (1989) showed that upbeat, warm and negative
feelings differ in their effects as well.
One problem with the operationalization of this last
approach has been that researchers who use the Edell and
Burke (1987) feelings scale tend to shorten the scale (53
items) and adapt it to their purposes (as an example, see
MacInnis, Rao, and Weiss 2002). In general though,
measurement scales are developed with the understanding that they should be used in their entirety and not
abridged according to the purposes of a particular piece of
research. Thus, there would seem to be a need for a shorter
scale which still captures all the multidimensional aspects
of qualitatively different affects. The CASC scale offers
such an alternative with only 16 items which purport to
measure four different affective and cognitive dimensions. One of the goals of this study was to test if the CASC
scale had the same predictive power of the feelings and
judgment scales. If so, then it presents a viable and
perhaps more practical alternative to the other two scales.
Although there has been considerable work, as cited
above (see also Batra and Ray 1986; Holbrook and Westwood 1989 and others), that suggests that a range of
emotional effects are evoked by advertising, no single
accepted theoretical paradigm has emerged that guides
research in this area. Individual studies have used a variety
of theoretical frameworks, such as Plutchik’s (1980)
typological approach (Holbrook and Westwood 1989)
and Mehrabian and Russell’s (1974) dimensional approach (Olney, Holbrook, and Batra 1991). None of these
approaches, however, are clearly anchored in the structure of the brain. The theory of the “triune brain,” as
adapted in the CASC scale, described below, bases itself
on knowledge of the human brain.
This scale was developed in the area of communication sciences (Chaudhuri and Buck 1995a) and subsequently refined and published in the social psychology
and consumer research literature (Chaudhuri and Buck
1995b, 1998). It claims, on the basis of confirmatory
factor analysis and repeated testing, to measure both
emotional and rational (syncretic and analytic cognitions)
responses to advertising with a short list of 16 items which
load on four different factors. It has been tested at both the
individual level of subjects and at the aggregate level
using ads as the units of analysis. It has been tested for both
print and television media. Its results have been replicated
across different subjects and different ads. The CASC
scale also has the virtue of being grounded in a widely
accepted theory based upon scientific evidence on the
workings of the human brain as described next.
The scale uses the theory of the triune brain (McLean
1973, 1990) as its conceptual basis. According to McLean,
the human brain has developed in a series of stages and
today there are essentially three brain structures that are
interconnected and represent a “triune brain.” The first of
these structures is the reptilian brain (reticular formation,
basal ganglia, and midbrain) that governs such basic
behavior as reproduction, aggression, territoriality, etc.
The second brain structure is the paleomammalian formation (limbic system) found in mammals which guides
prosocial behavior associated with the preservation of the
species and also agnostic behavior associated with the
preservation of the individual. The third, and most recent,
structure is the neomammalian formation (neocortex and
thalamic structures) and its primary functions are in the
realm of higher order cognitive processing, including
verbal communication, language, ideas, problem solving,
complex learning, and memory (Chaudhuri and Buck
1995b, 1998).
The reptilian counterpart of the human brain is still
considered to influence us in certain basic behavior such
as the struggle for power, adherence to routine, imitation,
obeisance to precedent and deception. These are some of
the same behaviors that are espoused in advertising –
“never let them see you sweat” (deception), “did you DQ
today?” (adherence to routine), “caviar for the power
hungry” (power), etc. While the reptilian brain programmes
stereotypical behaviors, the old mammalian portion of the
brain, or the limbic system, functions in the subjective
experience of feelings and desires. In general, circuits
involving the septal area are involved in prosocial feelings
associated with behaviors conducive to the preservation
of the species, nursing, maternal care, parenting, and play.
In contrast, circuits involving the amygdala are concerned
with individualistic feelings such as fear, anger and disgust, which are associated with self preservation and self
protection (Chaudhuri and Buck 1995b, 1998).
The CASC scale was developed within the framework of the triune brain and contains multidimensional
elements which conform to the mammalian brain (prosocial and individualistic dimensions), the reptilian brain
(reptilian dimension) and the neomammalian brain (analytic dimension). CASC is a seven point paper and pencil
scale anchored at two endpoints by “not at all” and “a lot.”
American Marketing Association / Winter 2005
The general form of the scale is “Did the ad make you feel/
think. . . .” In all there are sixteen items, four in each
dimension. The prosocial dimension comprises of the
questions “did the ad make you feel happy/proud/hopeful/
a sense of affiliation.” The individualistic dimension
contains the items “did the ad make you feel angry/afraid/
disgusted/irritated.” The reptilian dimension consists of
the items “did the ad make you feel sexy/aggressive/
envious/a sense of power.” The analytic dimension is
based on brand differentiation and asks questions on
whether the ad made the respondent think of the “facts
about the brand/pros and cons of the brand/arguments for
using or not using the brand/differences between the
brand and its competitors” (Chaudhuri and Buck 1995b,
1998). Thus, the CASC scale measures both emotional
and rational dimensions of responses to ads. The emotional items measure a spectrum of qualitatively different
affective responses that are relevant to advertising while
the rational items refer to the processing of the elements
in an ad which differentiate between brands. Brand differentiation strategies have repeatedly been found to be the
single most important executional factor that influences
ad effectiveness (Stewart and Furse 1986; Stewart and
Koslow 1989) and Holbrook (1987) specifically mentions such strategies among the more desirable effects of
The feelings scale was developed by Edell and Burke
(1987) in trying to understand the role of feeling responses to an ad (as distinct from thoughts about an ad) in
promoting advertising effects. They took their cue from,
among others, Zajonc (1980) in trying to establish that
affective responses are valid, reliable, and unique evaluations of objects that are independent of cognitive evaluations. Moreover, they asserted and established that ads
were capable of simultaneously evoking both positive and
negative feelings among viewers (unlike positive and
negative cognitive evaluations) and that such feelings
were as important in understanding and explaining advertising effects.
Edell and Burke (1987) used 69 items which were
drawn from a larger pool of items in a pretest prior to their
study. They reported that three factors with high internal
consistency between the factors were extracted from a
factor analysis of the items. They described these factors
as upbeat (“active/confident/good/lively, etc.”), negative
(“angry/bad/dull/sad, etc.”) and warm (“affectionate/calm/
kind/sentimental, etc.”). These three factors, the three
factors from the judgments scale (Burke and Edell 1986)
and prior attitude to the brand were used to predict attitude
to the ad. It was found that the upbeat and warm feelings
scales did not add uniquely to the explanation of variance
in attitude to the ad but that they were jointly significant.
The authors concluded that, overall, the feelings dimensions contributed importantly and differently from the
judgments scale. Edell and Burke (1987) also reported
that in a follow up study they reduced the list of items to
56 items based on the redundancy noted between the
Examination of the items in the feelings scale shows
that the three factors in this scale have some important
differences with the factors in the CASC scale. First, the
four items in the reptilian dimension of the CASC scale
are not represented at all in the feelings scale. Second, the
negative dimension of the feelings scale has three of the
four items in the individualistic dimension of the CASC
scale with the notable exception of the “fear” item. Third,
the feelings scale possesses three of the four items in the
prosocial dimension of the CASC scale with the exception
of the “sense of affiliation” item in the CASC scale.
Further, in the feelings scale, these three items are not all
on the same factor as in the CASC scale. Fourth, in spite
of having four dimensions, the CASC scale is far shorter
(sixteen items) than the feelings scale (53 items). Finally,
the analytic dimension (four items) of the CASC scale is
not represented in either the feelings scale or in the
judgments scale as discussed below.
The “judgments” scale was used by Burke and Edell
(1986) as an adjective based attitude to the ad scale in
order to capture ad reactions over time in a naturally
occurring situation. These authors used the scale to test
television commercial wearout – i.e., to see if subjects’
evaluation of ads declined as levels of exposure increased.
They used thirty of the items from the Reaction Profile for
TV commercials developed by Wells, Leavitt, and McConville (1971) and four additional items from other research on attitude to the ad in order to compile the scale.
The scale was found to be reliable (internal consistency)
and to have a stable three factor structure consisting of the
34 items. Notably, it was found in this study that ratings
for the scale did not change over time while the ratings of
an overall attitude to the ad scale did. Thus, this scale is
different from an overall attitude to the ad scale.
In a later study, Edell and Burke (1987) reported
reducing the scale to 25 items based on the redundancy
among some of the items. These authors referred to the
three factors of the scale as the “judgments” scale and they
found that this scale was qualitatively different from the
feelings scales also used in their study. These authors also
emphasized that the scale measures judgments about the
characteristics of an ad such as Humorous, Informative,
Gentle, Valuable, etc. while the feelings scale measures
responses that are properties of the individual (happy, sad,
etc.) and not a characteristic of the ad itself. This view may
be contested since the judgments scale also measures
American Marketing Association / Winter 2005
subjective responses by individuals to ads and it is not a
scale which assesses the objectively existing elements in
an ad such as the use of scenery, actors, music, etc. Such
reliably verifiable elements in an ad are often used in
content analysis of ads as in the method described by
Stewart and Furse (1986). The items in the judgments
scale constitute evaluations of ads and, thus, may be better
viewed as responses that are a result of the cognitive
processing of ads and which are considered opinions of
the overall effectiveness of ads while the feelings scale
measures affective responses to ads which are more spontaneous and less considered. Note, however, that the
judgments scale is different from the analytic dimension
of the CASC scale which measures the cognitive processing of brand differentiation (“did the ad make you think of
the differences between the brand and its competitors,”
etc.) in an ad while the judgments scale asks for a cognitive evaluation of the ad in terms of overall adjective based
judgments about the ad. Thus, the analytic dimension of
the CASC scale should have a different and unique effect
on attitude to the ad over and above the effect of the
judgments scale.
In any case, controlling for both affective and cognitive responses to ads provides for better model specification in the present study. Thus, the judgments scale was
also included in the study.
The following research goals formed the motivation
for the study. Attitude to the ad was chosen as the dependent variable on which to test the predictive ability of the
three scales since these scales all purport to measure
responses to advertising and not necessarily to brands or
companies. Further, attitude to the ad has been found to be
an important concept in determining the persuasiveness of
advertising messages (MacKenzie and Lutz 1989; Muehling and McCann 1993).
Which scale is better overall at predicting attitude to
the ad?
Which dimensions of the three scales predict attitude
to the ad?
Are the dimensions of these scales stable under the
following conditions?
When there is a natural viewing situation. While
the feelings and judgments scales were developed in a naturally occurring setting, the CASC
scale was not.
With a random sample of ads. None of the scales
were developed under this condition.
With a large sample of ads. Only the CASC scale
used over a hundred ads.
With a large sample of subjects. None of the
scales used a large sample of individual subjects
(not exposures).
When each observation is independent of the
others. All of the scales were developed using
subjects who responded to multiple ads. This
causes autocorrelation, since the units of observation are not independent of each other, resulting in biased estimates.
Data Collection
The data were collected in a natural viewing situation. Four hundred and forty eight undergraduate subjects
at a private university in the northeast were interviewed in
their dorm rooms while watching television. Respondents
were asked to tune into one of the major television
networks that they normally watched and to watch some
program content. During the first commercial break one
of the commercials in the pod was randomly chosen and
at the end of the commercial the respondent was asked to
switch off the television and to fill in a questionnaire about
the commercial just viewed.
As a result of asking one subject to react to one ad
only, a data set of 448 independent observations was
obtained for the measures discussed next.
The questionnaire contained items from all the three
scales and also on an attitude to the ad scale. The CASC
scale had 16 items all of which were taken from Chaudhuri
and Buck (1998). The feelings scale consisted of the 53
items described by Burke and Edell (1989) which loaded
greater than .5 on a factor in that study. The judgments
scale had the 25 items refined and used by Burke and Edell
(1989) and Edell and Burke (1987). The instructions to the
subjects reproduced the instructions provided by Chaudhuri and Buck (1998) and Edell and Burke (1987) for the
three scales.1
The attitude to the ad scale was measured as the sum
of the responses to a seven point semantic differential
scale with the following five items: pleasant/unpleasant,
unfavorable/favorable, unlikeable/likeable, good/bad, and
negative/positive. These items have been widely used to
measure attitude to the ad in previous research (Muehling
and McCann 1993).
American Marketing Association / Winter 2005
In order to investigate the structure of the three scales
the data in this study were analyzed using Principal
Components Analysis. This is appropriate since all three
scales report the use of exploratory factor analysis in the
development of the scales.
The CASC scale in this study was found to comprise
of three factors with an eigenvalue greater than one. A
fourth factor with an eigenvalue of .93 was also extracted
but not considered further since the cutoff for all the scales
was taken to be the customary eigenvalue of one. However, the presence of this fourth factor should be noted since
the CASC scale is supposed to have four dimensions.
Varimax rotation of the remaining three factor structure
extracted 54 percent of the variance in the items. All
sixteen items loaded higher than .50 on one of the three
factors and not higher than .40 on any other factor. With
the exception of the fourth factor which narrowly missed
the cutoff, the factor structure of the CASC scale seems to
be somewhat stable with three of the four expected factors
performing as expected for the set of randomly selected
ads. All the four items for the prosocial dimension of the
scale loaded on the first factor along with all the four items
in the reptilian dimension. Similarly, all the four items for
the analytic and individualistic items loaded on the second
and third factors respectively. The items were summed
according to the factors they loaded on.
The feelings scale, which was expected to comprise
of three factors, resulted in eleven factors for the 53 items
used in this study and explained 64.8 percent of the
variance in the items. Moreover, the varimax rotated
factor solution failed to converge. Examination of the
initial factor matrix showed that only the first three factors
had loadings greater than .50 and, accordingly, only these
three factors were used in further analysis. Burke and
Edell (1989) also state that these items should result in
three factors. Thus, only these 39 items were used in
further analysis and they were summed according to the
factors they loaded on. Thirty one of the items loaded
greater than .5 on the first factor; 6 items on the second
factor and 2 items on the third factor.
The 25 items in the judgements scale loaded on five
factors which together explained 60.8 percent of the
variance in the items. Burke and Edell (1989) reported that
these 25 items loaded on only three factors in their study
but this was not the case with regard to the data in the
present study. However, the original formulation of this
scale (Wells, Leavitt, and McConville 1977; Wells 1964)
reported six dimensions and, thus, the five factors were
accepted as valid dimensions to investigate further. Accordingly, the items which loaded greater than .5 on each
of the factors were summed on their respective factors. All
25 items loaded greater than .5 on one of the five factors
and did not cross load higher than .50. There were a
minimum of four items on each factor.
attitude to the ad and all three of the dimensions in the
CASC scale featured in this set of explanatory variables.
The three scales were next analyzed with regard to
their effects on attitude to the ad. Multiple regression was
used for this analysis. First, the feelings scale was used to
predict attitude to the ad. All three dimensions of the
feelings scale together accounted for 36.8 percent of the
variance in attitude to the ad and only two of the three
factors were significantly (p. < .05) related to attitude to
the ad. Second, the judgments scale was used to predict
attitude to the ad. The five dimensions of the scale accounted for 45 percent of the variance in attitude to the ad
and only four of the five factors in the scale were significantly (p. < .05) related to the dependent variable. Last,
the CASC scale was used to predict attitude to the ad. The
three dimensions of the CASC scale accounted for 44.2
percent of the variance in attitude to the ad and all three
dimensions were significantly related.
Of the three scales in the analysis described above,
the CASC scale emerges as the most successful in predicting consumer attitudes to advertising. First, it is the only
scale in which all the dimensions made unique and significant contributions to attitude to the ad. In fact, the
individualistic dimension of the CASC scale made the
highest contribution of all the dimensions in the three
scales. The prosocial dimension made the third highest
contribution and the analytic dimension made a smaller
but unique and significant contribution. Second, even
with only 16 items it accounted for more of the variance
(44.2%) in attitude to the ad than the 39 items used from
the feelings scale (36.8%)and almost as much of the
variance (45%) as the 25 items in the judgments scale.
Last, it accounted for 9.4 percent incremental explanation
of variance in attitude to the ad over and above the
contributions of the other two scales. Moreover, its factor
structure seems to be fairly stable, in spite of the fact that
the fourth dimension of the scale narrowly missed the
arbitrarily set eigenvalue cutoff point of one. Three of the
four dimensions had eigenvalues higher than one and
these explained more than half of the variance in the 16
To test the incremental variance in attitude to the ad,
if any, accounted for by the CASC scale over and above
the variance accounted for by the feelings and judgments
scales, a two step procedure was used. In the first step, all
the eight dimensions of the feelings and judgments scales
were used as independent variables with attitude to the ad
as the dependent variable. This resulted in an R square of
.484. Next, the three dimensions of the CASC scale were
also introduced into the equation. This resulted in an R
square of .578. Thus, the increase in R square, or the
additional variance explained in attitude to the ad by the
CASC scale was .094 or 9.4 percent. In this final step, only
one of the three dimensions in the feelings scale and two
of the dimensions in the judgments scale were significant
(p. < .05) predictors of attitude to the ad. However, all the
three dimensions of the CASC scale were significantly
(p. < .05) related to attitude to the ad. Thus, all the
dimensions of the CASC scale uniquely contributed to the
prediction of attitude to the ad and the scale as a whole also
uniquely and substantially contributed to the explanation
of variance in attitude to the ad over and above the
variance accounted for by the feelings and judgments
The significant (p. < .05) standardized coefficients
(beta) in the last step were .209 (prosocial), .097 (analytic)
and -.332 (individualistic) for the three factors in the
CASC scale. The only dimension of the feelings scale
which was significant (p. < .05) had a beta of -.122. The
only two significant dimensions of the judgments scale
had beta weights of .242 and -.164. Thus, only six of the
eleven independent variables in the equation made unique
and significant (p. < .05) contributions to the prediction of
American Marketing Association / Winter 2005
The feelings scale was the least successful of the three
scales with only one factor making a unique and significant contribution to attitude to the ad over and above the
unique contributions of the CASC and judgments scales.
Further, at least in this study, the factor structure of the
scale was not as expected. Instead of the three factors
which were expected, eleven factors with an eigenvalue
greater than one emerged. The judgments scale fared
better with all 25 items loading on five factors, more or
less according to the specifications of the original formulation of the reaction profile for television commercials
(Wells, Leavitt, and McConville 1971). The judgments
scale also made a sizeable contribution to the explanation
of variance in attitude to the ad and two of the dimensions
of the scale made unique and significant contributions.
Overall, it would seem from this study that the 16
items of the CASC scale deserve the attention of those
attempting to test the effectiveness of television commercials in terms of consumer attitudes. The CASC scale
offers the ability to measure both emotional and rational
responses to advertising in a practical and fairly stable
format. Moreover, it appears to contain unique elements
that are not in the other two scales. Further, even with a
shorter number of items, it predicts attitude to the ad as
well if not better than the other two scales. The CASC
scale does not claim to measure the entire range of human
emotional experience. However, the simplicity of the
CASC scale makes it useful for conducting large scale
testing of emotional and rational responses and advertising effectiveness. The scale can be used to aggregate
responses and assign scores to ads or it can be used to
assess individual level processing of ads. Further, it can be
used for ads in both print and electronic media and for a
variety of consumer products. And, finally, the scale can
be used to test ads with vastly different advertising strategies since it has previously been validated in a sample of
240 ads which contained sex, humor, animation, patriotism, status, fear appeals, family situations, celebrities,
animals, typical spokespersons, product demonstrations,
comparisons, price appeals, health appeals, etc. (Chaudhuri
and Buck 1995b).
Finally, the CASC scale performed well in the natural
and “real world” setting of the present study with a large
The three scales in the study are not reproduced here due
to space constraints but may be obtained from the
sources cited in this paper.
Batra, Rajeev and Michael L. Ray (1986), “Affective
Responses Mediating Acceptance of Advertising,”
Journal of Consumer Research, 13 (September),
Burke, Marian C. and Julie A. Edell (1986), “Ad Reactions Over Time: Capturing Changes in the Real
World,” Journal of Consumer Research, 13 (June),
____________ and ____________ (1989), “The Impact
of Feelings on Ad-Based Affect and Cognition,”
Journal of Marketing Research, 26 (February), 69–
Chaudhuri, Arjun (2004), “Testing the Independence of
Affect Using Prosocial and Reptilian Feelings,” in
Marketing Theory and Applications, William L. Cron
and George S. Low, eds. Chicago, IL: American
Marketing Association, 15, 286–92.
____________ and Ross Buck (1995a), “Affect, Reason,
and Persuasion: Advertising Strategies That Predict
Affective and Analytic-Cognitive Responses,” Human Communication Research, 21 (3), 422–41.
____________ and ____________ (1995b), “An Exploration of Triune Brain Effects in Advertising,” in
Advances in Consumer Research, Frank R. Kardes
and Mita Sujan, eds. Ann Arbor, MI: Association for
Consumer Research, 22, 133–38.
American Marketing Association / Winter 2005
sample of subjects and ads. Albeit, the study used only
student subjects and that may have been a shortcoming.
However, since the subjects were viewing the programs
that they wanted to watch, they were probably the target
audiences for these commercials and, thus, users or potential users of the products and services in the commercials.
Further testing of the CASC scale versus the other
two scales in this study is warranted. First, all three scales
should be tested among “real world” respondents as
pointed out above in a limitation of the present study.
Future studies should also test the efficacies of all three
scales against important outcome variables other than
attitude to the ad. For instance, it may be expected that the
CASC scale will perform better than the other scales with
regard to the formation of attitude to the brand since the
analytic dimension of the CASC scale specifically measures responses to brand differentiation within an ad.
____________ and ____________ (1998), “CASC – A
Scale for Measuring Emotional and Rational Responses to Advertising,” Zietschrift Fur Sozial Psychologie, 29 (2), 194–206.
Edell, Julie A. and Marian C. Burke (1987), “The Power
of Feelings in Understanding Advertising Effects,”
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Emotion in Advertising Revisited: Testing a Typology of Emotional Responses,” in Cognitive and Affective Responses to Advertising, P. Cafferata and Alice
M. Tybout, eds. Lexington, MA: Lexington Books.
MacInnis, Deborah J., Ambar G. Rao, and Allen M. Weiss
(2002), “Assessing When Increased Media Weight
of Real-World Advertisements Helps Sales,” Journal of Marketing Research, 39 (November), 391–
MacKenzie, Scott and Richard J. Lutz (1989), “An Empirical Examination of the Structural Antecedents of
Attitude Toward the Ad in an Advertising Pretesting
Context,” Journal of Marketing, 53 (April), 48–65
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and Behavior. Toronto: University of Toronto Press.
____________ (1990), The Triune Brain in Evolution:
Role in Paleocerebral Functions. New York: Plenum
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Environmental Psychology. Cambridge, MA: MIT
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(1991), “Consumer Responses to Advertising: The
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(1971), “A Reaction Profile for TV Commercials,”
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For further information contact:
Arjun Chaudhuri
Charles F. Dolan School of Business
Fairfield University
Fairfield, CT 06824
Phone: 203.2544000, Ext. 2823
FAX: 203.254.4105
E-Mail: [email protected]
American Marketing Association / Winter 2005
Marc Weinberger, University of Massachusetts, Amherst
Dale Taoping Tzeng, University of Massachusetts, Amherst
Paul Bottomley, Cardiff Business School, United Kingdom
Harlan Spotts, Western New England College, Springfield
The value of strong stakeholder brand attitudes toward companies has become increasingly apparent to
practitioners and academic researchers. Less apparent is
the role of the media in the formation of corporate brand
attitudes. This research draws on key literature from
branding and legitimacy theory to examine the interplay
between the volume and valence of publicity and volume
of advertising as well as the moderating effect of brand
strength in the formation of company brand attitudes. We
employ a unique dataset from three proprietary sources
providing company advertising, publicity and company
brand attitudes for a set of 18 technology firms over a 42
month time period. The outcome reinforces recent assertions about the importance of publicity compared to
advertising and also the growing recognition of company
brand strength in tempering media effects.
corporate reputation, as well as foundation work in branding, negativity, and branding and media effects.
The concept of corporate branding has resonance
with several disciplines that deal with business and organization theories, but its popularization can be traced to
product branding research in the early 1980’s. There is
considerable agreement that the corporate brand has important value that must be nurtured and protected.
The parallel but related trend to corporate branding
has been the emergence of integrated marketing communication with its recognition that product, service, or
company reputations are formed by many controllable
and uncontrollable forces. These forces may include advertising, but publicity and public relations may have an
equal or greater impact on brand perceptions.
The importance of branding and brand equity for
products, companies and organizations has become almost axiomatic over the past decade. Rather than debate
the importance of strong brands, research has focused on
the creation, maintenance, preservation and worth of
brands. This research focuses on the association between
marketing communications (advertising and publicity)
and company brand attitudes.
Research by Aaker and Jacobson (1994, 2001) and
Jacobson and Aaker (1987) examined various aspects of
company valuation and branding. Based on firms in
computer-related industries, they concluded that “. . .
company brand attitude, a component and indicator of
brand equity, has value relevance. Not only are changes in
brand attitude associated with stock return, but this association is also incremental to information contained in
accounting measures” (p. 492). Brand attitude is a major
component of brand equity, thus a follow-up question to
Aaker and Jacobson’s analysis is “what drives brand
attitude?” Our research examines marketing communications related antecedents of brand attitude; specifically,
volume and valence of publicity, and, the volume of
advertising for firms in the technology industry. The study
draws on conceptual work from legitimacy theory and
American Marketing Association / Winter 2005
Public relations activity related to branding has often
been treated by marketers as the step-child of advertising,
but that thinking has been changing in recent years. Rance
Crain (2002), Editor in Chief of Advertising Age, argues
that “the landscape of marketing is changing more quickly
and dramatically than I ever could have imagined, and its
new realities will require public relations to shoulder more
of the load. Kitchen (1996) argues that the role of advertising in corporate branding may be diminishing with
marketing public relations (MPR) and corporate public
relations (CPR) on the rise.” In their book The Fall of
Advertising and Rise of PR, Al and Laura Ries (2002)
assert that public relations has become the most powerful
marketing-services discipline.
Legitimacy Theory
The conceptual basis for the importance on company
branding is “Legitimacy Theory,” a field that began with
foundation work by Parson (1960) and Weber (1978). It
has been extended into the organization and strategy
literature in management (for a review see Suchman
1995). “Legitimacy is a generalized perception or assumption that the actions of an entity are desirable, proper,
or appropriate within some socially constructed system of
norms, values, beliefs, and definitions” (Suchman 1995,
p. 574). Accordingly, one type of legitimacy is pragmatic
legitimacy whose task is to Conform to Demands (respond
to needs, co-opt constituents, build reputations), Select
Markets (locate friendly audiences), Recruit Friendly CoOptees, and Advertise (advertise product, advertise image).
Intermediaries that distribute publicity in the media
and advertising by the firm are all potential sources that
legitimate the organization. Pollock and Rindova (2003)
use the term infomediary to describe the media as a funnel
that channels and shapes stakeholder knowledge and
The media may play a pivotal role in the branding
process, a view supported conceptually (Gray and Balmer
1997) and empirically (Fombrun and Rindova 1998). To
wit, Fombrun and Shanley (1990, 240) observed: “The
media themselves act not only as vehicles for advertising
and mirrors of reality reflecting firms’ actions, but also as
active agents shaping information through editorials and
feature articles.” Speaking from the “Legitimacy” perspective, Deephouse (2000) argues that media reputation
is a strategic resource for firms. “A firm’s reputation is
produced by the interactions of the firm with its stakeholders, and, by information about the firm and its actions
circulated among stakeholders, including specialized information intermediaries (Fombrun 1996; Logsdon and
Wartick 1995).” He further argues, that “a positive reputation assists the legitimation process is important for
competitive advantage because it signals stakeholders
about the attractiveness of the firm who are then more
willing to contract with it” (Fombrun and Shanley 1990;
Weigelt and Camerer 1988).
Pollock and Rindova (2003) examine the connection
between the media and its influence on market analysts of
IPO’s. In their social constructionist framework, social
structures like the media enhance the flow of credible
information that helps reduces uncertainty in market exchanges. These social structures include specific infomediaries or critics such as financial analyst reports, restaurants reviews, books, movies, and plays (Cameron 1995;
Caves 2000; Deephouse 2000; Rindova and Fombrun
1999). Pollock and Rindova (2003) point out that such
infomediaries legitimate firms or products by influencing
buyer or stakeholder desirability perceptions of an organization’s activities. They directly test this connection
between media and legitimacy. “The legitimate organization [is perceived] not only as more worthy, but also as
more meaningful, more predictable, and more trustworthy” (Suchman 1995, p. 571).
Communication Volume and Valence
There are important findings from social cognition
about the impact of information on impression formation
(Fiske and Taylor 1991) and judgment (Heath and Tversky 1991) that have a bearing on the media effects of
volume and valence of coverage. Pollock and Rindova
American Marketing Association / Winter 2005
summarize three key findings from social cognition that
involve the impact of volume. The first is a familiarity
effect that increased exposure is associated with greater
familiarity and stronger liking (Harrison 1977; Zajonc
1968). Research by Lee and Labroo (2004) provides
evidence that when processing fluency of the target is
enhanced by prior exposures, a more favorable attitude is
observed (Anand and Sternthal 1991; Bornstein 1989).
Second, research by Hawkins and Hoch (1992) suggests
that simple repetition increases acceptance of a statement.
Finally, the amount of available information about an
activity reduces perception of riskiness (Heath and Tversky 1991). Pollock and Rindova (2003) state, “all else
being equal, the combined effects of increased familiarity,
acceptance, and reduced perceptions of risk can generate
legitimacy benefits for a firm that receives a higher
volume of media coverage” (p. 633). Of course, all else is
usually not equal and so the evidence for a volume of
coverage effect is not universal.
In an advertising context, Lodish and his co-authors
concluded that ad weight is not enough to explain overall
sales effects (Lodish et al. 1995). Smaller or newer brands,
however, do benefit from greater advertising weight.
MacInnis, Rao, and Weiss (2002) examined a sample of
mature brands that did benefit from greater volume of
advertising and a set that did not. The difference in effects,
however, were driven by message type not the volume of
There are two general effects related to volume of
exposure and valence that may result from the framing of
a message as positive or negative (sometimes referred to
as tone). Reddy, Swaminathan, and Motley (1998) demonstrated that the valence of a critic’s (infomediary’s)
reviews are important for Broadway shows. Shows that
received extremely low reviews did not last beyond one or
two weeks before closing. In a study of movie reviews,
Basuroy, Chatterjee, and Ravid (2003) concluded that
both positive and negative reviews are correlated with
revenues; just the negative reviews diminish in their
impact over time.
Valence has also been shown to matter for negative
information from critical sources such as Consumers
Union when directed at services versus tangible goods
(Weinberger and Brown 1978). In a political context the
valence of “Ad Watch” coverage of candidate advertising
had a significant impact on voter preferences (Min 2002).
In a publicity context, message valence is an aspect of
media coverage that influences audiences by virtue of the
choice of topics covered and the interpretation or spin
placed on the coverage. “In particular, framing events and
issues in positive or negative terms provides audiences with
visible public expressions of approval or disapproval of
firms and their actions” (Pollock and Rindova 2003, p. 634).
Negativity and Impression Formation
Denigrating information about people, products, companies, or other products abound in the media. The impact
of negative and positive reports on impression formation
of political candidates (Golan and Wanta 2001), products
(Weinberger, Allen, and Dillon 1981; Weinberger and
Romeo 1989), and job candidates (Bolster and Springbett
1961) are well known. The mere mention of an issue on
the news makes a story important, possibly memorable,
and perhaps worthy to be passed along to others (Altheide
1977). Information in the media takes on a form of social
proof (Rao et al. 2001) leading to information cascades
(Bikhchandani, Hirschleifer, and Welch 1992) and availability cascades (Kuran and Sunstein 1999). The role as
“infomediary” may result in opinion leadership because
of its inherent social proof.
Under conditions of uncertainty audiences may
consciously or unknowingly imitate media statements
rather than form independent judgments (Bikhchandani
et al. 1992). Perhaps this helps explain why advertising
weight is more important for new products or small brands
than for mature brands. If simple volume or mere exposure effects prevailed, any kind of exposure in the media
would be expected to have a positive impact on liking of
the organization or message target. However, Lee and
Labroo (2004) suggest that conceptual fluency is triggered when negatively valenced information is presented,
resulting in a less favorable attitude when the valence of
other constructs brought to mind are negative. Like prior
experience with a company or brand, the conceptual
fluency effect presumes a more elaborate message effect
and less automatic positive frequency of exposure effect.
Existing Company Perceptions
Pollock and Rindova (2003) found that volume and
valence of media reports influenced the market for new
IPO’s (high uncertainty product). Volume affected interest and attention while the valence seemed to affect
investor preferences. Here the newness of the offering
could explain the inordinate reliance on media reports. A
study of consumer response to negative publicity (Ahluwalia, Burnkrant, and Unnava 2000) found that consumers committed to a brand were not affected as severely by
negative publicity. IPO’s by their general nature may have
fewer investors committed to the company, thus being
more influenced by media stories.
Company perception expressed as strength of corporate reputation was examined by Wartick (1992), specifically looking at both the volume and valence of media
coverage. His model suggests that a defined stakeholder
(audience) is exposed to media (amount, tone, and recency) through a filter defined by source credibility, selective
perception, and topic relevance. After exposure, stakeAmerican Marketing Association / Winter 2005
holders temper the media message based on prior experience formed through direct and/or indirect communication with an organization. The effect of new information
is either enhanced or diminished based on this prior
perception. For the overall sample of companies in
Wartick’s study, the valence, or tone of coverage, influenced change in corporate reputation. For good reputation
firms, volume of media exposure was most highly correlated with level of reputation. In contrast, valence was
most important for influencing reputation for firms with
poor reputations. It is possible that the mere exposure for
companies with neutral or positive reputation are reinforced by more exposure. Negative coverage, however,
may be discounted similar to consumers committed to a
brand seem to discount disconfirming brand information.
Firms with poor reputation may not have this shield
of protection and may be vulnerable to negative media
coverage. This is the protection that legitimacy theory
suggests positive reputation may provide. Perhaps it eases
the uncertainty that stakeholders have while a poor reputation may leave it vulnerable to negatively valenced
messages from the media.
The current study examines the relationship expressed
in Figure A looking at the relative impact of publicity
(volume and valence) and advertising weight (volume) on
brand attitude.
The research examines the important issue of relative
impact of advertising weight and publicity on company
brand attitudes (CBA). Further, the effect of the volume of
stories in comparison to the positive or negative framing
of the issues is investigated. The first research question
addresses this general issue.
RQ1 – What is the relative impact of publicity and
advertising volume and publicity valence on company brand attitude?
In keeping with current views about the dominance of
publicity, the expectation is that publicity will be more
closely related to company brand attitudes than advertising. Given that stakeholders are business people in technology firms, it might be expected that publicity dominance should be particularly apparent. Based on the mixed
results of past research, it is unclear whether volume or
valence will dominate in the overall sample.
The second research question (RQ2) addresses the
matter of prior brand strength.
RQ2 – Are the effects of RQ1 tempered by higher and
lower levels of prior company brand attitude?
Publicity (Volume &Valence) Media Communication
and Company Brand Attitude
Publicity (Volume &
Level of
Company Brand
Company Brand
The expectation is that for strong reputation firms,
volume will matter more than valence; for weaker firms,
valence should be more important than volume. In keeping with research showing information effects dependent
on stakeholder perceptions (Wartick 1992; Ahluwalia,
Burnkrant, and Unnava 2000), the analysis accounts for
stronger and weaker prior company brand attitudes.
This study utilizes data on publicity, advertising, and
company brand attitude for each of 18 firms, requiring
three separate sources. All data cover the period January 1, 2000 to July 1, 2003 encompassing 42 months or 14
Publicity Data
CARMA International provided the publicity data,
which are based on a Media Analysis Rating System first
developed in 1991. The system rates each article in the
context in which it appears. Using a pre-determined set of
seven criteria, each article is coded and receives a score
between zero (the least favorable) to 100 (the most favorable). All codings begin at 50 (the neutral point), with a
possible 50 points added or subtracted from this value.
CARMA conducts daily tracking of the volume of positive and negative press coverage as well as the valence
rating for each article appearing in eighteen major magazines and newspapers in the U.S. For this study daily data
were compiled into quarterly periods to match the company brand attitude data.
Advertising Data
Data on media spending were collected from
Ad$pender (2004), a multi-media database providing
American Marketing Association / Winter 2005
national advertising expenditure information on over
100,000 different brands. Monthly data were aggregated
into quarters over the time period of investigation for each
of the companies included in the study.
Company Brand Attitude Data
Techtel Corporation provided the company brand
attitude data, which was collected via quarterly surveys of
the personal computing and network computing markets.
Their panel surveyed approximately 1500 people influential in purchasing computer software and hardware (estimated 50% response rate). The Techtel measure of company brand attitude asked respondents whether they have
positive, negative, or no opinion of a company. Like
Aaker and Jacobson (2001), we made use of this information to develop a company brand attitude measure defined
as Net Positive Opinion (NPO = percent of respondents
with positive opinion about the firm –percent of respondents with a negative opinion about the company). A
simple 3 point scale (positive (1)/neutral (0)/negative (-1)
has been used in political science (Robinson, Shaver, and
Wrightsman 1999) and has been shown (e.g., Haley and
Case 1979) to provide information similar to measures
with more scale points. For this study we focus on Techtel’s Enterprise Panel consisting of firms also studied by
CARMA, including: AT&T, Cisco, Compaq, Computer
Associates, Dell, EMC, Gateway, Hewlett Packard, IBM,
Intel, Microsoft, Oracle, Peoplesoft, SAP, Siebel, Sun,
Sybase, Unisys.
Analysis of Data
The company brand attitude variable (NPO) is collected from the first quarter of 2000 to the second quarter
of 2003. Since the advertising data and the publicity data
on some of the firms in the Techtel enterprise data set were
not collected during the exact same period, observations
for companies with any missing values were eliminated
from further analysis. This process reduced the initial
dataset from 266 to 166 usable and unique observations.
Analysis first regressed the total number of favorable
(volfav) and unfavorable (volunf) articles, the overall
publicity rating (valence) and the total advertising spending (advol) on net positive opinion (NPO). Since we have
both time series and cross-sectional data, the independent
variables were checked for multicollinearity, heteroskedasticity (Breusch-Pagan) and autocorrelation (DurbinWatson). No multicollinearity or heterskedasticity were
observed among the variables; however, autocorrelation
was a problem, which was corrected with a first order
autoregressive process.
Research Question 1: What is the relative impact of
publicity and advertising volume and publicity valence on
company brand attitude?
Descriptive statistics for the overall sample of firms
are presented in Table 1. The average Net Positive Opinion for firms in the sample was 50.38. Volume of publicity
varied on average with 66 favorable articles to 43 unfavorable articles per quarter. The average valence of publicity
was slightly positive with a CARMA publicity rating of
51.76. Finally, average ad spending was $3,302,000 per
Results of the regression model were statistically
significant (see Table 2), explaining approximately 22
percent of the variation in Net Positive Opinion. After
appropriate corrections for serial correlation, Favorable
Publicity Volume was the only variable influencing Net
Positive Opinion. It appears that publicity valence and
advertising spending do not significantly influence attitudes toward the company.
Research Question 2: Are the effects of Research
Question 1 tempered by higher and lower levels of prior
company brand attitude?
Prior research has established that the effects of
publicity vary depending on prior company attitudes.
Thus, a median split of the sample was used to divide firms
into groups, Stronger versus Weaker Net Positive Opinion. The descriptive statistics for each group are presented
in Table 1. As expected, there is a statistically significant
difference between the two groups on Net Positive Opinion with higher mean opinions for Stronger than Weaker
Companies. While the two groups did not differ on the
level of favorable publicity volume, there was a significant difference in the average volume of unfavorable
publicity. Firms with Weaker opinion had almost twice
the volume of unfavorable publicity as firms with Stronger opinion. Similarly, the valence of publicity was more
positive for Stronger than Weaker firms.
A Chow test (Greene 1993) was used to test for
differences in regression models between the two groups.
The results of this test (F = 32.27, p < .0001) indicated that
significant differences exist between the two groups of
firms in terms of the relationship between marketing
communications and Net Positive Opinion. The models
differ on volume of favorable publicity (t = 2.25, p < .03)
and publicity valence (t = 3.63, p < .001). The other
variables in the model were not significant.
A regression model including the four independent
variables was fit for each group of Stronger and Weaker
opinion companies. For Stronger companies the volume
Descriptive Statistics of Variables Used in the Analysis for Overall Sample of Firms, and
Stronger and Weaker Net Positive Opinion Groups of Firms (per quarter)
Net Positive Opinion
Favorable Publicity Volume
Unfavorable Publicity Volume
Publicity Valence
Advertising Spending (‘000’s)
< .0001
< .003
< .0001
Number of Observations
* t-test results based on df = 164.
American Marketing Association / Winter 2005
Regression of Ad Spending, Volume of Publicity, and Valence on
Company Brand Attitudes
Favorable Publicity Volums
Unfavorable Publicity Volume
Publicity Valence
Advertising Spending
Regression Significance
F = 11.22
Df = 4, 161
P < .0001
of favorable publicity was the only significant influence
on Net Positive Opinion (see Table 3A). This model
accounts for over 50 percent of the variance in the dependent variable.
Results for the Weaker opinion companies were
markedly different (see Table 3B). The overall regression
model accounted for only 22 percent of the variance in Net
Positive Opinion. An examination of the individual coefficients revealed Publicity Valence as the only factor
having significant influence on Net Positive Opinion. It
appears that Volume of publicity and advertising spending had no significant influence on company brand attitude for those with Weaker reputations.
The task of this research was to examine marketing
communications related antecedents of company brand
attitude, namely the volume and valence of publicity and
the volume of advertising on a set of firms in the technology industry. In several articles noted earlier, Aaker and
Jacobson argued that company brand attitude is a component of brand equity. These attitudes are related to stock
returns and provided information beyond normal accounting measures. Our current research adds to insights
about company brand attitude by examining the role
advertising and publicity play in the support or weakening
of brand equity.
First, the volume of advertising is not related to brand
attitude for the full sample of 18 firms; nor for the separate
examination of firms with stronger or weaker net positive
opinion. This result is consistent with conclusions by
Lodish et al. (1995) that advertising weight is not sufficient to explain sales effects. In particular they suggested
that newer and smaller brands gain the most from advertising. Though our study did not examine newer or smaller
brands, firms with weaker company brand attitudes may
be expected to gain from advertising like a newer brand
American Marketing Association / Winter 2005
R-sq = .2180
where opinions are unformed or neutral. Such a result was
not found; no positive advertising effects were detected
here. This may support MacInnis et al. (2002) who contend that for mature brands, it is the type of message and
not the volume of ad spending that matters.
A second notable result was that publicity did matter,
with the influence of valence and volume nuanced. In the
overall model the volume of positive publicity accounted
for the variation in company brand attitude. We can see,
however, that this effect obscures a significant difference
in how publicity works. Wartick (1992) found that companies with stronger versus weaker reputations are differentially affected by the volume and valence of publicity.
In his analysis as in ours, volume of positive publicity
correlated with higher ratings for firms with better reputations. These firms were not influenced by publicity
valence per se. In the context of the social cognition
research discussed earlier, it is possible that companies
with prior positive reputations are reinforced by more
exposure, a mere exposure effect. Perhaps these stronger
perceptions are related to the stronger commitment found
to insulate audiences from negative information (Ahluwalia et al. 2000).
Firms with weaker prior attitudes are affected by the
valence of publicity in the media, but not the volume of
positive or negative articles. Again this result is consistent
with both Wartick’s and Ahluwalia’s findings that companies with weaker reputations are affected more by
unfavorable information than the amount of information.
It appears that that firms with stronger prior reputations
are given a limited shield of protection not afforded to
firms with weaker reputations.
Third, firms with stronger and weaker reputations do
have some important differences in publicity coverage.
As the descriptive statistics reveal, firms with stronger
brand attitudes have far fewer negative stories and a more
positive publicity rating on average. The levels of positive
Regression of Ad Spending, Volume of Publicity, and Valence on Company Brand Attitudes
for Firms with Stronger Prior Company Brand Attitudes
Favorable Publicity Volume
Unfavorable Publicity Volume
Publicity Valence
Advertising Spending
Regression Significance
F = 4.60
Df = 4, 67
P < .0024
R-sq = .2153
Regression of Ad Spending, Volume of Publicity, and Valence on Company Brand Attitudes
for Firms with Weaker Prior Company Brand Attitudes
Favorable Publicity Volume
Unfavorable Publicity Volume
Publicity Valence
Advertising Spending
Regression Significance
F = 4.60
publicity and advertising between stronger and weaker
firms are not different. The important result is that the
individual regression models run on the firms with stronger and weaker brand attitudes still finds a volume effect
for the stronger firms and a valence effect for the weaker
firms. Even though firms with stronger company attitudes
have about the same number of positive articles as do
firms with weaker company attitudes, the volume of
positive publicity continues to perpetuate the strong reputation. Firms with stronger prior reputations should
strive to enhance the volume of positive publicity they
At the same time, firms with weaker reputations have
an average publicity rating lower than the stronger firms;
however, they scored right at the CARMA neutral publicity rating of 50. It appears that the variation in valence is
influencing firm reputation. This implies that firms with
weaker reputations are not impacted by more articles,
rather it is the ratings or valence of the articles that is most
closely related to the level of company brand attitude.
Fluctuations in the rating valence of stories about these
firms is closely related to brand attitudes for these weaker
reputation firms.
American Marketing Association / Winter 2005
Df = 4, 67
P < .0024
R-sq = .2153
Finally, the results give credence to the belief that
public relations activity is gaining ascendance relative to
advertising in corporate branding. Here we see the unique
role of volume and valence of publicity shaping stakeholder opinions. It supports the view that the media may
play a pivotal role in the branding process. Though
beyond the scope of the current research, prior research
suggests that this media influence effect is magnified
under conditions of audience uncertainty where information may reduce riskiness perceptions.
No study is without limitations. The effects observed
in this investigation are clearly related to a small set of
firms within the technology industry for a set period of
time. An examination of a larger set of firms across a
variety of industries may reveal different relationships.
However, the results reported here are consistent with
those of other studies focused on different industries and
using different measures of company brand attitude, providing a level of convergent validity. The strong effects of
publicity found in this study should not be used to eliminate advertising. All that is clear from this study is that the
amount of advertising is not related to company brand
attitudes. As MacInnis and her colleagues suggested, it
may simply be that “what” firms say in their ads is more
important than how “loud” they say it.
The conclusion from this analysis is that publicity is
a driver of corporate brand attitude and that media repu-
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American Marketing Association / Winter 2005
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For further information contact:
Marc Weinberger
Isenberg School of Management
University of Massachusetts
Amherst, MA 01003
Phone: 413.545.5674
FAX: 413.545.3858
E-Mail: [email protected]
American Marketing Association / Winter 2005
J. Chris White, Michigan State University, East Lansing
Jeffrey S. Conant, Texas A&M University, College Station
Raj Echambadi, University of Central Florida, Orlando
Despite growing interest evidenced by recent publications in the marketing strategy literature and by the
Fortune 500 business members of Marketing Science
Institute (MSI), there is a dearth of research on and a need
to improve our understanding of the process of developing and implementing marketing strategy. Several important gaps in the literature have limited our understanding.
First, most existing models of strategy-making fail to fully
capture the complexity and variety of the phenomena, and
overlook the roles top managers and organizational members play in developing strategy. Second, prior research
has focused primarily on either antecedents or consequences of strategy-making, but not both (see Menon et al.
1999 for a notable exception). And third, despite evidence
suggesting the performance outcomes of strategy-making
may depend on complex contextual interactions, studies
of the implications of strategy-making have focused almost exclusively on direct financial payoffs, with inconsistent results.
In this paper, we address these gaps by developing a
model that incorporates organizational antecedents and
performance outcomes of marketing strategy development (MSD) styles in a contingency framework. The
organizational antecedents of MSD styles tap the domain
of organizational structure, organizational culture, and
top management team characteristics. We propose that the
number of MSD styles is positively influenced by organizational formalization, an innovative organizational culture, and heterogeneity of the top management team, and
negatively influenced by organizational centralization.
We draw on resource-based theory, the theory of competitive rationality, and the paradox perspective on organizational effectiveness to discuss the relationship between
the number of MSD styles used by the firm and the ability
to implement strategy. Specifically, we argue that even
though the use of multiple MSD styles results in benefits
(e.g., causal ambiguity, barriers to imitation, etc.), it may
also result in additional costs, such as those associated
American Marketing Association / Winter 2005
with control and coordination. Therefore, we propose that
the relationship between the number of MSD styles used
and implementation capability is curvilinear (an inverse
U-shaped relationship); that is, the number of MSD styles
used is positively associated with implementation capability and the number of MSD styles used squared is
negatively associated with implementation capability.
We propose that the relationship between MSD styles and
implementation capability is contingent on firm size,
environmental turbulence, and the organization’s competitive strategy emphasis. Finally, we argue that a firm’s
implementation capability will positively impact its performance and that the relationship between number of
MSD styles used and performance will be mediated by
implementation capability.
The conceptual model we develop has the potential to
make several important contributions to the marketing
strategy literature. First, empirical support would provide
evidence that multi-dimensional measures are necessary
to capture and better understand the complexity and
variety of the strategy development process. Second,
empirical testing of the proposed model can improve the
reliability of the strategy-making scales created by Hart
and Banbury (1994) and adapted to the marketing context
by White et al. (2003), thus incorporating an organizationwide approach to the study of marketing strategy development. Third, the propositions put forth in this paper
provide guidelines for testing a complex framework in
which the relationship between the number of MSD styles
used and implementation capability is contingent on the
interaction of strategy development with organizational,
environmental, and competitive strategy factors. And
fourth, we believe empirical testing of the proposed model
would support the notion that organizations with superior
implementation capability realize significantly greater
performance. In summary, this research has the potential
to provide managers and researchers alike with a better
understanding of the process of developing and implementing marketing strategy.
Hart, Stuart and Catherine Banbury (1994), “How Strategy-Making Processes Can Make a Difference,” Strategic Management Journal, 15 (May), 251–68.
Menon, Anil, Sundar G. Bharadwaj, Phani Tej Adidam,
and Steven W. Edison (1999), “Antecedents and
Consequences of Marketing Strategy-Making: A
Model and a Test,” Journal of Marketing, 63 (April),
White, J. Chris, Jeffrey S. Conant, and Raj Echambadi
(2003), “Marketing Strategy Development Styles,
Implementation Capability, and Firm Performance:
Investigating the Curvilinear Impact of Multiple Strategy-Making Styles,” Marketing Letters, 14 (July),
For further information contact:
Chris White
The Eli Broad College of Business
Michigan State University
N370 North Business Complex
East Lansing, MI 48824–1122
Phone: 517.353.6381
FAX: 527.432.1112
E-Mail: [email protected]
American Marketing Association / Winter 2005
Christian Homburg, University of Mannheim, Germany
Ove Jensen, University of Mannheim, Germany
Academic research has studied marketing’s interfunctional interfaces in detail (Maltz and Kohli 2000;
Ruekert and Walker 1987a). However, it has almost
completely neglected one interface that is very important
in managerial practice: the interface between marketing
units (such as product management, communication,
market research) and sales units (such as the field reps).
As a result of an MSI workshop on marketing’s interfaces,
Montgomery and Webster (1997, p. 16) noted that “intrafunctional conflict within marketing was a more important topic for discussion than we had expected. The most
frequently discussed issue was the conflict between sales
and marketing.”
Given growing recognition that this interface is highly conflict-laden in practice, our paper prepares the ground
for future empirical research. We develop a conceptual
framework of the interface and of coordination mechanisms for coping with it. Our framework defines the key
constructs and develops hypotheses.
Literature Review
One of the most important findings of our literature
review is what we did not find: dedicated empirical
research of the M&S interface. The vast majority of
studies dealing with organizational issues in marketing
have not distinguished between marketing and sales subfunctions or functions.
Among those studies that have dealt with the internal
structure of the marketing function, one group uses design
dimensions such as centralization, formalization, and
specialization (Dastmalchian and Boag 1990; Ruekert,
Walker, and Roering 1985). However, this work does not
further differentiate the marketing function into marketing subunits and sales subunits.
Very few articles explicitly deal with the distinction
between M&S. The pioneering work of Cespedes (1993,
1994) highlights the key challenges at the M&S interface
as well as instruments for managing the interface. Workman, Homburg, and Gruner (1998) develop a typology of
the structural location of M&S and identify environmental antecedents influencing the configuration chosen. M&S
subunits are found at the corporate level, at the business
American Marketing Association / Winter 2005
unit level, and at the local (country) level. However,
conflicts between M&S are not further explored. Dewsnap and Jobber (2000) conceptually explore the M&S
interface in consumer packaged-goods companies.
We identified two studies that provide empirical
information on the M&S interface. Strahle, Spiro, and
Acito (1996) observe that sales managers do not generally
set sales objectives which are consistent with the strategy
specified by a marketing executive for a particular product. Some of the reasons behind this gap are miscommunications and volume-goal differences. Their results underline the need for more research on communication as
well as coordination between M&S. Homburg, Workman, and Krohmer (1999) compare the influence of five
functional groups over marketing and non-marketing
issues: marketing, R&D, operations, and finance. However, their study does neither analyze the extent of conflict
between M&S nor mechanisms to cope with it.
Conceptual Framework
Our conceptual framework comprises three general
components: (1) coordination mechanisms, (2) performance domains, and (3) moderators and mediators of the
coordination-performance relationship.
We conceptualize two domains of coordination mechanisms for M&S units: boundary-reducing mechanisms and boundary-bridging mechanisms. These
two domains reflect two facets of integration that
have been distinguished in the literature. For example, Kahn and Mentzer (1998) differentiate between
an “interaction” facet, that focuses on information
exchange, and a “collaboration” facet focusing on the
willingness to work together. Recent work on coordination mechanisms increasingly acknowledges their
differential effects on an interfunctional boundary
and complements the classical coordination mechanisms (Galbraith 1973; Van den Ven, Delbequec, and
Koenig 1976) by mechanisms targeted at interdepartmental beliefs and values (Martinez and Jarillo 1989;
Roth, Schweiger, and Morrison 1991; St. John, Young,
and Miller 1999). We define boundary-reducing
mechanisms as the “pull” facets of coordination which
foster the willingness to cooperate, thereby diminishing the interdepartmental barriers. Among these are
integrative recruiting and HR development as well as
integrative reward systems. On the other hand, we
define boundary-bridging mechanisms as the “push”
facets of coordination which drive two departments
to cross the boundary, but do not decrease the interdepartmental barrier. These include formalization,
integration teams, joint planning, and information
Our framework contains two domains of success.
The first domain encompasses success at the business level. We distinguish between market-level
measures and financial measures. The second domain represents the integration success at the departmental level. Here, we subsume such constructs as
coordination efficiency, coordination effectiveness,
communication intensity, information quality, and
information usage.
Our moderators and mediators are centered around
the boundary between M&S. By boundary criticality, we understand the amount of coordination needed
at that interface. The greater the criticality, the more
traffic occurs at the boundary. Boundary criticality is
constituted by such constructs as task interdependence and market dynamism. Boundary-creating differences refer to the extent of barriers hampering
coordination. Among these are differences in goal
orientation, time orientation, and skills. The third
domain, integrativeness of the corporate environment, pertains to the extent to which M&S are embedded in an intraorganizational context that fosters
coordination between two units. Most importantly,
this includes top management support. References
available upon request.
For further information contact:
Christian Homburg
Marketing Department
Director of the Institute for Market-Oriented Management
University of Mannheim
68131 Mannheim
Phone: 49.621.181.1555
FAX: 49.621.181.1556
E-Mail: [email protected]
American Marketing Association / Winter 2005
Tianjiao Qiu, University of Illinois at Urbana–Champaign, Champaign
Deborah Rupp, University of Illinois at Urbana–Champaign, Champaign
William Qualls, University of Illinois at Urbana–Champaign, Champaign
In recent decades, cross-functional product development teams (CFPDTs) have become a popular mechanism
for achieving greater interfunctional integration in the
new product development process. Research has demonstrated that CFPDTs composed of members from various
areas such as marketing, product design, process design,
engineering, and finance work as an efficient mechanism
for generating innovative new product ideas (e.g., Sethi
2000; Wind and Mahajan 1997). A key characteristic of
CFPDTs is the diversity of functional areas represented in
the team. On one hand, cross-functional diversity provides for crucial functional inputs during the new product
development process. Successful cross-functional relationships ensure a high level of information sharing and
integration, which in turn leads to innovative new products. On the other hand, cross-functional diversity poses
great challenges to efficient working relationships, reflected in three potential barriers – turf barriers, interpretive barriers, and communication barriers (Hunt 1995).
To benefit from cross-functional diversity, a high
level of interaction and collaboration among CFPDT
members is necessary. Since each team member in CFPDTs is equipped with unique experience with the existing
product technology or manufacturing process, it is essential that he/she communicates effectively in order to create
the synergy that CFPDTs provide. Without such information sharing and integration, team members cannot develop a common understanding of or a shared goal regarding
the product development process.
One factor that can potentially influence the level of
cooperativeness among CFPDT members is their fairness
perceptions. Fairness perceptions have a significant impact on a wide variety of job-related attitudes and behaviors (e.g., Cohen-Charash and Spector 2001; Colquitt
2001; Colquitt et al. 2001). The literature shows that
employees make at least three types of fairness judgments: distributive, procedural, and interactional. Using
the reward structures as the key variables, Shikhar and
Vijay (2001) have examined the performance of CFPDT
through distributive and procedural justice perspectives
without mentioning the role of interactional justice. To
bridge the research gap, we examine how CFPDT members’ interactional justice perceptions about their project
American Marketing Association / Winter 2005
managers impact their task performance and interpersonal citizenship behaviors.
Interactional justice refers to the extent to which team
members feel they are treated with dignity and respect by
their project managers. Interactional justice is particularly
relevant in the study of CFPDT members’ performance
because it reflects the interpersonal dimension of the new
product development process. The quality of interpersonal treatment received during the product development
process from the project manager greatly influences team
members’ fairness judgment and predicts supervisorrelated outcomes. Three aspects of supervisor-related
outcomes are examined: team members’ multi-foci commitments, their task performance, and their interpersonal
citizenship behaviors.
In the paper, we develop and test an integrative model
relating interactional justice perceptions to CFPDT performance (see Figure 1). We hypothesize that higher
levels of supervisor-focused interactional justice climate
enhance the interpersonal relationships between team
members and project managers. Such enhanced relationships are reflected in team members’ multi-foci commitments to the team and to the product development project.
Furthermore, team members’ multi-foci commitments
serve as a mediator between the perceived interactional
justice and their task performance as well as their interpersonal citizenship behavior.
Members from 50 students’ product development
teams participated in the study. Student teams were composed of majors from the College of Engineering and the
Business school, which emulate the structure of crossfunctional product development teams. The model is
tested using structural equation modeling. The overall
model is strongly supported by the data, with satisfactory
goodness-of-fit statistics as follows: χ 2(58)=83.42 (p =
.02); RMSEA = 0.047; GFI = 0.937; CFI = 0.985; NFI =
0.951; AGFI = 0.902; and RMR = 0.036. All estimated
beta parameters for the model are significant at 0.05
The findings indicate that the relationship between
team members and the project manager is enhanced by
higher levels of perceived interactional justice. Such
enhanced relationship is reflected in team members’ multi181
The Conceptual Model of Interactional Justice on CFPDT Members’
Task Performance and Interpersonal Citizenship Behavior
Citizenship Behavior
foci commitments towards the team and the on-going
project. It is further demonstrated that multi-foci commitment serves as the partial mediator between the perceived
interactional justice and both team members’ task performance and interpersonal citizenship behavior. The paper
contributes to the better understanding of the role of
interactional justice perception in enhancing interfunctional communication and cooperation in the new product
development process.
For further information contact:
Tianjiao Qiu
Department of Business Administration
339 Wohlers Hall
University of Illinois at Urbana–Champaign
1206 S Sixth Street
Champaign, IL 61820
Phone: 217.333.4240
FAX: 217.244.7969
E-Mail: [email protected]
American Marketing Association / Winter 2005
Tanawat Hirunyawipada, University of North Texas, Denton
Archna Vahie, University of North Texas, Denton
Literature has emphasized the importance of the relation
between cross-functional integration (CFI) and the success of new products (e.g., Anderson 1982; Nystrom
1985; Ruekert and Walker 1987a, 1987b). Many empirical and theoretical studies confirm a positive relation
between CFI and new product performance (e.g., Gupta,
Raj, and Wilemon 1986; Griffin and Hauser 1992, 1996;
Song and Parry 1997a, 1997b). Yet other studies show
either non significant or negative effect of CFI on the
success of new product development (e.g., Zirger and
Hartley 1996; Henard and Szymanski 2001; Gray, Matear,
and Matheson 2002). These disparate findings in the
literature make the indispensability of CFI in new product
development (NPD) a questionable concept. We use metaanalysis to provide a clearer answer to the importance of
CFI for the success of new products.
Employing the model-level effect sizes, we found
108 correlations between CFI and new product performance. Findings from the meta-analysis show that the
relation between CFI and new product success is positively correlated, but that some key factors moderate this
relation. This meta-analysis provides three main findings.
First, attention must be paid to the operationalization of
the constructs because the way the dimensions of the
construct are defined can impact the findings. We find that
CFI is likely to be comprised of at least two distinct
dimensions: internal integration and inter-functional climate. Internal integration captures the concept of CFI in
terms of its physical interactivities between functions
whereas inter-functional climate is more likely to capture
the norm within group or organization that encourages the
trust and relationship among different functions. Interfunctional climate can increase the capability to resolve
conflicts among integrated teams. The result from the
meta-analysis indicates that CFI has stronger relation with
new product success when the CFI is defined as the
supportive climate for collaboration. This issue casts a
doubt on whether researchers have crafted enough dimensions to reflect the underlying concept of CFI. The results
also show that the CFI-new product success relation is
stronger when the new product performance is operationalized as product effectiveness than when it is operationalized as NPD productivity. This suggests that respondents view a potential outcome of CFI as product effectiveness rather than productivity.
American Marketing Association / Winter 2005
Second, the decisions to include or exclude any
specific characteristics into the samples always impact the
reliability of measures. The results show that the larger the
number of functions integrated, the more difficult it will
be for CFI to become effective. The results confirm the
importance of the inclusion of the R&D function in the
CFI team for the success of NPD. The inclusion of the
marketing function in CFI shows neutral impact on the
CFI-new product performance relation. This may imply
that the importance of the marketing function be made
clear before it is included in the CFI. Future research may
investigate which other function should be integrated for
the success of new product. The meta-analysis also shows
that the respondents from NPD teams have positive impacts toward effect size. This suggests that the NPD team
members, which are the primary source of data, represent
the actual information of the CFI-new product success
relation better than do the respondents from senior managements. However, this result serves as a warning that
people who are involved in CFI may provide biased
information about the CFI-new product success relation.
Researchers may consider using data from different informants for independent and dependent variables to prevent
common method bias. Interestingly, the authors find that
studies published in the year 2000 and thereafter show
considerably positive relation with effect size. This result
sheds some light on why Henard and Szymanski (2001)
found no significant relation between CFI and new product success as most of the extant studies they looked at
were published prior to year 2000. This finding supports
our expectation that the increasing needs for diverse
expertise and experiences can lead to more integration of
different functions, and therefore to greater outcomes.
The generalization of the results is limited because of
the moderating effects of contextual variables. Studies
with respondents from companies across multiple countries do not support the salient relation between CFI and
new product success. CFI may not be able to impact
consistently across countries with different norms and
cultures. Thus, researchers conducting CFI studies should
take the context, organizational environment, and culture
into consideration. Accordingly, different cultures and
societies can be studied to create a typology of norms that
are best suited for CFI. Future research may focus on how
multicultural the individual NPD teams are and what
impacts this characteristic has on the success of new
products. The result also shows that samples from high183
tech products appear to play a moderating role on the
effect size. NPD’s time constraint and technology convergence are among the reasons why NPD team in high-tech
industry is more likely to seek integration with other
functional areas. The samples from western countries also
show stronger negative impact on effect size than do
samples from other countries. This result can be explicated by the individualistic norm of people in western countries. Workforce in these countries is less likely to commit
to rigid group norm or CFI team. The result also implies
that CFI in development stage has negative impact on the
effect size, and that CFI performs different roles across
stages of NPD. A future implication is to research not only
the impact of CFI in various stages of NPD, but also the
factors and conditions that impact the CFI strategy in each
NPD stage. Not surprisingly, goods vs. services as well as
industrial products vs. non-industrial products do not
explain the variance of the effect size. Given that the
overall combined mean is significant, we conclude that
CFI is important for NPD irrespective of the nature of the
types of products.
For further information contact:
Tanawat Hirunyawipada
University of North Texas
P.O. Box 311396
Denton, TX 76203
Phone: 940.565.3120
FAX: 940.565.3837
E-Mail: [email protected]
American Marketing Association / Winter 2005
Kwaku Atuahene-Gima, City University of Hong Kong, Hong Kong
Gloria Barczak, Northeastern University, Boston
Many firms have instituted quality programs in an
effort to upgrade and continually improve the quality of
their products for the ultimate purpose of creating competitive advantage (Clark and Fujimoto 1991; Menon
et al. 1997). This emphasis on product quality is welldeserved as there is strong evidence that product quality
is an important determinant of firm performance (Buzzell
2004; Hildebrandt and Buzzell 1991; Jacobson and Aaker
1987; Phillips, Chang, and Buzzell 1983; Sethi 2000).
The positive impact of product quality on performance
(Buzzell 2004; Hackman and Wageman 1995; Hildebrandt and Buzzell 1991; Jacobson and Aaker 1987;
Phillips, Chang, and Buzzell 1983; Sethi 2000) is of
particular interest because it suggests a direct effect relationship. Research has investigated the direct effect of
product quality on various performance dimensions such
as market share and profitability (Buzzell 2004; Hildebrandt and Buzzell 1991; Phillips, Chang, and Buzzell
1983), price (Jacobson and Aaker 1987; Phillips, Chang,
and Buzzell 1983) and costs (Jacobson and Aaker 1987;
Phillips, Chang, and Buzzell 1983). Though the evidence
is substantial, uncritical acceptance of this result suggests
that product quality defies the logic of contingency theory. Such a view is subject to theoretical skepticism given
that a variety of marketing strategies (e.g., market orientation, innovation, strategic alliances) have been found to
follow contingency theory.
Practically, uncritical acceptance of the direct effect
of quality on performance down plays the role of marketing in ensuring market performance. The importance of
the marketing function in building product quality is wellestablished (Cravens et al. 1988; Kordupleski et al. 1993;
O’Neal and LaFief 1992). In fact, it has been argued that
marketing, as the most customer-focused function (Kordupleski et al. 1993), should play the lead role in establishing product quality (Kordupleski et al. 1993; O’Neal and
LaFief 1992) as its job is to understand customer needs
and translate those needs into products with high customer value (Cravens et al. 1988; Kordupleski et al. 1993;
O’Neal and LaFief 1992). Creation of value through high
product quality depends on marketing skills in analyzing
and determining customer needs, competitor analysis,
identifying appropriate target segments, product positioning, communication, pricing, distribution, and speedy
implementation of launch (Cravens et al. 1988; KorduAmerican Marketing Association / Winter 2005
pleski et al. 1993; O’Neal and LaFief 1992). Thus, acceptance of marketing’s key role in establishing product
quality implies a contingency view of product quality
(Varadarajan and Jayachandran 1999). However, there
has been little, if any, research on if and how environmental factors moderate the relationship between product
quality and performance.
Since product quality is a deliberate firm strategy to
differentiate one’s offerings from its competitors’ (Jacobson and Aaker 1987; Phillips, Chang, and Buzzell 1983;
Porter 1980; Varadarajan and Jayachandran 1999), we
propose that the effectiveness of such a strategy will be
influenced by the nature and dynamics of its environment
(internal and external). This proposition resonates with
Varadarajan and Jayachandran’s (1999) argument that
the “market performance outcome of a business’s decision to offer products of a high quality is contingent on . . .
consumers’ characteristics and competitors’ reactions”
(p. 130).
We define product quality from a customer, rather
than a supplier, perspective (Bounds et al. 1994; Kordupleski et al. 1993; Morgan and Piercy 1998). A customerfocused approach views quality as the customer’s perception of how well a given product meets their needs and
expectations (Kordupleski et al. 1993; Morgan and Piercy
1998; Parasuraman, Zeithaml, and Berry 1985). Put another way, quality is “simply conformance to [the] requirements” (O’Neal and LaFief 1992) of the customer.
Although product quality may influence new product
performance directly, it is possible that external market
factors may help or harm that relationship (Varadarajan
and Jayachandran 1999). Our theoretical arguments suggest that when technological uncertainty is high, firms
may need to commit to certain aspects of the technology
before they know and understand the ramifications of
their actions. The level of quality based on those actions
is likely to be rendered inferior by new technological
developments which may have a negative effect on product quality. Similarly, in situations of high market uncertainty, project teams need to monitor market shifts and
adjust product specifications accordingly (Menon et al.
1997). Since it takes time for firms to adjust the level of
quality to meet both rapidly changing customer needs and
competitive actions, the positive effect of product quality
on new product performance is likely to diminish. Greater
customer demandingness may indicate that customers are
not satisfied with existing products (Li and Calantone
1998), suggesting a lower level of competition for a
specific product of high quality. Hence, product quality
will be more positively related to new product performance under high level of customer demandingness.
Finally, as the hostility of a new product introduction
increases, so does the strength of competitors’ reactions
(Heil and Walters 1993; Heil and Robertson 1991; Moore
1992). Effective competitor responses suggest an erosion
of the competitive advantages of the focal firm’s new
Regarding internal moderators we argue that a product concept which is familiar to the organization will be
easier, less time consuming and less expensive to design,
develop, and market. Hence, a project team is more
capable of maintaining the level of quality than a product
concept high new to the firm. Further, in a new market,
where customers know little about how to evaluate a
product’s attributes and benefits, product quality may
have greater positive effect on performance because the
nature of the product “may be able to influence how
attributes are valued [and] define the ideal attribute combination” (Kerin, Varadarajan, and Peterson 1992, p. 35).
In other words, a quality new product in a new market may
define the product category and the nature and level of
quality expectations (Kerin, Varadarajan, and Peterson
1992). Finally, a quick implementation implies that product, price, distribution and promotion tactics and activities
are operational simultaneously, at full strength, over a
relative short period of time. The faster the implementation of a specific product’s marketing strategy, the more
likely that the product will be known and accessible to
customers and perceptions of value will be determined
(Buzzell 2004; Hildebrandt and Buzzell 1991; Jacobson
and Aaker 1987; Phillips, Chang, and Buzzell 1983).
Our model makes practical and theoretical contributions. From a practical perspective, we focus on understanding the effect, if any, of specific internal environmental variables with product quality. Because these
internal variables can be influenced and/or controlled by
managers, the findings of this study should provide useful
recommendations for enhancing product quality and ultimately, new product performance. It is possible that some
of these variables may have an adverse reaction with
product quality. Thus, our findings can provide insight as
to which variables enhance or weaken product quality and
thus, product performance. In terms of theory, an important contribution of this study is its extension of the
previous research on product quality to include potential
moderators of the relationship between product quality
and performance. Unlike existing research, this study
draws on contingency theory and argues that the impact of
product quality on product performance depends on particular internal product and strategy characteristics as well
as external market characteristics. Another major contribution of this study is its focus on specific product
outcomes as opposed to most prior research that examines
firm-level aggregate outcomes such as the quality of a
firm’s products relative to competitors (Clark and Fujimoto 1991; Menon, Jaworski, and Kohli 1997; Morgan and
Piercy 1998). By focusing on product quality at the
individual product level, this study can provide insights
about factors that interact with quality and the differential
effects they have on product performance.
For further information, contact:
Kwaku Atuahene-Gima
Department of Management
City University of Hong Kong
Hong Kong
E-Mail: [email protected]
American Marketing Association / Winter 2005
Kalyani Menon, Wilfrid Laurier University, Waterloo
Harvir Bansal, Wilfrid Laurier University, Waterloo
A survey derived scripts of consumer experiences of
powerfulness and powerlessness during service consumption. Most experiences occurred in high contact services,
underlining the social nature of consumer power. Powerfulness and powerlessness were linked with distinct antecedents and consequences that differ from non-consumption situations, and powerfulness appears to be a more
complex experience than powerlessness.
As repeatedly documented by consumer researchers,
the social interaction between consumers and service
providers is among the most significant determinants of
consumer experience in the service (Bitner, Booms, and
Tetrault 1990; Keaveney 1995; Menon and Dubé 2000).
Service satisfaction and dissatisfaction depends greatly
on how the provider relates to consumers, and how they in
turn perceive the provider.
Research on service provider – consumer dynamics
has looked at it primarily from a relationship marketing
perspective, to understand benefits to consumers and
firms due to long term relationships with service providers
(e.g., Gwinner, Gremler, Bitner 1998). These studies have
focused on various examples of interpersonal behaviour
such as empathy (e.g., Butcher, Sparks, and O’Callaghan
2003), friendship (Price and Arnould 1999) and affective
commitment (Shemwell, Cronin, and Bullard 1994). Social psychologists stress that these behaviours are exemplars of two key meta-constructs of power and communion that underlie most social interactions and map the
various modes of relating to the world. (Moskowitz et al.
1994). Understanding consumer-service provider interaction and the impact on the consumption experience
requires we go beyond examples of behaviour to examine
how the two meta-constructs of power and communion
occur in services where providers and consumers are
required to interact during service delivery and consumption. To our knowledge, no research has thus far adopted
such a theoretically anchored approach to the study of the
parameters of consumer-service provider interaction.
This paper presents an initial investigation of the
meta-construct of power from a consumer perspective as
American Marketing Association / Winter 2005
it arises during service consumption. The objective is to
initiate an in-depth understanding of the nature and components of consumer experiences of powerfulness and
powerlessness during service consumption. It is hoped
that such an understanding will enable service managers
to develop tools and strategies to enhance service experiences. The following section draws on the social psychology literature to describe the concept of power, what is
known of the experiential aspects of power and its implications for consumer behaviour. We then present our
empirical study of the subject. A survey of consumers of
a range of services was conducted and qualitative and
quantitative data collected on their experience of power
and the lack of it. The data were coded and analyzed to
develop scripts of consumer powerfulness and powerlessness. Such scripts map the mental representation of relevant experiences (Fitness and Fletcher 1993; Shaver et al.
1987) and may be crucial to understanding the dynamics
of consumer – provider interaction.
Social power has been defined as the control possessed by an individual over another and refers to attempts
to enhance and protect differentiation of the individual
(Depret and Fiske 1993; Moskowitz et al. 1994). As an
extension, we argue it may be thought of as the ability to
control another’s outcome. High power and low power
have been conceived as polar opposites with high power
being manifest in frequent behaviours of dominance and
assertiveness and low power expressed by submissive
acts. Power dynamics are thought to permeate most social
relationships, whether explicitly or implicitly. This concept of power and control may occur explicitly in services
such as the control a doctor has over a patient, or a banker
has over a mortgage application. While the power equation in such transactions is clearly weighted in favour of
the service provider, there may be several other service
situations where the power equation may not be so obvious. For instance, a restaurant patron has power in so far
as their patronage adds to the business of the restaurant
and of the individual waiter. But the restaurant and the
waiter in turn can affect the outcome of the diner’s eating
experience, and thus may have some power as well. There
may also be a range of services where the power equation
is mostly absent such as services at the post-office, routine
banking, and other such services where the consumer’s
and/or the provider’s ability to control the outcome may
be relatively irrelevant.
While initial research examined individual level factors such as gender as sources of social power (Ridgeway
1992), more recent research stresses the interaction between individual and situation level variables. Gender by
itself may not impact social power quite as much as the
gender composition of the social group with greater
stereotypical gender-power relationship in same gender
interactions than in opposite gender interactions (Macoby
1990; Moskowitz et al. 1994). Continuing with the idea
that power is a function of the interaction between a
person and the situation, social and professional roles
have been shown to impact power, For example, individuals express more power in the role of a supervisor but less
in the role of a supervisee (Moskowitz et al. 1994). The
first question of interest to this paper is what elicits service
consumer experiences of powerfulness and powerlessness? Are they mirror images of each other e.g., does the
absence of what elicits powerfulness elicit powerlessness
and vice versa?
This paper also examines the experiential consequences of power and lack of power on consumer cognition and expectations, emotions, and emotion expression.
The cognition and expectations of individuals experiencing power or the lack of it tend to have specific biases since
powerful individuals are motivated to defend their power
and the powerless to compensate for their lack of it
(Richeson and Ambady 2002). Thus, in order to preserve
their power, powerful consumers may have an exaggerated conception of their role and ability in the service, or
may have low expectations of others in the setting. Powerless individuals may focus their attention and cognitive
resources on monitoring others in the social setting since
they perceive themselves as being dependent on others.
In addition to its impact on cognition, powerfulness
and powerlessness may impact emotion experiences and
expression. According to the interpersonal view of emotions, emotions emerge and are defined during interaction
between individuals (Parkinson 1995). There are wellestablished norms about the appropriateness of emotions
relative to one’s power and emotions such as anger and
joy are typically experienced when one is in a powerful
situation while emotions such as anxiety and sadness are
experienced in powerless situations. Further, the extent to
which individuals express emotions may also be impacted
by their experience of power with powerful people being
more willing to express their emotions than the powerless
(Conway et al. 1999). Thus the second research question
of interest to this paper is: How does consumer perceptions of power or the lack of power in a service context
manifest itself? What kind of cognition, expectations,
emotions, and expressions occur as a result of consumer
American Marketing Association / Winter 2005
perceptions of their power in a service situation? Finally,
with the objective of examining the impact of power on
consumer service experience, we also examine how perceptions of two marketing outcome variables – service
quality and consumer satisfaction – vary due to the power
experience. The following section presents a survey used
to capture the components of consumer experiences of
power – antecedents, cognition, expectations, emotions,
and expression – as well as consumer evaluations of
service quality and satisfaction when they are powerful or
powerless in a service context.
Following the method used by previous research on
developing scripts of interpersonal dynamics (Fitness and
Fletcher 1993; Shaver et al. 1987), we used a self-administered survey with a mix of qualitative and quantitative
measures. Research has shown that repeated experiences
render people highly knowledgeable about various components of their experiences and that it is possible to elicit
memory representations or scripts of these experiences
(Fitness and Fletcher 1993; Shaver et al. 1987). Typically,
researchers provide individuals with a series of prompts
designed to elicit retrospective reports of the experience,
and scripts are developed using the most frequently mentioned features of the experience.
Sample and Procedure
A convenience sample of adult consumers of services
(n = 138; 54% male, 46% female) were approached on a
university campus and randomly assigned to one of two
versions of the survey questionnaire – either the version
asking them to recall an experience of powerfulness (n =
60) or one of powerlessness (n = 78) during consumption
of any type of service. The respondent pool was mainly
composed of the members of the university community
such as administrative staff, employees of local businesses, and some faculty. We did not approach any undergraduate students. Majority of the respondents were between
the ages of 26 and 50 (approx. 67%), 42 percent had
completed an undergraduate degree, 25 percent were
graduates, and 14 percent held post-graduate degrees.
In each version of the questionnaire, respondents
were instructed to recall and report the actual experience
of powerfulness/powerlessness in as much detail as possible. Powerfulness and powerlessness was defined for
the respondents as control/certainty and lack of control/
certainty respectively in a service context. The questionnaire began with demographic questions and was followed by a series of prompts to aid recall of a relevant
experience of powerfulness or powerlessness (e.g., what
happened, when, who was present, etc.). This was followed by measures for the dependent variables.
Dependent Variables
Open-ended questions asked respondents to provide
details of the antecedents of powerfulness/powerlessness
(what happened to make them feel powerful/powerless),
specifically the type of service setting in which the event
occurred, gender of the individuals present at the time of
the event, and details of the eliciting event.
Open-ended questions then captured the experiential
consequences of consumer thoughts and expectations.
Respondents were asked to describe their thoughts, and
their expectations of the service provider as they experienced powerfulness/powerlessness during the event described. Multi-item 5 point scales (not at all – strongly)
drawn from past research (Richins 1997) measured experiential consequences of some major consumer emotions.
Anger was measured by 5 items (anger, frustration, irritation, outrage, hostility; α = 0.94), anxiety was measured
by 3 items (nervousness, worry, anxiousness; α = 0.79),
shame was measured by 3 items (shame, embarrassment,
guilt, α = 0.71) and happiness was measured by 3 items
(joy, excitement, happiness; α = 0.85). The experiential
consequences of emotion expression was measured by a
single item 7 point scale (not at all – very much so) asking
respondents to indicate the extent to which they expressed
their emotions using hand and body gestures, facial or
vocal expressions.
The marketing outcome variables were all measured
by multi item scales. Service quality was measured by a 4
item (employee professionalism, quality of information
provided, care of customers, overall service quality; α =
0.95) 5-point scales (poor – excellent). Consumer satisfaction was measured by a 2-item 7-point scale (very
dissatisfied – very satisfied; very disappointed – very
delighted, α = 0.94) adapted from Oliver (1997).
Data Analysis
The qualitative responses dealing with the antecedents, cognition, and expectations were scrutinized and
coded by three coders working independently to reflect
underlying dimensions and/or categories. After careful,
repeated readings, the data was sorted in to groups reflecting underlying similarities. For instance, when coding
responses to the question of the eliciting event, data about
delayed service and condescending service provider were
assigned to the category of service failure. We ensured
that the data assigned to each category was more similar
to each other than to data assigned to other categories.
Conflicts were resolved by majority vote. The full list of
categories is presented in Table 1. Aggregate scores were
created for the quantitative measures. Chi square tests and
difference of means were conducted to develop scripts of
powerfulness and powerlessness.
American Marketing Association / Winter 2005
It is noteworthy that the majority of the experiences
recounted occurred in high contact services (retail, professional) rather than in low contact services (miscellaneous services such as online, cable) supporting the
contention that power is intrinsically social in nature and
arises in the context of interpersonal interaction. Results
indicate that while the majority of the powerless experiences (54%) occurred in the context of professional services, the majority of powerful experiences occurred in
the context of either retail services such as computer
stores, restaurants (48%) or professional services such as
financial services, legal services, and government services (45%). In keeping with past research, while consumers
were almost equally likely to feel powerful in mixed
gender and same gender groups, powerlessness was experienced primarily in mixed gender groups. The mixed
gender groups involved either a service provider or other
consumers of the opposite gender in close proximity
during the event.
Interesting differences arose in terms of the nature of
the eliciting events for powerful and powerlessness. Powerfulness occurred primarily when consumers perceived
they had high levels of knowledge in the service setting
(67%). This knowledge could relate to knowledge of the
nature of the service (e.g., knowledge of financial instruments a consumer wishes to purchase, knowledge of
computer hardware in a retail store) or to knowledge of the
script of the service encounter (e.g., consumers knew the
process to file a complaint, knowledge of the various
phases of consumption in a high-end restaurant). On the
other hand, while 32 percent of powerless experiences
occurred despite consumer perceptions of knowledge, the
majority of powerlessness occurred due to service failures
such as service delays, pushy service provider, and being
taken advantage of (68%). Powerless consumers did not
report lack of knowledge as a cause for their experience,
thus indicating that powerlessness, rather than being the
mirror image of powerfulness as documented by past
research, may be a distinct experience.
Experiential Consequences
Turning now to the experiential consequences of
powerfulness and powerlessness, powerfulness was linked
almost equally with provider oriented (49%) and action
oriented thoughts (43%). For example, an action oriented
thought may concern a consumer thinking of, “how to get
it [laptop under repair] back ASAP,” or being “better
aware,” so as to “to make a better decision.” Provider
oriented thoughts took the form of a consumer thinking of
“being ripped off as a consumer [by the service provider]
Frequencies and Mean Values for Episodes of Powerfulness and Powerlessness.
N = 60
N = 78
Service setting (% frequencies)
χ2 = 14.33 (p < 0.05)
Gender composition (% frequencies)
χ2 = 4.83 (p < 0.05)
Eliciting event (% frequencies)
χ2 = 18.49 (p < 0.05)
Consumer knowledge
Service failure
Experiential Consequences
Cognition (% frequencies)
χ2 = 21.49 (p < 0.05)
Action oriented
Provider oriented
Expectations (% frequencies)
χ2 = 9.07 (p < 0.05)
Core service related
Interpersonal service related
No expectations
Emotions (mean values)
t = -8.11 (p < 0.05)
t = 8.44 (p < 0.05)
t = -5.42 (p < 0.05)
t = -3.21 (p < 0.05)
Emotion expression (mean values)
t = 1.65 (p < 0.10)
Service quality perceptions (mean values)
t = 8.47 (p < 0.05)
Consumer satisfaction (mean values)
t = 9.11 (p < 0.05)
having already paid for this expensive chalet,” or focussing on how the provider was delivering the service.
Powerless consumers tended to have provider-oriented
thoughts (55%) and reported a very low frequency of any
American Marketing Association / Winter 2005
action-oriented thoughts. These results reflect past research indicating the “other-focus” of powerless consumers while powerful consumers focus on how they can
accentuate and protect their powerful position in the
situation. Interestingly, two categories of thoughts – ruminative (e.g., what can I do, how did I get in to this situation)
and avoidance (I’ll never come back here again, get out
immediately) occurred to some extent in powerlessness
but not in powerfulness.
Consumer expectations of the service provider during their experience of powerfulness and powerlessness
showed a pattern similar to that of consumer cognition.
Powerfulness was accompanied by expectations that the
provider would attend to both the core service (46%) as
well as the interpersonal service (36%). Powerlessness,
however, was dominated by expectations that the provider will attend to the interpersonal aspects of the service
(59%). For instance, the core service expectations could
take the form of, “yes, when I pay for a hotel room or a
chalet, I expect it to be ready when they tell me” or “. . . I
expected answers to all questions regarding food and the
restaurant.” On the other hand, examples of interpersonal
service expectations were, “they [the service provider]
would be helpful and knowledgeable,” “expected the
usual prompt attention,” “politeness,” “be friendly, pleasant,” or “consumer should be utmost.”
Regarding the emotions experienced, in keeping with
the fact that powerlessness occurred primarily due to
service failure, powerless respondents reported higher
intensity of all negative emotions (anger = 3.55, worry =
2.69, shame = 1.69) than did powerful respondents (anger = 1.98, worry = 1.84, shame = 1.21; all p < 0.05), while
the latter reported greater happiness than did the former
(2.30 and 1.48 respectively; p < 0.05). Further, while past
findings indicate that powerless individuals are highly
conscious of their self-presentation and thus may be less
expressive about their emotions, results here indicate that
although powerless consumers were indeed less likely to
be expressive than powerful consumers, the difference
was only marginally statistically significant (means 4.33
and 3.90 respectively, p < 0.10).
Marketing Outcomes
Results indicate that powerful consumers have higher perceptions of service quality (mean = 3.69) and satisfaction (mean = 4.87) than powerless consumers (2.15
and 2.49 respectively; p < 0.05).
This paper studied consumer experiences of power,
an important construct in our understanding of consumer – service provider interactions during service consumption. The research provides details of consumers’
mental representations of their experiences of powerfulness and powerlessness. Evidence indicates that powerfulness and powerlessness may not be simple mirror
images of each other. While consumer knowledge elicited
American Marketing Association / Winter 2005
powerfulness, respondents reporting powerless experiences did not cite lack of knowledge as a cause of their
powerlessness. Rather service failure (which can occur
despite consumer knowledge) led to powerlessness. Powerfulness appears to be a more complex experience than
powerlessness as evidenced by the fact that for the antecedents such as service setting, and experiential consequences of cognition and expectations, there was no one
clearly dominant category for powerfulness. Powerfulness was equally likely in retail and professional services,
led to both action oriented and provider oriented thoughts
and to expectations regarding both the core service and the
interpersonal service. Powerlessness, on the other hand,
had more clearly dominant categories. It tended to occur
most in professional services, was dominated by provider
oriented thoughts and expectations regarding the interpersonal aspects of the service. In this context it should be
mentioned that informal feedback from respondents after
having completed the surveys indicated that those recalling experiences of powerfulness had greater difficulty in
articulating the experiential aspects of this as compared to
those recalling experiences of powerlessness. This may
indicate that the concept of power becomes more salient
for consumers when they perceive the lack of it, and
therefore it is more clearly represented in their minds.
Since powerlessness was linked with a negative event
such as service failure, it is also possible that, since
individuals place more emphasis on the negative, these
experiences were more sharply sketched in their minds.
Managing consumer perceptions of power appears to
be an important managerial issue since powerful consumers had higher perceptions of service quality and satisfaction. For instance, consumers tended to feel more powerful in same gender groups than in mixed gender groups,
and this could have implications for segmenting consumers and assigning service provider responsibilities according to the gender of the consumer. Further, while service
failure is clearly to be avoided, merely preventing failure
may not enhance consumer power. Rather, providing
consumers with knowledge of the structure and process of
the service may go a long way in doing so.
Surprisingly, powerless respondents reported high
intensity anger, an emotion generally thought to occur
when an individual feels in control of a situation or wishes
to gain control over a situation (Conway et al. 1999).
Further, contradicting past findings indicating that powerless individuals are highly conscious of their self-presentation and thus may be less expressive, results indicate
that both powerful and powerless consumers are likely to
equally express their emotions. While the nature of our
data does not allow an examination of the reasons for this,
we speculate that this may be a deliberate strategy by the
powerless consumers to convey their experience to the
service provider and perhaps recruit the provider’s help in
navigating the remainder of the service. Such a reasoning
is in keeping with past research indicating that consumers
are highly aware of the communicative role of their
emotions and use it accordingly (Parkinson 1995). It is
also possible that since most people are aware of the
power standing connoted by discrete emotions (e.g., Conway et al. 1999), experiencing and expressing high power
emotions may be a strategy to try and gain more power in
the setting.
While as noted previously, experiences of powerfulness and powerlessness occurred primarily in high contact services thus underlining the social nature of power,
it will be interesting to study the occurrence of social
power in services that are migrating from high contact to
self service. Research indicates that consumers attribute
human characteristics to their interactions with technolo-
Bitner, M.J., B. Booms, and M. Tetrault (1990), “The
Service Encounter: Diagnosing Favorable and Unfavorable Incidents,” Journal of Marketing, 54, 71–84.
Butcher, K., B. Sparks, and F. O’Callaghan (2003). “Beyond Core Service,” Psychology and Marketing, 20
(3), 187–208.
Conway, M., R. Difazio, and S. Mayman (1999), “Judging Others’ Emotions as a Function of the Others’
Status,” Social Psychology Quarterly, 62, 291–305.
Depret, E. and S. Fiske (1993), “Social Cognition and
Power: Some Cognitive Consequences of Social
Structure as a Source of Control Deprivation,” in
Control Motivation and Social Cognition, G. Weary,
F. Gleicher, and K. Marsh, eds. New York: SpringerVerlag, 176–202
Fitness, J. and G. Fletcher (1993), “Love, Hate, Anger,
and Jealousy in Close Relationships: A Prototype and
Cognitive Attribution Analysis,” Journal of Personality and Social Psychology, 65, 942–58.
Gwinner, K., D. Gremler, and M.J. Bitner (1998), “Relational Benefits in Services Industries: The Customer’s Perspective,” Journal of the Academy of Marketing Science, 26, 101–14.
Keaveney, S. (1995), “Customer Switching Behavior in
Service Industries: An Exploratory Study,” Journal
of Marketing, 59, 71–82.
Macoby, E. (1990), “Gender and Relationships: A Developmental Account,” American Psychologist, 45, 513–
Menon, Kalyani and Laurette Dubé (2000), “Ensuring
Greater Satisfaction by Engineering Salesperson
Response to Customer Emotions,” Journal of Retail-
American Marketing Association / Winter 2005
gy and it will be interesting for future research to examine
consumer power in the context of consumer interactions
with technology as substitutes for service providers (Moon
2000). Further, the concept of social power may not be
restricted to service situations and consumer – service
provider interactions. Consumer perceptions of their power
may exist when they interact with other consumers such as
during communal consumption activities generated by
brand communities, and in fact any consumption situation
embedded in a social context.
While important insights into consumer experiences
of power were gained through this exploratory study,
future research is required to address the shortcoming of
this study (e.g., the use of a relatively small convenience
sample) as well as the queries that arise from its findings.
ing, 76 (3), 285–307.
Moon, Youngme (2000), “Intimate Exchanges: Using
Computers to Elicit Self-Disclosures from Consumers,” Journal of Consumer Research, 26 (4), 323–40.
Moskowitz, D., E. Suh, and J. Desaulniers (1994), “Situational Influences on Gender Differences in Agency
and Communion,” Journal of Personality and Social
Psychology, 66 (4), 753–61.
Oliver, R. (1997), Satisfaction: A Behavioral Perspective
on the Consumer. McGraw-Hill.
Parkinson, B. (1995), Ideas and Realities of Emotions.
New York: Routledge.
Price, L. and E. Arnould (1999), “Commercial Friendships: Service Provider – Client Relationships in
Context,” Journal of Marketing, 63, 38–56.
Richins, M. (1997), “Measuring Emotions in the Consumption Experience,” Journal of Consumer Research, 24, 127–46.
Richeson, J. and N. Ambady (2002), “Effects of Situational Power on Automatic Racial Prejudice,” Journal
of Experimental Social Psychology, 39, 177–83.
Ridgeway, C.J. (1992), “Gender, Interaction, and Inequality,” Personality and Social Psychology, 76 (5),
805–19, New York: Springer.
Shaver, P., J. Schwartz, D. Kirson, and C. O’ Connor
(1987), “Emotion Knowledge: Further Exploration
of a Prototype Approach,” Journal of Personality
and Social Psychology, 52, 1061–86.
Shemwell, D., J. Cronin, and W. Bullard (1994), “Relational Exchange in Services: An Empirical Investigation of Ongoing Customer Service-Provider Relationships,” International Journal of Service Industry
Management, 5 (3), 57–68.
For further information contact:
School of Business and Economics
Wilfrid Laurier University
Waterloo, ON, N2L 3C5
Phone: 519.884.0710, Ext. 2704
FAX: 519.884.0201
E-Mail: [email protected]
American Marketing Association / Winter 2005
Pete C. Honebein, University of Nevada, Reno
The consumer’s role in unlocking the value that
exists in products and services continues to attract the
interest of the marketing field. Spearheaded by Vargo and
Lusch (2004), the new dominant logic for marketing
defines the consumer’s role of coproducer, where the
consumer is continually involved in the production of
value as he consumes products and services. The consumer’s success as a coproducer is dependent upon the consumer’s physical and mental skills, or if the consumer
lacks those qualities, the embedding of those attributes in
the product or service itself. Vargo and Lusch (2004)
suggest that organizations that recognize this balance can
more effectively develop offerings that enable consumers
to realize greater value.
elements of the consumption environment that must be in
place to enable consumer performance. This not only
includes such things as policies, but also procedures,
tools, interfaces, and technologies. Incentive defines the
intrinsic and extrinsic motivators that stimulate consumers to perform in a certain way. Often, these motivators
take the form of rewards, punishments, or both. Expertise
reflects the knowledge and skills possessed by the consumer, developed through training programs and direct
Method and Procedure
The development of a consumer’s physical and mental skills through such strategies as consumer and customer education is well recognized, as is the embedding of
such qualities in products and services through selfservice technologies (Meuter, Ostrom, Roundtree, and
Bitner 2000). Yet, a consumer’s ability to perform activities that realize benefits associated with products and
services is dependent not only upon the acquisition of
skills or the transfer of skills to another entity, but upon the
expectations, feedback, and motivation the consumer
possesses and receives from external sources (Bateson
2002; Gilbert 1996). The combination of these factors,
which this paper defines as vision, access, incentive, and
expertise, forms a coproduction experience model that
offers organizations a framework of the causal factors that
make self-service possible in the context of coproduction
and value creation. The aim of this research is to investigate which consumer performance factor has the strongest
influence on consumers’ success and satisfaction with
products and services.
Given the exploratory nature of our research the
design of the study is based on critical incident technique
(Bitner, Booms, and Tetreault 1990; Meuter et al. 2000).
This methodology involves collecting actual stories that
describe, in as much detail as possible, situations in which
an organization enables or restrains customer performance. These stories are then classified to uncover patterns or themes, in this case using the coproduction
experience model as the primary classification structure.
A convenience sample of 144 students in an introductory
marketing class was invited to participate in the study.
Participation involved posting up to two stories on a webbased bulletin board during a two week period in exchange for extra credit. Participants were asked to write
stories of at least 200 words that reflected their personal
experience with performance success or failure in one of
the following roles: (1) a consumer; (2) an employee
working with consumers; or (3) an observation of another
consumer. Two example stories prepared by the principal
investigator provided participants a model of the form,
structure, and length expected for the stories. One example story described a tax preparer’s checklist, and the
other described a retail clerk teaching a customer about
using a camera.
Coproduction Experience Model
A performance orientation for consumers focuses on
four key constructs: vision, access, incentive, and expertise. We define vision in terms of two key components, the
consumer’s awareness of key performance goals or outcomes, and the feedback the consumer receives related to
the achievement of the goals or outcomes. Access defines
Seventy percent of the stories reflected situations
where consumer performance was enabled, while 30
percent of the stories reflected situations where consumer
performance was restrained. In terms of the consumer
performance model, a vast majority of the stories (72%)
described situations where access had the strongest influ-
American Marketing Association / Winter 2005
ence on consumer performance, followed by expertise
(13%), incentive (9%), and vision (6%). Within access,
SSTs were the most often identified influence on custom-
er performance (54%), followed by human policies/procedures (29%), and then other non-human solutions (17%).
For further information contact:
Peter C. Honebein
Managerial Sciences Department
University of Nevada at Reno
5450 Wintergreen Lane
Reno, NV 89511
Phone: 775.849.0371
E-Mail: [email protected]
American Marketing Association / Winter 2005
Elizabeth G. Miller, Boston College, Boston
Barbara E. Kahn, University of Pennsylvania, Philadelphia
Mary Frances Luce, Duke University, Durham
Most service experiences involve waiting and thus
the total experience can be described as being comprised
of multiple parts, e.g., arrival, wait, main event, departure,
that extend over time. Each of the components of the
experience may be associated with different emotions,
and consequently, may require different coping resources
and strategies which may interact. We examine such
interactions by investigating how the expected valence of
an event affects two different wait management strategies – providing duration information and reducing wait
times – for managing the stress experienced during the
wait. Four experiments demonstrate that event valence
can moderate, and even reverse, the effects of wait management strategies.
Waiting and Event Valence
While the literatures on services and operations management have examined many facets of waiting, such
research has not considered the effect of the waited-for
event on the waiting experience (other than to suggest that
people are willing to wait longer for more important
events; Houston et al. 1998; Maister 1985). In addition,
such research has typically been conducted in non-stressful environments, such as banks or restaurants. In these
environments, waiting is assumed to be negative because
the event being waited for is either positive or neutral, and
waiting is assumed to be the focal source of consumer
stress. In contrast, we argue that waits are not always
negative and the valence of the event matters. In particular, we propose that delay may have positive effects when
the event being waited for is negative or unwanted.
The literatures on procrastination, approach-avoidance, and coping provide support for this contention.
Specifically, the procrastination literature suggests procrastination is more likely when people want to avoid a
task (Greenleaf and Lehmann 1995), while Miller’s (1959)
approach-avoidance conflict theory suggests desires for
avoidance increase and are stronger than desires for
approach as one nears a feared stimulus. These tendencies
suggest that desire for delay may predominate over the
desire to have the experience completed. Consequently,
people may view delay less negatively (and perhaps even
positively) in such situations.
American Marketing Association / Winter 2005
In addition, various methods of coping suggest that
delay can be preferred. In particular, emotion-focused
coping attempts often take the form of denial or avoidance
(e.g., Lazarus 1991). To the degree that people practice
“wishful thinking” or feel that the event is psychologically further away during a wait, delays may be preferable.
Similarly, to the degree people use delay to cope, for
example, by taking deep-breaths and telling themselves
that things will be okay (more of a problem-focused
strategy), delay may also be beneficial.
Wait Duration and Duration Information
Thus, several literatures suggest that under certain
circumstances delay can be beneficial and desired. In
particular, such considerations are likely to become relevant when people are waiting for events which they find
stressful, negative, or otherwise aversive. We suggest that
in such negative situations, there are two sources of stress:
that associated with having to wait and that associated
with the event itself. Further, considering our arguments
about avoidance, coping, and procrastination, we believe
that interventions designed to attenuate wait stress may
have unintended negative consequences on the stress due
to the event. In particular, we believe that since duration
information – one popular intervention for reducing wait
stress – is thought to operate by reducing uncertainty (Hui
and Tse 1996; Osuna 1985), it may be particularly harmful. That is, we predict that when the waited-for event is
aversive, duration information can actually increase stress,
even though this information attenuates stress in more
neutral situations. Further, given that increased wait time
can be used for coping, we predict that longer waits may
actually result in reduced stress (and thus, a better waiting
experience) for aversive events, while the reverse finding
is typically found in more neutral situations.
We examine these two hypotheses across four studies
in several different waiting environments. In the first
study, in which participants were asked to wait prior to
participating in a discussion group where they would
either taste soft drinks or be required to give an impromptu
speech, we find evidence that duration information can
exacerbate stress when people are waiting for an aversive
event and that these adverse effects occur because duration information interferes with the coping process. These
results are replicated and further supported in study 2,
where we find that people who choose to cope with
avoidance-oriented strategies respond more negatively to
duration information when waiting for an aversive event
(watching an aversive film) than those who do not. Studies 3 and 4 extend these findings to a second wait management strategy – reducing wait times – while also lending
credence to the notion that delay can have beneficial
Based on these findings, we argue that marketers
should consider the characteristics of their service or
good, as well as the emotional state of their customers,
when determining the best way to manage delays. In
particular, managers seeking to apply wait management
strategies that have been used successfully in one context
should be careful when trying to apply those strategies in
other contexts, especially when those contexts differ in
their valences. For example, hospitals should be wary of
mimicking strategies currently employed by banks (and
other industries) to reduce the negativity of waits. In
addition, this research suggests that for situations involving negative or stressful aspects for consumers, managers
should consider wait management strategies other than
duration information to manage these waits. Strategies
that assist consumers in managing their stress (from all
sources) will likely yield the most positive experiences.
References available upon request.
For further information contact:
Elizabeth Miller
Boston College
140 Commonwealth Ave.
Chestnut Hill, MA 02467
Phone: 617.552.2988
FAX: 617.552.6677
E-Mail: [email protected]
American Marketing Association / Winter 2005
Niels J. Blunch, Aarhus School of Business, Denmark
Splitting a conjoint job involving many attributes
into several jobs each containing a sub-population of the
original attributes is a well-known method to overcome
respondent overload.
In traditional bridging the conjoint job is split into
two or more jobs each with a subsection of the attributes
(taking care not to split correlating attributes into different
jobs) and then combining the partial utility functions into
one using the technique of bridging. The name indicating
that a few of the attributes are included in both (all)
conjoint jobs, and are – so to speak – used as bridges to
bring the evaluations on a common scale.
This is done by estimating the “best” (in an OLSsense) scale factor, by which to multiply the utilities for
the bridging attributes in the second design to match the
utilities in the first. The hope being that the coefficients of
all factors in the second equation should also be made
comparable with those of the first equation by multiplication with the same constant. Only rarely will the “regulated” utilities of the bridging attributes from the second
design be the same as those estimated from the first
design, and consequently we end up with two estimates of
the utilities of the bridging attributes, as well as two
estimates of the constant. This problem is solved by
averaging these utilities.
Although bridging has been used in several conjoint
studies as an intuitively reasonable – although somewhat
rough – method for solving the problem of respondent
overload, the method is not quite satisfactory, as it is best
described as a sequence of ad hoc’eries. Consequently the
statistical (distributional) properties of the model are
rather obscure, making traditional testing meaningless –
or at least complicated.
In order to overcome the weaknesses of traditional
bridging, I would suggest Zellner’s seemingly unrelated
regression model (SUR). In its basic form, the model is:
Σi α X + ε
y =β + Σ βZ +ε
y1 = α0 +
The name “seemingly unrelated” is due to the fact
that the one and only connection between the two equations is the (possible) correlation of the error terms.
In the present application, the equations model the
first and second bundle of conjoint judgements by a single
respondent, and the possible correlation between the
error-terms is due to the fact that the two equations refer
to the same respondent – a fact that is ignored by traditional bridging. Also, we place the restrictions on the estimation of the parameters that the coefficients referring to the
bridging attributes are equal across the equations, and the
same goes for the two constants.
Comparing the Two Techniques
In an experiment seventy-nine business students at
master level were asked to express on a scale from 0 to 10
their willingness to by 2 x 27 different cars, each described
in an 18-attribute profile. A week later they were asked to
evaluate five car profiles (with all 18 attributes). This
second round was a holdout round, i.e., the data from this
round was not used to calculate the preference functions.
Rather they were used to evaluate the functions by comparing the results of the holdout round with predictions
based on the preference functions calculated on data from
the first round. The main results were as follows:
Compared to traditional bridging SUR reduced the
MAD (Mean Absolute Deviation) by about 30 percent and the correlation between actual and predicted
preferences was increased by no less than about 70
percent. These figures are averages taken over the
five holdout profiles.
The variation of MAD and correlations across the five
profiles was considerable smaller for SUR than for
traditional bridging – i.e., SUR is more stable.
Traditional bridging results in larger uncertainty on
parameters estimated in the second evaluation as
compared to the first.
To sum up: The advantages of SUR as compared to
traditional bridging are:
where (possibly) cov(ε1, ε2) =/ 0
American Marketing Association / Winter 2005
Estimation and “bridging” is done in one go instead
of in tandem.
The estimation is based on all variables, which makes
the result less erratic than traditional bridging, where
the result depends solely on the bridged attributes.
The uncertainty is more evenly divided among the
parameters in the model, whereas traditional bridging favours the first conjoint evaluation.
The possible correlation of the error terms – caused
by the fact that the two parts of the model are based
on data from the same respondent – are taken into
consideration, whereas it is ignored in traditional
Unlike bridging, SUR is a formal model with wellknown statistical properties; which means that statistical evaluation and testing etc. can be performed on
the total model, and not only on the separate (unbridged) models. References available upon request.
For further information contact:
Niels J. Blunch
Department of Marketing, Informatics, and Statistics
Aarhus School of Business
Haslegaardsvej 10
DK–8210 Aarhus V
Phone: +45.8948.6688
FAX: +45.8615.3988
E-Mail: [email protected]
American Marketing Association / Winter 2005
James R. Brown, West Virginia University, Morgantown
Anjala S. Krishen, Virginia Polytechnic Institute and State University, Blacksburg
Pushkin Kachroo, Virginia Polytechnic Institute and State University, Blacksburg
Chekitan S. Dev, Cornell University, Ithaca
Empirical researchers who investigate managerial
issues in marketing (e.g., sales force performance, marketing channel relationships) often rely upon the key
informant methodology to report on organizational structure and behavior, both within the firm and among organizations. For example, Brown and Peterson (1994) as
well as Weeks, Chonko, and Kahle (1989) have asked
sales managers to provide their subjective assessments of
the individual salespeople whom they supervise.
The problem with such an approach is that, for a
variety of reasons, supervisors’ subjective ratings of their
subordinates are not independent. This lack of independence violates a key assumption of multivariate analysis
(e.g., ordinary least squares regression, structural equation modeling) that the error terms are independently
distributed. Violating this critical assumption can result in
biased standard errors (Johnston 1984; Kennedy 1998)
and unstable parameter estimates (Johnston 1984; Kennedy
1998). Thus, the objective of this paper is to present and
illustrate two methods for reducing the biases that occur
when key informants report on multiple organizational
units (e.g., customer service reps, salespeople, retail managers, channel member firms).
Perceptual reports of informants lack independence
because of several factors, including halo effects, leniency or harshness, and central tendency (Cocanougher and
Ivancevich 1978). Retrospective accounts of performance
may also lack independence because of a desire to appear
consistent and rational as a result of the consistency motif
(Podsakoff, MacKenzie, Lee, and Podsakoff 2003; Podsakoff and Organ 1986).
The problem of within-informant bias can be addressed in at least two ways. One is to use data based upon
completely independent observations (e.g., John and Reve
1982). Another is to correct for the within-informant bias
mathematically. We take this latter approach here.
One method that we propose to adjust for withininformant bias is the mean-centering bias adjustment
method. Another is the matrix invest-based bias elimination method, a refinement of the first method.
American Marketing Association / Winter 2005
We illustrate our two approaches for reducing within-informant bias using data from two concurrent and
related surveys of hotel-brand headquarters relationships
in the U.S. and Canada. In the first survey, we gathered
data from the general managers of a number of hotels
representing two well-known U.S. lodging chains. The
second survey asked brand headquarters field representatives of these two chains to report on the relationships
between the brand headquarters and the hotels that the
reps supervised. The two surveys yielded 245 matched
pairs – general managers and brand headquarters reps –
with complete enough data, representing a 14.2 percent
response rate, to illustrate our approach. Further, virtually
all of the headquarters reps reported on their relationships
with multiple hotels. Hence, the potential for withininformant bias in our data set appears strong.
Reliable and valid measures based on these data were
used to estimate an identified system of two simultaneous
equations, with hotel opportunism and brand headquarters opportunism as the two dependent variables.
Our results show that, as compared to the parameter
estimates derived from the unadjusted data, the meancentered bias adjustment method strengthens parameter
estimates in some cases and weakens parameter estimates
in others, while in still other instances, this method has no
strong effect on the parameter estimates. The matrix
inversion-based bias elimination method operates similarly.
In comparing the two correction methods, the inferences drawn from the 2SLS analysis are not different,
although certain parameters do vary somewhat. Thus, for
our sample, the particular method used to adjust for
within-informant bias appears to matter less than the
simple act of correcting for that bias.
When key informants (e.g., sales managers) report on
more than one organizational entity (e.g., salespeople),
those reports cannot be considered independent. When
used in multivariate analyses, these dependent reports
violate the important assumption that the multivariate
error terms are independently distributed. As a result, the
parameters estimated from these multivariate analyses
can lead researchers to make inferential errors. Such
errors can be avoided, however, by correcting for withininformant bias (i.e., the lack of independence among key
informant subjective assessments). References available
upon request.
For further information contact:
James R. Brown
College of Business and Economics
West Virginia University
P.O. Box 6025
Morgantown, WV 26506–6025
Phone: 304.293.3053
FAX: 304.293.5652
E-Mail: [email protected]
American Marketing Association / Winter 2005
Sabrina Helm, University of Duesseldorf, Germany
The epistemic relationship between variable and indicators in latent variable structural equation modeling
(SEM) is often not considered by researchers, leading to
measurement model misspecification (Burke et al. 2003).
Latent variables may be associated with reflective or
formative indicators. From a conceptual and methodological standpoint, it is very important which kind of indicator specification is used. Taking the example of the
construct of corporate reputation, the paper therefore
raises two research questions:
How can the correct mode of indicator specification
be determined for a complex construct?
How can a formative approach to measuring reputation be developed and tested?
Due to a resurgence of interest in corporate reputation, an abundance of different definitions of the construct
can be found in the literature. Wartick (1992, p. 34) for
example defines corporate reputation as “the aggregation
of a single stakeholder’s perceptions of how well organizational responses are meeting the demands and expectations of many organizational stakeholders.” In accordance to this and similar definitions, corporate reputation
can be understood as a construct based on a firm’s contributions to its stakeholders. This understanding is also
relevant concerning the most discussed reputation measures such as Fortune’s “Most Admired Companies” or
the “Reputation Quotient” developed by the Reputation
Institute. In empirical terms, this definition of reputation
results in the formative conceptualization of the measurement model for reputation as rankings are used to measure
reputation and to compare companies based on their
reputation. Rankings and indices are classical examples
of formative construct conceptualization. But as the literature on the two measures implies, they are created using
reflective indicators.
In the paper, the meaning of a formative and reflective structure of a measure is pointed out in detail. Using
reflective indicators, the researcher assumes that the observable indicators represent the construct, the direction
of causality runs from the construct to the items. These are
interchangeable which means that the construct is unidimensional and the items correlated; they are required to
share the same antecedents and consequences. An in-
American Marketing Association / Winter 2005
crease in one indicator is accompanied by increases of the
other indicators. If reputation were modeled as a reflective
construct, the indicators – understood as a stakeholder’s
perceptions of (e.g., product quality, treatment of employees, management quality, care for the environment, etc.) –
are interpreted as “effects of a construct“ (Bollen and
Lennox 1991, p. 305). Reputation leads to these effects
meaning that reputation determines the quality of products, the quality of management, the treatment of employees, and so forth, as outcomes of reputation.
Formative indicators “cause” the latent variable,
they represent different dimensions of it. The construct is
a summation of the formative observed variables associated with it meaning that changes in the indicators change
the construct. The indicators need not be correlated or
represent the same underlying dimension (Bollen and
Lennox 1991). Conceptualizing corporate reputation as a
formative construct means that the indicators lead to the
construct as inputs which seems to be the more suitable
relationship between indicators and construct. Reputation
is an aggregation of all its indicators such as product
quality or treatment of employees. This implies that because it delivers high quality products, a firm has a good
reputation; because it treats employees right, it has a good
reputation, and so forth. The process of conceptualizing a
formative measurement model for reputation is different
to the process used for reflective modeling. In the paper,
the process is discussed in detail following a set of
conceptual criteria to clarify the construct’s epistemic
nature. An empirical study in the consumer goods sector
serves to illustrate the tasks associated with formative
modeling. Diamantopoulos and Winklhofer (2001) suggest a four step approach for index construction, which is
used for guidance in our study of reputation. It includes
content specification, indicator specification, test for
multicollinearity, and external construct validity.
The results of the study support a formative measurement model containing 10 indicators. As some of the
indicators have low weights (which are the equivalent for
loadings in reflective measurement models), the discussions part of the paper is devoted to the implications of
formative modeling and the handling of low weights.
Generally, ex-post removal of indicators is not considered
an option if the formative construct is changed by that
deletion procedure (Diamantopoulos and Winklhofer
2001). The findings imply that the individual differences
in the importance that stakeholder groups attach to the
proposed reputation dimensions need to be investigated
more closely. If the importance – meaning the weights of
the formative indicators – would prove to be low in one
stakeholder setting, but high in another, measurement
models for reputation could be adapted to the stakeholder
groups if this were acceptable for formative models. This
finding would corroborate some authors’ understanding
that different stakeholder groups “give different weight”
to the reputation dimensions. Eliminating low-weighted
indicators would result in a shortened, stakeholder-specific list of indicators. Of course, this would reduce the
capacity of the measure to compare different stakeholder
groups’ perceptions of a certain company – thereby limiting a study’s generalizability.
sumer Research, 30, 199–218.
Diamantopoulos, A. and H.M. Winklhofer (2001), “Index
Construction with Formative Indicators: An Alternative to Scale Development,” Journal of Marketing
Research, 38, 269–77.
Wartick, S.L. (1992), “The Relationship Between Intense
Media Exposure and Change in Corporate Reputation,” Business & Society, 31, 33–49
Bollen, K. and R. Lennox (1991), “Conventional Wisdom
on Measurement: A Structural Equation Perspective,” Psychological Bulletin, 110, 305–14.
Burke, Jarvis C., S.B. Mackenzie, and P.M. Podsakoff
(2003), “A Critical Review of Construct Indicators
and Measurement Model Misspecification in Marketing and Consumer Research,” Journal of Con-
For further information contact:
Sabrina Helm
Department of Marketing
University of Duesseldorf
Geb. 23.31, Universitaetsstrasse 1
40225 Duesseldorf
Phone: ++49.211.811.13 49
FAX: ++49.211.811.52 26
E-Mail: [email protected]
American Marketing Association / Winter 2005
Miao Zhao, Roger Williams University, Bristol
Ruby Roy Dholakia, The University of Rhode Island, Kingston
With the emergence of computer-mediated communication (CMC), online stores are experimenting with
attributes that are unique to the new media. There is a
choice of many attributes (such as search engine, ordering
system, order status tracking, customer survey, personalization, and virtual reality display, etc.), each performing
a specific function and distinct from other attributes
within the website. In addition to deciding which attributes to include and how to specifically operationalize
the selected attributes, online store managers are also
concerned about the impact of an attribute or a set of
attributes on customer satisfaction and loyalty.
While there is an established body of literature and
decades of experience regarding the design of physical
stores, the new world of online stores and website attributes are now beginning to receive attention. In addition to describing multiple attributes, several authors have
attempted to categorize them into “must have” and “should
have” attributes (e.g., Burke 2002). Given the large number of possible attributes as well as the changing nature of
technology that makes new attributes increasingly possible, it is not surprising that there is a lack of consensus
regarding “must have” and “optional” attributes.
Online Store Attributes and Customer Satisfaction
In this paper, the main focus is on the relationships
between online store attributes and customer satisfaction.
While Baker (1986) and Bitner (1992) proposed categories of attributes that impact consumer responses to retailer cues, Eroglu, Machleit, and Davis (2003) argue that
these typologies do not easily translate into the online
world. Existing empirical research is limited.
We report on an empirical study designed to test
whether retail store attributes affect users’ satisfaction
with and loyalty to the website. Secondary data, collected
at the online store level, were compiled directly from in August 2003. Customer ratings on
1079 individual online stores were collected.
First, factor analysis of 12 attributes (excluding “overall look and design of site”) was performed and the results
indicate that the time at which the measures are taken
contribute to the factor loadings; hence the two factors are
labeled “at check out” and “after delivery.” The two
factors explain 68 percent of the variance. Second, several
multiple regression analyses are performed to examine
the relationship between the attributes and the attributes
and customer satisfaction and loyalty (intention to revisit).
Website Attributes
Using Ghose and Dou’s (1998) classification of website attributes, we first attempt to identify potential attributes across four different types of websites – communication, entertainment, information, and transaction (online store). With so many website attributes to choose
from, our analysis suggests that transaction (or online
store) sites are more likely to include certain types of
attributes. It also suggests that online stores are “attribute
rich” – potentially containing the maximum number (16)
of the 25 specific attributes. It is also very likely that online
stores will differ not only on the number of specific
attributes incorporated within specific websites, but also
how a specific attribute such as “customer support” is
operationalized. These variations create important challenges for research on the effects of individual attributes
on customer satisfaction and loyalty.
American Marketing Association / Winter 2005
From the analysis of the customer ratings, we draw
some conclusions regarding the influence of online store
attributes on site design, satisfaction and repeat purchase
intentions. First of all, “ease of finding what you are
looking for” and “clarity of product information” are the
two most important attributes for generating positive
ratings of overall look and design of the site. The analysis
also suggests how specific attributes are operationalized
are as important as whether or not a specific attribute is
We also find that the time gap between interacting
with a site and evaluating the experience or indicating
revisit intentions affects the impact of attributes; some
attributes persist in their impact. Others appear to lose
some of their impact.
Since the analysis relied on secondary data from
Bizrate, interpretation of results and conclusions must
consider several methodological limitations. While the
customer ratings were acquired twice, the temporal association of the second set of attribute ratings with the
dependent variables seems to be the primary reason for the
observed relationship. Also, it is not surprising that “fulfillment” variables such as “on time delivery,” “product
met expectations” became the dominant attributes influencing online store ratings once the customer received
actual delivery of the product. These fulfillment variables
are biggest challenges to all non-store retailing, including
internet retailing. This suggests that the most creative,
interactive, vivid online site won’t compensate for weak
fulfillment and customer support capabilities. References
available upon request.
For further information contact:
Miao Zhao
Roger Williams University
One Old Ferry Road
Bristol, RI 02809
Phone: 401.253.5351
E-Mail: [email protected]
American Marketing Association / Winter 2005
Debra Zahay, Northern Illinois University, DeKalb
Organizations are continually reassessing and realigning their capabilities and seeking to enhance their
business performance. There are many factors that contribute to organizational success. In recent years, many
firms have turned to a new area, the management of
Customer Information Systems (CIS) (Zahay and Griffin
2004) or the use of customer information in systems such
as Customer Relationship Management (CRM) systems
(Reinartz, Krafft, and Hoyer 2003), to contribute to firm
profitability. In addition, failure rates of applications
associated with customer information, like Sales Force
Automation (SFA) and Customer Relationship Management (CRM), remain high, averaging 50–60 percent (Rigby et al. 2002) and empirical support for their contribution
to management success is ongoing.
Therefore, factors not included in these prior studies
must explain the variance between firms in terms of the
use of customer information and its translation of the use
of those difficult-to-imitate resources into ultimate firm
performance. One possible explanation for these differences is organizational implementation factors. For example, in New Product Development, organizational factors are found to be important in developing successful
new products In-depth interviews with 17 managers in
Reinartz, Werner, Manfred Krafft, and Wayne D. Hoyer
(2003), “Measuring the Customer Relationship Management Construct and Linking it to Performance
Outcomes,” Teradata Center for CRM at Duke University Working Paper Series (www.teradataduke.
five firms identified specific organizational factors pertinent to the management of customer information in a
strategic context. One exemplary company was compared
to four others to uncover organizational issues and processes leading to effective management of customer information.
During the interviews a pattern emerged which indicated how customer information is integrated throughout
the organization in a manner similar to the process by
which new products are successfully managed within the
organization. Co-location, teamwork, and functional integration were recurring themes. Although one exemplary
company seemed to do an outstanding job of collecting
and disseminating information, all firms struggled with
issues of inter-functional conflict, including the role of the
sales force in contributing data to these systems. However, there also appear to be organizational factors somewhat unique to the management of customer information.
For example, customer-centric strategies are developed
interactively as a dialogue between middle and upper
management, using customer data and competitive trends.
The similarities and differences of the CIS process to the
NPD process is the organizing structure of the results
section of the paper, which is available upon request from
the author.
Rigby, D.K., Frederick F. Reichheld, and Phil Schefter
(2002), “Avoid the Four Perils of CRM,” Harvard
Business Review, 80 (2), 101–109.
Zahay, Debra and Abbie Griffin (2004), “Customer Learning Processes, Strategy Selection, and Performance
in Business-to-Business Service Firms,” Decision
Sciences, 35 (2), 169–203.
For further information contact:
Debra Zahay
Northern Illinois University
DeKalb, IL 60115
Phone: 815.753.6215
FAX: 815.753.6014
E-Mail: [email protected]
American Marketing Association / Winter 2005
Angela Hausman, University of Texas – Pan American, Edinburg
Americans are fat, and getting fatter (Martin, Robinson, and Moore 2000). Despite this over-consumption,
people are not eating healthier (Kim, Nayga, and Capps
2001). Consumers are not happy about this trend – that is
why they spend billions of dollars trying to correct the
defects caused by overeating (Thompson and Hirschman
1995) and 120,000 each year will die prematurely due to
nutrition related ailments (Frazao 2000). Governments
are not happy about it either – that is why they spend
billions of dollars promoting healthier food consumption.
Taxpayers and insurance carriers are not happy – since
medical costs associated with obesity account for five
percent of direct and ten percent of indirect costs (Martin,
Robinson, and Moore, Robinson, and Moore 2000). The
food industry is not happy as customers line up to file
lawsuits blaming restaurants for their excess weight (CBS
Evening News 2003).
Nothing seems to help. Consumers take off weight
through expensive diet programs, pills, surgery, and exercise only to put it back on again. Promotional advertising
and educational programs run by the government and
insurance companies fall on deaf ears (Wansink 2002).
Nutritional labeling, once thought to be the panacea for
enabling consumers’ desires to eat healthier, does not
appear to be having the desired effect (Hill et al. 2002).
Marketing studies have developed models attempting to explain why consumers engage in behaviors that
thwart weight control goals. For instance, Bagozzi and
various colleagues have developed the theory of trying,
and more recently, the theory of goal directed behavior,
which explain more of the variance in observed behaviors
by incorporating past efforts, control, and desires as
antecedents of food consumption (cf., Bagozzi and Warshaw 1990; Bagozzi and Edwards 2000). Recently, Wansink (2002) contributed to this understanding by reviewing research related to World War II efforts to modify
food consumption. His study underscored the importance
of food availability and familiarity in evaluations of food
acceptability. Unfortunately, most of these studies suffer
from narrow sampling frames – mainly employing students – and low explanatory ability. Developing reliable
and valid measures of modeled constructs has also contributed to the lack of theoretical progress in understanding these behaviors (Bhaskaran 2002).
American Marketing Association / Winter 2005
This study attempts to create a more comprehensive
understanding of the factors affecting weight control
efforts by employing non-student samples and building
on Perugini and Bagozzi’s (2001) Model of Goal Directed
Behavior (GDB). The resulting model, while developed
in the context of weight control, might be equally valuable
in understanding similar purposive behaviors, including
other health behaviors such as smoking cessation and
exercise, dark-side consumption behaviors, such as gambling and eating disorders (Hirschman 1992), and other
process behaviors (Bagozzi and Edwards 2000). Hypotheses tested were:
H1: (a) Negative attitudes toward diet foods and (b)
negative attitudes toward giving up non-diet foods
negatively affect the relationship between desires to
control weight and performance of weight control
H2: The perceived usefulness of food information positively affects the relationship between desires and
performance of weight control behaviors.
H3: The perceived ease of implementing food restrictions
positively affects the relationship between desires
and performance of weight control behaviors.
H4: Mood states affect the performance of weight control
H5: Satisfying social needs negatively affects performance of weight control behaviors.
A preliminary questionnaire was developed and distributed to members of the community using a quota
sampling technique. Using a system similar to the one
employed by Keaveney (1995), data quality was assessed
by contacting randomly selected respondents from each
sample. These procedures produced a usable sample size
of 199. Existing scales were used to measure constructs.
Reliability assessment demonstrated acceptable Cronbach’s alpha for all scales.
Analysis showed 95 respondents were not trying to
lose weight, while 101 were, using a median split on
intentions to lose weight next week as the criterion. As
expected from prior research, more women than men were
trying to lose weight. Dieters also tended to be under 40,
single, and better educated. The effect of income and
dieting appeared bimodal, with lower and higher income
earners being more likely to be dieters than those in
between. Demographic factors affected these variables,
showing that women are likely to diet more frequently
than men, as are those who are married and working full
To understand factors effecting weight control, a
series of hierarchical regressions were conducted using
performance of weight control behaviors as the dependent
variable. The regression was run first on the entire dataset,
then on subsets of those who are attempting to lose weight
and those who are not. Variables were added in sequential
blocks starting with exogenous variables and ending with
the proposed moderators on performance. Resulting regressions were all significant (at .05 level) and the explained variance was 41.6 percent for the entire dataset,
51.1 percent for dieters, and 47.4 percent for non-dieters,
providing superior explanatory ability over those obtained using the GDB alone (r2 = .25), although the
variables are best at explaining the behavior of dieters as
would be expected. References available upon request.
For further information contact:
Angela Hausman
Management, Marketing, and International Business
University of Texas – Pan American
1201 W. University Drive
Edinburg, TX 78504
Phone: 956.381.2826
FAX: 956.384.5065
E-Mail: [email protected]
American Marketing Association / Winter 2005
Merlyn A. Griffiths, University of California, Irvine
Discussions of person-product bonding relationships
in the consumer behavior literature have focused on
consumer involvement with one category of products;
namely physical goods. Yet, evidence exists that people
have similar relationships with other types of products
like place. Environmental Psychology recognizes personplace bonding relationships as “place attachment.” Drawing on the literatures of product involvement in consumer
behavior and place attachment from environmental psychology, this paper provides a conceptual framework
through which to understand consumer bonding relationships with places.
Although products have been defined in the typical
marketing textbook to include person, physical good,
organization, service, events, properties, places, experience, information, and ideas; anything that can be offered
to a market to satisfy consumers want or need (for example, Kotler 2003, p. 407), a preponderance of the consumer behavior literature on product involvement emphasizes
consumers’ involvement with physical goods. However,
evidence exists that people have similar relationships with
other types of products like places. Bonding with places,
similar to involvement with products, objects, personal
possessions, and other people, is recognized as a universal
human phenomenon.
Person-place bonding relationships although not classified as such, exist minimally in the consumer behavior
literature as part of consumer consumption of places. For
example, Penaloza (2000, 2001) demonstrates consumers’ place attachment to the American West through the
recreation and commoditization of the Wild West era in
American history, through Rodeo and Stock Shows. This
reenactment of America’s rich historical legacy has international appeal, and is relived in the United States, Europe
(e.g., Old Texas Town in Berlin), and the United Kingdom. It is the cultural meanings ascribed to the West, the
values of freedom, family, and naturalism which facilitate
the formation of person-place bonds with this historic
place of an era long ago.
From a psychological standpoint, person-place bonding, similar to person-person attachment (like the bond
between infant and caregiver), is a biological human
American Marketing Association / Winter 2005
function for attaining security, comfort, connectedness,
and survival (Ainsworth and Bell 1970). An apparent
congruity exists between the bonding relationships consumers develop with products and that which they develop with places. Although consumer product involvement
is extensively studied (e.g., Andrews et al. 1990; Beatty
et al. 1988; Bloch 1982, 1984; Higie and Feick 1989;
Laaksonen 1994; Lastovicka 1979; Lastovicka and Gardner 1978; Laurent and Kapferer 1985; Richins and Bloch
1986; Zaichkowsky 1985, 1986, 1994), relatively little is
known about consumer involvement with places. Unlike
the products studied in the consumer behavior literature
regarding involvement (e.g., cosmetics, automobiles, clothing, etc.), places offer a wide variety of uses, activities,
settings, cultures, and landscapes that marketers can use to
build an ongoing relationship with consumers, emphasizing various enticing and attraction factors. These attributes of places, maintain stability as the geographic
location and spatial nature of the place never changes
(e.g., Brazil never ceases to be Brazil), however, the
adventures, excitement, and experiences one can engage
in is limited only by the individual’s imagination.
Person-place bonding relationships have been recognized in environmental psychology as “place attachment.” This literature offers potentially significant theoretical contributions to the product involvement literature
by expanding the range and type of products studied to
include “place” as a product. First, it broadens our understanding of person-place relationships that contribute to
the individual’s identity. The strength of individuals’
attachment to place is determined by the degree to which
they perceive the place as being an innate part of their
existence, self image, and self concept (Sirgy 1982),
similar to the strength of one’s attachment to personal
possessions. As Belk (1988) describes, possessions become a part of the extended self. The extended self, he
summarizes, include “body, internal processes, ideas and
experiences, and those persons, places, and things to
which one feels attached” (p. 141). Thus, one’s identity is
tied to the categories of things equated to be a part of the
self, including places. Consequently, if place can be a part
of the extended self like material possessions, then place
must be ultimately tied to one’s identity. Place as it relates
to one’s identity is identified in the environmental psychology literature as place identity which is one of the
determinants of place attachment representing the emotive and affective aspects including preferences, feelings,
and values (Proshansky 1978).
Second, place attachment adds to our understanding
of the mobility of meanings (McCracken 1986) ascribed
to place by individuals. McCracken’s (1986) theoretical
account of meaning movement emphasizes the transfer of
meaning from the culturally constituted world to the
consumer good, to the individual consumer. The place
attachment literature presents a theoretical framework
through which to explore the breadth of meaning movement by extending our understanding of how and why
person-place attachments are formed, the symbolic meanings ascribed to place and the relevance and importance
that characterizes these meanings for the individual.
Third, understanding how different types of attachments are classified will help researchers clarify boundaries of not only place attachment, but also attachments to
brands, products, and material possessions. Kleine and
Baker (2004) recognized the lack of overlap between the
place attachment literature and possession attachment in
consumer behavior, and make a pressing call for researchers to integrate both literatures to broaden the scope of
attachment research, further clarifying boundaries, meaning, and value of person-object and person-place bonding
Understanding consumers’ involvement and attachment to places has practical implications for both relationship and place marketers (i.e., tourism and destination
marketers) as well. As many segments of the tourism
industry reach the maturation stage, these providers of
experiential consumption scramble to enhance customer’s psychological attachment to place by seeking to build
long term programs that communicate investments of
love, status, and reciprocal loyalty (Morais et al. 2004).
Leisure and recreation providers have sought to not only
understand the formation of and processes involved in
person-place bonding relationships, but also the impact
on consumer commitment, satisfaction and loyalty to
place (Iwasaki and Havitz 2004). For relationship marketers whose primary focus is building strategies of personalization (i.e., one-on-one interaction) individualization
(i.e., specific needs and preferences) and continuity (i.e.,
repeat patronage) (Gordon et al. 1998) comprehension of
the process and degree to which consumers’ attachment to
places evolves, presents invaluable information in influencing consumer preference, expectation, satisfaction,
and loyalty (Lau and McKercher 2004). Although the
social aspects of place are often emphasized by these
marketers, some promote the importance of bonding with
the physical place. Summer camps, for example want
individuals to be attached to the place independent of the
people that may be a part of the place. In this respect, the
physical space, rather than merely social ties, drives
campers to return each year, even if their friends do not.
Institutions like colleges and universities yearn to increase place bonding relationships with their alumni to
gain benefits like increased donations and positive wordAmerican Marketing Association / Winter 2005
of-mouth. These institutions strive to endear alums to the
school independent of social ties to other alums. For many
alumni the physical place is endowed with relevance and
meanings often ascribed to churches, synagogues, or
religious institutions. For example, some universities like
University of Richmond and University of Virginia are
offering columbariums or burial sites on campus, the
ultimate extreme in person-place bonding with the physical place even after death.
Place as an Entity
Place refers to space that has been given meaning
through personal, group, or cultural processes (Low and
Altman 1992). As a spatial entity to which people develop
attachments, place can vary in scope, size, and scale. It can
be tangible versus symbolic, known and experienced
versus unknown or not experienced (Low and Altman
1992). The tangible, known and experienced places are
for example, homes, neighborhoods, communities, and
cities. Bonding with these everyday familiar places occurs
as a result of long term residential exposure. Similarly,
recreational places visited (e.g., Appalachian Trail, Hawaii, Jamaica, Disneyland) are also tangible, known and
experienced places however, the experience is short term
and non-residential in nature. Yet, special feelings of
connectedness develop toward these places that are experienced for a short period of time. Symbolic, unknown and
unexperienced places (e.g., heaven, Italy, if one has never
visited) are places that have not been physically experienced by the individual. The activities, rituals, or landscape are elaborated on only through the individual’s
imagination, influenced by stories, readings, or pictures
(i.e., TV, magazines, and internet). Yet for many individuals and groups, although there is no actual exposure in
the physical sense with these places, an existential bond
An example of an individual’s involvement and subsequent attachment to a place is the 1995 film “While You
Were Sleeping,” where the main character (played by
Sandra Bullock) has a fantasy world of romance that
includes an attachment to Florence, Italy, a place she has
strong desires and affinity for, but has never visited. She
carries a passport daily in hopes of one day going there.
Her endearment to Florence is further evident in the way
she speaks of the place as a significant part of her life. The
level of her involvement and attachment to this place is
based on the feelings and romantic meanings she ascribed
to Florence, implying a revered place that if she were to
physically experience it, would represent a phenomenal
accomplishment. Thus, a place with strong self relevance
in its meanings to the individual will be salient in thoughts,
have a high degree of emotional significance and expectation of future experiences imagined or anticipated to be
possible in that place.
Much of the environmental psychology literature
emphasizes longevity in residence as a requirement for
place attachment to develop. However, Stueve, Gerson,
and Fischer (1975) found that the effect of length of
residence on feelings about a locale is largely explained
by the mediation of local ties. This finding weakens
studies that argued that attachment develops as a direct
result of length of residence. The narrow geographic view
and the bounded condition relegated by the length of
residence have limited our understanding of place attachment, a complex and multi-faceted phenomenon (Manzo
2003). This limitation was addressed when Low and
Altman (1992) extended the spatial range of previous
studies, and asserted that people can be attached to places
of varying scale, specificity, and tangibility, from the very
small, like objects, to the nation, planet Earth, or the
Universe. In a recent study, Hidalgo and Hernandez
(2002) found that attachment can also develop after brief
contact with place. The subjects in the study demonstrated
attachment type behaviors after only short term exposure
to place, in particular where the opportunity for social
interaction was absent. This finding demonstrates that
people can develop attachment to places after short term
exposure, and in the absence of social relationships that
are typically formed through long term exposure.
Based on the arguments above, it is my position that
place attachment can also be formed through short term
non-residential exposure (i.e., recreational or tourist places) or even non-exposure (i.e., wanting to visit Italy) to a
place. This paper introduces place attachment to the
consumer behavior literature in an effort to extend our
understanding of person-place bonding relationships.
Drawing on well-established theories and empirical studies of place attachment from environmental psychology,
this paper aims to provide a conceptual framework through
which to understand the characteristics of people-place
bonding relationships. The goal is to examine the properties of product involvement in its applicability to place as
a product. In the sections to follow, an abbreviated review
of the place attachment and product involvement literatures is presented, followed by a summary of the key
concepts of person-place bonding relationships and potential implications for the product involvement literature.
Place Attachment
Place attachment is a complex phenomenon that
integrates many aspects of person-place bonding. In the
environmental psychology literature, theories of place
attachment involve the affective aspects of bonds people
form with places (Low and Altman 1992). The emotional
qualities are often accompanied by cognition (thought,
American Marketing Association / Winter 2005
knowledge, and belief) and practice (action and behavior)
(Low and Altman 1992). Within the intellectual milieu,
place attachment research builds on the premise that
people develop long-standing and meaningful relationships with places. Place attachment can develop through
four distinct ways; namely; biological, the evolutionary
and physiological adaptations and ecological fit of people
to places (Riley 1992); environmental, the interactional
experiences of cultural ecology (Hufford 1992); psychological, the experiences across life stages from childhood
to adult life (Chawla 1992; Cooper-Marcus 1992; Rubinstein and Parmelee 1992); and sociocultural, the social
norm and ideologies, ritual performance, and culturally
shared meanings (Ahrentzen 1992; Low 1992).
Like product involvement, place attachment has wide
variability in its definition and operationalization across
studies. According to Low and Altman (1992) place
attachment is the bonding of people to places. Hummon
(1992) identifies it as an “emotional involvement with
places” (p. 256). Low (1992) considers it as “an individual’s cognitive or emotional connection to a particular
setting or milieu” (p. 165), and Shumaker and Taylor
(1983) views it as a “multilevel person-place bond that
evolves from specifiable conditions of place and characteristics of people, and that has implications for the
attitudes and behaviors of individuals toward their sociophysical environments” (p. 223). Consensus however,
leads to the definition adopted in this paper: place attachment is “a positive affective bond between an individual
and a specific place, the main characteristic of which is the
tendency of the individual to maintain closeness to such a
place” (Hidalgo and Hernandez 2001). In this respect,
maintaining closeness includes nearness in physical proximity, cognitive closeness through the imagination, and/
or emotional closeness through the feelings evoked when
the place is considered by an individual.
Studies of place attachment in environmental psychology first establish a geographic or conceptual terrain
of interest as the boundary place to which attachment
develops. With few exceptions studies have emphasized
limited spatial range of place to routinely familiar places:
homes (Ahrentzen 1992; Brown et al. 2003; Harris et al.
1996; Hidalgo and Hernandez 2001), near-home territories (Fuhrer et al. 1993), home town (McAndrew 1998);
neighborhood (Bonaiuto et al. 1999; Low 1992) community (Hummon 1992; Pretty et al. 2003; Riger and Lavrakas 1981) and city (Brown and Perkins 1992). These
limited spatial ranges represent the tangible, known and
experienced aspects of place, which carries a necessary
requirement of longevity in residence as a determinant of
place attachment. Each type of place offers different
experiences and exposure that facilitates the forming of
Spatial Ranges of Place
Home: Home as a place we inhabit has many meanings. It is the stage of much of our everyday performances,
and cultural artifacts eliciting important meanings to
people (Ahrentzen 1992). As a primary territory, home
affords residents a sense of control that is rarely experienced in other locations. Home is a safe haven, a place of
connection with family, a setting for enjoyed activities,
and a medium for identity displayed (Harris et al. 1996).
Thoughts of home can elicit powerful memories and
affective responses, as among other meanings, home can
mean the house one grew up in, the setting where love was
first felt, the dwelling where one raised children (CooperMarcus 1992). In his focus on attachment to possessions,
Belk (1992) posits that we spend much of our lives in our
homes; our desire for what he calls “homeyness” results in
feelings of attachment to home.
Neighborhood: Neighborhood has been considered
the range most important in the formation of attachment
bonds, thus the most often studied (Hidalgo and Hernandez 2001). A neighborhood has as its main composition
people and the interrelated social ties among them. According to Rubinstein and Parmelee (1992) “life stage and
patterns of interdependence are consistent influences on
the nature and objective manifestations of emotional
bonds with neighborhoods” (p. 150). Neighborhood social ties are held together through group collective behaviors that also serve to maintain order and cohesiveness
among the residents. The physical boundaries of neighborhoods vary in size and configuration, and are a result
of the residents’ collective demarcation and sentiments
(Lawrence 1992). Neighborhoods are an extension of
individuals collectively coexisting. Brown et al. (2003,
2004) examined attachment to neighborhood by focusing
on the neighborhood blocks as the level analysis. The
complexity in a neighborhood has at its source the wide
heterogeneity of residents, demographically, socioeconomically, and ethnically, making it a more dynamic
concept for place attachment studies.
Community: Communities are a composition of multiple neighborhoods, allowing for a wider range of interaction among residents of the neighborhoods that make up
the community. According to Riger and Lavrakas (1981)
“attachment to communities refer to the neighborhood as
a “network of necessities, that go beyond the minimal
level of functional necessity and become conscious communities, in which attachment persists because of adherence to a clear set of values, despite the absence of
traditional functions which formerly bound people to
neighborhoods” (p. 57). A key indicator of community
attachment is greater freedom of behavior, exploration,
confidence, and affective responses within the local community (Fried 2000).
American Marketing Association / Winter 2005
City: The city, larger in spatial range than home,
neighborhood and community, represents collective or
group ownership of public space and place. As a possession to which individuals and groups become attached,
Belk (1992) identified city as “a collection of monuments,
including buildings, cemeteries, and museums that extend
our personalities” (p. 43). The city encompasses the
community, neighborhood, and homes. In this respect, the
city allows for further exploration by the residents (insiders), and non-residents (outsiders) alike. As the city is
public domain, it is likely that transient non-resident
individuals more than residents would utilize the collective sites (museums, monuments) and other public establishments.
Determinants of Place Attachment
Several concepts have emerged in the environmental
psychology literature focusing on person-place bonding,
that have been used inconsistently and in some cases
interchangeably in the literature. In particular, place identity (Proshansky et al. 1983); place dependence (Shumaker and Taylor 1983), and sense of place (Hay 1998) are
most commonly used. The concepts are behaviorally
related in that they are concerned with the bonds between
people and places. However, in some studies, the concepts
have been operationalized as consequences of place attachment, while in others one term has been used to
encapsulate the others. Twigger-Ross and Uzzell (1996)
for example, purport that place attachment functions to
support and develop aspects of place identity. Jorgensen
and Stedman (2001) posits that place attachment, place
identity, and place dependence are three dimensions of
sense of place. Kyle et al. (2004) claims place identity and
place dependence are dimensions of place attachment,
and Pretty et al. (2003) emphasizes place attachment and
place dependence are two of three indicators of place
identity. The significant overlap in terminology and definitions of these place related constructs and the lack of
uniqueness in operationalization should signal researchers to consider whether these concepts are the same or
whether they are theoretically different ways of looking at
the same phenomenon: person-place bonding. In this
regard, it is logically necessary to examine these constructs to ascertain each of their relation to place attachment and applicability in understanding individual and
group bonding relationships with place.
Place Identity: Place identity has been defined as
“those dimensions of the self that define the individual’s
personal identity in relation to the physical environment
by means of a complex pattern of conscious and unconscious ideas, beliefs, preferences, feelings, values, goals
and behavioral tendencies, and skills relevant to this
environment” (Proshansky 1978, p. 155). Place identity
relates to “the variety and complexity of physical settings
that define the day-to-day existence of every human
being” (Proshansky et al. 1983, p. 59). Thus, place identity is one of many facets of an individual’s self-identity
that helps in structuring experiences with physical places
(Shumaker and Taylor 1983). Place identity is most concerned with how places form identity (Moore 2000), and
how a place shapes or builds aspects of an individual’s self
identity. For example, a person who identifies with the
neighborhood of the South End of Boston might identify
himself or herself as a “Southie,” expressing the dimension of self that is defined by and related to the physical
environment. The strength of the individual’s emotional
attachment to place is based on self definitions of who and
what he or she is relative to place (Proshansky et al. 1983).
Thus, for an individual to become attached to a place they
must first identify with the place. It is the meanings they
ascribe to the place that enforces the feeling of similarity,
belonging, and relatedness. Place attachment is integral to
self-definitions (Brown and Perkins 1992), making place
identity the reinforced symbolic representation of the self
that identifies with the particular place. In this respect,
place identity is representative of the emotive and affective aspects of place attachment. It is the intimate selfinterpretation of what an individual may take to be a sign
or locus of one’s identity.
Place Dependence: Place dependence refers to “an
occupant’s perceived strength of association between him
or herself and specific places” (Stokols and Shumaker
1981, p. 457). The strength of the association between
person and place is based on the individual’s comparative
judgment of the current place as a mechanism to satisfy
needs and goals, and expectations of having goals and
needs met by alternative comparable places (Shumaker
and Taylor 1983). The outcome from each option may be
negative; meaning that the current or alternative place
may not be ideal in satisfying the individual’s goals.
However, in comparison, the judgment is made to choose
the better of the two less than ideal options. Place dependence is therefore setting specific, as its main concern is
the adequacy of fit between the individual’s goals and the
particular place, and the achievement of those goals. It is
the functionality of the place that drives the level of
dependence an individual develops to the place. Place
dependence differs from place attachment in two ways.
First, place dependence can be negative depending on the
limitations of the place in achieving the individual’s
desired goals; and second, the strength of the connection
between the person and place is based on specific behavioral goals rather than general affect (Jorgensen and
Stedman 2001). The functional aspect of place dependence suggests it is representative of the “commitment to
place” aspect of place attachment.
Sense of Place: Sense of place is the meaning attached to a spatial setting by a person or group. Further,
American Marketing Association / Winter 2005
sense of place is not imbued in the physical setting, but
resides in human interpretations of the setting (Jorgensen
and Stedman 2001). As viewed by Hay (1998), sense of
place can be broader in context than place attachment, as
a result of the “subjective qualities, and the sensing of
place to create personal meaning” (p. 7). Shamai (1991)
describes sense of place as having levels of intensity of
feeling and behavior from belonging (affiliation) and
attachment (special affinity) to commitment (ready to do
something for the place). He further notes that “place is
never merely an object, but a part of a larger whole that is
being felt through the ‘actual’ experience of meaningful
events . . . the experience is felt through all the senses
(sight, hearing, smell, taste, and touch)” (p. 348). From
this perspective, it can be surmised that sense of place is
a necessary requirement for place attachment, as it is the
meanings individuals and groups ascribed to the place that
feeds attachment.
Measurement Approaches of Place Attachment
Across studies, the most common measure used to
identify the existence of place attachment has been “length
of residence” (Bonaiuto et al. 1999; Brown et al. 2003;
Riger and Lavrakas 1981). As an indicator of place
attachment, length of residence hinges on residents’ demonstration of attachment through physical manifestations
like upkeep of the appearance of their homes and property
(Jorgensen and Stedman 2001), protecting the home and
neighborhood from crime and other incivilities (Brown
et al. 2003; Brown et al. 2004), and interacting with other
residents (i.e., knowing names of neighbors and neighborhood children) (Mesch and Manor 1998). Length of
residence, by the nature of its mandatory requirement of
long term participation, neglects attachment bonds that
can be formed with temporary residences, places to which
exposure is short term or limited, places that are not yet
physically experienced, symbolic and other intangible
places. Harris et al. (1996) demonstrated that attachment
to temporary residence is possible, with their study of
attachment to a student housing facility. Kyle et al.’s
(2004) study of attachment to the natural setting Appalachian Trail demonstrated that attachment does form through
non-residential and short term exposure to place. The
length of residence measure is acknowledged as a powerful correlate of attachment; however, it is theoretically
problematic as it excludes attachment to non-residential
places. A brief review of product involvement is presented here to explore the factors characteristic of product
involvement that may be applicable to person-place bonding.
Consumer behavior researchers have examined the
person-product bonding relationships by focusing on
consumer involvement with different product categories.
A significant number of empirical studies of product
involvement begin by first setting specific parameters
identifying a product or object of interest, like automobiles (Bloch and Richins 1983) cosmetics (Coulter et al.
2003) and fashion clothing (O’Cass 2001). As a construct,
product involvement has been operationalized in numerous ways, resulting in a great deal of variability in the
interpretation of empirical evidence across studies. Coulter
et al. (2003) defines product involvement as the personal
relevance or importance of a product category; O’Cass
(2001) sees it as a person specific characteristic that exists
among consumers in varying degrees; Bloch (1986)
recognizes it as an unobservable state reflecting the amount
of interest, arousal or emotional attachment a consumer
has with a product; and Zaichkowsky (1985), Celsi and
Olson (1988) and Warrington and Shim (2000) believe
product involvement is a person’s perceived relevance of
the object or product class based on inherent needs,
values, and interests.
It is well documented that levels of product involvement exists on a continuum from high to low (Antil 1984;
Lastovicka and Gardner 1978; Leavitt et al. 1981). Determination of high versus low is in large part a function of
the level of interest in the product and the level of
cognitive processing and behavioral activities that the
consumer engages in (Antil 1984). Consumers with high
product involvement exhibit strong interest in a product
that conceivably occupies their thoughts (Richins and
Bloch 1986) and demonstrates strong commitment (Warrington and Shim 2000) and enthusiasm (Bloch 1986).
Consumers with low involvement product rely on short
term memory and routine behaviors or minimal cognitive
processing (Leavitt et al. 1981) as they are not closely tied
to the product or brand outside of their focal attention
(Robertson 1975).
As an individually defined phenomenon, involvement with products requires ongoing commitment with
regard to thoughts, feelings, and behavioral response
(Quester and Lim 2003), emotional connection (Bloch
1986) as a function of the meanings ascribed to the
product, and strong personal relevance (Bloch 1986;
Bloch and Richins 1983; Higie and Feick 1989). Empirically studied, product involvement has been said to have
robust influencing effects on consumer cognitive and
behavioral responses, including memory, attention, processing, early adoption, search, brand commitment, satisfaction, and opinion leadership (see Laaksonen 1994).
Determinants of Product Involvement
Several concepts have emerged in the consumer
behavior literature relating to consumer involvement with
products. Most often found intermingled with product
involvement are brand commitment and brand loyalty.
American Marketing Association / Winter 2005
Brand Commitment: Brand commitment and product involvement have been identified as related but distinct constructs (Traylor 1981). These constructs differ in
that the object of involvement is a product, while the
object of commitment is a brand. In fact, according to
Fournier (1998), “brand has no objective existence at all:
it is simply a collection of perceptions held in the mind of
the consumer. The brand cannot act or think or feel –
except through the activities of the manager that administers it” (p. 345). Brand commitment has been defined as an
emotional or psychological attachment to a brand or
product class (Beatty et al. 1988; Robertson 1976; Traylor
1981; Warrington and Shim 2000). Strong brand commitment has been associated with high levels of involvement
(Warrington and Shim 2000), implying the greater the
brand commitment, the more firmly fixed is the brand as
the only choice for the consumer (Traylor 1981). The
strength of the consumer commitment to a brand lies in the
distinguishable attributes of the brand and the salience of
these attributes relative to the consumer’s belief system in
regard to the product (Robertson 1976). However, involvement is not a necessary requirement for commitment, as a consumer can become involved with a product
and not be committed to it. Involvement occurs when
values important to the individual’s self-image are made
salient. Commitment results when these values, selfimage or important attitudes are cognitively connected to
a specific situation. In this respect, product involvement
leads to brand commitment (Beatty et al. 1988; Coulter
et al. 2003; Fournier 1998).
Brand Loyalty: Brand loyalty has also been linked to
both brand commitment and product involvement. As
closely related concepts, distinction in operationalization
is often blurred. For example, Quester and Lim’s (2003)
study examining the relationship between brand loyalty
and product involvement, states that “brand loyalty develops when the brand fits the personality or self-image of the
consumer or when the brand offers gratifying and unique
benefits that the consumer seeks . . . in both instances,
personal attachment develops toward the brand” (p. 26).
However, in an earlier study Beatty et al. (1988) claimed
that not brand loyalty, but “commitment results when
these values, self-images or important attitudes become
cognitively linked to a particular stand or choice alternative” (p. 152). Consumer loyalty, as described by Oliver
(1999) is “a deeply held commitment to rebuy or repatronize a preferred product/service consistently in the
future, thereby causing repetitive same-brand or same
brand-set purchasing” (p. 34). Thus, loyalty has two
distinctive concepts; namely, behavioral which relates to
the purchase and repeat aspect, and attitudinal which
emphasizes the commitment depth relating to the preferred product or service. This distinction is the basis for
the difference between product involvement, brand loyalty, and brand commitment.
From the literature review on place attachment and
product involvement, it can be determined that both are
psychological constructs that involve the interplay of
individually determined self relevant meanings ascribed
to the product or place of interest. However, similarities
and differences exist between these constructs. Place, like
product can become irreplaceable. When an individual
identifies with place and endows it with meanings the
extent to which place becomes an interpretation of the self
which draws on place as a locus of identity (Hummon
1992), place becomes unsubstitutable. Like products,
these places are those that for the individual there are no
alternatives or substitutes that have the same meaning as
the original.
The factors that drive the development of place
attachment (i.e., biological, psychological, environmental, and socio-cultural) contributes to our understanding
of product involvement. The aspects of an individual’s
upbringing, the environmental and sociocultural facets
indigenous to where one grew up and the cultural norms
and rituals experienced may predispose one to become
involved with specific products. For example, an individual growing up in a region where wine consumption is a
ritualistic part of meals, (e.g., Italy or France) may influ-
Ainsworth, Mary D. Salter and Silvia M. Bell (1970),
“Attachment, Exploration, and Separation: Illustrated by the Behavior of One-Year-Olds in a Strange
Situation,” Child Development, 41, 49–67.
Bloch, Peter H. and Marsha L. Richins (1983), “A Theoretical Model for the Study of Product Importance
Perceptions,” Journal of Marketing, 47 (3), 69–81.
Hidalgo, M. Carmen and Bernardo Hernandez (2001),
“Place Attachment: Conceptual and Empirical Questions,” Journal of Environmental Psychology, 21,
Laaksonen, Pirjo (1994), Consumer Involvement: Concepts and Research. New York: Routledge.
Low, Setha M. and Irwin Altman (1992), “Place Attach-
ence their interest to the extent to which they become a
wine enthusiast. Product involved enthusiasts have been
characterized by Bloch (1986) as having high levels of
information seeking, opinion leadership, innovativeness,
product nurturance, or care and represent a significant
marketplace force.
The position taken in this paper is that bonding with
place is a cognitive, affective, and behavioral commitment. Further, short term exposure as well as non-exposure can also result in the forming of bonds with place.
Experience through fantasy, desire, and imagination supply equally strong interest and involvement to which
attachment develops. Developing a bond with place does
not require physical experience. Similarly, developing a
bond with products does not require ownership of the
product. It is generally accepted that a product can be a
place. Place, like tangible products, can become an integral part of one’s self image and identity. However, the
properties of place that influence an individual in the
forming of bonds are not fully explored. In this respect,
researchers are encouraged to explore the dynamic nature
of place to deepen our understanding of person-place
bonds, and extend the product involvement literature
using the insights of place attachment from the environmental psychology literature.
ment: A Conceptual Inquiry,” in Place Attachment,
Irwin Altman and Setha M. Low, eds. Vol. 12, New
York: Plenum Pres.
Penaloza, Lisa (2000), “The Commodification of the
American West: Marketers’ Production of Cultural
Meanings at the Trade Show,” Journal of Marketing,
64 (October), 82–109.
Proshansky, Harold M., Abbe K. Fabian, and Robert
Kaminoff (1983), “Place-Identity: Physical World
Socialization of the Self,” Journal of Environmental
Psychology, 3, 57–83.
Richins, Marsha L. and Peter H. Bloch (1986), “After the
New Wears Off: The Temporal Context of Product
Involvement,” Journal of Consumer Research, 13,
Complete set of references will be provided upon request
For further information contact:
Merlyn A. Griffiths
Graduate School of Management
University of California, Irvine
Irvine, CA 92697
Phone: 714.366.6998
E-Mail: [email protected]
American Marketing Association / Winter 2005
Andrew M. Parker, Virginia Polytechnic Institute and State University, Blacksburg
Melanie A. Gold, University of Pittsburgh, Pittsburgh
Emergency contraception (EC) is a form of contraception that reduces the risk of pregnancy after unprotected sex or contraceptive failure. Though available in some
form since the late 1960’s, only recently has it been the
focus of behavioral research. Recent FDA deliberations
on switching one EC product (Plan B) from prescriptiononly to over-the-counter status have brought EC even
more public attention. Focused on a specialized market
(particularly young women) and being potentially stigmaand affect-laden (because it is a medication used solely
after unprotected intercourse to prevent pregnancy), EC
represents a rather unusual product class. From a marketing perspective, in trying to deliver the product to the
consumer in a way that is most useful, it is important to
understand how consumers think about, use, and are
affected by EC, particularly adolescents and young women. From a public-health perspective, this same information could be invaluable in protecting individuals’ safety
and well-being.
Because use and misuse of EC reside at the center of
this important public health debate, understanding what
motivates individuals to seek out and use EC (i.e., market
demand) is crucial. The focus here will be on one piece of
the EC product-consumer relationship that has not been
considered – expectations of the future. Expectations, in
this case of having unprotected sex and possibly needing
EC, are central to most theories of choice. To the extent
that the perceived likelihood of needing EC is high (i.e.,
unprotected sex seems likely), and to the extent that
having EC on hand will diminish the chances of an
unwanted outcome (i.e., pregnancy), seeking out EC will
be a more attractive option.
It is hypothesized that expectations of having unprotected sex will correlate positively with future reports of
actual unprotected sex. Similarly, expectations of EC use
will correlate with future reports of actual EC use. However, each expectation is hypothesized to correlate poorly
with the other behavior. A crucial concern is whether the
expectation of using EC will in fact lead to more irresponsible behavior (i.e., unprotected sex). To the extent that
EC expectations are not related to subsequent unprotected
sex, however, such a concern holds less weight. A similar
issue involves the expectation of unprotected sex and
actual past EC use. While EC is not recommended as a
American Marketing Association / Winter 2005
primary contraceptive, it is possible that experience with
EC could lead individuals to think of it as such. On the
other hand, EC use can cause a number of temporary but
uncomfortable side effects, which if seen as significant
may actually decrease future willingness to engage in
unprotected sex. Lastly, it is expected that the perceived
risk of getting pregnant from an episode of unprotected
sex will moderate the positive relationship between actual
unprotected sex and actual EC use, with this relationship
being stronger for those with higher risk perception.
In a longitudinal study, 301 sexually active female
adolescents participants completed an initial, one-on-one
interview conducted in a research office, followed by six
monthly 10-minute telephone interviews (see Gold et al.
2004). At each interview, the perceived likelihood of their
next sexual intercourse being unprotected and of using EC
in the next month were gathered, as well as whether they
had engaged in unprotected sex and/or used EC in the
preceding month. Participants also indicated the perceived risk of pregnancy from one episode of unprotected
Across the six months, only 5 percent to 9 percent
predicted that their next sexual intercourse would be
unprotected, while 24 percent to 33 percent predicted EC
use during the next month. The overall pattern, across
visits, is that expectations of having unprotected sex
correlated positively with reports of subsequent unprotected sex (omnibus p < .0001; Strube 1985), while
expectations of EC use correlated positively with subsequent reports of actual EC use (p = .03). Significant
correlations were not found between expectation of unprotected sex and EC use or between expectation of use
and unprotected sex. Finally, reports of actual unprotected sex correlated positively with EC use, although this
relationship was not moderated by risk perception. A very
similar pattern arose when looking at the relationships
between past behavior and expectations of the future.
In summary, expectations do correlate with behavior,
both past and future. However, a key distinction is between the expectation of having sex (and potentially
needing EC) and the expectation of actually using EC.
Much of the public policy debate regarding EC has
centered on how EC could encourage irresponsible sexual
and contraceptive behavior, particularly among adolescents. Two of the results here argue against that concern.
First, expectation of EC use did not predict future reports
of unprotected sexual behavior. Second, past EC experience did not predict expectation of future unprotected sex.
From the perspective of advance provision and EC’s overthe-counter status, while unprotected sex definitely influences EC use (EC wouldn’t be necessary without it), we
have no evidence that EC use is influencing unprotected
For healthcare providers and marketers, these results
suggest the validity of interventions that recognize the
usefulness of expectations. If a young woman expects that
she will use EC in the future, then this expectation should
be identified during a health care visit and counseling
should include a discussion about how to facilitate timely
use of EC and when the medicine is most effective.
haviors,” Journal of Pediatric and Adolescent Gynecology, 17, 87–96.
Strube, Michael J. (1985), “Combining and Comparing
Significance Levels from Nonindependent Hypothesis Tests,” Psychological Bulletin, 97, 334–41.
Gold, Melanie A., Jennifer E. Wolford, Kym A. Smith,
and Andrew M. Parker (2004), “The Effects of Advance Provision of Emergency Contraception on
Adolescent Women’s Sexual and Contraceptive Be-
For further information contact:
Andrew M. Parker
Department of Marketing (0236)
Virginia Tech
Blacksburg, VA 24061
Phone: 540.231.3096
FAX: 540.231.3076
E-Mail: [email protected]
American Marketing Association / Winter 2005
Thomas Hollmann, Arizona State University, Tempe
Cheryl Burke Jarvis, Arizona State University, Tempe
Customer satisfaction, loyalty and retention are central tenets in the practice of customer relationship management (CRM) for both goods and services, and these
concepts have been the focus of heavy study. Yet customer defection rates remain quite high in many service-based
industries, as shown by Griffin and Lowenstein (2001).
Therefore it may be surprising that defection itself has
received far less attention in both research and practice
than its counterparts of loyalty and retention. Only recently, a variety of studies have started to look at specific
drivers of customer defection (e.g., Ahmad 2002; Capraro, Borniaczyk, and Srivastava 2003; Keaveney 1995) or
more generally at influences on repurchase decisions
(e.g., Bolton and Lemon 1999; Jones, Mothersbaugh, and
Beatty 2003).
Interestingly, Keaveney’s (1995) qualitative research
found that the majority of defected customers identified a
complex combination of multiple reasons for a decision to
switch service providers, rather than a single driver of
defection. This finding highlights the need for both academics and practitioners to understand drivers of defection in the context of a comprehensive model, rather than
through individual investigations of single factors in
isolation as is typical of the literature to date.
In addition, measurement has complicated the study
of defection drivers in two ways. First, researchers often
have relied on measures of customer satisfaction to identify problem areas in service delivery that might influence
future defection. Satisfaction has been found to have a
significant impact on repurchase intentions, but that impact is typically small (Bolton 1998), and it has been
shown that in some cases as much as 65 percent to 85
percent of defected customers report being “satisfied” or
“highly satisfied” (Reichheld 1996). Even dissatisfaction
is not necessarily a predictor of defection (Hennig-Thurau
and Klee 1997). For a loyal customer, it may take repeated
incidences of dissatisfaction with various elements of a
product purchase or service encounter before the customer chooses to switch. Or, it may require that a customer
reach a threshold level of dissatisfaction on a particular
factor or combination of factors to choose to leave. Even
if a customer is not particularly loyal, defection may not
occur despite unsatisfactory experiences, because of convenience or competitive issues.
American Marketing Association / Winter 2005
Second, much of the extant research in satisfaction
and loyalty uses behavioral intention probabilities (e.g.,
“likelihood to renew the contract” on a 7-point Likert
scale) rather than actual defection data (e.g., Anderson
and Sullivan 1993; Parasuraman, Zeithaml, and Berry
1988), despite the fact that Garland (2002) has shown that
self-reported switching probabilities overestimate actual
defection rates. Thus, both measuring satisfaction as a
predictor of defection and measuring self-reports of behavioral intentions fall short in providing researchers a
valid tool for identifying and analyzing drivers of customer defection. Different methodological approaches are
needed to more effectively measure and evaluate the
system of factors that influence customer switching behaviors.
Therefore, the goal of this paper is to extend the
methodological arsenal of customer loyalty research by
proposing and illustrating the use of a defection weight
method (DWM) of data collection and analysis to assess
the relative influence of key drivers of customer defection. This method allow researchers to investigate the
relative influence of a constellation of factors that contribute to switching decisions, rather than evaluating influences in isolation from each other. DWM employs graded
paired comparisons to understand the preference structure
of defection drivers.
The paper reports results from a survey of recently
defected consumers on a variety of services using the five
elements of the Servqual scale, price, and the physical
product as defection driver categories. The study shows
that a vast majority of defection decisions are multidimensional. Less than 10 percent of the respondents have
a uni-dimensional defection weight profile in which one
reason dominates, i.e., represents 75 percent or more of
the decision to defect. This finding supports Keaveney’s
(1995) qualitative findings of the complexity of the defection decision.
The paper also compares the relative influence of the
tested defection drivers using the DWM technique to the
relative influence of the same drivers as reported by
traditional customer satisfaction measures using regression analysis. Significant differences in the relative weights
of the tested factors are demonstrated between the two
methods, supporting past evidence that traditional measures of satisfaction are not valid proxies for drivers of
Finally, we use the DWM results to perform a cluster
analysis of customers based on defection drivers, illustrating a method that practitioners and academics alike could
use to segment customers and differentiate services. Close
to 70 percent of respondents were more heavily influ-
enced to defect by the elements of service quality as
expressed by the Servqual, while about 30 percent of
respondents were more strongly influenced by the nonServqual elements. References are available upon request.
For further information contact:
Thomas Hollmann
W.P. Carey School of Business
Arizona State University
P.O. Box 874106
Tempe, AZ 85287–4106
Phone: 480.965.3621
FAX: 480.965.8000
E-Mail: Thomas.Hollm[email protected]
American Marketing Association / Winter 2005
Heiner Evanschitzky, University of Muenster (MCM), Germany
Gianfranco Walsh, University of Strathclyde, Scotland
Research on the relationship between customer satisfaction and customer loyalty has advanced to a stage in
which moderator variables need to be examined more
thoroughly. The relevance of customer satisfaction for
maintaining successful relationships with customers has
been discussed widely (e.g., Oliva, Oliver, and MacMillan 1992; Reichheld 1993; Hennig-Thurau and Klee 1997)
and early work on that relationship demonstrates a positive and direct relationship. However, more recent studies
argue that satisfaction can have a direct and indirect
impact on loyalty (e.g., Hennig-Thurau 1997).
Consistent with the notion of a non-linear relationship (e.g., Mittal, Ross, and Baldasare 1998; Audrian
2002), some research suggests that the satisfaction-loyalty relationship is influenced by certain moderator variables (Jones and Sasser 1995). The objective of this study
is to provide additional insight into the relationship between customer satisfaction and customer loyalty by
empirically examining the effects of selected moderators
(loyalty-card membership, critical incidents, expertise,
gender, age, income) on this relationship.
The sample consisted of 776 customers of a large
DIY chain. Testing for moderation, we first looked at a
non-restricted model and then restricted the four paths
from satisfaction to loyalty to be equal across subgroups.
Chi-square differences (with four degrees of freedom)
were assessed. Next, we compared two models that only
differed in one effect of one satisfaction dimension on one
loyalty dimension. One model restricts the parameter to be
equal across groups while the second model allows variation in one of that parameter across groups. The restricted
model has one degree of freedom more than the general
model. A moderating effect would be present when the
improvement in Chi-square moving from the restricted to
the non-restricted model is significant, meaning the Chisquare difference between the two models (and one degree of freedom) is larger than 3.84 (p = .05).
After confirming the influence of the four postulated
main effects, we tested for moderator effects. A Chisquare difference test was conducted for all six possible
moderator effects, comparing a restricted and a non-
American Marketing Association / Winter 2005
restricted model. With four degrees of freedom more, the
restricted model exhibits a significant Chi-square difference (at p < .05) for three effects: “critical incident,”
“expertise,” and “income.” The Chi-square difference for
the “loyalty-card membership” is slightly less than 9.49,
indicating a difference significant at a level slightly below
.05. Because this effect just fails the threshold, we decided
to test for moderation here as well. Only “age” and
“gender” showed no general moderating effect (Chisquare difference with four degrees of freedom were
1.913 for age and 1.282 for gender). Therefore, we did not
test for specific moderator effects. In summary, it appears
that “loyalty-card membership,” “expertise,” “critical incident,” and “income” are relevant general moderators of
the link between satisfaction and loyalty.
Next, we analyzed specific moderator effects of the
two satisfaction dimensions on the two loyalty dimensions for the moderators. Loyalty-card membership impacts only one out of the four effects. It moderates the link
between “satisfaction with employees” and “positive wordof-mouth.” Those customers who do not hold a loyalty
card seem more likely to relate to their positive experiences with the retailer’s employees to others. Apparently, the
loyalty card holders seem to expect employees to be
friendly and competent and by doing that, expectancy
level of that factor is high. This result questions the
appropriateness of investing in loyalty-card programs.
Our finding is in line with findings from Reinartz and
Kumar (2002) who found little support for the general
positive link between loyalty and profitability.
Three effects are moderated by “critical incidence.”
It is worth mentioning that we only looked at those critical
incidents that were resolved to the satisfaction of the
customer, meaning we are looking at “recovered customers.” With that in mind, it can be noted that recovered
customers – if satisfied with the employees – are far more
loyal than customers who did not experience a critical
incident. In addition, the link between “satisfaction with
the assortment/tangibles” and “positive word-of-mouth”
is also moderated by a positively resolved critical incident. Interestingly, “expertise” moderated only the link
between “satisfaction with assortment/tangibles” and repurchase intention. It is economically highly relevant that
lucrative professional customers (e.g., craftsmen such as
carpenters or plumbers) buying their products at the DIY
retailer are far more likely to repurchase if satisfied with
the assortment.
The analysis of income as a moderator shows mixed
results. The link between satisfaction with the assortment
and positive word-of-mouth is stronger for wealthier
customers. Moreover, the link between satisfaction with
employees and both loyalty dimensions is stronger for
customers with lower income. It seems that high-income
consumers are more concerned with the availability of a
wide variety of products and less concerned with the
friendliness and competence of the employees.
The link between satisfaction and loyalty is less
straightforward and more complex than previous studies
have suggested. Gender and age do not moderate the link
from satisfaction to loyalty. Contrary to previous findings
(e.g., Homburg and Giering 1999), the satisfaction di-
mensions are equally important to men and women and all
age-groups in their effect on customer loyalty. A reason
for that could be that DIY stores usually offer lowinvolvement goods that are normally purchased less impulsively. Particularly for certain high-involvement products, we would expect a moderating role of gender and age
on the satisfaction-loyalty link. Despite the fact that we
found no support for the moderating effect of gender and
age, there is sufficient evidence for a non-linear relationship between the two constructs “satisfaction” and “loyalty.” Our research suggests that the two satisfaction
dimensions, “satisfaction with assortment/tangibles” and
“satisfaction with employees,” positively influence the
two loyalty outcomes “repurchase intention” and “positive word-of-mouth.” In particular, we found that “loyalty-card membership,” “expertise,” “critical incident,” and
“income” are relevant general moderators of the link
between satisfaction and loyalty. References and tables
with results available upon request.
For further information contact:
Heiner Evanschitzky
Marketing Center Muenster
University of Muenster
Am Stadtgraben 13–15
D-48143 Muenster
Phone: +
FAX: +
E-Mail: [email protected]
American Marketing Association / Winter 2005
Christian Homburg, University of Mannheim, Germany
Nicole Koschate, University of Mannheim, Germany
Wayne D. Hoyer, The University of Texas at Austin, Austin
Previous research has recognized that both cognition
and affect significantly predict satisfaction judgments.
However, only a few studies have investigated cognitive
and affective antecedents of customer satisfaction simultaneously. Moreover, these studies have been static (i.e.,
cross-sectional) in nature. This represents a significant
shortcoming since it is well established that customer
satisfaction is a dynamic phenomenon. Despite the strong
recognition that customer satisfaction should be viewed
from a dynamic perspective, the role of cognitive and
affective influences has not been systematically studied in
this manner. The few studies which have investigated the
antecedents of customers satisfaction from a dynamic
perspective have focused on the cognitive component of
customer satisfaction.
Against this background, this study provides a dynamic analysis of the simultaneous influence of cognition
and affect in the satisfaction formation process. The
fundamental proposition is that the role of cognition and
affect may change over time. We argue that affect plays its
strongest role at the early stages of satisfaction development, whereas the impact of cognition should increase
over time. In addition, we build a case that this phenomenon also depends on the level of consistency of the
consumption experience (i.e., is it consistently positive or
consistently negative). Furthermore, we argue that satisfaction judgments should become more stable over time
and that the ability of both cognition and affect to predict
customer satisfaction should increases.
The results of an experimental study based on a real
consumption experience indicate that the impact of cognition on the satisfaction evaluation increases over time
and that the influence of affect decreases. Moreover, these
effects are more pronounced in the case of consistent
performance experiences. Finally, the study shows that
the variance in customer satisfaction jointly explained by
cognition and affect increases as experience accumulates.
The findings have several important implications for
marketing managers. For example, the study helps managers to understand customer satisfaction in a more thorough way. It sheds light on the formation process of
customer satisfaction and shows that customers satisfaction has a more stochastic character in early stages. Thus,
it is more easily for managers to influence the satisfaction
judgment in the early stages where the satisfaction evaluation has not yet been crystallized. Further, it is common
in practice for managers to think of customer satisfaction
in a logical, rational manner (i.e., if the product or service
performs well, satisfaction will be higher). The results of
this study point out that affect can play a critical role as
well, particularly in the early stages of the satisfaction
formation process. Thus, for new relationships or new
products and services managers must pay close attention
to affective aspects and be careful to manage them effectively.
For further information contact:
Christian Homburg
Institute for Market-Oriented Management (IMM)
University of Mannheim
68161 Mannheim
Phone: +49.621.181.1555
FAX: +49.621.181.1556
E-Mail: [email protected]
American Marketing Association / Winter 2005
Martin C. Reimann, Freiberg University, Germany
Ulrich F. Luenemann, California State University, Sacramento
The Six Sigma methodology, traditionally referring
to defect reduction and quality improvement in manufacturing, can also be applied successfully to marketing.
Some service quality defects are related to intercultural
differences, especially when taking the direct integration
of external factors – international customers – into account. In a study involving German, Spanish, and Swedish customers, the authors found that people from cultures
with a high degree of uncertainty avoidance were less
satisfied when their service expectations were not met.
This suggests that Six Sigma can reduce service quality
defects related to intercultural differences if preceded by
sound intercultural operative planning and training of
service personnel.
Six Sigma, originally developed in Japan and adapted
at Motorola in the late 1980s to eliminate waste by
achieving near-perfect results in production processes, is
credited with saving billions of dollars also at other wellknown U.S. multinational companies, like General Electric and Allied Signals, just to name a few (Biolos 2002).
Traditionally, Six Sigma refers to reduction of defects and
improvement of quality in manufacturing; however, it can
be applied to marketing as well (Ehrlich 2002). Especially
services with high involvement of the customer, the Six
Sigma methodology can help to improve service quality
(Pande, Neuman, and Cavangh 2000; Biolos 2002; Ehrlich
2000). In this regard, Six Sigma can be defined as a databased methodology or process to prevent service defects
and improve customer satisfaction. The statistical concept
behind it represents the amount of process variation in
relation to customer requirements as the source of all
service quality considerations. If a process functions on
the Six Sigma level, variation is almost non-existent.
Thus, the process results are defect-free in 99.9997 percent of all cases, which means only 3.4 defects per million
process steps.
According to Kotler (2003), a service features the
following three characteristics: (a) the intangibility of the
service; (b) the integration of an external factor (an object
or a subject on which the service is applied and which is
integrated into the service process); and (c) the quality
variation of the service. Of special interest for this paper
American Marketing Association / Winter 2005
were the two factors integration of the external factor and
service quality variation. It was assumed that, as a result
of cultural value differences between the service provider
and the customer, the integration of the external factor
could be defective. This might be based on the perception
of the customer, who measures the service’s quality
according to his/her own specific cultural values while the
service provider might base the service on another culture
value. Thus, the integration of external factor – the international customer – is defective. Since the perceived
service quality varies based on cultural value differences
and there is a dependency between service quality and the
integration of the external factor (Hutchens 1989; Stamatis
1996), another assumption was that if the integration of
the external factor was defective, the level of perceived
service quality would be low.
In this paper, different cultural values and their impact on international service marketing will be explained
first. Subsequently, the two relevant service characteristics – the integration of the external factor as well as
quality variation – will be examined with regard to customers responding differently to a delivered service and
its quality. At this stage, cultural value differences and
their influence on customer and service provider interactions will be taken into account. In this intercultural
context, the Six Sigma methodology will be introduced.
The study will show how Six Sigma can help to reduce the
defects in the integration of the external factor by focusing
on quality variation. Thus, this paper suggests that Six
Sigma can be used as a workable tool for enhancing
international service marketing provided that it is built
into the company’s operative programs and the service
personnel has undergone adequate cultural awareness and
intercultural preparation training.
The growth and spread of multinational business on
a global scale puts strong emphasis on the importance of
integrating cultural elements in international service marketing. According to Hofstede (1997, p. 9), culture is “the
collective programming of the mind which distinguishes
the members of one group or category of people from
another.” Thus, “culture is not a characteristic of individuals; it encompasses a number of people who were conditioned by the same education and life experience” (Hofstede
1997, p. 5). Values, the most basic manifestation of
culture, are defined as “broad tendencies to prefer a
certain state of affairs over others” (DeMooji 1997, p. 46).
Values are among the first things children learn, not
consciously but implicitly. Developmental psychologists
consider that by the age of 10, most children have their
basic value system definitely in place and that changes
beyond this age are difficult to obtain (Rokeach 1973).
Since people are not consciously aware of the values they
hold, it is difficult to discuss or observe them (DeMooji
1997, p. 46). Based on the receptivity to the idea of cultural
values as an important factor for organizational success,
however, the need for intensified cultural value research –
especially for multinational companies – became widely
acknowledged. During the last two decades, many researchers have tried to make specific predictions of intercultural differences and the related behaviors (Hall 1984;
Hall and Hall 1990b; Trompenaars and Hampden-Turner
1998; Schwartz 1999). The most comprehensive study to
date on cultural differences in work-related values was
done by Hofstede (1980, 2001), who obtained data from
over 116,000 questionnaires answered by employees at
all levels of a large U.S. multinational company. His
research took place in more than 60 countries around the
world over a period of six years. In his fundamental
approach, Hofstede (1980) concentrated on four basic
dimensions of cultural values to which the selected countries have found different answers in explaining. These
dimensions were:
the degree of power distance (indicating the extent to
which a society accepts the fact that power in institutions and organizations is distributed unequally);
the degree of uncertainty avoidance (indicating the
extent to which a society tries to avoid uncertain
situations by, for example, establishing more formal
rules and believing in, and/or striving for expertise);
the degree of individualism (indicating the extent to
which relationships are based on loose social frameworks rather than on collectivism, where people are
tightly integrated in primary groups, such as families
and organizations);
the degree of masculinity (indicating the extent to
which dominant values or roles in society are viewed
“masculine,” for example achievement, assertiveness and performance, when measured against its
opposite pole, femininity, defined as quality of life,
caring for other people as well as social and gender
equality (Hofstede 1980, 1997, 2001).
In his research, Hofstede (1980, 2001) compares low
and high uncertainty avoidance in societies and uses the
degree of uncertainty avoidance to distinguish between
societal norms. With regard to peoples’ beliefs, attitudes,
and behaviors, low uncertainty avoidance refers to: low
levels of stress and anxiety; weaker superegos and less
showing of emotions; aggressive behavior is frowned
upon; greater tolerance and acceptance of diversity and
uncertain situations; strong belief in general approaches
and common sense to problem solving, where people
should be rewarded for innovative approaches; commitments are less binding and relationships are built quickly
but can also be dissolved as quickly; focus on short-term
planning (up to five years); rules and laws should be
adaptive and changed if they don’t work; more acceptance
of dissent; and willingness to take unknown risk.
Based on their research in Asia, Hofstede and Bond
(1988) found a new dimension, which was later added to
Hofstede’s (1997, 2001) research as a fifth dimension and
American Marketing Association / Winter 2005
the degree of long-term orientation (indicating the
extent to which a society exhibits a pragmatic futureoriented perspective rather than a conventional, historic short-time point of view.
These five cultural value dimensions (Hofstede 1997;
Hofstede and Bond 1988) can be used to make important
predictions of intercultural differences in work-related
values including customer satisfaction.
Cultural values influence how service providers interact with customers. This paper assumes that service
defects in the integration of the external customer will
happen if different cultural values are not understood. The
analytical ability to determine the uncertainty avoidance
orientation seems to be the most important cultural value
dimension that refers to defects in intercultural service
quality. Uncertainty avoidance posits that humans reduce
their inherent uncertainty by dint of technology, law, and
general rituals (Hofstede 2001, p. 147). As shown in
Figure 1, the degree to which uncertainty is generally
acceptable within a given culture can differ greatly from
another (Hofstede 2001, p. 151). For this study, the
German, Spanish, and Swedish cultures were selected due
to availability and easy access of data.
On the other hand, high uncertainty avoidance refers
to: higher stress levels and an inner urge to be busy; robust
superegos and more showing of emotions; aggressive
behavior of self and others is accepted; less tolerance and
acceptance of unclear situations; less acceptance of dissent and strong need for consensus, clarity and structure;
strong belief in expertise and knowledge for problem
solving, where accuracy should be rewarded; commitments are long-lasting and relationships, which are built
slowly, are expected to last for a long time; focus on long-
American Marketing Association / Winter 2005
New Zealand
South Africa
Czech Republic
El Salvador
United States
Arab World
Costa Rica
United Kindom
Hong Kong
South Korea
West Africa
East Africa
* UAI = Uncertainty Avoidance Index
term planning (up to 20 years); strong need and adherence
to rules and regulations to make behavior predictable;
concern with security in life; and knowing about risks
(Adler 1997, p. 53; Hofstede 2001, p. 161). Based on these
general comparisons, service providers can and should
use Hofstede’s (1980, 2001) uncertainty avoidance index
to integrate the external service factor in their operations
by defining service quality for international customers in
terms of cultural awareness and intercultural preparedness of service employees in addition to their obvious
business and organizational skills. A specially tailored
intercultural training – including service factors such as
reliability, responsiveness, competence, courtesy, credibility, security, access, communication, and understanding the customer – can provide appropriate and useful
approaches for adaptation to international customers’
different value systems and behaviors. This is especially
true when the training focuses on the aforementioned
uncertainty avoidance differences as the result of different
cultural backgrounds. Therefore, to achieve a high level
of external factor integration, service providers should
strive continuously to improve the level of customer
satisfaction, which should include intercultural understanding and display of correct and appropriate behavior
towards international customers. Based on the cultural
differences in Hofstede’s uncertainty avoidance dimension, it can be hypothesized: H1: Customers from cultures
with a high degree of uncertainty avoidance will be less
satisfied when their service expectations are not met.
Consequently, in order to achieve customer satisfaction
with people from high uncertainty avoidance cultures, the
service provider needs to meet all relevant service expectations.
Quality variation characterizes service as well. The
central source of quality variation is the defective integration of the external factor (Hutchens 1989; Stamatis
1996). Among the reasons for defective customer integration are some of the following service personnel shortcomings: lack of responsiveness and timeliness, missing
competence and courtesy, miscommunication and faulty
understanding of the customer (Heineke and Davis 1994).
Kotler (2003) identifies three actions to overcome quality
variation: process improvement, customer satisfaction
measurement, and service personnel training. All three
actions can be achieved with the Six Sigma methodology:
Process Improvement: Six Sigma not only implies
statistics; it also uses managerial tools for process
improvement. A Six Sigma project usually follows
the so called D-M-A-I-C approach (Define-MeasureAnalyze-Improve-Control). In the Definition phase,
customer requirements are surveyed, potential savings are evaluated and the process is mapped. The
customer requirements directly lead to the relevant
American Marketing Association / Winter 2005
process variables, which will then be measured, analyzed, improved, and controlled. The Measurement
phase comprises the setup of a capable measurement
system to measure the dependent variables: in this
case customer satisfaction with regard to a specific
service. In the Analysis phase, the independent variables are assessed, which was the service variable
“delivery time” in this study. Then, in the Improvement phase, the value of the independent variables
will be increased. Finally, the Control phase is necessary to review the measurement system and the correctness of its outputs (Pande, Neuman, and Cavanagh 2000, p. 39).
Customer Satisfaction Measurement: Six Sigma aims
at the achievement of fullest customer satisfaction by
providing a defect-free process or service. As already
mentioned above, customer satisfaction can be selected as dependent target variable, which is influenced by one or more process drivers. Its measurement should be done before as well as after the
process improvement to compare and view progress.
Cultural Awareness and Preparation Training: Six
Sigma also integrates change management. Improving a process also means changing human behavior in
organizations to minimize defects. In international
service marketing, operational planning for special
cultural awareness as well as preparation training on
intercultural differences is necessary and especially
essential for the integration of the external factor
when service providers and customers have different
cultural backgrounds and opposing views on how to
deal with uncertainty avoidance. As explained before, the differences between low and high degrees of
uncertainty avoidance can be so severe between
people from diverse cultural backgrounds that understanding their behavior and being aware of their
different perceptions are very important to prevent
irreparable service defects. Therefore, proactive intercultural communication training programs based
on Hofstede’s (1980, 2001) uncertainty avoidance
dimension have to emerge as critical events in the
development of the international service provider’s
management strategies to improve service quality.
Such training can effectively enhance future service
quality both for service providers and customers in
overseas assignments, as well as in multicultural and
ethnically diverse domestic settings. The information
gained and behavioral skills learned will not only
help to prevent service defects, but also enable the
service provider to perform on a much higher quality
level. Thus, customers will experience the service
function on a much higher satisfaction level.
There are basically two ways to achieve a Six Sigma
level. One way is through reduction of scattering, the
other is through expansion of tolerance. As shown in
Figure 2, the defects in the upper normal distribution refer
to a three sigma level with a possible yield of 93.32
The two lower distributions refer to a six sigma level
with a 99.9997 percent yield. While the reduction of
scattering focuses on minimizing variance, the expansion
of tolerance focuses on the customer-related requirements
(the acceptance of a longer-than-promised delivery time).
Achieving Six Sigma Through Reduction of Scattering: As the description of differences between low and
high uncertainty cultures has shown, customers coming
from cultures with a relatively high degree of uncertainty
avoidance have a much lower tolerance for ambiguity.
They do not accept unclear situations and deviation from
the normal variation as easily as customers coming from
cultures with a relatively low degree of uncertainty avoidance. A high uncertainty avoidance index generally also
indicates higher anxiety and stress levels, a greater propensity to display emotions, and a tendency towards
aggressive behavior when challenged. If a service provider interacts with such an external factor, there is only very
little chance to prevent a service defect if the customer
encounters a situation or behavior that does not conform
to the customer’s cultural and normative expectations.
For example, if hotel customers with a high degree of
uncertainty avoidance do not get the expected and/or
reserved room at check-in, they might not accept any
alternate arrangements without aggressive, emotional,
and stressful behavior which, in turn, may lead to a fullsize service defect. In such a situation, the service provider has to consider the customers’ level or degree of
tolerance to be so narrow that any deviation or scattering
from the promised or expected service would automatically lead to the customers’ perception of low service
quality or even total dissatisfaction. Therefore, and within
the scope of the specific study, it can be hypothesized: H2:
If customers posses a high degree of uncertainty avoidance, then a wider tolerance with regard to the promised
delivery time is not accepted. Consequently, the reduction
of scattering (or upgrading of service) should be an
adequate instrument and part of the service provider’s
operational planning to meet the requirements of customers with a high degree of uncertainty avoidance.
Achieving Six Sigma Through Expansion of Tolerance: Contrary to the previous example, customers coming from cultures with a relatively low degree of uncertainty avoidance have a much higher tolerance for ambiguity. They see uncertainty as an inherent part of life and
accept more easily each situation as it comes. A low
uncertainty avoidance index generally also indicates that
people are more at ease, show less emotions and frown
upon aggressive behavior. Based on their higher level of
tolerance, they are more flexible and do not feel threatAmerican Marketing Association / Winter 2005
ened as much when encountering deviations from their
normative expectations. To use the same hotel example, if
customers with a low degree of uncertainty avoidance do
not get the expected and/or reserved room at check-in,
they are more likely to accept a wider range of alternatives. Thus, a possible conflict can be contained on the
level of fairness, flexibility, and common sense without
leading to a service defect. Even if all service expectations
are not met, such customers are still able to come across
with a positive and satisfying service experience. If confronted with such a situation, the service provider can
safely assume that the customers’ tolerance level is high
enough to allow for certain deviations from the expected
service and still perceive a high quality service. As a
result, it can be hypothesized for this study: H3: If customers posses a low degree of uncertainty avoidance, then a
wider tolerance with regard to the promised delivery time
will be accepted. Consequently, the expansion of tolerance could be an adequate instrument and part of the
service provider’s operational planning to meet the requirements of customers with a low degree of uncertainty
To test all three hypotheses, a study was carried out
within a Six Sigma project of a global company from the
chemical industry. In a questionnaire, which was filled out
immediately after a specific service was delivered, 500
customers of three different national cultures were asked
about a certain service quality as well as their satisfaction
level with regard to only this service. Of the 303 received
responses (equaling a response rate of 60.6%), 34 percent
were from Germany, another 34 percent from Spain, and
32 percent from Sweden. Using the Six Sigma methodology in this study, customer satisfaction was treated as the
dependent variable, whereas a culturally varying degree
of uncertainty avoidance, which influences customer service quality satisfaction, was the independent variable.
The study had the following parameters: it used a precise
delivery time of 240 hours to measure the degree of
customers’ service expectation; both data streams were
discrete: the degree of customer satisfaction (from 1 =
“very satisfied” to 5 = “not satisfied”) as well as the degree
of uncertainty avoidance; and it featured three cultures on
three different degrees of uncertainty avoidance (1 =
“high,” 2 = “medium,” and 3 = “low”). The question asked
regarding customer satisfaction was: “In compliance with
the achieved delivery time for this delivery, were you
satisfied with our service?” According to Hofstede (2001,
p. 151), and as shown in Figure 1, Spain ranks fairly high
on uncertainty avoidance, Germany takes a rather medium position, and Sweden has a fairly low uncertainty
avoidance index. Based on these different ranking positions, the study was able to compare the relevant degrees
of uncertainty avoidance in the target cultures. Given the
same performance level, hypothesis H1 predicted that
American Marketing Association / Winter 2005
customers from cultures with a high degree of uncertainty
avoidance, in this case Spain, will be less satisfied then
customers from Sweden when their service expectations
were not met. To test this hypothesis, a Chi-Square-test
was applied. As shown in Figure 3, the test of hypothesis
H1 displayed a high chi-square (χ2 = 141.947) as well as
a p-value below 0.05 (p = 0.000). The high Chi-Square
resulted from combining the degree of uncertainty avoidance with the level of customer satisfaction based on the
outcome of the study. Therefore, the linkage between a
high degree of uncertainty avoidance and a certain satisfaction level was established. While 37.8 percent of the
Spanish customers were satisfied and 62.1 percent were
dissatisfied, there was almost the opposite picture for
German customers (62.1% satisfied versus 14.6% dissatisfied). In Sweden, however, most customers were satisfied (85.5% satisfied versus 0.0% dissatisfied). In comparison, this means that people in Spain were overall less
satisfied than those in Germany – and especially Sweden – given the same service performance level. Thus, it
was found that customer satisfaction is influenced by a
culturally varying degree of uncertainty avoidance, which
strongly supports hypothesis H1.
71.9%; the p-value is always below 0.05) between all
three variables.
When inserting the values for the degree of uncertainty avoidance (“1” for Spain with a high degree, “2” for
Germany with a medium degree, and “3” for Sweden with
a low degree) as well as for delivery time (for example 238
hours versus 245 hours) into the regression equation, it
showed that Spanish customers were less satisfied – and
much earlier – than their German and Swedish counterparts although the same level of service quality (slower
delivery time) was provided. Therefore, the central finding of the study was that the degree of uncertainty avoidance as a cultural variable has significant influence on
customer satisfaction. As stated in hypothesis H2, it was
found that customers from cultures with a high degree of
uncertainty avoidance do not accept a wider tolerance of
quality variation as measured by the length of the time for
delivery. Customers from cultures with a low degree of
uncertainty avoidance, however, do accept a wider tolerance as was hypothesized in hypothesis H3. Consequently, H2 and H3 were also strongly supported.
After that, hypotheses H2 and H3 were tested. As
already stated above, it was assumed that the customer
with a lower degree of uncertainty avoidance would
accept a wider tolerance in service quality, whereby a
fulfilled service would be referred to as a high service
quality. In the study, a fulfilled service was the accomplishment of a specific product delivery in a certain
amount of time. The average delivery time was 240 hours.
Thus, it was defined that a faster or on-time delivery
(below or within 240 hours) would be perceived as high
service quality while a slower delivery (above 240 hours)
would be perceived as low service quality. This relatively
small variation in delivery time referred to the “just-intime” production at the customer side. Taking longer than
240 hours meant loss of production or sales since the
customer was running empty on the chemical product
delivered by the service provider. Thus, and according to
the Six Sigma methodology, a delivery taking longer than
240 hours was considered a defect in the service process.
The study found that customer satisfaction varied across
cultures even if the same variance within the service
quality (slower delivery time) had been provided. The
reason for this finding was the culturally varying degree
of uncertainty avoidance. Respondents from cultures with
a higher degree of uncertainty avoidance were less satisfied with the provided service quality than their counterparts from cultures with a lower degree of uncertainty
avoidance. As illustrated in Figure 4, it was found that
service quality as well as cultural value differences (in this
case the degree of uncertainty avoidance) will influence
customer satisfaction. The regression equation shows a
significant relationship (R2 = 72.1% and R2 adjusted =
American Marketing Association / Winter 2005
Although this study provides a unique insight into the
relationship between service quality, cultural value differences, and customer satisfaction, some limitations have to
be highlighted. First, the study was conducted only in the
chemical industry with a rather small sample of customers. Second, although the observed cultures represented a
high, medium, and low degree of uncertainty avoidance,
members of only three different cultures were interviewed. Thus, conducting more research in other cultures
is recommended. Third, the use of additional cultural
variables, for examples Hall’s (1984) distinction of
chronemics, which relates to the culturally different perception of time as a form of non-verbal communication, or
economic differences in supply and demand situations of
the target cultures, may have changed or influenced the
study’s outcome. Fourth, the application of Hofstede’s
cultural value dimensions to further research has to be
considered carefully. Critics argue that Hofstede’s model
lacks transferability and, therefore, is not representative
for a specific nation or a culture since only data from one
single U.S. company (IBM) were used as samples (Triandis
1982; Yoo and Donthu 1998). On the other hand, this also
ensures some consistency in the research since IBM
employees are somewhat similar in regarding organizational culture, job description, or educational level (Lowe
1996). Overall, the above listed limitations show that
further efforts must be made to understand the behavioral
impact of cultural differences and, if possible, incorporate
other cultural values in future research models for more
complete explanations.
American Marketing Association / Winter 2005
χ2 = Σ
(Observed Count – Expected Count)2
Expected Count
very satisfied
not satisfied
(high degree
of uncertainty
Observed Count
Expected Count
degree of
Observed Count
Expected Count
(low degree
of uncertainty
Observed Count
Expected Count
Observed Count
5.922 + 3.475 + 12.917 + 7.870 + 52.549 +
0.029 + 0.101 + 9.508 + 0.336 + 13.937 +
7.195 + 2.541 + 0.277 + 12.165 + 13.125
American Marketing Association / Winter 2005
For quite a while, cultural issues had been closely
observed in terms of overall life and job satisfaction
(Hofstede 2001). Previous research, however, has not
looked into the relationship between certain levels of
service quality satisfaction and cultural values. While
some researchers have recognized that international service is people-centered and, therefore, culture must somehow play a role (Clark, Rajaratnam, and Smith 1996; De
Ruyter, Wetzels, and Lemmink 1996; Dahringer 1991),
their focus has not been on the impact of cultural values on
customer satisfaction in terms of a delivered service.
Based on the study presented in this paper, it has been
shown that uncertainty avoidance – a very important
cultural value – has a significant influence on global
business and how customers from different cultures perceive a certain service quality level differently. Given the
variance of uncertainty avoidance across cultures, the
study also shows how global service marketing can improve efficiency and reduce customer dissatisfaction by
adopting cultural education and training programs for
service personnel. With regard to this study, the research
implications demand a closer investigation of the cohesion between cultural values and customer satisfaction in
terms of delivery time. For example, not only Hofstede’s
degree of uncertainty avoidance but also that of long-term
orientation could have implications on the service of
delivery time. Furthermore, cultural value items of other
researchers, such as Hall and Hall’s (1990a) degree of
timing, which differentiates between cultures working
parallel on many tasks versus cultures working on one
task at a time, might be taken into account as well. As
suggested by Kotler (2003), one key characteristic in
service marketing is quality variation. The managerial
implications in service quality variations are straightforward and can be achieved by applying the Six Sigma
methodology. The presented study illustrates through a
Adler, Nancy (1997), International Dimensions of Organizational Behavior. Cincinnati, OH: South-Western.
Biolos, Jim (2002), “Six Sigma Meets the Service Economy,” Harvard Management Update, 7 (11), 10.
Clark, Terry, Daniel Rajaratnam, and Timothy Smith
(1996), “Towards a Theory of International Services:
Marketing Intangibles in a World of Nations,” Journal of International Marketing, 4 (2), 9–28.
Dahringer, Lee D. (1991), “Marketing Services Internationally: Barriers and Management Strategies,” Journal of Service Marketing, 5 (3), 5–17.
American Marketing Association / Winter 2005
customer satisfaction measurement tool based on uncertainty avoidance that there are major differences in the
customers’ perceptions of service quality across cultures.
Subsequently, service process improvement should be
applied according to the customers’ requirements in each
country or culture (Fitzsimmons and Fitzsimmons 1994).
The study’s findings clearly show that only a narrow
service quality tolerance delivered in the service process
will be accepted by customers from cultures with a high
degree of uncertainty avoidance. This means that service
managers have to especially plan and aim for a defect-free
process in high uncertainty avoidance countries like Spain
in this case. One could also deduct from the findings,
however, that cultural differences can play a role as a
moderator between lower service performance and customer satisfaction in low uncertainty avoidance countries
like Sweden.
Therefore, and in addition to a stringent service
process improvement, new operational service planning
for increased quality should include intense cultural awareness and intercultural preparation training for all involved
service personnel. More specifically, training with the
main focus on Hofstede’s (1980, 2001) cultural dimension of uncertainty avoidance must be seen as critical part
of the Six Sigma methodology to achieve zero defects in
intercultural service quality. The increased intercultural
competence derived from such training not only gives the
multinational service provider the opportunity to adjust
behavioral patterns accordingly, but can also help to
relieve much of the normal anxieties experienced by
trying to integrate the external customer in a novel but
satisfying cultural setting. It will also help to strive for a
defect-free service process and enable the international
service provider to perform on the highest achievable
service quality level, which will result in an even higher
satisfaction level on the customers’ side.
DeMooij, Marieke (1997), Global Marketing and Advertising: Understanding Cultural Paradoxes. Thousand Oaks, CA: Sage.
De Ruyter, Ko, Martin Wetzels, and Jos Lemmink (1996),
“The Power of Perceived Service Quality in International Marketing Channels,” European Journal of
Marketing, 30 (12), 22–38.
Ehrlich, Betsie H. (2002), Transactional Six Sigma and
Lean Servicing. Boca Raton, FL: St. Lucie Press.
Fitzsimmons, James A. and Mona J. Fitzsimmons (1994),
Service Management for Competitive Advantage.
New York: McGraw-Hill.
Hall, Edward T. (1984), The Dance of Life. Garden City,
NY: Doubleday.
____________ and Mildred Hall (1990a), Hidden Differences: Doing Business with the Japanese. New York:
____________ and Mildred Hall (1990b), Understanding Cultural Differences: Germans, French, and
Americans. Yarmouth, ME: Intercultural Press.
Hofstede, Geert (1980), Culture’s Consequences: International Differences in Work-Related Values. Beverly Hills, CA: Sage.
____________ and Michael Bond (1988), “The Confucius Connection: From Cultural Roots to Economic Growth,” Organizational Dynamics, 16 (4), 4–21.
____________ (1997), Cultures and Organizations: Software of the Mind. New York: McGraw-Hill.
____________ (2001), Culture’s Consequence: Comparing Values, Behavior, Institutions, and Organizations Across Nations. Thousand Oaks, CA: Sage.
Hutchens, Spencer (1989), “What Customers Want: Results of ASQC/Gallup Survey,” Quality Process,
(February), 29–35.
Kotler, Philip (2003), Marketing Management. Englewood Cliffs, NJ: Prentice-Hall.
Lowe, Sid (1996), “Culture’s Consequences for Manage-
ment in Hong Kong,” Asia Pacific Business Review,
2 (1), 120–33.
Pande, Peter S., Robert P. Neuman, and Roland R. Cavangh (2000), The Six Sigma Way: How GE, Motorola, and Other Top Companies Are Honing Their
Performance. New York: McGraw Hill.
Rokeach, Milton (1973), The Nature of Human Values.
New York: The Free Press.
Schwartz, Shalom H. (1999), “Cultural Value Differences: Some Implications for Work,” Applied Psychology International Review, 23.
Stamatis, Dean H. (1996), Total Quality Service. Delray
Beach, FL: St. Lucie Press.
Triandis, Harry C. (1982), “Culture’s Consequences,”
Human Organization, 41 (1), 86–90.
Trompenaars, Alfons and Charles Hampden-Turner
(1998), Riding the Waves of Culture. New York:
Yoo, Boonghee and Naveen Donthu (1998), “Validating
Hofstede’s Five-Dimensional Measure of Culture at
the Individual Level,” Proceedings of the 1998 Summer Marketing Educators’ Conference of the American Marketing Association, Boston, MA.
For further information contact:
Martin C. Reimann
Marketing and International Trade
Freiberg University
Lessingstrasse 45
Freiberg, Germany 09596
Phone: +49.3731.392004
FAX: +49.3731.394006
E-Mail: [email protected]
Ulrich F. Luenemann
Department of Communication Studies
California State University, Sacramento
6000 J Street
Sacramento, CA 95819
Phone: 916.278.6688
FAX: 916.929.1638
E-Mail: [email protected]
American Marketing Association / Winter 2005
Taewon Suh, Texas State University, San Marcos
Hongxin Zhao, Saint Louis University, St. Louis
Seung H. Kim, Saint Louis University, St. Louis
Mark J. Arnold, Saint Louis University, St. Louis
Mueun Bae, Inha University, Republic of Korea
This study focuses on testing the relationships between the constructs of knowledge and creativity of an
international project team and their consequential performance. More specifically, this study attempts to fill in the
research void by (1) establishing a research model at the
project-team level; (2) centering on the crucial factors
concerning knowledge and knowledge-creation for the
success of the international project (i.e., experiential knowledge and creativity); and (3) constructing a structural
model comprising the multiple relationships between the
explaining factors and performance. In the research model, the constructs of experiential knowledge measured at
both the firm- and the team-level make the exogenous
variables in the model. Experiential knowledge as presented is associated with team creativity, project creativity, and project performance. Team creativity, subsequently, influences the other two endogenous variables,
project creativity and project performance. And, project
creativity is associated with project performance.
Hypotheses are tested through structural equation
modeling using Korean MNCs’ sample. Hypothesis 1,
predicting that Team-Level Experiential Knowledge (EKT)
positively affects Team Creativity (TC), was supported
(EKT Î TC: t = 5.62, p < .001). The influence of firmlevel experiential knowledge on creativity was presented
in Hypothesis 2. Firm-Level Experiential Knowledge
(EKF) is not significantly associated with Project Creativity (PC) (EKF Î PC: t = .93, p > .05). As predicted,
TC was highly associated with PC (t = 3.89, p < .001),
which supports Hypothesis 3. Hypothesis 4 and 5 were
also held up. Project Performance (PP) was significantly
influenced by EKF (t = 5.27, p < .001) and TC (t = 2.72,
p < .01). However, as the impact PC on PP failed to
achieve significance (t = -.80, p > .05), Hypothesis 6 was
not supported.
Theoretical contributions of this study are summarized to few points. First, the study first used creativity
construct in the international business setting, investigating the structured relationships with experiential knowledge and performance. Second, related, experiential knowl-
American Marketing Association / Winter 2005
edge as intellectual market-based assets was assessed at
the multilevel. Both team-level and firm-level experiential knowledge were identified as unique, independent
constructs, exerting important roles in the proposed model. Particularly, team-level experiential knowledge was
significant on knowledge implication and transfer, and
firm-level experiential knowledge played importantly on
the outcomes. Third, this study differentiated the two
creativity constructs and their unlike influences in the
modeled relationships. With the dual conceptualization, it
is quite effectively questioning the seemingly unconscious assumption that creativity is a unitary construct.
Fourth, this study has confirmed the fact that project
performance is nested in the organization recognizing the
need for a multi-level study using the broad framework of
the resource-based views.
For better performance of a project, we can find two
important factors according to the current research setting: firm-level experiential knowledge and team creativity. MNCs should accumulate the domain-specific knowledge at the firm level and encourage creative behavior by
nurturing supportive environments and organizational
culture. First, in terms of the experiential knowledge,
knowledge accumulation would better be focused on
developing routines and structures to manage operations
since such routines and processes are not sensitive in
terms of geographic application. Second, summarizing
the literature, the following actions will prove beneficial
for better team creativity. Encourage employees to express their ideas openly; provide help in developing ideas;
provide time for individual efforts; encourage risk taking
and initiative; provide freedom for employees to enable
them to do things differently; provide a non-punitive
environment using a low level of supervision; encourage
team members to interact and participate with other groups
besides their own; maintain an optimal amount of work
pressure; provide realistic work goals; encourage the
delegation of responsibilities; demonstrate confidence in
the workforce in a climate of mutual respect; allow individuals to be part of the decision-making process; encourage management to provide immediate and timely feedback to their team members.
For further information contact:
Taewon Suh
Department of Marketing
McCoy College of Business Administration
Texas State University
601 University Drive
San Marcos, TX 78666
Phone: 512.245.3239
E-Mail: [email protected]
American Marketing Association / Winter 2005
Kelly D. Martin, Washington State University, Pullman
Jean L. Johnson, Washington State University, Pullman
More than ten years ago, Achrol’s (1991) work on the
evolution of the marketing organization envisaged the
dynamic environment in which marketers exist today. He
portends, “The future will be characterized most notably
by unprecedented levels of diversity, knowledge richness, and turbulence” (Achrol 1991, p. 77). Our discipline
has witnessed Achrol’s prophecies come to fruition, as the
marketing environment is characterized by unprecedented dynamism and turbulence. Broad social and cultural
change in the form of technological intensity, globalization and global outsourcing, and regulatory and political
unrest is illustrative of our marketing landscape. Therefore, to extend the predictions of Achrol into the present,
and in the spirit of “understanding diverse and emerging
markets, technologies, and strategies,” our aim is to advance appreciation of change and its role in the marketing
Little is known about the effects of broad social,
cultural, and strategic change on the marketing organization in particular. Further, no commonly accepted framework exists by which to categorize and thus better understand specific types of change in marketing. As a foundation, we draw from existing literature in organizational
theory on change. Most organizational theorists agree that
change may occur either incrementally and peripherally
which causes a small scale impact, or radically by altering
the core functioning of the organization. Because this
first-order or periphery change is the most predominant
type of change to be experienced by organizations (FoxWolfgramm, Boal, and Hunt 1998), it is surprising that
contemporary research has made little attempt to refine
this conceptualization further. One important exception is
the typology introduced by Golembiewski, Billingsley,
and Yeager (1976), which delineates three distinct categories of change. This typology is considered a relevant
lens through which to view marketing specific change,
and has been usefully employed in other marketing research (e.g., Cooper 2000).
Similar to the radical change classifications of core
and second-order change, the typology considers gamma
change. The authors define gamma change as a “quantum
shift in ways of conceptualizing salient dimensions of
reality,” (Golembiewski et al. 1976, p. 138). Alpha change
involves smaller scale change such as that described by
the terms periphery, non-core, or first-order. Change of
American Marketing Association / Winter 2005
the alpha type occurs within a fixed and stable system and
can be accurately measured with reliable dimensions.
Beta change also involves periphery change within a fixed
system, but is complicated by the fact that the dimensions
of measurement or calibration have changed as well. Beta
change may be likened to changes occurring in a stable
system, however fluctuating “rubber yardsticks” provide
unreliable measurement. We extend the discussion of this
type of change by proposing two distinct forms of beta
change. The typology has relevant application to a broad
spectrum of change affecting marketing strategy, and we
highlight some examples for illustration.
In response to the unique impact of change, a few key
organizational phenomena will combine to determine
marketing’s ability to overcome change. Three relevant
factors instrumental to the marketing function’s change
response include opacity, asperity, and intricacy. Research has demonstrated these variables’ impact on an
organization’s ability to manage and ultimately survive
significant change (Hannan, Pólos, and Carroll 2003).
Opacity describes phenomena at the individual level,
specifically concerning marketing managers’ perceptions,
actions, or possible oversights. In particular, we consider
opacity as marketing mangers’ inability to foresee, effectively comprehend, and thus plan accordingly in the face
of change. Asperity describes normative, cultural phenomena affecting large groups or subgroups within the
organization. Within marketing, interrelatedness between
normative structures and organizational culture makes the
marketing function more or less susceptible to failure in
light of change. Finally intricacy describes the overall
organizational design, specifically the degree of interconnectedness between relevant organizational units. Although highly interconnected organizations may promote
positive communication structures and decentralized decision making for example, organizations that are too
highly interconnected may lose flexibility. Achrol (1991)
emphasizes that the impact of change will be intensified in
densely interconnected and interdependent settings. We
apply these organizational phenomena to the marketing
discipline with specific descriptions and examples of each
opacity, asperity, and intricacy.
Our research marries these marketing organizational
phenomena to the various conceptualizations of change.
Just as alpha, beta, and gamma changes are defined so
differently, it follows that their impact on opacity, asperity, and intricacy will fluctuate and vary. In worst-case
situations, these variables combine in such a way to divert
marketing managers’ time and attention away from opportunities and thus potential resource generating activities (Hannan et al. 2003). Thus, missed opportunities
become the key, detrimental outcome of change mismanagement in the marketing organization. Depletion of
resources through missed opportunities can ultimately
drain the life from a marketing organization. Only significant caches of resources accumulated prior to the change
can possibly offset substantial resource depletion occur-
ring as a result of missed opportunities. The ultimate
consequence of missed opportunities and subsequent resource depletion is marketing failure or even death. It
follows that understanding how specific combinations of
opacity, asperity, and intricacy impact the marketing
organization’s ability to capitalize on, rather than neglect,
important resource-generating opportunities is imperative. We consider the consequences for other strategic
marketing outcomes, as well as overall firm performance.
References are available from the authors upon request.
For further information contact:
Kelly D. Martin
Department of Marketing
College of Business and Economics
Washington State University
Pullman, WA 99164–4730
Phone: 509.335.5848
FAX: 509.335.3865
E-Mail: [email protected]
American Marketing Association / Winter 2005
Mona Srivastava, Texas A&M University, College Station
Robert Harmon, Portland State University, Portland
Organizations and customers are engaged in a battle
over information. Too much information being collected
has raised privacy concerns amongst customers whereas
too little information hampers organizations in their efforts to create long-term customer relationships. Although
society may force privacy regulations on marketers through
governmental action or legal initiatives, we believe that a
market-based solution focused on educating organizations on the benefits of finding the right balance between
too much and too little information would alleviate customers’ privacy concerns as well as translate into costsavings for organizations. This paper reviews extant literature on the factors that affect the customer’s willingness
to provide information to organizations and explores
implications for future research to draw managerial attention towards the ethics of collecting customer information. The potential relationships between the factors that
impact the customer’s willingness to provide information
to organizations are detailed below.
Customer’s Privacy Concerns: Sieber (1998, p.
136) has defined privacy as a person’s “degree of control
of the access that others have to them and to information
about them.” Customers are increasingly concerned about
retaining control over their personal data, and want organizations to reward them for giving information and
allowing for its use (Hof 2001). The degree of privacy
concern differs as per the type of information (Nowak and
Phelps 1992, 1995), type of industry, culture, age, and
gender (Petrison and Wang 1995; Milne and Boza 1999;
Sheehan 1999). We posit that privacy concerns directly
impact trust. Since the role of trust in the relational context
has been acknowledged as crucial, it is important to study
the impact of privacy concerns on trust (Regan 2003;
Fonseca and McCarthy 2003; Cavoukian et al. 2002; Miln
and Boza 1999).
Customer’s Trust in an Organization: Some of the
factors that may determine the degree to which customers
are willing to trust an organization include who their
personal information is shared with, how it is used, what
is the cost-benefit of sharing their information, and the
reliability of the organization. Technology has enabled
the collection and use of customer information without
American Marketing Association / Winter 2005
even the customer’s awareness or permission, and has
also helped make the provider, delivery process, and
process controls invisible especially in an online environment, which has had a negative effect on trust. We posit
an inverse relationship between privacy concerns and
trust which may be accentuated or attenuated depending
the organizations’ need-to-know that information. Further trust is the mediating factor in the relationship between privacy concerns and the customer’s motivation for
a relationship with the organization.
Organization’s Need-to-Know: When approached
by an organization for information customers are concerned about how this information will be used, can the
organization can be trusted with this information and most
importantly, whether the organization needs to have this
information for better satisfying its customers’ needs?
P1: The relationship between the customer’s privacy
concerns and the customer’s trust in an organization
is moderated by the organization’s need-to-know
that information.
Customer’s Motivation for a Relationship: Bendapudi and Berry (1997) argue that individuals participate in
relationships either because they want to or because they
have to. Intrinsic desires like dedication drives high motivation for a customer relationship and such relationships
are based on trust as well as dependence. However, when
customers are constrained to maintain a relationship,
perhaps due to lack of alternatives, then dependence,
without trust, leads to a low motivation for a customer
relationship. We believe that customers with a high motivation for a relationship would be more likely to acquiesce
to an organization’s request for information, providing
better quality and/or quantity of information, to achieve
mutual benefits.
P2: The customer’s trust in an organization increases the
motivation of the customer to have a relationship
with an organization.
P3: Customers with a higher motivation for a relationship
with an organization would be more willing to provide better quality and quantity of information to the
organization, than those with a lower motivation.
Customer’s Technology-Readiness: Parasuraman
and Colby (2001, p. 27) define technology-readiness as
“people’s propensity to use, embrace and employ new
technologies for accomplishing goals in home life and at
work.” On one hand it may be argued that people who are
more technology-ready would be better able to interact
with the technologies that organizations use to collect
customer information. However a counter argument may
be that highly technology-ready customers would be more
aware of how their information can be surreptitiously
collected and used, and so would be less willing to provide
information to organizations. Further we believe that the
impact of the customer’s technology-readiness on the
customers’ willingness to provide information occurs
only in a relational context. So despite the customers’
technology-readiness, they may not be willing to provide
information to an organization unless they trust the organization and have a relationship with that organization.
Additionally we argue that the technology-readiness of
customers also impacts the relationship between privacy
concerns and trust. For different levels of technologyreadiness, the relationship between privacy concerns and
trust may be accentuated or attenuated, again depending
on the industry context i.e., the organizations’ need-toknow.
P4a: Customers with high scores on the technology-
readiness index would be more willing to provide
information to an organization.
P4b: Customer with high scores on the technology-readiness index would be less willing to provide information to an organization.
The customer’s motivation for a relationship moderates the relationship between the customers’ technology-readiness and the customer’s willingness to
provide information.
The customer’s technology-readiness moderates
the relationship between customers’ privacy concerns and the customers’ trust in an organization.
The answer to this privacy question is not simple and
opens up new avenues for research geared towards resolving the tug-of-war between organizations and their customers over customer information, and thus making mutually beneficial customer relationships more fact than
fiction. By protecting customer privacy, the contribution
made to society would be tremendous and the onus of
protecting the rights of customers may shift somewhat
from policymakers to organizations, which then would
become the enforcers of privacy protection rather than
perpetuators of what has become a societal dilemma.
References available upon request.
Mona Srivastava
Texas A&M University
College Station, TX 77843
Phone: 979.845.4525
FAX: 979.862.2811
E-Mail: [email protected]
American Marketing Association / Winter 2005
Paul L. Sauer, Canisius College, Buffalo
Paul Chao, Eastern Michigan University, Ann Arbor
The increased availability and use or abuse of office
technology in the workplace is the concern of recent ethics
research (Oz 2001; Stone and Henry 2003). Victor and
Cullen (1987, 1988) develop a classification of nine types
of ethical climate that vary along two dimensions: types of
criteria (or ethical criteria) and level of analysis (or locus
of analysis). Peterson (2002) shows that giving gifts and
favors such as described in items that are contained in our
gifts and entertainment section, is related to both the
personal morality and corporate rules dimensions of the
Victor and Cullen (1988) theoretical framework. Peterson
(2002) also provides evidence that calling in sick and
lying such as described in items that are in our truth and
lies section, are related to Victor and Cullen’s (1988)
ethical climate dimensions of personal morality and corporate rules. The purpose of our research to examine the
extent of temporal shifts in personal beliefs, in perceptions of the ethical climate in the workplace, and in the
potential for conflict caused by changes in incongruence
between self-reported beliefs and climate perceptions
Building on the concept of value congruence between and individual and the office environment (Liedtka
1989), an approach is developed to assess the shifts in the
congruence between individuals’ beliefs and their workplace climate. Subjective perception is the determinant of
whether conflict exists (Moser 1988) and depends on the
ethical congruence between the individual and his or her
workplace. Restraint incongruence occurs when the individual does not perceive a behavior as wrong, but perceives that such behavior is not common in the workplace.
Compelled incongruence occurs when an individual perceives a behavior as wrong, but the perceives the same
behavior as common in the workplace.
Because there is evidence of regional geographic
differences in individuals’ consumption habits, lifestyles
and values (Kahle 1986; Mittal, Kamakura, and Govind
2004), we administer the survey to working professionals
enrolled in part-time management programs operated by
a private university in the northeastern region of the
United States and a public university in the Midwest. The
time frames for administration include pre-2001 and post2001 survey administration. We chose these time frames
to span the time before and after ethical scandals revealed
in late 2000 and in 2001. We did pre-2001 sampling in the
first half of 2000 and post-2001 in spring and fall of 2003.
American Marketing Association / Winter 2005
For each workplace behavior we use two scales, one
to measure a self-report of strength of personal belief as to
how wrong that behavior is and a second to measure selfreport of perceived commonality of that behavior in the
respondent’s workplace. All items use a 7-point bi-polar
scale with end-points anchored by strongly agree and
strongly disagree. This is equivalent to the wording of
items and scales used to assess ethical beliefs and confirm
dimensions of climate (Cullen and Victor 1987; Peterson
2002). We operationalize perceived incongruence by
subtracting each respondent’s perception of ethical climate rating score from that respondent’s ethical belief
rating score for each behavior. A score of zero would
indicate a consonant state. The greater the positive difference, the greater is the potential for compelled incongruence. The greater the negative difference, the greater is the
potential for restraint incongruence.
The overall sample consisted of 14.8 percent toplevel managers or directors, 31.7 percent middle level
managers, and 35.5 percent lower level staff such as
technical employees or assistant managers. Regarding
office technology, independent sample t-tests reveal two
significant shifts in the direction of weaker ethical beliefs
for Midwest respondents and three significant shifts occur
in the direction of stronger ethical beliefs for Northeast
respondents. Midwest respondents indicate that use of
company e-mail for personal reasons is significantly more
common while Northeast respondents perceive use of an
office computer for Internet shopping to be more common
in post-2001. For Northeast respondents perceived compelled incongruence increased for use of company e-mail,
use of the office computer for Internet shopping
Midwest respondents exhibited a shift toward weaker beliefs regarding gifts and entertainment. For gifts and
entertainment, Midwest respondents perceive receiving a
$50 gift from the boss as being significantly more common while Northeast respondents’ perception of receiving $200 football tickets from a supplier is significantly
less common after 2001. Perceived restraint incongruence increased for a $25 gift certificate from a supplier.
For Midwest respondents an increase in perceived restraint incongruence for a $75 raffle prize at a suppliers’
conference occurred. There were no shifts in ethical
beliefs about truth and lies. No significant shifts in climate
occurred with respect to the two items measuring truth and
lies. Overall only four (4) of the 108 tests for pre-2001 and
post-2001 differences for the gifts and entertainment and
truth and lies items were significant which is less than
Results with respect to shifts in beliefs indicate that
there is some change with respect to office technology, but
essentially none with respect to gifts and entertainment or
truth and lies. In spite of the fact that no significant shifts
occur with respect to truth and lies behaviors, these forms
of ethical abuse appear to provide the most fertile ground
for perceived incongruence and conflict. Personal beliefs
are very strong that these two behaviors are wrong, yet the
perception is that they are generally common in the
workplace, especially after 2001. One reason for the lack
of more significance effects may be the fact that individ-
uals simply do not associate the personal behaviors used
in this study with the higher corporate level of illegal and
unethical behavior. Another problem is that the pre-2001
and post-2001 data came from two different sets of
respondents, thus there is no way to know if individuals
changed, only if the aggregate sample changed. This also
may explain that not only were there a large number of
non-significant differences, but also that there were differences that went in the opposite direction of what was
hypothesized. Improvements would include using matching samples over time and confining the study to employees in one or two companies. References available upon
For further information contact:
Paul L. Sauer
Canisius College
2001 Main St.
Buffalo, NY 14208–1098
Phone: 716.888.2631
FAX: 716.888.3215
E-Mail: [email protected]
American Marketing Association / Winter 2005
Elizabeth Hemphill, University of South Australia, Australia
Chris Dubelaar, Monash University, Australia
Steven Goodman, University of South Australia, Australia
Gus Geursen, University of South Australia, Australia
This paper examines the role of disclosure on agency
establishment. Structural Equation Modeling reveals the
need for salespeople to reach a level of “rapport” for a
phase transition prior to any eventual sale. Reaching this
level is a key driver of successful outcomes, rather than
the negotiating skills.
“sales” on behalf of the principal? Industry view has long
held the importance of rapport building to lead to sales.
This paper examines this notion from an academic sense.
The objective of this paper is to explain what a salesperson
should do to maximize their chances of establishing
agency agreements by assembling and empirically testing
a model of agent-principal relationship establishment.
Marketing centres on the process of exchange between buyers and sellers (Kotler, Adam, Brown, and
Armstrong 2001). As sellers enter into relationships with
suppliers they act as agents in pursuit of consumers/
buyers to the extent that “most of the world’s work is done
by agents” (Reuschlein and Gregory 1990). To date
marketing literature has adopted a focus on relationship
maintenance (Weitz and Jap 1995; Dahlstrom and Ingram
2003), essentially skirting around formation of this relationship (Dahlstrom and Ingram 2003) so that how sales
relationships are developed is not well covered, even in
personal sales (Weitz and Jap 1995). This paper examines
what it is about a specific seller that maximizes their
chance of establishing the right to pursue buyers in a way
overlooked until now in the literature. Specifically, the
approach taken in this paper is to understand the role of
rapport building in the establishment of agency relationships.
When a seller (agent) is engaged by a supplier (as
principal) to undertake some action (such as pursuing
buyers) on behalf of that principal, an agency relationship
is established. Thus, formation of the agency relationship
is essential prior to any longer term association or marketing exchange. In forming the agency exchange, an agent
“sells” to a buyer (principal) their offer to serve in a
master-servant relationship governed at least by the “rules
of agency” (established consensually between agent and
principal) and both agency and partnership law (Reuschlein and Gregory 1990). On the surface, establishing the
agency agreement therefore looks like a normal sales
transaction. As a purpose driven process (Sheth and
Parvatuyar 2000), the question remains: What can a sales
person really do to increase their chance of forming an
agency relationship so they can subsequently pursue
American Marketing Association / Winter 2005
The roots of agency relationships come from legal
literature that adopts a perspective of enforceability of all
terms, covenants, and conditions of the agency agreement. In legal literature (Reuschlein and Gregory 1990)
and contract law (e.g., U.S.A. District Court Case: Paul T.
Freund Corp. v. Commonwealth Packaging Co.) elements of agency include: consent, fiduciary agreement,
absence of gain or risk to the agent, and control by the
principal (Reuschlein and Gregory 1990). Legally this
fiduciary consensual relationship between agent and principal exists when “one person manifests an intention that
another shall act in his behalf and the other person consents to represent him” (Reuschlein and Gregory 1990).
Marketing literature has studied the application of agency
theory and the role of information in relationship formation (Dahlstrom and Ingram 2003); the purchaser’s perspective of influences that determine a decision to commit
(Bagozzi and Dholakia 1999; Bagozzi 2000); relationship
maintenance (Sitkin and Roth 1993; Sheth and Parvatuyar
2000; Singh 2000); agency relationship definitions and
outcomes (Bergen, Dutta, and Walker 1992); drivers of
agent behavior (Richins, Black, and Sirmons 1987; Moore,
Smolen, and Conway 1992; Marsh and Zumpano 1998);
and significant behavioral predispositions of a salesperson that influence sales performance (Weitz 1981).
Relationship marketing literature adopts a focus on
the relationship rather than the transaction resulting from
relationship formation (Sheth and Parvatuyar 2000), in
which a process model clearly differentiates formation of
the relationship from other aspects of relationship maintenance. However, even this literature fails to adequately
define the process of formation, slipping quickly into an
emphasis demonstrated by Levitt (1983) in which the real
value of a relationship between customer and seller occurs
after a sale. Such a relationship is dependent on establish242
ing trust and cooperation (Morgan and Hunt 1994) and
avoiding cognitive dissonance (Festinger 1957) in order
for it to continue. If we accept Sheth and Parvatuyar’s
(2000) observation that forming a relationship is more
important than customer acquisition, agency formation
emerges as a critical part yet to be examined empirically
for marketing. This paper is therefore an essential first
step in understanding how a supplier of agent services is
selected from a pool of potential agents. This paper firstly
adopts the agent’s perspective. Due to imperfections in
self-assessment noted by authors such as (Jaramillo, Carrillat, and Locander 2003), we secondly offer results from
a pilot study of principals as a basis for future research to
further compare the agent’s perspective with that of the
Theoretical Model
Based on a number of propositions framed by Weitz
and Jap (1995) and Jacobs et al. (2000) we examine how
the salesperson influences formation of the agency relationship. Weitz and Jap (1995) argue that relationships are
built around trust, communication and negotiation in what
is described by other authors as the first stage of relationship building, known also as pre-sale distinct from sale
(Sheth and Parvatuyar 2000, p. 332).
Communication: Models of customer-salesperson
interaction traditionally include an element of information exchange. For example: Information exchange drives
a negotiation process (Olekalns 2002), the final stage of
which is a level of “give and take” that result in a mutually
agreeable outcome; And a noted distinction between the
contributions of exchange specific self-disclosure and
social self-disclosure in sales exchanges between life
insurance sales agents and potential customers/investors
(Jacobs, Hyman, and McQuitty 2000). A seller’s commitment to a sale therefore depends on information disclosure between the principal and seller (as agent) on both
transactional and personal levels (Jacobs et al. 2000).
Negotiation: Weitz and Jap (1995) further find that
the sales presentation comes before, and leads to, negotiation. A clear link from salesperson’s behavior to a
principal’s decision to commit exists in personal sales
literature based on appraisal of interactions with the sales
person (Lee and Dubinsky 2003), despite the specific
decision influencing criteria of the principal being unavailable to the salesperson as a matter of competition
(Spekman 1988). Lee and Dubinsky (2003) establish that
courteousness, expertise, and friendliness are assessed to
determine satisfaction levels which then influence a purchase decision. Throughout this process, known as “priming” (Whittler 1994), purchase decisions can be influenced by at least the salesman depending on their capacity
to establish a sense of trust (Morgan and Hunt 1994), by
achieving a level of acceptance by the principal. This
research paper tests the conceptual model below (Figure 1) using adaptations of propositions offered by Weitz
and Jap (1995) and Jacobs et al. (2000).
This study empirically tests propositions detailed in
Table 1 above that have only previously been tested in
other environments by Weitz and Jap (1995) and Jacobs
et al. (2000). These are based firmly on avoiding cognitive
dissonance (Festinger 1957; Spekman 1988; Hunt 1991)
Conceptual Model
P2, P5
P1, P3
Empirical examination of the propositions presented in Table 1 tests this graphical model.
American Marketing Association / Winter 2005
Propositions Tested In This Research
Research Propositions
Instrument Item
Interest is communicated and partner
worthiness assessed (Weitz and Jap 1995)
The agent came across as
being competent
Norms are used to provide a context for
messages (Weitz and Jap 1995)
Information the agent acquired
included which other agents
were being considered
Communication increases over time spent
on the relationship (Weitz and Jap 1995)
The agent got to know the
Salespersons must be skilled active listeners
that have the ability to communicate (Weitz
and Jap 1995)
The agent got to know the
Exchange specific self-disclosure influences
the outcome of a sales attempt (Jacobs et al.
The agent got the principal to
share good things about the
Social self-disclosure influences the
outcome of a sales attempt(Jacobs et al.
The agent got the principal to
share why they were selling and
if they had already purchased
Negotiation of terms leads to a sale (Weitz
and Jap 1995)
The amount of changes to the
agent’s proposed service
offering (sales commission, list
and reserve price, advertisements)
and aim to determine which agent characteristics influence whether an agent-principal relationship was formed
between agent and principal.
In this paper real estate agents, or realtors, are used as
sellers to examine agent-principal relationship establishment because they engage in commonly occurring agency
experiences with property sales (and purchases) that require establishment of an agent-principal relationship for
technical or economic reasons. They operate in agentprincipal relationships in which people generally have
multi-agent experiences as they sell houses and property
at different points in their lives. In general, people who
have engaged in such agent-principal relationships as
either agent and/or as principal (property vendors that
wish to sell their properties with the assistance of an agent)
readily share information about their experience. The
dependent variable for this research is a relationship
establishment attempt. This can be either successful or
unsuccessful. If successful, a legally binding agent-prin-
American Marketing Association / Winter 2005
cipal relationship is established (a sale of agent services
occurs). If unsuccessful, no legally binding agreement is
established between that agent and that principal (no sale
occurs). Whether an agency agreement is established with
another agent, or does nothing at all is not measured.
Construct Operationalisation
Based on Churchill’s (1979) paradigm, discussions
provided a breadth and depth of qualitative data required
for empirical instrument development to test Figure 1.
For this research we define negotiation as: the bargaining, trading-off, “haggling,” that results in change to
the terms of the agent-principal agreement. This excludes
the design, plan, and assembling of the agent proposal,
anything prior to the completion of initial principal evaluation of the agent proposal, anything prior to both parties
establishing their goals, measurement of the principal’s
previous experiences, and anything to do directly with
potential buyers. We did this because the literature clearly
indicates this as an important stage of negotiation (Olekalns 2002). We measure negotiation from the perspective of its contribution to agent-principal relationship
establishment by examining the amount of change to a
proposed agency agreement.
Information disclosure underpins negotiation (Olekalns 2002). We define this as the acquisition of exchange
information (about the property) and social information
(about the property owner that is the potential purchaser
of the agent services). Exchange disclosure is important in
this sales process [Agent Focus Group]. “If a house has
white ants we need to know it is fixed . . . and if buyers ask
we tell them to get an inspection done . . . we tread
carefully” [Agent W]. Due to legal requirements of full
disclosure in the final sale to a property purchaser, we
suggest that agents filter information by probing for
resolutions of potentially problematic information but
otherwise do not probe for information, thus the amount
and nature of exchange information is important.
Social information is important in the process of
establishing an agent-principal relationship. Real estate
agents continually ask questions like “What were you
thinking of? Is that all right with you? Do you agree with
that?” [Agent Z] and “We try to find out who else the
vendor is considering and shy they are selling” [Agent
W]. Agents in fact selectively appropriate social information in relationship establishment to simplify agent-principal relationship maintenance and increase their chance
of being accepted by the principal. Our definition excludes how the agent uses the information, how the agent
acquires the information, whether the information was
requested, offered directly, observed indirectly, or acquired by other means, and the quantity of information
about the vendor. We did this because “In any negotiation,
information is power” (Latz 2001). Measurement of information disclosure is focussed on the opportunity for
selective acquisition of property and property seller specific information. As agents’ selectively appropriate information that will improve their chances of selling their
services to the principal, measurement of information is
focussed on the selectivity of exchange specific information and more personal social information.
Data Collection and Analysis Method
A self-completion mail questionnaire was developed
and sent to 1600 real estate sales agents (as sellers) that
had experienced both successful and unsuccessful attempts to establish supply relationships with property
vendors. These were randomly selected from the Real
Estate Institute of Victoria’s member database but followup data collection involved convenience sampling from
the original database. Respondents were screened to ensure they were representative of agents in general providAmerican Marketing Association / Winter 2005
ing in total 274 usable sale attempts. Each response
included information on two sale attempts – one successful and one unsuccessful.
Differences between the two groups were examined
closely to ensure that data were not distorted by selfvalidity bias. Based on McQuitty (2003), sufficient level
of power was achieved to enable the model to verified
using SEM. Missing answers were imputed using expectation maximisation (Figueredo, McKnight, McKnight,
and Sidani 2000; Flury and Zoppe 2000) to best preserve
the integrity of this data set. The final response rate was
around eight percent. Although this could be considered
a major limitation to this research, there is only a six
percent (.060412) chance that the sample does not represent the population through calculation of the margin of
error (Kline 1998).
Verification of sample representativeness involved
examining respondents’ personal previous month’s median residential property price sold and comparing this to
published property prices for their city of operations.
From this, two different types of agent sales performance
estimations were evident. Firstly, a large number of agents
estimated their sales performance close to published prices. These agents, on average, underestimated their sales
performance compared to published sales figures by only
approximately 12 percent. This is a relatively small discrepancy, suggesting that respondents were representative of their locations. In these cities, property prices were
relatively stable at the time of this research.
Secondly, a number of agents underestimated their
sales performance compared with published property
prices by up to 50 percent. Notably these agents operated
in cities that experienced large house price increases over
the past 18 months revealing a telescoping effect resulting
from agents being asked to consider back over time whilst
we take a single snapshot. This means that should this
research be replicated at a later date, with more stable
property prices, it would be reasonable to expect fewer
discrepancies between estimations and published prices.
Responding agents were found to be reasonably representative of the regions in which they operate.
Anderson and Gerbing’s (1988) approach to Structural Equation Modeling (SEM) was used for data analysis to test the theoretical model (Figure 1) so that indirect
effects of model constructs could be estimated and interactions between constructs could be examined. Direct
influences of model constructs on the dependent variable
were examined with Logistic Regression (McFadden
1976). Variance and correlations were examined to affirm
measure reliability, validity, and purity based on Campbell and Fiske (1959), Churchill (1979), Cronbach (1951),
Finn and Kayande (1997), Menezes and Elbert (1979) and
Peter (1981) prior to structural model evaluation in order
to justify implementation of a model evaluation technique
(Bagozzi 1982; Bhargava, Dubelaar, and Ramaswami
1994; Churchill 1979; Finn and Kayande 1997; Menezes
and Elbert 1979; Nunnally and Bernstein 1994; Peter
Examination of Bollen and Stine p-values reveals
that similar results could be expected in 39.9 percent of
cases (95.6% for sales compared to 16.3% for no-sales).
Such poor model indicators for the unsuccessful relationship establishment attempt (no-sale model) suggest that it
is not just the interaction with the salesperson that accounts for no-sale being made. Table 3 shows differences
between a sale and no sale estimates. Incorporating the
work of Pearl (2000) links tested with SEM are significant
when Critical Ratio estimates are greater than 1.96 (Arbuckle and Wothke 1999, p. 74); or Differences between
relationship establishment attempt outcomes for a single
degree of freedom are significant (if Discrepancy estimates are less than 3.84146 then estimates are considered
significantly different from each other at a significance
level of 0.05).
Diagrammatic representation of the resulting structural equation model is shown in Figure 2 below with
Table 2 detailing results of model statistics.
Structural equation model indicators in the Table
show the structural model estimated in the Figure below
delivers a reasonable fit within the measurement model
(with Fit indicators close to 1), confirming a significant
difference between successful (a sale) and unsuccessful
(no sale) relationship attempt outcomes. The likelihood
that test statistics are correct exists because there is nearly
an 80 percent chance that acceptable structural models
were rejected, meaning that if not rejected the statistics are
more likely understated than overstated to a level of 0.8
for the full data set (McQuitty 2003, p. 7).
This Table shows that people skills are significantly
related to exchange (CR > 1.96) and social disclosure
(CR > 1.96) and that the importance of social disclosure
differs significantly between successful and unsuccessful
relationship establishment attempts (Significant difference between estimate of 0.40 and -0.47). Logistic regres-
Structural Model Estimates
eq 14 a
eq 14 d
eq 11 k
q 11 e
q 14 d
q 14 a
eq 11 e
q 11 k
q 11 d
eq 11 d
e exch
1.15 1.00
1.03 1.00
q 11 b
q 11 a
eq 11 b
eq 11 a
American Marketing Association / Winter 2005
q 13 a
eq 13 a
q 13 c
q 13 b
eq 13 b
eq 13 c
Model Statistics
SE of
No sale
Differences Between a Sale and No-Sale (SEM Results)
A Sale (Successful
Establishment Attempt)
No Sale (Unsuccessful
Establishment Attempt)
People Skills to
Exchange Disclosure
People Skills to
Social Disclosure
Social Disclosure to
Exchange Disclosure to
sion results in the table below show significant relationships between modelled constructs and the outcome of an
agent-principal relationship establishment attempt when
Sig. < 0.05.
These results show that getting to know the customer
(sig. = .009 in Table 4) is the best way to (a) achieve social
disclosure and (b) establish the relationship that determines the likelihood that a marketing exchange will
occur; Knowing the competition is important aspect for a
sale (sig. = .037 in Table 4); That negotiation and exchange specific disclosure will not assist in establishing a
sales exchange without the support of the people skills
American Marketing Association / Winter 2005
On a theoretical level, negotiation should depend on
information disclosure for setting up terms of a business
relationship. Personal relationships set up the clients’
satisfaction prior to any sharing of information that may
lead to commencement of negotiations, or eventuate in a
sale. We propose therefore that this can be viewed as two
distinct phases of the sales process. The people skills
construct can be viewed as what is commonly discussed in
industry sales literature and training courses as “rapport
building,” or “empathy selling” (Golis 1991). These results give empirical support to the notion that the selling
process can be observed as a “phase transition” where
people skills (the ability to build rapport) are most important and come first. Without establishing rapport, and
completing the phase transition to commitment to purchase, a sale (and an agency agreement) is not likely to be
The notion that self-evaluation in the area of sales and
agency relationships is unreliable is supported in our
results on the basis that people skills are clearly attributable to success but not necessarily attributed to failure to
achieve a sale. Model differences suggest a distinct inability to acknowledge fault when the sale relationship is not
established. Given the nature of sales and personal selling,
this difference is to be intuitively expected and demon-
strates the need for research in which data are gathered
from the client side of the agency exchange. Admission of
personal inadequacies such as this would be unlikely, as
individual agents seek to preserve their self-esteem. Consequently, steps were taken to overcome such a bias in this
research by conducting an exploratory pilot study of 200
This Table shows that the most important “sale”
influences mirror closely the aspects that significantly
differ between the model for a “sale” and “no sale.” That
is, personal relationships between agent and vendor are
Logistic Regressions Results
Instrument Item
Construct Measured
by Instrument Item
Why the vendor was selling
Which other agents they were considering
If the vendors had already purchased
Good things about the property
All there was to know about the property
Change in sales commission
Change in property list and reserve price
Changes in the advertising campaign
Agent persuasively demonstrating competence
Agent getting to know the vendor
Social Disclosure
Social Disclosure
Social Disclosure
Exchange Disclosure
Exchange Disclosure
People Skills
People Skills
Purchaser Pilot Study Results
Influence in Purchase commitment
% Responses
Relationship(acquaintance) with agent
Market Share
Verbal/written submission
Corporate identity
Media presence
Auction/For Sale boards
Total responses
American Marketing Association / Winter 2005
established as the agent gets to know the vendor and
perceives a position of competitive advantage in the
agent’s ability to perform contracted services after the
purchase. These results further support our view that the
personal relationship with the agent is most influential in
moving the purchaser through the initial phase of their
purchase commitment and accept the salesperson and
their competence to perform tasks of the agency agreement.
We argue that it is not just trust and satisfaction that lead
to a sale but the degree to which a salesperson can “Get to
know” the customer, thus entering their “space.” Direct
interaction and information disclosure between agent and
purchaser results in a level of commitment to a purchase
decision prior to the actual sale transaction. However,
only if rapport is right then transition can be direct to
relationship establishment without incurring further risk
to the outcome via negotiation.
This paper strongly argues therefore that agency
establishment (as a normal sales exchange) is a multiphase process. In this process the first phase requires
establishment of trust between the seller and purchaser
(Morgan and Hunt 1994) and establishment of a personal
relationship. This relationship must in fact include a level
of satisfaction (Weitz 1981) and avoidance of cognitive
dissonance (Festinger 1957). Subsequent to moving
through this first phase other elements of buyer behavior
models may account for the eventual outcome of a sales
attempt but in the first instance of phase transition, establishing rapport with a potential customer is critical.
This paper examines the point of a sales relationship
establishment from the perspective of agent-principal
relationship establishment. We do this because (i) an
agent must establish these relationships with a principal
prior to any further money making transactions on behalf
of that principal (ii) as part of a sales transaction marketing
is dependent on establishment of these relationships and
(iii) more and more, business structures can be seen as
agency structures as often business is conducted through
networks of independent agents. Establishment of the
agency agreement is clearly similar to normal sales transactions in which the agent’s role of establishing rapport
with the principal is critical as purchasers are led to a sales
commitment by their personal rapport with a salesperson.
The key principle this research addresses is the way
in which a salesperson (agent) contributes to a position of
competitive edge in the mind of the purchaser (principal)
in what is essentially a normal sales process (establishment of the agent-principal relationship). Sales literature
strongly suggests that a movement towards commitment
to a sale is based on the customers’ perception of trust and
satisfaction with the sales person (Morgan and Hunt 1994;
Weitz and Jap 1995; Jacobs et al. 2000; Olekalns 2002).
This paper confirms that agency establishment is a
normal sales exchange on the basis that (i) legal requirements prescribe steps prior to agent action on behalf on the
principal (ii) vendor (principal) selection of an agent is a
competitive process and (iii) the transaction is basically a
services marketing transaction in which personal skills of
the agent are the driving force. This paper also establishes
that the process of negotiation is incorrectly positioned in
existing literature because it: (i) cannot occur until a
personal relationship has been established; (ii) does not
necessarily lead to a final sales transaction; and (iii) does
not necessarily rely on information disclosure from the
principal (vendor).
Revised Model
P2, P5
P1, P3
American Marketing Association / Winter 2005
Significant implications for practitioners (general
sales people, agents, and agencies) and theory exist from
these findings because:
“Selling is a process of influence . . . the ability to
present information, without being abrasive or apologetic, is a learnable and important skill . . . [involving a] . . . willingness to be shaped, influenced, and
impacted upon by the customer” (Shaw 1981).
The important practical implication from our research is in the area of sales training known currently to be
a process of (i) developing a taxonomy of behaviors (ii)
practicing skills and (iii) providing support and reinforcement (Shaw 1981). This research takes the first step in
defining a taxonomy of behavior that leads to sales relationship establishment.
By modeling and empirically testing behavior that
influences the likelihood that a sale is made, the outcome
of a sales attempt is found not to be determined, as
described by Bergen et al. (1992), by processes that follow
initial contact between an agent and a principal in which
terms of an agency agreement are negotiated. It is instead
determined at the point at which an initial context, or
reference point, is established. This point is translated by
the principal into their measure, or perception, of equity
and fairness that actually determines the outcome of the
agent-principal relationship establishment attempt rather
than any negotiation.
For the literature, this paper contributes the finding
that information disclosure is seen as an influence of the
likelihood that a sale will result, rather than negotiation
although social information is seen as an influence on
negotiation. Quigg and Wisner’s (1998) work needs to be
reworked to reflect the contributions of Levitt’s (1986)
consumer reference point thereby acknowledging attitudinal psychology; Braun’s (1999) work needs to be modified to reflect the substantial benefit to agent-principal
relationship establishment from identification of Kahneman, Knetsch, and Thaler’s (1986) framing effects (identification of the competition); and Jacoby, Chestnut, and
Fisher (1978) and Marsh and Zumpano’s (1998) work
needs to be modified because these authors incorrectly
detail the role of information in agent-principal relationship establishment.
Although we do not specifically focus on communication, interpersonal communication between agent and
client (in generally getting along and getting to know each
other) is shown to be paramount to a sale. Bagozzi (2000)
clearly acknowledges the role of emotions in consumer
purchase decisions and the level of rationality behind
agents’ efforts to avert cognitive dissonance on the part of
the purchaser (Bagozzi and Dholakia 1999; Bagozzi,
American Marketing Association / Winter 2005
Gopinath, and Nyer 1999; Bagozzi 2000). Adding to
Bagozzi and Dholakia’s (1999) definition of the consumer’s pursuit of specific goals, this paper contributes to
sales presentation literature by empirically demonstrating
that, as the interface with the client, the sales presentation
is the highest level predictor variable. People skills are the
agent’s mechanism (as a salesperson) with which to enter
a client’s space so these skills represent the highest order
of the variables in relationship establishment.
Negotiation emerges as a demand side benefit (post
relationship establishment, post-“sale”) for pursuit of a
final transaction and is not needed for relationship establishment. Currently, agent-principal relationships (sales)
begin in the case of real estate by presenting a proposed
marketing campaign to a client in the context of selective
successes and failures that is often tweaked and altered.
Our research demonstrates that negotiation is not even
desirable when tendering a relationship proposal to a
potential client. As a result agency owners should hire
agents that have excellent people skills and can get along
with a potential client because of the importance of these
to a relationship establishment attempt outcome directly;
have adequate processes in place so that agents are not put
in the position of having to negotiate terms of an agentprincipal relationship because this will not assist in relationship establishment; and ensure adequate training processes are available for personal skill acquisition, practice, and support.
Agents need to be most concerned about gaining
acceptance by a client at the initial point of contact so that
the client will disclose sufficient information to the agent
so that the agent can consolidate the initial relationship
into a sales transaction. As a result, the client is less likely
to experience cognitive dissonance that will result in an
unsuccessful relationship establishment attempt.
A fresh view of the selling process as one of phase
transitions offers great potential. At a practitioner level,
the notion of “rapport” reaching as a prerequisite for a
phase transition to negotiation and then onto a sale offers
empirical evidence not provided in this way before whilst
not being a startling new insight for the sales profession.
Thus this research provides new support for existing
training methods. Gathering further data from the client
side of the agency transaction and replication in other
industries offers much scope for developing the model
into accountable marketing knowledge. The scope also
exists for work across cultures and geographic locations
to even further refine and confirm the model. Interesting
insights may result from the application of the model in a
cross-cultural setting. Importantly, this research is held
out for comment, and contribution to the divide between
academic knowledge and practitioner experience and use
in the area of personal selling. In the theme of this
conference, it is presented as a piece of marketing research
that can assist in the production of research outcomes that
are of assistance to both industry and academia.
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American Marketing Association / Winter 2005
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For further information contact:
Liz Hemphill
School of Marketing
University of South Australia
27 North Terrace
Adelaide, South Australia 5000
Phone: +61.8.8302.0623
FAX: +61.4.1788.2176
E-Mail: [email protected]
American Marketing Association / Winter 2005
Somjit Barat, University of North Texas, Denton
Coupons are distributed with the intent of promoting
the product through an increase in sales or encouraging
new trials. Even though this widely popular medium of
promotion has been extensively researched (Ailawadi
et al. 2001; Bawa et al. 1997; Garretson et al. 1999;
Heilman et al. 2002; Lichtenstein 1990; Mittal 1994;
Raghubir 1998; Reibstein 1982; Ward 1978; Taylor 2001;
Nevo 2002) in social science, this paper contributes to the
body of knowledge by addressing at least one major
shortcoming, that coupons have some inherent disadvantages. These latent weaknesses might eventually act as a
detriment to the “promoted” product. Such a possibility
arises from the disposition of customers towards coupons
in general and the promoted product in particular.
Data was collected from a sample consisting of both
students and non-students at a large university in the
southwestern part of United States. While students are a
major segment of coupon-users, the analysis was also
restricted to convenience products because this category
is one of those where coupons are redeemed the most. The
author attempts to buttress his point by investigating how
customers evaluate a coupon when they see one. For
example, results showed that such an evaluation is based
on how strongly customers feel towards a coupon per se
as well as on how they view the savings that results from
redeeming a coupon. Similarly, on encountering a coupon, customers feel suspicious as well as confused about
the real price of the product. Finally, seeing a coupon also
influences the perception of the promoted product by the
customer. This perception can be operationalized through
the income effect and substitution effect, both of which
are concepts well grounded in economic theory.
The author also categorizes coupons into two major
classes: buy-one-get-one-free and half-off coupons, the
reason being, they influence the customer’s coupon-value
perception and savings-perception in different ways. The
conceptual framework, therefore, may be laid out as
follows: The perceived value of a coupon affects the
direction and magnitude of income and substitution effects and are moderated by the type and face value of
coupons, which, in turn, affects the price-perception of
the product. Based on this framework, eight hypotheses
are suggested out of which, five are strongly and two are
partially supported, while one is not supported.
As far as implications are concerned, a good knowledge of how coupons might adversely affect sales prospects is critical for managers, manufacturers, and retailers
alike. Even within a single product category, one should
note what kind of coupon is more appropriate for what
kind of products. It also helps to address what face-value
to put on a coupon so that it encourages the customer to
redeem the coupon as well as increases the bottom line of
the coupon issuer. Results from this study can help the
customer use coupons in a more efficient way. Moreover,
given that the sample consists of both students and nonstudents, the results can be generalized with reasonable
level of comfort.
On the other hand, future studies can investigate how
customers actually utilize the “extra savings” they enjoy
by redeeming coupons i.e., whether they just hold on to
their savings, buy more of the same or of some other
products. Information on redeeming specific type of coupons (e.g., half-off vs. buy-one-get-one-free) can be used
to target specific customers, thereby making the whole
process more efficient.
For further information contact:
Somjit Barat
University of North Texas
P.O. Box 311396
Denton, TX 76203–1396
Phone: 940.565.3121
FAX: 940.565.3837
E-Mail: [email protected]
American Marketing Association / Winter 2005
Shirley Y. Cheng, The Chinese University of Hong Kong, Hong Kong
Jessica Y. Kwong, The Chinese University of Hong Kong, Hong Kong
In the past few years, loyalty program (LP) started
drawing attention from researchers. However, extant literature focused mainly on consumer behavior before
joining an LP (e.g., joining decisions and program evaluations); how consumers perceive and response to LPs
during the program is left largely unexplored. This paper
draws on mental accounting theory to explain how LP
joining affects a consumer purchase decisions after joining an LP. This focus on purchase decisions subsequent to
program joining is crucial because getting the reward
requires a consumer to make a series of purchase with the
LP-offering company. This extended effort-investing process (Kivetz and Simonson 2003) implies that consumers
can decide at any time whether to keep pursuing or not,
and the effectiveness an LP depends largely on whether it
can influence participants subsequent purchase decisions
in favor of the LP-offering company.
Thus, we propose that compared to someone who
does not join the LP, an LP participant is expected to
evaluate a repurchase decision with the LP-offering company more favorably due to the prospect of reward. On the
other hand, an LP participant may evaluate a similar
transaction with a non-LP-offering company less favorably, because the loss in prospect of reward would result
in a deduction of acquisition utility. Due to risk aversion,
we predict that losing prospect of reward has greater
impact than gaining the same prospect of reward on
In view of the effects of prospect of reward on
acquisition utility, this paper proposes that evaluation of
acquisition utility can be influenced by an LP structural
features, which either: (1) make the value of the prospect
definite; or (2) segregate the prospect of reward from
other components (e.g., price and value of products) of the
How Does an LP Work?
Making the Prospect of Reward Definite
According to Thaler (1985) mental accounting theory, consumers evaluate the acquisition utility of transactions, combining what is obtained relative to its price and
valuating the utility, in accordance to Kahneman and
Tversky (1979) prospect theory. Prospect theory holds
that utilities are evaluated as gains and losses relative to
some reference point, and while both gain and loss functions are concave (i.e., displaying diminishing sensitivity), loss function is steeper (i.e., loss aversion). Based on
these features of value function, Thaler (1985) formulated
principles of hedonic framing, which specifies the way of
evaluating joint outcomes to maximize resulting utility.
To many participants of LPs, the program rewards are
uncertain and delayed because they are contingent to a
series of subsequent purchases. In response to uncertainty
and delay outcomes, people discount their values and
impacts on present decisions (Frederick, Loewenstein,
and O’Donoghue 2003; Rachlin, Raineri, and Cross 1991