Download Marketing communication strategies in support of product launch: An

Industrial Marketing Management 36 (2007) 1046 – 1056
Marketing communication strategies in support of product launch:
An empirical study of Taiwanese high-tech firms
Chien-Wei Chen a,⁎, Chung-Chi Shen b , Wan-Yu Chiu c
a
National Chengchi University, College of Commerce, Department of International Business, No. 64, Sec. 2, ZhiNan Rd., Taipei 11605, Taiwan
b
Providence University, College of Management, Department of International Business, No. 200, Chung-Chi Rd., Taichung 43301, Taiwan
c
Bristol-Meyers Squibb Taiwan, Taiwan
Received 15 November 2004; received in revised form 24 August 2005; accepted 22 August 2006
Available online 2 October 2006
Abstract
To understand the mechanisms that underlie marketing communication support for product launches, the authors conduct an empirical study
and propose a conceptual framework that depicts the relationships between informational/transformational or elaborational/relational messages
and their effectiveness. The hypothesized message–communication and message–sales effect links are moderated by three communication process
characteristics: message clarity, message uniformity, and integration of the communication. On the basis of data collected from an industrial survey
of 101 high-tech firms in Taiwan, the authors find that informational and relational messages offer greater support for new products. Whereas
message clarity and integration of communication expectedly demonstrate positive moderating effects on message–performance links, message
uniformity only affects messages–sales effect relationships. The authors explore research insights and discuss implications for both academia and
practitioners from the perspectives of new product management and integrated marketing communications.
© 2006 Elsevier Inc. All rights reserved.
Keywords: Communication strategy; New product launch; Integrated marketing communication
1. Introduction
Product launch is perhaps the most expensive, risky, and
poorly managed phase of new product development process, in
the sense that firms must commit enormous time, financial, and
managerial resources, and the average failure rate is as high as
40% for consumer and industrial new products (Hultink, Hart,
Robben, & Griffin, 2000) and more than 60% in high-tech
industries (Goldenberg, Lehmann, & Mazursky, 2001). Despite
the risks inherent in commercialization, launch efforts often are
decisive in securing new product success (Crawford & Di
Benedetto, 2003; Guiltinan, 1999). In this challenging context,
a firm that is proficient in communicating the positioning of its
new products and leveraging its affiliated brands may maximize
⁎ Corresponding author. Tel.: +886 2 29393091x81135; fax: +886 2
29379071.
E-mail addresses: [email protected] (C.-W. Chen),
[email protected] (C.-C. Shen).
0019-8501/$ - see front matter © 2006 Elsevier Inc. All rights reserved.
doi:10.1016/j.indmarman.2006.08.002
its chances of achieving profitable product acceptance in the
target market (Guiltinan, 1999).
Launch planning involves both strategic and tactical
decisions (Biggadike, 1979). Whereas the former entails details
such as product innovation, market targeting, and market
leadership, the latter pertains to choosing marketing mix elements, of which marketing communications represents the central concern (Guiltinan, 1999). In the launch process, marketing
communications refer to all of the information and attitude
efforts expended to influence product adoption, including
product attribute expressions and strong persuasion attempts
(Crawford & Di Benedetto, 2003). Existing literature clearly
supports the positive relationship between effective marketing
communications and new product success (e.g., Cooper &
Kleinschmidt, 1994; Song & Parry, 1994).
However, high-tech industries are unique in the great
uncertainties that derive from their market, technology, and
competitive factors (Mohr, 2001; Moriarty & Kosnik, 1989). In
such industries, market offerings generally are founded on
significant amounts of scientific and technical know-how (John,
C.-W. Chen et al. / Industrial Marketing Management 36 (2007) 1046–1056
Weiss, & Dutta, 1999). These unique industry characteristics
result in different information processing patterns among buyers
(Capon & Glazer, 1987; Glazer, 1991), which require adaptive
marketing strategies and tools (Rangan & Bartus, 1995;
Shanklin & Ryans, 1987). In response to such environmental
complexity and turbulence, high-tech marketers may use marketing communications to build strong brand names (Morris,
1996) and assuage customers' fear and doubt involved in
product adoption (Lee & O'Connor, 2003).
From both theoretical and practical perspectives, it is worth
studying what makes marketing communications that introduce
new products effective, especially in high-tech industries. For
example, Taiwanese high-tech firms previously based their
business models on original equipment manufacturing (OEM),
but OEM firms have suffered drastic profitability losses as a
result of strong competition from companies located in other
countries with lower labor costs. To escape this quandary,
several firms, including Acer, Asus, and BenQ, began to recognize the importance of their own brands and switched their
investments and endeavors toward high value-added activities
such as research and development, product innovation, and
brand building. Those firms that switched their business focus
thus needed to engage in different marketing communications
than they had used in the past. That is, unlike marketers of
consumer products, which mainly rely on mass media communications (Hultink et al., 2000), firms specializing OEM
businesses behave more like industrial product manufacturers,
which usually communicate product-related information to
buyers through personal selling or trade shows. For Taiwanese
high-tech firms, the marketing communication decision has
become far more complicated, because they essentially function
in both business and consumer markets. Therefore, an investigation of the marketing communications used to launch
products in Taiwan's high-tech industries may offer interesting
and significant insights into various launch-supporting communication behaviors across product categories and markets.
This research attempts to find a normative model to guide
high-tech firms to effective marketing communications in support of their product launches. Specifically, we aim to achieve
two related objectives: (1) determining which message content
is most effective in introducing new high-tech products and (2)
understanding how to manage the communication process to
achieve greater effectiveness. These distinct objectives are both
legitimate, in that what to say and how to say it are equally
important in any type of communications.
We also propose a conceptual framework, illustrated in
Fig. 1, to depict the relationships among three components
related to marketing communications for product launch: message content, communication process characteristics, and effectiveness. Message content consists of two dimensions:
informational/transformational (Aaker & Norris, 1982; Aaker
& Stayman, 1992; MacInnis & Stayman, 1993; Puto & Wells,
1984) and elaborational/relational (Bridges, Keller, & Sood,
2000). Our framework proposes that various types of message
content impose different effects on the performance of launched
products, which we capture with communication and sales
effects. The message content–effectiveness links furthermore
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Fig. 1. Conceptual framework of marketing communications for product launch.
are moderated by three characteristics of the marketing communication process: message clarity, message uniformity, and integration of communication. Our theoretical foundation for this
model stems from exchange theory's model of interpersonal
communications (Gatignon & Robertson, 1986) and integrated
marketing communications (IMC), which advocates the alignment of communications to deliver a flow of consistent messages about a product or service to meet a common set of
communication objectives or support a single positioning
(Percy, 1997; Pickton & Broderick, 2001). Briefly, the
moderation works as a result of the communication efficiency
or synergy created by messages that are coordinated throughout
the communication process. In examining the hypothesized
relationships, we hope to shed some light on the mechanism by
which IMC should provide greater message delivery capabilities.
2. Research hypotheses
2.1. Informational/transformational messages and
effectiveness
Messages disseminated to the market normally possess a dual
nature of both rational and emotional elements (Johar & Sirgy,
1991; Liebermann & Flint-Goor, 1996; Vakratsas & Ambler,
1999). Puto and Wells (1984) similarly classify approaches to
marketing messages (specifically, advertising) according to two
dimensions, informational and transformational. Informational
messages are factual and meaningful descriptions of the relevant
product information, delivered in a logical, verifiable manner to
attract customers. Transformational messages convey affectbased contents that associate the experience of owning or using a
product with psychological characteristics, such as richness,
warmth, excitement, enjoyment, and so on (Aaker & Stayman,
1992). For most marketing communications, messages can be
conveyed in an informational or transformational form or a
combination thereof (Cohen & Areni, 1991).
During IMC planning, it is crucial to understand the target
audience's purchase motivation, whether negative or positive,
to create, maintain, modify, or change brand attitudes (Percy,
1997; Rossiter, Percy, & Donovan, 1991). Negatively originated motives, such as problem removal and avoidance, trigger
customers to eliminate negative feelings or affect caused by a
problem by acquiring product-related information or buying
and using the chosen product. Therefore, an informational
message strategy may match the needs driven by such motives.
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C.-W. Chen et al. / Industrial Marketing Management 36 (2007) 1046–1056
Positive motives, in contrast, correspond to a transformational
message strategy, which links the use of the new product to
sensory benefits or intellectually or socially rewarding states.
Feeling or affect becomes positively transformed by the anticipated or actual consumption of the product (Rossiter & Percy,
1987).
According to the elaboration likelihood model (ELM) of
persuasion (Petty & Cacioppo, 1981), people form or change
their attitudes as a result of their exposure to persuasive
communications, which can be divided into two distinct routes–
central and peripheral–that anchor an elaboration likelihood
continuum. When attitudes form or change via the central route,
the elaboration likelihood condition is high; that is, the person's
motivation and ability to process issue-relevant information both
are high. This person is more likely to be persuaded by product
attribute-based message arguments, whereas a person who lacks
the motivation or ability to process such information follows a
peripheral route, and persuasion occurs through peripheral cues
such as music, endorsers, country of origin, and so forth.
According to the ELM, message senders should increase the
strategic fit of their messages by taking into consideration the
persuasion routes that message receivers are likely to use.
In high-tech markets, the continuously improving and highly
overlapping product generations exacerbate product obsolescence, so products of prior generations depreciate because of the
launch of a new generation or model, even if they are still
perfectly functional. Customers' decisions about whether or
when to adopt a new generation of technology largely depend
on their expectations about the pace and magnitude of product
improvements (Mohr, 2001). If a new product represents a new
generation or significant upgrade, potential customers' willingness to migrate to the product varies as a function of their
assessment of the value derived from that change (Guiltinan,
1999; Norton & Bass, 1987). To help prospective customers
manage this migration, firms may engage in product-inherent
value message communications.
Most high-tech products are sophisticated, technologically
complex, and/or difficult to explain or understand. Their buyers
speak the same language, share the same mindset, possess
specialized interests, and need the same technical information.
Regardless of their product knowledge, they often have rational
buying motives and high levels of involvement, and their
purchase decisions involve their evaluation of product performance in terms of established objective standards (Alden,
Steenkamp, Jan-Benedict, & Batra, 1999). Using a variety of
analytical tools, modern purchasing professionals can conduct a
broad range of evaluations for any new product offerings.
Therefore, rational claims may increase their perception of the
value of a new product by providing information that improves
their comprehension of the product. Alternatively, marketing
communications about new products could be conducted in a
bipolar fashion, such that the messages deliver informational
cues while evoking an emotional response. Nokia offers a
salient example of communications that combine state-of-theart technical performance with a humane theme, which allows
users to regard their highly technical phones as means to
connect with other people. Although both types of messages can
be used to launch high-tech products, informational messages
should be more effective in this context than transformational
messages. Accordingly, we hypothesize that
H1. The use of informational messages to launch a high-tech
product has greater (a) communication and (b) sales effects than
does the use of transformational messages.
2.2. Elaborational/relational strategy and effectiveness
Marketing communications can be also classified as elaborational or relational, distinguished according to how the message
contents are linked to the parent brand of a new extension
product (Bridges et al., 2000). On the one hand, elaborational
messages mainly address the product attributes of an innovation
and therefore represent a better communication strategy if the
innovation is a new brand or exhibits a low perceived fit with
the parent brand (Aaker & Keller, 1990). On the other hand,
relational messages emphasize the relationship between the new
product and its parent brand, which, assuming a high perceived
fit, helps transfer existing brand equity to the focal new product
(Aaker & Keller, 1990; Bridges et al., 2000). A good example of
relational messages occurs whenever IBM launches its new
products under the umbrella of its corporate brand.
Brand management critically differentiates a successful hightech venture from an unsuccessful one. Developing and maintaining a strong brand helps promise and deliver value to
customers and establishes a differentiation foundation for all
marketing activities in general and marketing messages in
particular (Bendixen, Bukasa, & Abratt, 2004; Ward, Light, &
Goldstine, 1999). In the high-tech context, purchases involve
both business managers and end users, and business managers
who make purchases for organizations are concerned about not
only how the vendor's products and services will complement
their company's business and technological environment but
also how the purchase decision will look to others. In addition,
Mohr (2001) advocates that high-tech brands must promise
value to end users, not to resellers. Whereas the former are far
more interested in what a technology product will do for them,
the latter focus more on high margins than on reinforcing the
manufacturer's promise of value.
Moreover, the speed with which high-tech products are
launched increases the complexity of using new products,
which causes customer confusion and fears about using any new
products (Beard & Easingwood, 1996; Moriarty & Kosnik,
1989). Marketers of strong brands, whose customers perceive
them as trustworthy and expert, likely supply a steady stream of
innovations, because customers' adoption risks and the cognitive effort associated with confusing information clutter are
lessened (Keller, 1998; Mudambi, 2002). In a sense, creating
strong brands is no less, if not more, important in high-tech
markets than in the consumer packaged goods industry.
Apparently, however, adoption resistance to new high-tech
products cannot be removed simply by sending elaborational
messages. Customers face uncertainty-derived risks and often
become highly confused by information overload, even if they
have sufficient product knowledge. The use of relational
C.-W. Chen et al. / Industrial Marketing Management 36 (2007) 1046–1056
messages takes advantage of existing brand equity, because given
substantial brand equity, relational messages can shape customers' attitudes toward new products. High-tech firms therefore
can launch new products more successfully by sending relational
messages than by sending elaborational messages.
H2. The use of relational messages to launch a high-tech
product has greater (a) communication and (b) sales effects than
does the use of elaborational messages.
2.3. Moderation of communication process characteristics
The way message contents get conveyed by the communications process is as imperative an element in marketing communications as the content. Accordingly, maintaining process
quality becomes a critical issue to ensure the effectiveness of
marketing communications (Phelps, Harris, & Johnson, 1996;
Zahay, Peltier, Schultz, & Griffin, 2004). In the IMC era, every
communication aspect must be executed in such a unified manner
that information is clear and uniform and thereby achieves the
maximum impact on customers (Schultz, Tannenbaum, &
Lauterborn, 1993).
The exchange theory model of interpersonal communications proposed by Gatignon and Robertson (1986) posits that
message clarity and message uniformity represent two characteristics of the communication process that influence the
uncertainty related to a message. The degree of uncertainty
reflects receivers' confidence regarding the conveyed information and acts as a weight of message persuasiveness. Message
clarity refers to the extent to which messages are communicated
without ambiguity or noise (Gatignon & Robertson, 1991;
Shannon & Weaver, 1949). In high-tech industries, market
uncertainty, technological uncertainty, and competitive volatility challenge customers' cognitive capabilities, so messages
with high clarity should be more readily accepted and precisely
interpreted by customers, which makes the messages more
persuasive (Gatignon & Robertson, 1991; Heil & Robertson,
1991). Because customers feel more comfortable and confident
in making their subsequent decisions, they become more likely
to react in accordance with the message sender's expectations.
H3. The (a) communication and (b) sales effects of conveying
informational messages increase as message clarity increases.
H4. The (a) communication and (b) sales effects of conveying
relational messages increase as message clarity increases.
Message uniformity refers to the degree to which messages
stay compatible or consistent from different sources and over
time (Lilly & Walters, 1997). Higher message uniformity–that
is, greater consistency among messages–increases the receivers' confidence with regard to processing and interpreting the
information and enhances their coherent cognition of the
product attributes (Heil & Robertson, 1991; Howell & Burnett,
1978). Consistency between new and old messages also is
crucial, in the sense that previous information creates expectations, and receivers react differently when their expectations are
confirmed or disconfirmed (Oliver 1997).
1049
H5. The (a) communication and (b) sales effects of conveying
informational messages increase as message uniformity
increases.
H6. The (a) communication and (b) sales effects of conveying
relational messages increase as message uniformity increases.
The need for IMC increases with the size and number of
activities or campaigns, which can range from discrete promotional pieces to a massive campaign involving various
promotional tools and even to multiple campaigns coordinated
across many countries. The integration of marketing communications occurs to different degrees that can be described in
terms of a spectrum anchored by two extremes: completely
detached and fully integrated. The core concept of IMC promotes synergism, which means that greater benefits accrue from
greater integration. In contrast, a loose collection of unconnected activities leads to separation and dysfunction and,
accordingly, imposes negative impacts on the marketing communication effort (Duncan & Everett, 2000; Pickton &
Broderick, 2001; Shimp, 2000).
H7. The (a) communication and (b) sales effects of conveying
informational messages increase as the integration of communication increases.
H8. The (a) communication and (b) sales effects of conveying
relational messages increase as the integration of communication increases.
3. Research method
3.1. Measures
In an attempt to test the proposed hypotheses, we designed a
self-administrated questionnaire to gather information with
respect to the marketing communications used by Taiwanese
high-tech companies for their product launches. We provide the
constructs and a sample of their corresponding measurement
items in Table 1. The scales were developed on the basis of
relevant studies and according to Churchill's (1979) recommendations. Seven-point Likert scales were used, for which
1 = “strongly disagree” and 7 = “strongly agree.”
We developed a preliminary questionnaire from existing
research, then conducted in-depth interviews with two academics and a pretest of 30 managers to refine the questionnaire, measures, and data collection methods. To analyze the
pretest results, we use a series of factor analyses and eliminate
items with factor loadings lower than .5 (Hair, Anderson,
Tatham, & Black, 1995).
The informational messages scale refers to the extent to
which messages are rational, relevant, and factual, whereas the
transformational messages scale captures the degree of emotional contents used in the marketing communications (Puto &
Wells, 1984). To measure the level of contents associated with
branding, we develop two constructs of elaborational and
relational messages from Bridges et al. (2000). The first scale
measures the extent to which messages focus on product-related
features and customer benefits; the second scale assesses how
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C.-W. Chen et al. / Industrial Marketing Management 36 (2007) 1046–1056
Table 1
Summary of measures
Construct
Operational
definition
Informational
messages
Messages convey
information about
the identity of the
new product
logically
Sample item
Communicated
messages
emphasize the
specifications of
the focused
product
Transformational Messages convey Communicated
messages
experiential and
messages make
sentimental
much of good
information about experiences in
using the product using the product
Elaborational
Messages feature
Communicated
messages
the attributes and
messages
benefits of the new emphasize the
product
attributes or
characteristics
of the product
Relational
Messages stress
Communicated
messages
the relationships
messages
between the new
emphasize the
product and its
relationships
parent brand
between the new
product and the
brand of parent
company
Messages for
Message clarity
Disseminated
launching the
messages are
unambiguous and new product are
delivered clearly
precise
Messages for
Message
The
launching the
uniformity
communication
new product are
messages for the
consistent from
product are
beginning to end
consistent
throughout the
launch activities
The company
Integration of
A variety of
has formulated a
communication marketing
well-defined
communication
strategy to guide
activities are
integrated
the marketing
communications
strategically
Communication The extent to
The launched
effect
which the launch
product enjoys
great awareness
activities achieve
communicationrelated objectives
Sales effect
The extent to
The sales of the
which the launch
launched product
activities achieve
are really great
sales-related
objectives
Items Cronbach's
α
9
0.9272
8
0.9073
7
0.9065
4
0.8265
5
0.8815
5
0.8908
6
0.9077
5
0.8919
5
0.8728
much the message contents relate to the parent brand of the
focal product. We developed the scales of the three moderator
variables as follows: Message clarity assesses the extent to
which messages are conveyed in a precise and unambiguous
way (Heil & Robertson, 1991; Robertson, Eliasberg, & Rymon,
1995); message uniformity measures whether communicated
messages for the focal product are consistent across time and
activities (Heil & Robertson, 1991; Lilly & Walters, 1997); and
integration of communications captures the extent to which all
marketing communications fall in line with the set objectives
and complement one another (Duncan & Everett, 2000; Pickton
& Broderick, 2001; Schultz et al., 1993). Finally, as is common,
we assess the effectiveness of marketing communications according to communication and sales effects (Cooper &
Kleinschmidt, 1987; Lavidge & Steiner, 1961; Rogers, 1962;
Ruekert & Walker, 1987). Table 1 includes the Cronbach's
alpha values of all scales and shows that all coefficients are
greater than .80, indicating acceptable reliability and unidimensionality (Nunnally, 1978).
3.2. Sample
The sampling frame of our research includes a broad spectrum
of high-tech sectors in which product innovation and launch are
prevalent phenomena. We obtained a combined list of high-tech
firms from two sources: the database list of the Winners of the
Symbol of Excellence Award held by the Taiwan External Trade
Development Council (TAITRA) and a database list of the top
1000 Taiwanese enterprises from Commonwealth Magazine, one
of Taiwan's leading business publications. The sample size for
our research is 530 firms, which enables us to address both
theoretical and practical considerations. In advance of mailing the
questionnaires, preliminary telephone contacts were made to
identify key informants, solicit their cooperation, and verify
mailing addresses. Overall, 114 questionnaires were completed
and returned, but 13 were eliminated because of missing data
on key construct items. Accordingly, we have 101 usable
questionnaires left for our data analysis, a response rate of
19.06%.
We calculated the means of three industry-related constructs–
market uncertainty, technological uncertainty, and competitive
volatility (Jaworski & Kohli, 1993)–to verify the legitimacy of
the samples. All three values are greater than 5, indicating a
successful sample selection. To ensure that the sample is representative of the entire population, we used t-tests to examine the
differences in two firm-related variables, annual sales and number of employees, between early and late respondents (Armstrong & Overton, 1977). We consider responses received within
4 weeks after the initial mailing early (n = 45) and those received
after 4 weeks late (n = 56) (cf. Mishra, Heide, &Cort, 1998) and
find no significant differences between the two groups on either
measure. We therefore conclude that nonresponse bias is not a
serious concern in this research.
3.3. Data analysis
We employ a series of moderated regression analyses (Aiken,
West, & Reno, 1991) to test the proposed hypotheses. The
regression models include the main effects of the predictor and
moderator variables, along with the predictor × moderator interaction effects. All predictor and moderator variables are meancentered to reduce multicollinearity among the product terms and
their constituent terms (Cohen & Cohen, 1983; Jaccard, Wan, &
Turrisi, 1990). We also calculate variance inflation factors for the
C.-W. Chen et al. / Industrial Marketing Management 36 (2007) 1046–1056
1051
Table 2
Descriptive statistics and correlation matrix
Variable
Informational message (IM)
Transformational message (TM)
Elaborational message (EM)
Relational message (RM)
Integration of communication (IC)
Message uniformity (MU)
Message clarity (MC)
Mean
5.77
4.98
5.71
5.88
5.12
5.43
5.64
S.D.
0.76
1.13
0.80
0.79
0.95
0.78
0.68
Coefficients of Pearson correlations
IM
TM
EM
RM
IC
MU
MC
1.000
0.057
0.194
0.982 ⁎⁎
0.106
0.293 ⁎⁎
0.449 ⁎⁎
1.000
− 0.050
0.079
0.514 ⁎⁎
0.140
0.195
1.000
0.154
− 0.009
0.183
0.301 ⁎⁎
1.000
0.123
0.240
0.39
1.000
0.136
0.199 ⁎
1.000
0.582 ⁎
1.000
⁎ p b .05.
⁎⁎ p b .01.
independent variables and find that all values are well below 10,
the cutoff point for eliminating multicollinearity (Myers, 1986).
To examine the effectiveness of the messages, we use a procedure suggested by Neter et al. (1990) and test whether the
parameters estimated by the same regression differ. Specifically,
we develop in sequence the following full model: Yi = β0 + β1Xi1 +
β 2Xi2 + εi, where β1 ≠ β2, and a reduced model under the null
hypothesis (β1 = β2). The F-statistics differ significantly at the .05
level, so the null hypothesis is rejected.
4. Results
In Table 2, we provide the descriptive statistics and correlation matrix for all variables. We perform separate regression
analyses with both categories of messages as predictor variables
and the two effectiveness measures as criterion variables; thus,
we report the results of four moderated regression analyses in
Tables 3 and 4.
4.1. Informational/transformational messages and
effectiveness
As we show in Table 3, H1a is supported; informational
messages are positively related to the communication aspect of
effectiveness, and the effect is significantly greater than that of
transformational messages (βIM = .53 N βTM = − .09; ΔF N F0.05
(1, 97)). Moreover, the regression coefficients of informational
and transformational messages for sales effect differ signifi′ = .42 N β TM
′ =
cantly and in the hypothesized direction (β IM
− .11; ΔF N F0.05 (1, 97)), in support of H1b. To test the
moderating effects, we calculate the F-statistic differences
between Models 2 and 3 for communication and sales effects
and find that both ΔF values are statistically significant (ΔF
communication = 2.88; ΔF sales = 3.95), which indicates that
variances in the criterion variables can be explained by
incorporating the moderator variables into the models. Specifically, the significance of the respective product terms clearly
Table 3
Informational/transformational messages and effectiveness
Variables
Main effects of predictor variables
Informational messages (IM)
Transformational messages (TM)
(a) Communication effect
Model 1
Model 2
Model 3
Model 1
Model 2
Model 3
.53 ⁎⁎⁎
− .09
.33 ⁎⁎
− .21 ⁎⁎
.16 ⁎
−.10
.42 ⁎⁎⁎
− .11
.22 ⁎⁎
−.23 ⁎⁎
.02
− .05
Main effects of moderator variables
Message clarity (MC)
Message uniformity (MU)
Integration of communication (IC)
Moderating effects
IM × MC
IM × MU
IM × IC
TM × MC
TM × MU
TM × IC
F-statistic
Adjusted R2
⁎ Significant at p b .10.
⁎⁎ Significant at p b .05.
⁎⁎⁎ Significant at p b .01.
(b) Sales effect
19.28 ⁎⁎⁎
.27
.35 ⁎⁎
.15
.09
.28 ⁎⁎⁎
.11
−.07
15.73 ⁎⁎⁎
.42
.24 ⁎⁎
.16
.22 ⁎⁎
.04
.01
−.11
12.85 ⁎⁎⁎
.57
11.12 ⁎⁎⁎
.17
.38 ⁎⁎
.10
.08
.29 ⁎⁎⁎
.01
− .06
13.13 ⁎⁎⁎
.31
.30 ⁎⁎
.24 ⁎⁎
.22 ⁎⁎
.02
− .02
.01
17.08 ⁎⁎⁎
.60
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C.-W. Chen et al. / Industrial Marketing Management 36 (2007) 1046–1056
offers support for our hypothesized moderating effects.
Consistent with our expectations, both communication and
sales effects of informational messages are strengthened by
message clarity (βIM × MC = .24, p b .05; β′IM × MC = .30, p b .05),
which confirms H3a and b. However, the moderation effect of
message uniformity on the informational message–communication link is not significant (βIM × MU = .16, p N .10), so H5a is
not supported. In contrast, H5b is confirmed, because the sales
effect of informational messages is positively moderated by
message uniformity (β′IM × MU = .24, p b .05). The hypothesized
positive moderating effects of integrated communications on
the relationships of informational message with communication
and sales effects are both statistically significant, with βIM × IC
and β′IM × IC = − .22 ( p b .05).
′ × MC = .24,
specific performance (βRM × MC = .24, p b .05; βRM
p b .05). Although message uniformity's moderation of the
communication effect of relational messages is not significant,
according to the insignificant regression coefficient of the
product term βRM × MU = .13 ( p N .10), message uniformity imposes a positive moderating effect on the sales effect of relational messages (βRM
′ × MU = .32, p b .01). Thus, though H6a is
not supported, H6b is confirmed. The positive moderating
effects of integrated communications on the relational message–
communication effect (H8a) and relational message–sales effect
(H8b) links are both statistically significant, with βRM × IC = .15
( p b .1) and βRM
′ × IC = .29 ( p b .01).
4.2. Relational/elaborational messages and effectiveness
We summarize our hypothesis testing results in Table 5 and
use the subsequent discussions to recapitulate the rationale
behind the supported hypotheses and explore some explanations for the unsupported hypotheses.
As Table 4 shows, both relational and elaborational messages
have significant influences on communication objective-related
performance, though the impact of relational messages is
significantly greater than that of elaborational messages
(βRM = .45 N βEM = .24, ΔF N F0.05 (1, 97)). Similarly, Model 1
indicates significant coefficients for both elaborational and
relational messages. Relational messages have significantly
greater sales effects than do elaborational messages (βRM
′ = .19 N
β′EM = .18, ΔF N F0.05 (1, 97)), so both H2a and b are supported.
The differences in the F-values of Models 2 and 3 (communication and sales effects) are statistically significant, which
indicates that the moderator variables substantially improve the
variance explanation (ΔF communication = 3.11; ΔF sales =
6.51). The moderating effects tests show that, as we hypothesized in H4, message clarity strengthens the impacts of relational messages on both communication-specific and sales-
4.3. Discussion
4.3.1. Main effects of predictor variables
The ELM theory suggests that a message receiver's amount
of elaboration of product-related information varies with his or
her motivations and abilities (Petty & Cacioppo, 1981). The fast
pace of technological change creates high uncertainty levels for
high-tech customers, who must continuously search for timesensitive information, which quickly loses its value, to lessen
their uncertainty (Mohr, 2001). Most customers in high-tech
markets also are relatively knowledgeable and able to evaluate
product-related information (Alden et al., 1999). With their
greater involvement, need for cognition, and product knowledge, these customers are more inclined to follow a central
processing route (Lee & O'Connor, 2003). Compared with
Table 4
Elaborational/relational messages and effectiveness
Variables
(a) Communication effect
Model 1
Main effects of predictor variables
Elaborational message (EM)
Relational message (RM)
.24 ⁎⁎⁎
.45 ⁎⁎⁎
Main effects of moderator variables
Message clarity (MC)
Message uniformity (MU)
Integration of communication (IC)
Moderating effects
EM × MC
EM × MU
EM × IC
RM × MC
RM × MU
RM × IC
F-statistic
Adjusted R2
⁎ Significant at p b .10.
⁎⁎ Significant at p b .05.
⁎⁎⁎ Significant at p b .01.
19.77 ⁎⁎⁎
.28
Model 2
.14 ⁎
.30 ⁎⁎⁎
(b) Sales effect
Model 3
.08
.20 ⁎⁎
.32 ⁎⁎⁎
.15
− .02
.32 ⁎⁎⁎
.10
− .06
14.29 ⁎⁎⁎
.40
− .01
− .07
.07
.24 ⁎⁎
.13
.15 ⁎
11.18 ⁎⁎⁎
.53
Model 1
.18 ⁎
.19 ⁎
4.10 ⁎⁎
.08
Model 2
.11
.06
Model 3
.01
− .13
.31 ⁎⁎
.03
− .02
.31 ⁎⁎⁎
− .10
− .08
3.60 ⁎⁎⁎
.12
.01
.002
.07
.24 ⁎⁎
.32 ⁎⁎⁎
.29 ⁎⁎⁎
10.11 ⁎⁎⁎
.50
C.-W. Chen et al. / Industrial Marketing Management 36 (2007) 1046–1056
1053
Table 5
Summary of results
Variables
Main effects
Informational messages (IM)
Transformational messages (TM)
Relational message (RM)
Elaborational message (EM)
Moderating effects
IM × Message clarity (MC)
RM × Message clarity (MC)
IM × Message uniformity (MU)
RM × Message uniformity (MU)
IM × Integration of Communication (IC)
RM × Integration of Communication (IC)
Hypothesis
H1a and b
H2a and b
H3a and b
H4a and b
H5a and b
H6a and b
H7a and b
H8a and b
Expected result (sign)
βIM a
βTM
βRM a
βEM
(+)
(+)
(+)
(+)
(+)
(+)
Coefficient
Final result
(a) Communication
(b) Sales
.53 ⁎⁎⁎
−.09
.45 ⁎⁎⁎
.24 ⁎⁎⁎
.42 ⁎⁎⁎
− .11
.19 ⁎
.18 ⁎
.24 ⁎⁎
.24 ⁎⁎
.16
.13
.22 ⁎⁎
.15 ⁎
.30 ⁎⁎
.24 ⁎⁎
.24 ⁎⁎
.32 ⁎⁎⁎
.22 ⁎⁎
.29 ⁎⁎⁎
Supported
Supported
Supported
Supported
Partially supported
Partially supported
Supported
Supported
a
Expected greater impact.
⁎ Significant at p b .10.
⁎⁎ Significant at p b .05.
⁎⁎⁎ Significant at p b .01.
transformational messages, informational messages, which present factual and relevant product information, therefore tend to
improve communication- and sales-based launch performance.
The fast-moving and volatile characteristics of high-tech
industries also may result in customers' confusion and resistance
to adoption (Beard & Easingwood, 1996). In the high-tech arena,
a strong brand provides a distinctive identity that establishes a
relevant, enduring, and credible promise of value, as well as a
reassuring beacon that customers can use as a heuristic to reduce
their perceived risks and anxiety (Mohr, 2000). A brand can be a
powerful source of competitive advantage, in the sense that it can
be understood better because it has remained the same and
therefore can “buy time” in the face of new technology or serious
lapses in product quality (Ward et al., 1999). In turn, brand
extensions have become important launch strategies for high-tech
firms like Microsoft, Intel, and Hewlett-Packard. Our findings
support the use of relational messages to support product launch,
because though both elaborational and relational messages enjoy
positive communication and sales effects, relational messages
tend to have greater impacts. Accordingly, a high-tech firm may
accelerate the diffusion of its new products by associating them
firmly with the family or corporate brand, in addition to conveying product attribute messages.
4.3.2. Moderating effects
Overall, our findings confirm the hypotheses that suggest
message clarity, message uniformity, and integration of communications moderate the relationships between messages and their
effectiveness. The empirical results demonstrate the importance
of communication quality for an effective message strategy.
Message clarity strengthens the effects of messages, whether
informational or relational, and clear, unequivocal, specific messages offer receivers a single, straightforward interpretation with
which they may make causal attributions with minimal errors
(Daft & Macintosh, 1981; Jervis, 1970). Thus, clearly delivered
messages facilitate the message sender's intention to enhance
product comprehension or increase the association with the
parent brand.
Uniform messages also facilitate message reception (Heil &
Robertson, 1991; Howell & Burnett, 1978), but our regression
analyses provide mixed results with respect to their hypothesized moderation effect. Although message uniformity fails to
impose any significant moderating effect on the message–
communication effect link, it demonstrates positive impacts on
the message–sales effect relationship. Because message uniformity means the consistency of communications throughout
launch activities and over time, it may influence the early phases
of customer cognition, such as awareness, interest, and attitude
(Rogers, 1962), only minimally. Instead, customers may perceive various messages as consistent only after they receive a
series of communications. Hence, uniformity moderates only
the influence of messages about adoption, which entail the
directly sales-related aspect of cognition.
Finally, the integration of communications positively affects
the relationships of both informational and relational messages
with communication- and sales-based performance. These
findings further confirm the importance of IMC. In addition
to creating and selecting the correct messages, firms must align
their communication campaigns or activities with their set
objectives to deliver effective and efficient marketing communications for product launches.
5. Conclusion and managerial implications
Our research shows that in high-tech industries, what to say
and how to say it are both essential for marketing communications designed to support a product launch. We explore the
strategies for designing messages (i.e., what to say) according to
informational/transformational and elaborational/relational
dimensions and propose that high-tech customers, who are
relatively motivated and able to process new product-related
information easily, may be better swayed by informational
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C.-W. Chen et al. / Industrial Marketing Management 36 (2007) 1046–1056
messages, which increase their awareness of, interest in, and
comprehension of new products and lead to their adoption of the
product. That is, the use of informational messages is more
effective for launching high-tech products than is the use of
transformational messages. Moreover, it is beneficial to use relational messages, which emphasize the association of the new
product with its parent brand, than elaborational messages,
because the high speed of product innovation in high-tech industries increases customers' perceived adoption risks associated
with product obsolescence or network externality. Marketers can
overcome adoption resistance by delivering messages that link
products to their parent brands, which, if they possess strong
brand equity, can generate customer trust and confidence in the
new products.
These aforementioned findings have managerial implications
for designing new product-related messages. The messages
communicated to facilitate product launch should balance informational and relational elements, and the firm should make its
informational and relational messages complementary, not
mutually exclusive. Performance represents the price of admission in high-tech markets, so many high-tech companies promise
value on the basis of cutting-edge products and superior service
and support (Ward et al., 1999), which causes consumers of new
high-tech products to consider them full of perceived and
cognitive risks and resist their adoption (Lee & O'Connor, 2003).
It is therefore critical that marketers use appropriate message
strategies to reduce such risks and increase product adoption.
High-tech firms also should give priority to branding and
brand-building programs. Keller (1998) indicates that the short
product life cycle of high-tech products places a premium on
corporate or family brands with strong credibility associations.
When it comes to brand strategy, a high-tech firm is less likely
to brand its new products with totally new names; rapid product
obsolescence would make it costly for the firm to do so and
difficult for customers to develop product or brand loyalty.
Corporate and product family names thus serve as naming
platforms, to which modifiers are attached to name new product
versions—Windows 2000, or Microsoft Word, Microsoft
Works, Microsoft Explorer, and so forth (Ryder, 1994; Shipley
& Howard, 1993). For example, the successful “Intel Inside”
campaign has led end users to generate favorable associations
with Intel's corporate brand. Likewise, Cisco Systems has
leveraged its success in the behind-the-scenes business market
into the growing consumer network market through its television commercials. Brand-building efforts also emerge from
companies like Nokia, Qualcomm, and Oracle, which have
started to use mass media to reach broader customer markets to
establish and nurture their corporate or brand identities (Mohr,
2001).
Managers must bear in mind that the quality of the communication process, given effective message content, is critical to
new product success. Clear messages influence receivers'
cognitive efficiency so they may accurately perceive and respond to the communication. The effectiveness of launch-related
marketing communications, in terms of communication or sales
effects, therefore can be improved. Our research reveals that the
extent to which marketing communications are integrated is
critical to the effectiveness of a message strategy; thus, synergy
will heighten the impact of specific marketing communications.
Surprisingly, message uniformity fails to impose any impact on
the message–communication relationship, but it does positively
moderate the sales effect—possibly because receivers perceive a
series of messages as uniform only in the late stages of cognition,
close to their adoption decision. High technological uncertainty, a
salient characteristic of high-tech industries, may lengthen the
customer's cognition process and diminish the moderating
effects of consistent messages. However, marketing communications may be enhanced by accelerating customer perceptions of
messages as uniform during earlier cognition stages. Overall,
messages must communicate in such a clear, uniform, and integrated manner that the target audience responds or reacts just as
marketers expected. For effective communication to occur,
messages should fit the cognitive capability of the target audience
and be delivered through coordinated, integrated marketing
communications (Fill, 2001).
Our findings also have important implications for high-tech
firms in emerging economies like Taiwan. Most Taiwanese
high-tech firms are involved in OEM, though some have been
trying to change their business model into original design
manufacturing or original brand manufacturing. We find that
new product success hinges on the successful planning and
execution of supportive marketing communications that focus
messages not only on product attributes but also branding.
Taiwanese high-tech firms, which possess great expertise in
R&D and engineering, must start learning how to build their
own brands and implement essential marketing communications to promote their brands and affiliated products if they want
to increase their value for customers and themselves.
6. Directions for future research
Additional research might attempt to probe the typology of
message strategies, especially for product launches. Communication process represents another topic worth exploring, and the
role of process quality in marketing communications needs more
academic attention and efforts. For example, the frequency and
strength of communications may differ across products, firms,
and industries, and if we can understand the manner in which
messages are carried to promote new products, we could gather
normative implications. Finally, a more comprehensive framework might be established by incorporating more relevant
variables, such as industry and firm factors, into our model.
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Chien-Wei Chen, Ph.D., is an assistant professor in the Department of
International Business, College of Commerce, National Chengchi University,
Taiwan. His research focuses on new product management, marketing
communications, and international marketing.
Chung-Chi Shen is an assistant professor in the Department of International
Business at Providence University in Taiwan. His research interests include
marketing strategy, e-tailing, and online consumer behavior.
Wan-Yu Chiu is an MBA graduate of the Department of International
Business, National Chengchi University. Currently she works for Bristol
Meyers Squibb (Taiwan) Ltd.