Download Goal-congruent Extension Goal

The Impact of Branding and Marketing Communication Strategies on
the Transfer of Purposive, Goal–Oriented Brand Meaning
Ingrid M. Martin,
David W. Stewart,
And
Shashi Matta 1
DO NOT QUOTE WITHOUT AUTHORS’ PERMISSION
1Ingrid Martin is Associate Professor of Marketing at California State University at Long Beach, Dept. of Marketing, CBA,
Long Beach, CA 90840. David W. Stewart is the Robert E. Brooker Professor of Marketing and Deputy Dean in the
Marshall School of Business at the University of Southern California. Shashi Matta is a doctoral student in the Department
of Marketing in the Marshall School of Business at the University of Southern California. The authors gratefully
acknowledge the comments and suggestions of Deborah J. MacInnis, C.W. Park, and Stephen J. Read. Correspondence
regarding this manuscript should be directed to the first author. Office: 562.985.4767. FAX: 562.985.1588. Email:
[email protected].
The Impact on Branding and Marketing Communication Strategies on the Transfer of
Purposive, Goal–Oriented Brand Meaning
Abstract
Drawing on prior research on brand extensions and the theories of goal-derived categorization and
attitude accessibility in cognitive psychology, the authors develop and test a conceptual framework of
the process of consumer knowledge and attitude transfer from one product category to another in the
context of two hypothetical product extensions. The empirical results are consistent with the
theoretical expectations that the availability of well-formed, goal-derived categories associated with a
core product facilitates the transfer of consumer knowledge and attitude toward an extension of that
product category to another product category. No such facilitating effect was observed in the absence
of goal-derived categories. The results also reveal how marketing communication, particularly as a
part of new product introduction strategy, can be used to aid the transfer process of consumer
knowledge and attitude towards an extension. Implications of the results for the organization of
consumer knowledge and affect across product categories and for understanding the variety of prior
research findings on extension categories are discussed.
The Impact on Branding and Marketing Communication Strategies on the Transfer of
Purposive, Goal–Oriented Brand Meaning
A brand name is among the most fundamental and long lasting assets of a firm. Recognition of
the value of brands has lead marketers to seek ways to leverage brands to increase their value through
brand extensions and other means. Such leverage potentially arises from two sets of factors working
together: 1) awareness, knowledge, attitudes, and behavioral intentions associated with the parent
brand are transferred to the new brand extension and 2) because such transfer occurs, the costs of
introducing an extension are generally lower than launching a completely new brand. Critical to the
realization of such leverage is the degree to which transfer occurs from the parent brand to a brand
extension (at a given cost). That such transfer may occur is well established, but there remains debate
about the cognitive and affective process(es) by which it occurs. How transfer of consumer knowledge
and attitude from a brand to an extension occurs has important implications for understanding how
consumers organize information about brands and the cognitive and affective processes that influence
this organization of information. The nature of these processes, in turn, has important practical
implications for both forecasting the likely success of a brand extension and for determining the
resources required to assure such success. From a theoretical perspective, consumer response to brand
extensions provides a particularly appropriate setting in which to examine the processes consumers use
when assigning meaning to products and for investigating factors that may influence the process(es) by
which knowledge and affect are transferred from one product to another.
In this research, we extend prior research on brand extensions and brand associations by
offering a conceptual model of a goal-based brand meaning and the process by which transfer occurs
based on two related theories: goal-derived categorization (Barsalou 1985) and attitude accessibility
(Fazio 1989). The framework developed and tested in this paper is shown to be a general, robust
predictor of the transfer of knowledge and attitudes from a well-known brand in one product category
to an extension of the brand in another product category and extends the prior methodological work of
Martin & Stewart (2001) on dimensions of brand similarity. In addition, this research and other past
research on brand extensions has not explicitly examined the role and impact of marketing
communication on the transfer process (for exceptions, see Bridges, Keller, & Sood, 2000; Lane 2000).
The meaning or associations between the core brand and the new extension can be learned in a variety
of ways including marketing communication (Ratneshwar, Mick, & Huffman 2001). Thus,
understanding how marketing communication can be used to facilitate the transfer process also has the
potential to help marketers design new product introduction strategies.
CONCEPTUAL BACKGROUND
Prior Research in Brand Extensions. Virtually all prior research on brand extensions rests on
the premise that knowledge and attitudes (“brand meaning”) associated with an established brand are
part of a network of associations that includes the brand name, concrete and abstract product attributes,
and use occasions, among other things, that may be transferred to an extension of the brand. Implicit in
this research is the notion that the more similar products are with respect to certain key dimensions, the
more likely the transfer of cognition and affect from the core product to the extension (cf: Larkin 1978,
Novick 1988). The focus of much of the research on brand extensions has been the identification of
various “fit” indices, both concrete and abstract. (e. g., Aaker & Keller 1990, Boush & Loken 1991,
Park, Milberg & Lawson 1991, Broniarcyzk & Alba 1994, Morrin 1999, Martin & Stewart 2001).
Prior research leaves little doubt that the extendibility of a brand is a function of cognitive and affective
processes for both product class and brand-specific associations and that feature-based similarity,
brand-specific associations, brand concept (schema) consistency, shared goals and usage occasions are
associated with an increased likelihood of cognitive and affective transfer from a core product to an
extension. The literature is less clear about how such shared characteristics facilitate transfer or how
these shared characteristics might be used to predict the likelihood of the success of a brand extension.
An especially important distinction among empirical studies of brand extensions has revolved
4
around differences in the particular product or brand attributes (e.g., brand specific associations) that
have been used to define various fit indices. Four general approaches to the measurement of product
similarity have been proposed in the context of brand extension research: feature-based similarity,
usage-based similarity, brand-concept similarity, and goal-based similarity (Martin & Stewart 2001,
Klink & Smith, 2001). While there is evidence that several alternative approaches to the definition and
measurement of “fit” are correlated, the degree of association appears to be contingent on a variety of
factors (Martin & Stewart 2001). Park, et al. (1991) found that knowledge and affect transferred from a
“prestige” brand to an extension but not from a more utilitarian product to an extension. Broniarczyk &
Alba (1994) demonstrate that core brand associations must “fit” with the key benefits sought in the
extension category but they do not explain how this process occurs. Thus, absent a higher-order
organizing framework, it is unclear which of many product features or brand associations form the
basis for an index of similarity and which features are relevant to the transfer of knowledge and
attitudes from a well-known brand to an extension (Goodman 1972, Murphy & Medin 1985).
Some prior research has examined the role of mediating factors in the relationships among
various measures of similarity (fit), attitudes, and behavioral intention. Martin & Stewart (2001)
demonstrated that structural models that included a latent organizing construct, which served to
summarize various measures of product similarity (brand meaning) explained more variance in affect
and purchase intent toward a brand extension than models that included only a direct link between
various measures of similarity and measures of affect and purchase intention for a brand extension.
Interestingly, these authors found that such a latent construct provided a better fit even when the core
brand and brand extension were goal incongruent, though the fit was especially strong in cases where a
core brand and brand extension were goal congruent. Thus, consistent with the literature on
categorization (Barsalou, 1985, Shocker, et al. 1990), the Martin and Stewart study found that
perceptions of product similarity are mediated by some latent organizing construct or process. While
these authors suggested that the mediating construct they identified was somehow related to
5
consumers’ goals, their work focused on a comparison of alternative models of measurement and did
not include any effort to examine the processes that give rise to the differential measurement models
they examined.
An understanding of the processes that give rise to summary measures of similarity or fit is
important for both theoretical and practical reasons. From a theoretical perspective it is important to
differentiate among alternative processes. Schema are the result of summary processes and Park et al.
(1991) rely on this construct as the basis for their notion of brand concept similarity. Similarly,
common use occasion (Shocker, et al. 1990) might be viewed as an organizing construct. Thus,
although Martin & Stewart (2001) find support for the role of a mediating construct and ascribe this
construct to a goal-derived process, they did not offer a test of whether a goal-driven process or some
other latent organizing process was responsible. Thus, the development of a theory of the transfer of
knowledge, affect and behavioral intention would be substantially advanced if it can be demonstrated
that the process is goal-driven, as recent work on the role of goals would suggest (Ratneshwar, Mick, &
Huffman, 2001) or is driven by some other process.
From the perspective of a manager, identification of the processes underlying consumers’
development of summary perceptions of similarity or fit would provide useful guidance for identifying
potential brand extensions most likely to be successful and those marketing actions, such as strategies
for marketing communication, that are likely to increase the probability for success of a given brand
extension. The remainder of this paper focuses on the development, elaboration and testing of an
explicit goal-driven process that provides the basis for explaining consumers’ summary judgments of
similarity and consequent differences in transfer of knowledge, affect and intention from a core brand
to an extension of that brand in another product category. In contrast to prior research on brand
extensions, the present paper includes specific examination of process measures intended to reveal the
extent to which underlying processes are driven by goals or some other construct. In addition, this
research examines the extent to which marketing factors other than the product itself, namely
6
marketing communications, may play a role in mediating the transfer of knowledge, affect, and
intention from a core brand to an extension of the brand.
Goal-Driven Categorization. As noted earlier, one candidate for a comprehensive organizing
process of product similarity is found in goal-derived categorization that is receiving increasing
attention in marketing and other disciplines interested in human cognition and affect (Ratneshwar,
Mick, & Huffman, 2001; Ratneshwar, Pechmann, & Shocker 1996, Martin & Stewart 2001). There is
considerable empirical evidence that consumers’ goals are an especially important factor in the
organization of information (Barsalou 1985; Huffman & Houston 1993; Martin & Stewart 2001).
In general, knowledge and attitude transfer will most likely occur when consumers create a link
between products and their ability to fulfill a goal or set of goals (Barsalou 1985). Hence, a brand
extension should be most successful when the individual readily links a goal associated with the core
category to that of a brand extension. The less congruent the goal(s) between the parent brand and the
extension, the less likely cognition and affect will transfer from the parent brand to the extension. This
view is different from other approaches in brand extension research. Prior research treated the brand
name as the critical organizing element; the goal congruency approach treats the individual’s goal(s) as
the organizing framework that link(s) the extension to the core category.
When an individual does not associate similar goals with the core product category and the
extension category, the individual must construct a new category to explain the relationship between
the parent brand and the extension. This new category, an ad hoc category, will be based on whatever
shared characteristics are prominent (c.f. Barsalou 1991). However, this ad hoc category will be less
well organized and the transfer of cognition and affect from the parent brand to the extension will be
diminished. The lack of shared goals presents a situation in which the individual has no prior
organizing framework for linking the two products. If the individual constructs a link between two
products with a shared brand name and a goal-derived category structure is not available to guide
information processing and transfer, the individual may focus on readily identifiable attributes as
7
shared features or usage similar for re-categorization and piecemeal processing (Fiske & Neuberg
1990, Martin & Stewart 2001).
Nevertheless, the cognitive and affective transfer from the core to the extension category will be
diminished in such cases. Mandler (1982, p. 14) suggests “… incongruency leads to the activation or
formation of an [associational network] that fits the new information”. Thus, if a goal associated with
a brand is not readily associated with the new extension, the probability of linking the two products in
memory is significantly reduced because goal congruency is perceived as low. The preceding
discussion suggests goal-related measures will account for more unique variance than typicality
measures (Barsalou 1985, p. 640). This greater explanatory power is consistent with the view that goalderived categories provide a stronger, more robust basis for explaining the transfer of cognition and
affect from a core product category to an extension category. The primacy of the goal-based approach
was demonstrated in Martin & Stewart (2001) and is tested again here. Thus:
H1: Goal congruency between a core product and an extension category will have greater
explanatory power (account for more variance) in measures of attitude and purchase
intent toward a brand extension than traditional typicality measures.
Objects that share a common goal should facilitate greater transfer of cognition and affect than
objects that are not goal congruent. If goal congruency does facilitate the transfer of knowledge and
evaluations, individuals exposed to a congruent extension should be able to access information and
affect faster than individuals exposed to an incongruent extension (Barsalou 1985, Fazio 1986). Thus,
reaction time (RT) measures should be significantly faster in the case of goal congruent extensions.
Fazio (1986) has demonstrated that attitudes that are highly accessible and consistent are much more
likely to guide behavior than attitudes that are less accessible. Hence, the likelihood that an individual
will select the proposed extension should be influenced by the degree of goal congruency. Finally,
congruent goals elicit product information (features, usage occasions, and other attributes) and attitudes
that have been stored in the goal-derived category. Thus, the attitude toward the core product is
transferred to the extension (c.f., Novick 1988). That process would be evidenced by the elicitation of
8
an attitude associated with the extension that is similar to that associated with the parent brand. When
the goal associated with an extension is incongruent with those of the core category, such transfer is
less likely (Mandler 1982, Meyers-Levy & Tybout1989). Thus:
H2: Individuals exposed to a brand extension associated with a goal that is congruent with
that of the parent brand will exhibit:
a: higher goal-related knowledge (ideals, goodness-of-fit) 2 and a closer fit (e.g.,
overall perceived similarity, manufacturing similarity),
b: more readily accessible knowledge and attitudes (as evidenced by a faster
reaction time), and
c: have a higher purchase likelihood than individuals exposed to a goalincongruent extension.
H2d: Given a positively evaluated brand, subjects exposed to a goal congruent brand extension will
have more positive attitudes toward the extension than those exposed to a goal-incongruent
extension.
The Role of Communication. Although goal congruency may be the impetus for the transfer
of knowledge and attitudes, there remains the question of how consumers become aware of such
congruency. In some cases, congruency may be obvious upon exposure to an extension, but more
often the introduction of a new product is accompanied by various communication vehicles (e.g.,
advertising, packaging) designed to provide an organizing framework for interpreting the brandspecific associations between the parent brand and the extension product (Batra, Aaker & Myers
1995). Likewise, favorable consumer evaluations may be obtained by providing information in ads
regarding the bases for fit between a parent brand and its extension (Chakravarti, et al. 1991).
Curiously, the role of marketing communication in facilitating acceptance of brand extensions has
received little attention in the marketing literature (see Boush 1993, Bridges et al. 2000, Lane 2000).
Prior research suggests that goal-oriented communications play an important role in
establishing linkages among products. Simonson & Tversky (1992) found that an individual can adapt
to constraints imposed by the context of “… available alternatives by fitting goals to the information
9
encountered …,” that is, external information such as advertising may influence or act as a reminder
of which goals are salient. Marketing communications that establish shared goals directly or
indirectly should facilitate the cognitive and affective transfer from the core product to the extension.
It should be possible for marketing communication to at least strengthen, if not create, the linkages
between the core and the extension categories. Thus, it is reasonable to hypothesize communication
effects similar to extension congruency main effects stated in H2a to H2d. However, there are other
reasons grounded in prior empirical research to expect such communication effects.
Boush (1993) demonstrated that when brand slogans, used to introduce new extensions, focused
on salient product attributes that were similar to those of the core product it resulted in positive
evaluations for those extensions that were more similar to the core product. However, the focus of the
Boush study was on fictitious brands and product attributes. Such research, while clearly
demonstrating the potential importance of marketing communications in positioning a brand extension
as similar to a core brand, fails to capture the richness of consumers’ existing cognitive structures
associated with well-known, highly familiar brands. There is a need to focus on existing well-known
brands and the impact of goal congruent advertising messages rather than mere slogans associated
with a fictitious brand created in the context of a laboratory study.
Indeed, Bridges, et al. (2000) investigated the impact of a relational communication strategy on
brand extensions that were perceived by consumers to possess a high degree of fit with the core brand.
These researchers found that the most effective communication strategy for the extension focused on
the salient parent brand associations, which served to elicit associations that improved the consumers’
perceptions of the fit between the parent and the extension. Although instructive, this research did not
examine the differential impact of goal congruent and incongruent extension or the impact of different
communication on the perceived fit, attitude and purchase intent of an extension. Further limiting the
Bridges, et al. (2000) study was its use of generic product categories rather than actual brands. Thus, to
2These measures will be discussed in the section on Dependent Measures.
10
the extent that this study found communication effects it did so within conditions that are likely far
weaker than would be the case when communications involve information about a brand extensions
that focuses on the characteristics and goals associated with a well-known brand.
Lane (2000) also examined the effects of communication on brand extensions and did so in the
context of incongruent extensions. This researcher examined the differential impact of repeated
advertising exposures on perception and attitudes toward incongruent extensions, using messages that
focused on either peripheral cues or brand benefits. This study found that moderately incongruent
extensions benefited from numerous exposures to both peripheral and benefit brand associations, that
is, that communication had the potential to overcome at least some of the perceived incongruency
between the core brand and an incongruent extension. For extremely incongruent extensions, repeated
exposure to advertising messages with brand benefit associations reduced the perceived incongruity of
the extension category. This effect was not present for advertising that used peripheral cues to
communicate extremely incongruent extensions. Thus, the few studies that have examined
communication effects within a brand extension context suggest that communication can influence
consumers’ perceptions of the brand extension, especially when the message focuses on explicit brand
associations. While these studies are useful and suggest an important role for marketing
communication in determining the success of brand extensions, they did not examine the differential
impact of goal congruent and goal incongruent messages on the new product introduction strategy.
Prior research on communication strategies for brand extensions has tended to focus on the
main effects of the communication or the main effects of the extension type. It is likely that there is an
interaction of goal congruency with respect to perception of the core brand itself and goal congruency
with respect to marketing communication for the extension. When an extension is goal-congruent with
the core brand, the degree of congruency in a message should have a differential impact on the
cognitive and affective transfer across categories. In addition, even if a brand extension is incongruent
with the goals associated with the parent brand, communication strategies may create links that would
11
otherwise not be present. Thus, a communication strategy might indicate to consumers how the
brand’s goals and the extension are related even if not immediately obvious from the product category
into which the extension is introduced.
It is unlikely that the effect of a goal congruent/incongruent brand extension and the effect of a
goal congruent/incongruent advertising message will be additive, though empirical research to date
offers little guidance with respect to the relative strength of main effects and simple main effects. It
likely that product congruency will dominate communication effects. Congruent advertising messages
should not compensate for products that are inherently goal incongruent. It is likely that goal
congruency between products may compensate for an otherwise goal-incongruent communication
strategy and vice-versa. However, it is not unreasonable to expect that these effects will not be
symmetrical, that is, that the effect of product congruency/incongruency will be stronger than the effect
of message congruency/incongruency. Hence, it is likely that an interaction will be present. Thus:
H3:
Consumers exposed to a goal-congruent extension and a congruent message will
have:
a: higher goal-related knowledge (e.g., ideals, goodness-of-fit) and a closer fit (e.g., overall
perceived similarity, manufacturing similarity),
b: more readily accessible knowledge and attitudes (as evidenced by a faster
reaction time), and
c: a higher purchase likelihood between the extension and the core product
than consumers in the other three conditions. This is followed by the goal congruent
extension with an incongruent message, which is followed by the goal incongruent
extension and congruent message, which in turn is followed by the goal incongruent
extension and incongruent message.
H3d:
Given a positively evaluated brand, those exposed to a goal-congruent extension and who
receive a goal congruent message will have more positive attitudes toward the extension than
those exposed to a goal congruent extension and a goal incongruent message. (The same
order effects as stated in H3 applies to the order of attitudinal preference.)
An open question is whether advertising has a general effect regardless of its congruency with
the goals associated with the core product or the degree of congruency between the product and the
extension. There is little research to guide hypotheses generation on this issue in the context of brand
12
extensions. Marketing communication for a brand can suggest a relationship between two products
even if this would contradict the beliefs that a consumer may form without such information (Batra,
Aaker, & Myers 1995). Any communication, regardless of congruency, might be assumed to have the
ability to stimulate elaboration, resulting in some links being made across product categories.
MacInnis, Nakamoto, & Mani (1992) found evidence of this effect in an exploratory study where
consumers were capable of making links, however abstract or obscure, between seemingly
noncomparable products. Advertising may act as a cue to facilitate the occurrence of such associations
while defining the relationships between noncomparable products (c.f., Bridges, et al. 2000). Thus:
H4: Consumers exposed to marketing communication for a brand extension will have:
a:
higher goal related knowledge (e.g., ideals, goodness of fit) and a closer fit (e.g., overall
perceived similarity, manufacturing similarity).
b.
more readily accessible knowledge and attitudes (as evidenced by a faster RT) and
c.
have a higher purchase likelihood than consumers who are not exposed to any
marketing communication.
The sections that follow report the design and results of a study to test these hypotheses.
METHOD
Research on brand extensions requires extensive pre-testing to develop potential extensions and
to identify brands that will satisfy the requirements of the experimental manipulations while still
providing control for extraneous factors. Likewise, the manipulation of goal congruency is linked to
the types of brands and product categories selected. With this in mind, two pretests were conducted to
select products, identify brand names, and develop both the goal manipulation and the message stimuli
suitable for manipulation and hypotheses testing. Since the use of brand extensions in the marketplace
is based on the premise that individuals are familiar with the parent brand it was important to select
product categories and brand names that were familiar to the subjects involved in the study.
Pretest – Goal Congruency Manipulation. The first step in the pretest was to identify two
brands and two potential extension categories for each of the two brands. A sample of undergraduate
13
students, similar in composition to that used in the main study, was asked to generate and evaluate the
relative goal congruency of brand extensions for a variety of brands. For each brand a goal-congruent
extension and a goal-incongruent extension was identified. This was done through a series of in-depth
interviews and focus groups to develop a list of potential brand names, product categories, and the
goals that consumers associate with them. Numerous iterations of this process resulted in the selection
of Reebok and Benetton as the two brand names and dress leather shoes and cotton spandex athletic
wear as the two product categories. The goal-congruent extension for Benetton was dress leather shoes
and for Reebok was cotton spandex athletic wear. The goal-incongruent extensions simply involved a
reversal of the brand names and the product categories to which they were extended -- Benetton to
athletic wear and Reebok to dress leather shoes. An important point is that the subjects in this pretest
suggested the degree of goal congruency, thus, ensuring that goals were established from the
consumer’s perspectives not the researcher’s perspective.3
Next, a new sample of 45 students was randomly assigned to 1 of 4 possible extension
categories. These subjects were asked to rate how well the extension fit with the core product, rate the
presence of ideal attributes, and rate the level of similarity between the extension and the core product
on several dimensions. Following the completion of these measures 4 all subjects were also asked to
list the goal(s) that they associated with the brand. The results confirmed the focus groups and the indepth interview results.5 Thus, the use of these two product categories as goal-congruent and goalincongruent was empirically supported. The objective of this last step was to further ensure the degree
3Further evidence that the various combinations of products and brands are appropriate representations of goal congruent
and goal incongruent extensions is found in the market place. Shortly after data for this study were collected Nike attempted
to extend its product line by offering dress leather shoes. This extension failed in the market and was withdrawn. In
addition, since the completion of this study Benetton has successfully introduced leather dress shoes and Reebok
successfully introduced cotton Spandex athletic wear.
4The measures used in the pretest are the same as the measures used in the main study. To avoid redundancy, the measures
are described in the next section and in Table One.
5The goodness-of-fit measure for the two Benetton extension categories was significantly different (M=5.0 v. 3.2, t43=4.01 ,
p<.01) as were the two Reebok extension categories (M=5.6 v. 3.9, t 43 =3.53, p<.01). The ideal measure was also
significantly different for the Benetton and the Reebok extension categories (M=6.1 v. 2.3, t 43=8.16 and M=6.6 v. 4.4,
14
of goal congruency that consumers used to link a brand name to seemingly unrelated product
categories.
Pretest – Message Congruency Manipulation. The second pretest was designed to develop a
set of messages that were congruent or incongruent with the brand meaning and the goals of each core
product. Congruency was defined in terms of whether subjects perceived the message to have an
appropriate fit with the marketing communication strategy of the parent brand. The executional
elements of the messages were as similar as possible to avoid confounding based on differences in the
message layout. The same messages were used for both brand names, changing the brand name to fit
the respective brand. Since the products were gender–specific there were two sets of messages for a
total of sixteen messages. The messages were developed through this process were ultimately produced
as finished color print ads by a professional graphic illustrator (see Appendix 2 for an example of a
print ad used as the message stimulus).
Verifying messages as goal-congruent and goal-incongruent with the core product involved the
same two-step process as in Pretest One. First, a sample of students was brought together for a series
of in-depth interviews in which they were asked to explain how well the message fit with the core
product and its advertising strategy. The criteria used to judge congruency included how suitable the
message was in communicating the goal associated with the core product. Subjects were also asked to
evaluate the degree to which each message exemplified the type of advertising that each brand typically
uses for its products. For example, the congruent Reebok ad featured a serious cyclist in a race wearing
full cycling gear including Reebok's athletic wear. In the goal-incongruent version, the ad featured a
cyclist wearing Reebok clothing but instead the focus was on fashion rather than athleticism. The
second step in the process employed a new sample of 60 students to verify the degree of congruency of
the messages. A difference of means test was run within each brand to determine whether the
t,43=3.46, p<.01). Other measures were taken and were also significantly different but, for the sake of brevity, only a subset
is reported here.
15
congruent message was perceived as a better fit with the type of advertising that the core product uses.6
The pretests provided empirical evidence that the proposed extensions and marketing communications
were perceived as relatively congruent with the goals of the parent brand by a group of subjects
representative of those used in the main study.
THE MAIN STUDY
Experimental Design. The main study employed a 2x2x3 between subjects design. The first
independent variable was extension congruency (goal congruent vs. goal incongruent). The second
independent variable, brand (Reebok vs. Benetton) provided a means for examining brand-specific
effects as well as a replication if brand specific effects were not present. Thus, we used two brand
names with two extension categories (dress leather shoes and athletic wear) for each brand. The same
two extension categories were used for both brand names, but they were reversed for the goal
incongruent condition. The third independent variable was a three–level message factor (congruent vs.
goal-incongruent vs. no message). The no message condition was used as a control to isolate the
general effect of advertising without regard to content.
Dependent Measures. The literature on brand extensions reviewed earlier in this paper was
examined to identify measures of product similarity (see Martin & Stewart 2001 for a review of these
measures). The perceived feature-based similarity measures used in the research are based on Aaker &
Keller (1994), Boush & Loken (1991), Broniarcyzk & Alba (1993) and include two measures of
overall perceived similarity and one measure of manufacturing similarity. The three usage-similarity
measures are based on Ratneshwar & Shocker (1991) and Chakravarti, et al. (1991). The brand
concept consistency measures are derived from Park, et al. (1991) and Shavitt (1989) and include six
measures of attitude toward the parent brand and the category. Measures of parent brand attitudes are a
6 Some examples of the types of measures used are: "how similar is this message to the type of advertising
Benetton/Reebok uses" (anchored by 1=not at all similar to 5= very similar) and "how good of an example is this message
of the type of advertising that Benetton/Reebok does for its other products" (anchored by 1= poor example to 5= excellent
example). Congruency measures were significantly different when comparing the congruent message to the incongruent
16
variation of the affective measures developed by Fazio (1986) and are used to examine the similarity of
the affect (attitude) evoked by products (For a description of the dependent measures, see Table One).
_____________________________
Insert Table One about here
_____________________________
Two of the most common and useful of the goal-derived measures are ideals and goodness-offit (Barsalou 1985, 1991). Ideals refer to the attributes of products or brands that are most closely
associated with the goal that forms the nexus of the category. Similarly, measures of goodness-of-fit
are obtained for a particular context, the extent to which the products are perceived to be associated
with the goal-derived category, thus providing a similar outcome. Purchase intention with respect to
the brand extension was also measured. All dependent variables are composite measures of two or
more variables. Measures of internal consistency were compatible with the use of composite measures
(see Table One). Finally, reaction time (RT) for the knowledge and evaluative measures was used to
assess differences between the congruent and the incongruent extensions with respect to accessibility
and transfer of both knowledge and attitudes. Accessibility is a process measure that establishes the
strength of the link between the extension and the parent brand (Fazio 1986). A strong link between a
congruent extension and a core product should facilitate retrieval of the information and attitudes held
for the brand upon presentation of the new extension. On the other hand, an incongruent extension
should require consumers to spend more time processing information about the extension since strong
preexisting associations are not readily accessible.
Control Variables. Several variables designed to provide information about the subjects’
familiarity and experience with the brands and product categories were also obtained (see Table One).
Seven measures of familiarity and expertise with the brand, the product category, and the purchase
location were used. Each subject’s familiarity with each brand was then evaluated. Since brand
message within each brand (t= 6.87, t=5.21, t=6.13, t=4.94; p<.01, df=57). Students were also asked to write down the
goal(s) that they associated with the extension and the ad. Results further confirmed the goal congruency of the message.
17
familiarity is critical to evaluating a brand and assessing its salient goal (Broniarcyzk & Alba 1994),
subjects who were not familiar with the brands were not included in the study. Each subject’s
familiarity with each brand was then evaluated. The composite measure of familiarity had a bimodal
distribution that provided guidance to determine which subjects were categorized as “familiars” and
which were categorized as “unfamiliars”. Measures of goal congruency for the extension and the
message were obtained as manipulation checks (see Table 1).
Sample. The final sample consisted of 256 subjects drawn from the student populations of
three universities (56% male and 44% female). The product categories and brand names used in the
study have a high degree of familiarity within this target group. The population from which the subjects
were selected reported that they were regular users and purchasers of Reebok and Benetton products.
They also reported having extensive knowledge about the advertising for these products and the types
of stores where the products were sold.
Experimental Procedure. All subjects were randomly assigned to one of the twelve
experimental conditions by means of a subject scheduler in an interactive computer program, Micro
Experimental Lab (MEL) (Schneider 1990). Goal-congruency was manipulated through a twoparagraph description of the new extension product that included the relevant goal (see Appendix 1).
Subjects were told they were part of a marketing study designed to select the next line of new products
being considered by either Benetton or Reebok. The product description and goal-congruency
manipulation developed in Pretest One used a procedure similar to that used in other research on
consumer goals (e. g., Huffman & Houston 1993). Subjects were also given a message (developed in
Pretest 2, see Appendix 2 for an example) for the respective product (except in the “no Message”
condition). To control for elaboration, they were given two minutes to view the information.
All dependent measures were obtained via MEL so that reaction time (RT) measures could be
taken to determine knowledge and attitude accessibility for the transfer process (see Table One for
additional information on the reaction time methodology). Reaction time measures were taken as
18
subjects answered each of the dependent measures. The keyboard was covered except for the one to
five number keys. The computer measured the speed with which each question was answered.
Subjects were instructed to respond to each question as quickly as possible. First, they were given a
series of practice trials to reduce the variability in the response data. This was followed by a set of filler
questions to get a baseline speed of responding for each subject (Fazio 1990). This methodology is
consistent with Morrin’s (1999) study in brand extensions.
The order of presentation of the dependent measures was designed to ensure that exposure to
the knowledge measures did not influence subjects' attitudes toward the core and the extension.
Affective measures were taken first followed by the knowledge measures. After finishing the
interactive portion of the experiment, subjects were asked a series of in-depth questions as
manipulation checks on the extension and message congruency conditions. Finally, subjects were
debriefed and it was evident that they were made aware that the study was concerned with the
evaluation of specific brand extensions but were not aware that goal congruency was the primary focus
of the study.
ANALYSES AND RESULTS
An initial test for the effect of brand name and differences in the three student populations produced no
significant differences for any of the dependent measures. Hence, the data were collapsed across the
two brand names and the three populations for all other analyses, creating a 2 by 3 between subjects
design with extension congruency (goal-congruent vs. goal-incongruent) and message congruency
(goal-congruent vs. goal-incongruent vs. no-message) as the independent variables.
Manipulation Checks. The extension congruency manipulation check showed a significant
difference between the goal congruent and the goal-incongruent extensions (M=4.52 vs. 2.38,
F1,249=67.62, p<.0001, =.48). The manipulation of message congruency was also successful (M=3.52
vs. 2.61, F1,167=4.06, p<.03, =.15). A second manipulation check for both the extension and message
congruency involved analysis of verbal protocols (questions used in the depth interviews are in Table
19
1). The purpose was to confirm that the goal(s) and brand meaning(s) were similar to those identified
in Pretests 1 and 2 as well as to further uncover the transfer process in each condition. Allowing all
respondents two minutes to view the ad and the experimental manipulations controlled elaboration.
The result was a difference in elaboration across the various conditions that could not be attributed to a
difference in time to process. Instead this difference can be attributed to the congruency manipulation.
This view is consistent with MacInnis & Jaworski (1989) who argued that consumers engage in
different levels of processing based on a number of factors, including whether the ad contains affectladen stimuli and respondents’ motivation.
A content analysis conducted by two judges’ blind to the hypotheses indicated that subjects in
the goal congruent condition had longer, more detailed elaborations than subjects in the goalincongruent condition. (Intercoder agreement was 82% with differences resolved by discussions
between the two coders.) Subjects used attribute level goals (i.e., comfortable shoes; colorful clothing)
or benefit level goals (i.e., makes exercising easier; stands out in a crowd) as a way to tap into their
goal hierarchies. Using the laddering technique, these individuals were able to verbalize how seeking
attributes lead to the fulfillment (or not) of a sought after benefit which in turn resulted in fulfilling a
more abstract goal or value, (Little 1989). For example, Barsalou (1991) finds that individuals can
access a goal-derived category at different levels of specificity that is consistent with the Means-end
Chain framework (Reynolds & Guttman 1988) as well as the goal literature in general (Austin and
Vancouver 1996). In addition, 93% of the verbal protocols for the subjects in the goal-congruent
condition identified similar goals for the core and the extension. For example, an individual would start
by stating that “having brightly colored clothing” was the reason for buying Benetton clothing, then
they would elaborate by adding the desire “to have high quality, well styled clothing” that is “socially
acceptable”. Such sequences demonstrate a goal hierarchy with concrete goals leading to more abstract
goals. See Table Two for examples of the goal hierarchies elicited in the verbatims for all conditions.
______________________
20
Insert Table 2 about here
________________________________
Subjects were also more likely to attach attributes, both concrete and abstract, to the goalcongruent extension. For example, they were more likely to associate many different colors, wellmade stitching, well-fitting, and so on with Benetton’s dress leather shoes than with Benetton’s cotton
Spandex athletic wear. The same pattern emerged for the Reebok athletic wear versus dress leather
shoes. Those brand-specific associations included information about the core product that was
transferred across product categories in the goal-congruent but not in the goal-incongruent condition,
consistent with Broniarcyzk and Alba (1994). Subjects in the goal-incongruent condition were less
likely to provide any elaboration about shared goals. Eighty-four percent of subjects identified
dissimilar goals associated with the two products. They described why they did not like the extension
and why it did not make sense. This is further evidenced in the sample goal hierarchies for Benetton
athletic wear and Reebok dress shoes found in Table Two.
A further breakdown by the message condition revealed an interesting pattern of results. In the
congruent extension condition, the degree of message congruency had some influence on whether a
shared goal was identified for the two products. In the goal-congruent message group, all subjects
offered goals that were shared by the two products. In the goal-incongruent condition message group,
10% cited goals that were not shared by the two extensions (12% in the no-message condition). The
reverse pattern appeared in the goal-incongruent extension condition. The effect of goal congruency in
the message appeared to be mediated by the degree of extension congruency. The results from the
analysis of verbatims provide support for the extension and message congruency manipulations and the
role of goals in the transfer of attitudes and knowledge across non-comparable product categories.
Goal-Derived versus Perceived Similarity Measures (H1). To test H1, a two-step process
was used. First, a set of regression models was developed to compare the traditional perceived
similarity approaches to the goal-based framework. The goal-derived measures of ideals and goodness-
21
of-fit were used as independent variables to predict attitude toward the extension (Aextn) and purchase
intent in the first regression model. The second regression model used perceived similarity and usage
similarity as independent variables to predict Aextn and purchase intent. In sum, the goal-derived
measures explain more variance in both dependent measures. Maddala (1988) has shown that the
amount of variance explained (R2) is a useful approach for comparing models involving the same
dependent measures (AEXTN and Purchase Intent) and the same number of independent variables (two).
________________________
Insert Table 3 about here
_________________________
In addition, a more robust test of the differential explanatory power of various typicality
measures was conducted to test for any unique predictive power after accounting for variance
associated with the goal-related measures. This method is consistent with that used by Barsalou (1985)
in his comparison between goal-derived and taxonomic measures of typicality. Each independent
variable was correlated with each dependent variable after the other three measures were partialed out.
This was done for the goal-congruent and the goal-incongruent conditions separately. As shown in
Table 3, the original relationship between the typicality measures almost completely disappears in the
goal-congruent condition. In the goal-incongruent condition, the typicality measures and the goalderived measures accounted for significant amounts of the unique variance. Thus, goal-derived
measures were found to be better indicators of “fit” than perceived similarity measures used in past
brand extension research in the goal congruent condition, providing additional support for H1. These
findings are consistent with Martin and Stewart (2001). This sets the foundation to further test the goalbased concept as the organizing framework to transfer brand meaning from the parent brand to the
proposed extension category.
Extension and Message Congruency (H2).
Dependent Measures. Table 4 demonstrates the consistent support for both the extension and
22
message congruency main effects (H2a-H2d) for all dependent measures. For the extension
congruency, the goal-related knowledge, typicality, and affective measures are significant. Likewise,
for message congruency, the goal-related measures, the overall perceived similarity and usage
similarity measures and Aextn are significantly different. Finally, purchase intent had a strong extension
congruency but not message congruency main effect.
___________________________
Insert Table 4 about here
___________________________
Reaction Time Measures. The results of the dependent measures provide a glimpse into the
structure of brand information for extensions that are congruent and incongruent. In addition, the RT
results, shown in Table 4, provide a glimpse as to the process that subjects use to categorize and
evaluate the different extension categories. For all the RT measures associated with the categorization
dependent variables, subjects responded faster for the congruent extension versus the incongruent
extension. The speed with which subjects rate the congruent extension as a better fit with the parent
brand is significantly higher for all measures except purchase intent compared to the incongruent
extension (see Table 4). This demonstrates that subjects appear to engage in heightened processing of
the incongruent advertising messages consistent with Meyers Levy, Louis & Curren (1994). The nonsignificant RT measures for purchase intent is consistent with the belief that knowledgeable consumers
would know equally quickly whether they would buy or not the extension, regardless of its congruency.
For the message congruency RT measures the results are consistent with the extension
congruency results (Table 4). The congruent message facilitated the transfer of knowledge and attitude
from the parent brand to the new extension. The exceptions were the lack of significant differences for
manufacturing similarity, attitude toward the brand and purchase intent. Since the extension categories
are physically dissimilar to the parent brand, the finding of non-significance is not surprising. The nonsignificant difference in RT for attitude toward the brand and purchase intent implies that the degree of
message congruency does not inhibit the affective transfer process. A comparison of effect sizes
23
between the extension and the message congruency manipulations indicates that the former may have a
stronger influence on the dependent measures. Finally, the analyses of main effects appear to obscure
some important interactions between the type of extension and the type of message.
Interaction of Type of Extension and Type of Message (H3). As expected, an analysis of the
interaction between extension and message congruency resulted in statistically significant interaction
effects. The analysis shows that there was a significant interaction effect on the goal-related measures,
the perceived similarity measures and the Aextn measures as well as RT measures (see Table 4). In
order to better understand these interactions, simple main effects were examined (see Table 5 for the
contrasts). First, we discuss the results of the structure and process measures for the goal-congruent
extension conditions followed by the incongruent extension conditions.
____________________________
Insert Table 5 about here
____________________________
Congruent Extension Conditions.
Dependent Measures. The hypothesized simple main effects in H3a through H3d suggest that
an incongruent message will have a detrimental effect on a goal-congruent extension category. In
general, the results for these simple main effect tests provide support for H3a, H3b, and H3d
(knowledge and attitudinal measures). A goal-incongruent message produced lower levels of
knowledge transfer (M=4.0 v. 4.7, M=4.3v. 4.7, M=3.9 v. 4.3 and M=4.1 v. 4.5; goodness-of-fit,
ideals, use similarity, and manufacturing similarity, respectively), lower overall perceived similarity
(M=3.4 vs. 4.0), and less positive Aextn (M=4.2 v. 4.6) than a goal congruent message (see Table 5 for
F-statistics). In contrast, AB and purchase intent were not significantly lower when subjects were
exposed to a goal-incongruent message (H3c was not supported). Thus, a poor communication
strategy is not enough to create brand dilution effects or to “hurt” the likelihood that a consumer will
purchase a goal congruent extension.
Reaction Time Measures. As predicted, there were no significant differences in RT measures
24
for the related dependent variables (see Table 5). This provides additional support for the primacy of
the effect of extension congruency on the transfer process. In other words, a congruent extension
facilitates the transfer of knowledge and affect from parent to extension category. The differences for
all the related RT measures were non-significant resulting in a lack of support for H3b and H4b (see
Table 5). The pattern of results for the RT measures, with a few exceptions, is consistent with the
hypothesized transfer process of knowledge and attitudes for the goal congruent extension. This
transfer occurs regardless of whether the message is congruent, goal-incongruent, or whether there is
no message, though the goal-congruent message has a facilitating effect and the goal incongruent
message may hinder transfer.
A second set of comparisons involves the test of the order of effects stated in H3a through
H3d. A goal-incongruent message was found to perform no better than no message at all on the
goodness-of-fit, overall perceived similarity, AB, and purchase intent measures (see Table 5). However,
the goal-incongruent message did have a significant influence on ideals, usage similarity, and Aextn
(M=4.3 v.3.3, M=3.9 v. 3.6, M=4.2 v. 3.9; respectively). This implies that just getting information
about the extension is more important than receiving no information at all when an individual is
attempting to link information about the attributes of a core product and the manner in which the
product is used, with that of the proposed extension. The information that the goal-incongruent
message presents, regardless of extension congruency, also improves the evaluation of the extension.
This probably occurs because exposure to the communication, even if it is goal-incongruent, causes the
message recipient to begin the categorization process. This is consistent with Fiske & Neuberg’s
(1990) findings on impression formation and category-based versus piecemeal processing.
Goal-Incongruent Extension Conditions.
Dependent Measures. The hypothesized simple main effects in H3a through H3d suggest that
a congruent message will produce positive effects on goal-related knowledge, perceived similarity,
attitudes, and purchase intent for a goal-incongruent extension. With minor exceptions, the results did
25
not support H3a through H3d. Although the congruent message generally performed significantly
better than the goal-incongruent message, it did no better than the no-message condition in the goal
congruent extension condition and was significantly lower than the performance of any of the message
conditions within the congruent extension condition. In sum, congruent messages did perform better
than incongruent messages for a goal-incongruent extension, but do not appear to compensate for the
incongruency of goals associated with the core product and its proposed extension (see Table 5). These
results suggest that a poor product selection strategy overrides a good message strategy.
Reaction Time Measures. For the most part the RT measures were significantly different
across conditions providing support for H3b and H4b (see Table 5). The comparison between the
congruent and incongruent message groups shows subjects reacted significantly faster to the congruent
message for all dependent measures except AB and purchase intent (M=2.44 v. 2.51, M=2.44 v. 2.51,
M=2.42 v. 2.48, M=2.43 v. 2.50, M=2.44 v. 2.48, M=2.42 v. 2.51; goodness-of-fit, ideals, overall
perceived similarity, use similarity, manufacturing similarity, and Aextn; respectively). The results are
also significantly different when we compare the congruent message to the no-message condition.
Thus, the congruent message facilitates transfer of information across product categories and the goalincongruent message seems to inhibit this transfer process much like the results in the congruent
extension condition. In sum, message congruency has little impact on a congruent extension but does
have a facilitating effect on the transfer process for a goal-incongruent extension. This is likely to be
the result of the communication facilitating initiation of the categorization process. Thus, the prior
exposure to the congruent communication reduces the perceived incongruency when exposed to the
goal-incongruent extension, consistent with the findings of Lane (2000) and Klink & Smith (2001).
DISCUSSION
The results of this study provide strong support for the goal-derived categorization framework
as a general theory of transfer of brand meaning across product categories. The present study also
offers results based on process measures that complement the findings of earlier studies that focused on
26
measurement properties of goal-derived categorization models. This theory suggests that individuals
organize brand information and attitudes in memory around goals. To the extent that products using
the same brand name share goals, the transfer of knowledge and attitudes is facilitated. The present
findings also clearly demonstrate the primacy of product strategy over communication strategy in the
context of brand extensions. In other words, poor selection of the extension product overrides a good
communications strategy, but a poor communication strategy is not necessarily a death knell for a good
selection of an extension. These results are clearly consistent with prevailing wisdom in the marketing
profession that the best advertising is a good product (Lane 2000, Loken & Roedder John 1993,
Roedder John, Loken & Joiner 1998, Romeo 1991).
The results obtained for the RT measures suggest that goal congruency facilitates the
accessibility and transfer of brand meaning for use in responding to questions about a proposed
extension. In addition, the types of elaborations made by subjects during the post experimental
protocols were consistent with the theory of goal-derived categorization. Individuals in the goalcongruent condition focused on the links between the extension and the core product while those in the
goal-incongruent condition focused on what was wrong with the proposed extension as well as what
they perceived the “ideal” for that particular brand. Thus, subjects in the later condition tried to make
sense of information by piecing together information from the experimental stimuli with other types of
information in memory, hence the longer reaction time measures. The longer RT measures are
consistent with Fiske & Neuberg’s (1990) Continuum Of Impression-Formation model.
The resulting category structure fits the description of Barsalou’s (1983) ad hoc categories and
is consistent with Fiske & Neuberg’s (1990) re-categorization and piecemeal processing. These
findings are also consistent with the view that exposure to a goal-incongruent extension gives rise to
the construction of an attitude toward the new extension (c.f., Fazio 1986, 1990). The construction
process is evident in both the measures of AB and Aextn and their related RT measures. These findings
are consistent with the attitude (Fazio 1986) and categorization literature (Barsalou 1983, 1985; Fiske
27
& Neuberg 1990). The empirical results also suggest that goal congruency facilitates the transfer of
brand meaning across product categories (c.f. Novick 1988, Morrin 1999).
For marketers, the ultimate question is whether consumers will choose their products. In our
study, subjects were more likely to consider purchasing a goal-congruent extension compared to a goalincongruent extension. Surprisingly, marketing communication (as presented in our study) did not
differentially influence the likelihood of selecting either a goal-congruent or a goal-incongruent
extension. Unlike Lane (2000), subjects in this study were presented both congruent and incongruent
ad exposures. The findings for Aextn are similar to those for purchase intention. Goal congruency
influenced the evaluation of the parent brand that is consistent with the findings in Lee (1995). In her
study, message congruency had a significant effect in the comparable extension condition (line
extension) but not in the non-comparable extension condition (brand extension). In contrast, AB was
not influenced by goal congruency within each extension condition. These findings provide support for
the lack of brand dilution effects in the brand management literature (e.g., Keller & Aaker 1992, Loken
& Roedder John 1993, Roedder John, Loken & Joiner 1998, Romeo 1991).
Finally, the goal-derived framework proposed in this study demonstrated, through empirical
support for H1, that the traditional typicality measures used in the brand extension research are better
linked within the goal framework, consistent with Loken & Ward (1990) and Martin & Stewart (2001).
This framework also finds support for both types of extensions and numerous goals and sub-goals. The
two brands and product categories are very different and the study found empirical support for both,
thus, demonstrating that the goal framework can subsume the brand schema framework. Thus, the goal
congruency approach clearly shows that the consumer’s goals, not the brand name, are the organizing
framework that facilitates the transfer of brand knowledge and affect from the brand category to the
extension. Thus the perceived fit between the brand schema and the new product facilitates the transfer
of brand associations. This is also consistent with market-related examples of many failed extensions.
Limitations. Like most laboratory studies, the present study suffers from several limitations.
28
Because it examined only two brands and two potential extensions, the degree to which the results
generalize to other product categories and brands remains an empirical question. In addition, only
respondents who were already familiar with the core products were included in the study. Hence, the
differential effects of product familiarity were not examined. A further limitation is that product
descriptions rather than real products were used and only one exposure to a single print advertisement
was used to examine the effects of marketing communications. There could be different results in
response to actual products or multiple exposures to advertising (see Lane, 2000 for a discussion).
Exposure to both the product descriptions and the advertising was forced, so effects that might be
mediated by attention were not examined. These limitations provide some ideas for future research.
IMPLICATIONS AND FUTURE RESEARCH
Brand Meaning. The search for meaning as related to products has been shown to be an
intrinsic part of consumer behavior (Fournier 1998, Levy 1981). Our study suggests that consumers'
search for meaning is influenced by a purposive, goal–derived categorization process. This process
appears to facilitate the accessibility of and the transfer of brand meaning. Goal congruency manifests
an effect on a variety of quantitative measures including reaction time measures and in the verbatim
responses of subjects in this study. These results suggest that understanding individuals’ goals is
critical to place behavior in context. This view is consistent with research suggesting that a complete
understanding of behavior must begin with an appreciation of the purposiveness of the individual
(Ratneshwar, Mick & Huffman 2001, Pervin 1982). The present findings are also consistent with the
suggestions that studying the meaning of objects (i.e., brands), in terms of the goals they serve for the
individual, is a fruitful avenue of research (c.f. Austin & Vancouver 1996).
Some interesting questions are raised about the meaning of brands that might be explored in
future research. For example, some products are associated with multiple goals. For example, a
designer apparel brand such as Betsy Johnson can satisfy a consumer’s goals of “being seen as a
trendsetter,” “looking thinner, and hence good,” and also “conforming to societal norms of choosing
29
an expensive brand”. The nature of the brand meaning for such products is more complex than the
meanings associated with the products reported in this research. It would be useful to determine the
extent to which multiple goals are integrated or whether multiple goals dilute the brand meaning. In
addition, the effect of changing a salient goal associated with a product (such as the extension of
Listerine Dandruff Wash to Listerine Oral Care products, or that of Ivory Soap to Ivory Snow) would
also be an interesting area for future exploration.
Goal–driven Categorization. This study provides evidence consistent with previous
suggestions that goals influence the network of associations of objects in memory (Aaker & Keller
1990, Barsalou 1991, Chakravarti, et al. 1991). The empirical results offered in the present paper are
consistent with a related stream of research that has investigated the impact of product congruency on
the transfer of knowledge and affect from a product to a more general product schema (Mandler 1982;
Meyers–Levy & Tybout 1989). That research examined product congruency within a product category
rather than cross-category goal congruency that is the focus of the present work.
The Role of Marketing Communication. Marketing communication preceding the
introduction of a product extension does begin the process by which consumers assess similarity
between the parent brand and the extension. It can cause the message recipient to begin the
categorization process. A goal-congruent extension would need little support in terms of marketing
communication, whereas a goal-incongruent extension would need the support of a congruent message,
for the recipient to start perceiving similarity. An interesting theoretical question concerns the structure
of goal-incongruent brand meaning (knowledge and affect associated with a particular brand). The
process by which consumers form ad hoc categories and the evolution of these categories over time
would be a particularly interesting avenue for future research. It can be argued that a goal-congruent
message for a goal-incongruent extension can aid in the formation of stronger ad hoc categories.
Exposure to such communication repeatedly, over time, can possibly overcome the disadvantage of a
goal-incongruent extension. Though Lane (2000) does find support for the case of ad repetition and ad
30
content on consumer perceptions of incongruent extensions, exploration of how this affects the
formation and strengthening of ad hoc categories would be an interesting extension.
Identification of factors that influence the retention of specific cognitive and affective elements
of brand meaning over time and the processes by which such categories become linked to goals would
also be useful. Further, it would also be interesting to examine how the individual deals with
information that is goal-incongruent with an existing goal–derived category. Such information may not
be readily assimilated into an existing category (Mandler 1982). It may be completely forgotten or, if a
well-known cue (i.e. brand name) is used there may be more effort expended to make sense of the
information thus forming an ad hoc category (Martin and Stewart 2001).
The present findings on the role of marketing communication (in the transfer of knowledge
from the parent brand to the extension) are consistent with Fiske & Neuberg’s (1990) Continuum of
Impression Formation. According to Fiske & Neuberg, “People seem to use a continuum of
impression formation process, ranging from more category-based or schematic processes to more
attribute-based or individuating processes”. Consumers will use initial categories when that is all they
have, i.e., category label only (in this study, this condition is similar to the goal congruent extension, no
message condition), or when data are easily categorized. If sufficiently motivated to continue,
individuals attempt to confirm these initial categories. Category confirmation is generally successful (a)
if there is a label and category consistent data (similar to the goal congruent extension, congruent
message condition), (b) if the data are mixed, or (c) if the data are irrelevant to a strong category. If
category confirmation fails, people re-categorize, generating better-fitting categories, sub-categories or
exemplars. In re-categorization, (a) if the category is weak, even irrelevant data will undermine it (not
surprising, and consistent with our results that a goal incongruent extension suffers, making the
selection of the extension category very important) and (b) clearly inconsistent data will undermine
most categories (goal incongruent message will undermine both goal congruent and incongruent
extensions) Finally, when it is not easy to re-categorize, an individual will proceed piecemeal, attribute
31
by attribute, through the data (similar to the formation of ad hoc categories explained in our
framework). Hence the concept of goal congruency in brand extensions and marketing communications
is consistent with prior well-established research on impression formation in social cognition.
Brand Extensions. The findings suggest that brand-to-goal associations facilitate the transfer
of brand meaning from a core product to an extension. Little prior research has examined the extent to
which the transfer of brand meaning influences purchase intention. Our results suggest that transfer is
associated with an increase in purchase intention, which implies that goal congruency is an important
factor for brand extension success. Hence, marketing managers should consider the degree to which
the product category shares a goal or goals with the core product. In contrast, goal congruency in the
communication strategy alone does not have the same impact on purchase intention although it does
impact the transfer of brand meaning to a goal-congruent extension. Such suggestions of common
goals in a communication strategy will be effective when consumers associate the goal with the new
product. Thus, goals tend to mediate response to communication as well as response to a product
category.
Future research should investigate the impact that multiple exposures of goal-congruent and
goal-incongruent advertising messages could have on the new product introduction strategy. This
would help understand whether multiple exposures of goal-incongruent messages result in a
repositioning of the brand or can the distance that is created by the incongruent extension and repeated
incongruent messages result in stretching the brand meaning to include previously incongruent
extension into the brand meaning. Thus, the perceived fit of an incongruent extension has now
changed to fit with the brand meaning. Also of interest would be an understanding of the effect of
marketing communications on consumer perception of an extension with conflicting /competing goals
as compared to those of the parent brand (possibly a special case of a goal-incongruent extension).
32
REFERENCES
Aaker, David .A. & Kevin Lane Keller (1990), “Consumer Evaluations of Brand Extensions,” Journal
of Marketing, 54 (February), 27–41.
Austin, Jeffrey.T. & James B.Vancouver (1996), “Goal Constructs in Psychology: Structure, Process,
and Content,” Psychological Bulletin, 120 (3), 338-75.
Barsalou, Lawrence.W. (1983), “Ad Hoc Categories,” Memory and Cognition, 11 (May), 211–27.
_____________ (1985), “Ideals, Central Tendency, and Frequency of Instantiation as Determinants of
Graded Structure in Categories,” Journal of Experimental Psychology: Learning, Memory and
Cognition, 11 (4), 629–48.
_____________ (1991), “Deriving Categories to Achieve Goals,” In The Psychology of Learning and
Motivation: Advances in Research and Theory, 27, Academic Press, New York, NY.
Batra, Rajeev., David A. Aaker & John G. Myers (1995), Advertising Management, Fifth Edition,
Englewood Cliffs, NJ: Prentice-Hall.
Boush, David M. (1993), “How Advertising Slogans Can Prime Evaluations of Brand Extensions,”
Psychology and Marketing, 10(1), 67-78.
_________________ & Barbara Loken (1991), “A Process–Tracing Study of Brand Extension
Evaluation,” Journal of Marketing Research, 28 (February), 16–28.
Bridges, Sheri, Kevin Lane Keller & Sanjay Sood (2000), “Communication Strategies for Brand
Extensions: Enhancing Perceived Fit by Establishing Explanatory Links,” Journal of Advertising, 29
(4), 1-11.
Bronciarcyzk, Susan M. & Joseph W. Alba (1994), “The Importance of the Brand in Brand Extension,”
Journal of Marketing Research, 31 (May), 214–28.
Chakravarti, Dipankar, Deborah J. MacInnis & Kent Nakamoto (1991), “Product Category Perceptions,
Elaborative Processing and Brand Name Extension Strategies,” In Advances in Consumer Research,
17, Provo, UT: Association for Consumer Research, 910–16.
Farquhar, Peter H., Paul Herr & Russell Fazio, R. (1989}, “On the Power and Functionality of
Attitudes: The Role of Attitude Accessibility,” In Attitude Structure and Function, Pratkanis, et al.
(eds.), 153–80.
Fazio, Russell H. (1990), “A Practical Guide to the Use of Response Latency in Social Psychological
Research,” In Research Methods in Personality and Social Psychology, Vol. 11, C. Hendrick and M.S.
Clark (eds), Newbury Park, CA., Sage Publications, 74-97.
___________ (1986), “How Do Attitudes Guide Behavior?,” In The Handbook of Motivation and
Cognition: Foundations of Social Behavior, Robert M. Sorrentino & E. Thomas Higgins, (eds.), 204–
43.
33
Fiske, S.T. & Taylor, S.E. (1992). Social Cognition, second edition, NY: MacGraw-Hill.
________________ & Mark A. Pavelchak (1986), “Category-based versus Piecemeal-based Affective
Responses: Developments in Schema-triggered Affect,” In The Handbook of Motivation and
Cognition: Foundations of Social Behavior, Sorrentino, R.M. & Higgins, E.T. (Eds.), Guilford Press.
______________ & Steven L.Neuberg (1990), “A Continuum of Impression Formation, from
Category-based to Individuating Processes: Influences of Information and Motivation on Attention and
Interpretation,” In M.P. Zanna (ed), Advances in Experimental Social Psychology, Vol.23, New York:
Academic Press, 1-74.
Fournier, Susan (1998), “Consumers and Their Brands: Developing Relationship Theory in Consumer
Research,” Journal of Consumer Research, 24 (March), 342-373.
Goodman, Nelson (1972), “Seven Strictures on Similarity,” In Problems and Projects, N. Goodman
(ed.), NY: Bobbs-Merrill, 437-47.
Hebb, Donald O. (1955), “Drives and the CNS (Conceptual Nervous System),” Psychological Review,
6, 243-54.
Huffman, Cynthia & Michael Houston (1993), “Goal–oriented Experiences and the Development of
Knowledge,” Journal of Consumer Research, 20 (September), 190–207.
Keller, Kevin Lane & David A. Aaker (1992), “The Effects of Sequential Introduction of Brand
Extensions,” Journal of Marketing Research, 29 (1), 35-50.
Kirk, Roger (1995), Experimental Design: Procedures for the Behavioral Sciences, Wadsworth
Publishing, Monterey, CA.
Klink, Richard R. & Daniel C. Smith (2001), “Threats to the External Validity of Brand Extensoin
Research”, Journal of Marketing Research, (Summer), 326-32.
Lane, Vicki R. (2000), “The Impact of Ad Repetition and Ad Content on Consumer Perceptions of
Incongruent Extensions,” Journal of Marketing, 64 (April), 80-91.
Larkin, Jill (1978), “Processing Information for Effective Problem Solving,” Engineering Education,
70 (3), 285-88.
Lee, J.S. (1995), “Effects of Congruency Between Brand Advertising and Extension Category on
Consumers’ Perceptions of a Brand Extension: Moderated by Extension Comparability,” In the
Proceedings of the 1995 American Association of Advertisers, 118.
Levy, Sidney J. (1981), “Interpreting Consumer Mythology: A Structural Approach to Consumer
Behavior,” Journal of Marketing, 45 (Summer), 49–61.
Little, Brian R. (1989), “Personal Projects Analysis: Trivial Pursuits, Magnificent Obsessions, and the
Search for Coherence,” In Personality Psychology: Recent Trends and Emerging Directions, David M.
Buss & Nancy Cantor (eds.), NY: Springer-Verlag.
34
Loken, Barbara & James Ward (1990), “Alternative Approaches to Understanding the Determinants of
Typicality,” Journal of Consumer Research, 17 (September), 111–26.
_________________ & Deborah Roedder John (1993), “Diluting Brand Equity: The Negative Impact
of Brand Extensions,” Journal of Marketing, 57 (3), 71-84.
MacInnis, Deborah J., Kent Nakamoto & Gayathri Mani (1992), “Cognitive Associations and Product
Category Comparisons: The Role of Knowledge Structure and Context,” In Advances in Consumer
Research, 19, 260-67.
Maddala, G. S. (1988), Introduction to Econometrics, MacMillan, NY, 420–25.
Mandler, George (1982), “The Structure of Value: Accounting for Taste,” In Affect and Cognition:
The 17th Annual Carnegie Symposium, M.S. Clark & S.T. Fiske, (eds.), Hillsdale, NJ: Lawrence
Erlbaum Associates, 203–30.
Martin, Ingrid M. & David W. Stewart (2001), “The Differential Impact of Goal Congruency on
Attitudes, Intentions, and the Transfer of Brand Equity,”.Journal of Marketing Research, 38
(November), 471-84.
Meyers Levy, Joan, Therese Louie & Mary Curren (1994), “How Does Congruity of Brand Names
Affect Evaluations of Brand Name Extensions,” Journal of Applied Psychology, 79 (1), 46-53.
_____________ &Alice M. Tybout (1989), “Schema Congruency as a Basis for Product Evaluation,”
Journal of Consumer Research, 16 (July), 39–54.
Morrin, Maureen (1999), “The Impact of Brand Extensions on Parent Brand Memory Structures and
Retrieval Processes,” Journal of Marketing Research,36 (November), 517-25.
Murphy, Gregory L. & Douglas L. Medin (1985), “The Role of Theories in Conceptual Coherence,”
Psychological Review, 92 (July), 289–316.
Nedungadi, Prakash & J. Wesley Hutchinson (1985), “The Prototypicality of Brands: Relationships
with Brand Awareness, Preference, and Usage,” In Advances in Consumer Research, E.C. Hirschman
& M. Holbrook (eds.), Provo, UT: Association of Consumer Research, 498–503.
Novick, Laura (1988), “Analogical Transfer, Problem Similarity, and Expertise,” Journal of
Experimental Psychology: Learning, Memory and Cognition, 14 (3), 510-20.
Park, C. Whan, Sandra Milberg, & Robert Lawson (1991), “Evaluation of Brand Extensions: The
Role of Product Feature Similarity and Brand Concept Congruency,” Journal of Consumer Research,
18 (September), 185–93.
____________ & Daniel Smith (1989), “Product-Level Choice: A Top-Down and Bottom-Up
Process?,” Journal of Consumer Research, 16 (December), 289-99.
Pervin, Lawrence (1983), “The Stasis and Flow of Behavior: Toward a Theory of Goals,” In Nebraska
Symposium on Motivation, 1982, M. Page (ed.), Lincoln, NE: Univ. of NE Press, 1–53.
35
Ratneshwar, Srinivasan, David Glen Mick & Cynthia Huffman (2001), The Why of Consumption:
Contemporary Perspectives on Consumer Motives, Goals, and Desires, New York: Routledge Press.
_________________, Connie Pechmann & Allan D. Shocker (1996), “Goal-Derived Categories and
the Antecedents of Across-Category Consideration,” Journal of Consumer Research, 23 (3), 240-50.
___________________ & Allan D. Shocker (1991), “Substitution in Use and the Role of Usage
Context in Product Category Structures,” Journal of Marketing Research, 28 (August), 281–295.
Reynolds, Thomas & Jonathan Guttman (1988), “Laddering Theory, Method, Analysis, and
Interpretation,” Journal of Advertising Research, 28 (1), 11-31.
Roedder, Deborah, Barbara Loken & Christopher Joiner (1998), “The Negative Impact of Extensions:
Can Flagship Products be Diluted,” Journal of Marketing, 62 (1), 19-32.
Romeo, Jean (1991), “The Effect of Negative Information on the Evaluations of Brand Extensions and
the Family Brand,” In Advances in Consumer Research, Vol. 18, R.H. Holman and M.R. Solomon,
(eds.), Association for Consumer Research, 399-406.
Schneider, W. (1990), Micro Experimental Laboratory, Pittsburgh, PA: Psychology Software Tools.
Shavitt, Sharon (1989), “Operationalizing Functional Theories of Attitudes,” In Attitude Structure and
Functions, Pratkanis, A.R., Breckler, S.J. & Greenwald, A.G. (Eds.), Hillsdale, NJ: Lawrence Erlbaum
Associates, 311-37.
Shocker, Allan D., David W. Stewart & Anthony J. Zahorik (1990), “Determining the Competitive
Structure of Product-Markets: Practices, Issues, and Suggestions,” Journal of Managerial Issues, 2,
127-59.
Simonson, Itamar & Amos Tversky (1992), “Choice in Context: Trade-off Contrast and Extremeness
Aversion,” Journal of Marketing Research, 29 (August), 281-95.
36
TABLE 1
Dependent Measures
1. Feature-Based Typicality Measures:
a) Overall Perceived Similarity (OPS):
“How similar\typical is Benetton leather shoes and Benetton clothing?”
 Scales anchored by” ‘not at all similar’ to ‘very similar’ and ‘not at all typical’ to ‘very typical’.
  = .75
b) Manufacturing Similarity (MS):
“What is the ability of Benetton to manufacture and product dress leather shoes\clothing?
 Scales anchored by: ‘very low amount’ to ‘very high amount’.
  = .71.
2. Usage-Based Similarity Measures:
a) Usage Similarity (US):
“How similar are Reebok athletic shoes and Reebok dress leather shoes in terms of how \when they are used?”
“How likely are you to use Reebok athletic shoes and Reebok dress leather shoes together?”
“How appropriate is it to use Reebok athletic wear to exercise?”
 Scales anchored by: “‘not at all similar’ to ‘very similar’, ‘not at all likely’ to ‘very likely’, and ‘not at all
appropriate’ to ‘very appropriate’.
  = .82.
3. Brand Concept Consistency Measures:
a) Attitude toward the parent brand (AB):
“How favorable\likable\pleasing are Reebok athletic shoes?”
“How favorable\likable\pleasing is the category of athletic shoes?”
 Scales anchored by: ‘not at all favorable\likable\pleasing’ to ‘very favorable\likable\pleasing’.
  = .83.
4. Goal-Derived Categorization Measures:
a) Goodness-of-fit (GOF):
“How well does Benetton’s leather shoes fit with the goal of wanting high quality, colorful clothing?”
“How consistent is Benetton’s dress leather shoes with the goal of wanting high quality, colorful clothing?”
“How well does Benetton’s dress leather shoes exemplify the goal of wanting high quality, colorful clothing?”
 Scales anchored by ‘not at all well’ to ‘very well’, ‘not at all consistent’ to ‘very consistent’ and ‘extremely
poor example’ to ‘extremely good example’.
  = .69
b) Ideal Attributes (Ideals):
“To what degree would Reebok dress leather shoes have bright colors that you can mix and match with your
wardrobe?”
“How likely is it that Reebok dress leather shoes would have bright colors that you can mix and match with
your wardrobe?”
“How likely is it that dress leather shoes would be made of high quality, soft pliable leather?”
“How likely is it that dress leather shoes would come in bright, stylish colors to complete that fashionable, yet
casual image?”
37
“How likely is it that dress leather shoes would come in many bright colors to mix and match with your
wardrobe?”
 Scales anchored by: ‘very low amount’ to ‘very high amount’ and ‘not at all likely’ to ‘very likely’.
  = .79
5. Affective and Purchase Intent Measures:
a) Attitude toward the extension (AEXTN):
“How favorable\likable\pleasing is Reebok athletic clothing?”
“How favorable\likable\pleasing is the category of athletic clothing?”
 Scales anchored by: ‘not at all favorable\likable\pleasing’ to ‘very favorable\likable\pleasing’.
  = .86.
b) Purchase Intention (PI):
“How likely are you to purchase Benetton athletic wear?”
“How likely are you to frequent a store that sells Benetton products?”
“How often have you purchased products made by Benetton?”
 Scales anchored by: ‘not at all likely’ to ‘very likely’, ‘never been in one’ to ‘as often as possible’, and ‘not
at all’ to ‘very often’.
  = .59.
6. Manipulation Check Scales:
a) Goal Congruency:
“How similar is the goal that you associate with Benetton clothing and the goal that you associate with
Benetton athletic wear?”
“How similar is the reason for using Benetton clothing and the reason for using Benetton athletic wear?”
 Scales anchored by: ‘not at all similar’ to ‘very similar’.
  = .73
b) Message Congruency:
“How similar is the type of advertising that you associate with Reebok and the type of message that you see
here for Reebok?”,
“How well does this message exemplify the type of advertising that Reebok uses for its other products?”
“How consistent is this message with the type of advertising that Reebok uses for its other products?”
 Five point scales anchored by: “not at all similar” to “very similar”, “extremely poor example” to
“extremely good example” and “not at all consistent” to “very consistent”.
  = .69
7. In-depth Probes Used For The Goal Congruency Manipulation:



8.



What goal or goals do you associate with Reebok athletic shoes\Reebok athletic wear\Reebok dress leather
shoes?
Does it make sense that Reebok would introduce athletic wear\dress leather shoes? Why or why not?
Do you like the ideas that Reebok is considering introducing athletic wear\dress leather shoes? Why or
why not?
In-depth Probes Used For The Message Congruency Manipulation:
Please describe the type of advertising that Reebok\Benetton uses for its products?
Does this ad fit with the type of advertising that Reebok\Benetton uses for its products?
 How does it fit or not fit with the type of advertising that Reebok\Benetton uses for its products?
If you were to develop an advertisement for Reebok athletic wear\dress leather shoes how should it look so
that it fit with the type of advertising that Reebok uses for its other products? (The same question was also
asked for Benetton.)
38
9. Familiarity and Experience Measures:
“How familiar are you with Reebok\Benetton?”
“How familiar are you with Reebok athletic shoes\Benetton clothing?”
“How familiar are you with retail stores that carry Reebok\Benetton products?”
“How familiar are you with the type of advertising that Reebok\Benetton currently uses?”
“How familiar are you with athletic shoes\high quality clothing in general?”
“How familiar are you with cotton spandex athletic wear\dress leather shoes in general?”
“How much experience do you have with Reebok products\Benetton products?”
 Five point scales anchored by: ‘not at all familiar’ to ‘very familiar’ and ‘no experience at all’ to ‘much
experience’.
  = .91
10. Reaction Time Measures
Before beginning the substantive part of the questionnaire, subjects engaged in a practice task to
establish a baseline RT measure. These practice scales were used to control for individual differences
in reading speed and speed of response (Fazio 1990). The raw RT data revealed substantial positive
skewness typical of such measures, indicating that a log transformation to normalize the data was
needed (Kirk 1994). The analysis of variance results are based on a natural logarithmic transformation
of the data.
TABLE 2
Examples of Goal Hierarchies
Sample Goal Hierarchy for Reebok Athletic Wear:
 Attribute-level goal: “I want athletic wear that is comfortable”
 Benefit-level goal: “Athletic wear that is comfortable makes exercising easier and helps me to perform at
my best”
 Value-level goal: “I want to feel good about myself (high self-esteem)”
Sample Goal Hierarchy for Reebok Dress leather shoes:
 Attribute-level goal: “Reebok dress leather shoes would look like fancy athletic shoes”
 Benefit-level goal: “They would provide comfort at the expense of style and good looks”
 Value-level goal: “I don’t want to feel foolish and embarrased (low self-esteem)
Sample Goal Hierarchy for Benetton Dress leather shoes:
 Attribute-level goal: “Benetton has bright colors that you can mix and match”
 Benefit-level goal: “Wearing Benetton would allow me to stand out and be different”
 Value-level goal: “I want to be different and seen as an individual”
Sample Goal Hierarchy for Benetton Athletic Wear:
 Attribute-level goal: “Benetton athletic wear would be worn by someone who wants to make a fashion
statement, not a serious athlete”
 Benefit-level goal: “It would help them fit in”
 Value-level goal: “They are more concerned with fashion than being a true athlete”
39
TABLE 3
Regression Equations for Goal–Derived
and Perceived Similarity Measuresa
Goal–Derived Categorization Measures:
Typicality Measures:
Aextn= .40Ideals + .39GOF
(2.81)b (2.55)b
R2 = .63d
Aextn= .01OPS + .31US
(0.11) (2.04)b
R2= .52d
PI = .35Ideals + .32GOF
(1.98)b (1.85)b
R2 = .27d
PI = .09OPS + .28US
(.82) (1.57)c
R2 = .19d
a
Maddala (1988) has shown that the amount of variance explained (R 2) is a useful approach for comparing models involving the same
dependent measures and the same number of independent variables.
b p<.05
c p<.08
d R2 are significantly different between the Goal derived and the typicality measures for both attitudes and purchase intention.
Note1: GOF = goodness-of-fit, OPS = perceived similarity, US = usage similarity, PI = purchase intention, Aextn = attitude toward the
extension.
________________________________________________________________________________
Partial Correlations for Perceived Similarity
Measures After Removal of
Variance of the Goal–Derived Measures
Goal Congruent
Goal-incongruent
Goal-derived Categorization Measures:
Aextn – Ideals
.62
Aextn - GOF
.73
PI – Ideals
.46
PI – GOF
.43
.51
.68
.29
.21
Typicality Measures:
Aextn – OPS
Aextn – US
PI – OPS
PI – US
.78
.53
.46
.39
.12
.11
.02
.04
Note2: GOF = goodness-of-fit, OPS = perceived similarity, US = usage similarity, PI = purchase intention, Aextn = attitude toward the
extension.
Note 3: There is a reduction in relationship of typicality measures to attitude and purchase intention measures when the brand extension
is goal-congruent.
40
TABLE 4
ANOVA Results for Dependent Variables
Dependent
Measures:
Goodness-of-fit
Reaction Time for
Goodness-of-fit
Ideals
Reaction Time for Ideals
Perceived Similarity
Reaction Time for
Perceived Similarity
Usage Similarity
Reaction Time for Usage
Similarity
Manufacturing
Similarity
Reaction Time for
Manufacturing Similarity
Attitude (extension)
Reaction Time for
Attitude (extension)
Attitude (brand)
Reaction Time for
Attitude (brand)
Purchase Intent
Reaction Time for
Purchase Intent
a
Main Effects:
Extension
Congruency
M=4.23 v. 2.63,
F=38.39
M= 2.37 vs. 2.50,
F=71.38
M= 4.07 vs. 2.67,
F=10.08
M=2.33 vs. 2.50,
F=9.68a
M=3.60 vs. 2.33,
F=28.46
M=2.34 vs. 2.47,
F=48.63
M= 3.59 vs. 1.84,
F=69.69
M= 2.32 vs. 2.49,
F=60.45
M=4.23 vs. 3.77,
F=19.67
M=2.32, vs. 2.49,
F=90.32
M=4.22 vs. 2.52,
F=94.90
M=2.35 vs. 2.46,
F=69.86
M=4.06 vs. 3.45,
F=24.62
M=2.24 vs. 2.35,
F= 8.67a
M=3.60 vs. 2.39,
F=32.95
M=2.35 vs. 2.36, NS
Main Effects:
Message Congruency
M=3.73 vs. 3.24 vs.
3.17, F=19.56
M=2.41 v 2.45 v 2.45,
F=10.02
M=3.60 v 3.37 v 3.00,
F=16.87
M=2.39 v 2.41 v 2.43,
F=10.02
M=3.20 v 2.76 v 2.82,
F=7.45a
M=2.39 v 2.41 v. 2.44,
F=16.22
M=2.79 v 2.59 v 2.62,
F=4.03a
M=2.39 v 2.41 v 2.44,
F=12.72
M=4.11 v 3.94 v 3.90,
NS
2.38 v 2.40 v 2.44,
F=16.19
M=3.51 v 3.32 v 3.12,
F=15.41
M=2.39 v 2.41 v 2.41,
F= 5.17a
M=3.88 v 3.74 v 3.58,
NS
M=2.25 v 2.26 v 2.26,
NS
M=3.35 v 3.10 v 3.0,
NS
M=2.36 v 2.35 v 2.35
NS
Interaction Effects:
Extension x Message
Congruency
F=11.43
F=9.20a
F=14.81
F=19.55
F=15.45
F=16.22
F=8.61a
F=12.32
NS
F=8.50a
F=4.16a
F=5.23a
NS
NS
NS
NS
F-statistics are significant at p<.05. All other F-statistics are significant at p<.000. DF=1,249.
41
42
TABLE 5
Contrasts for Simple Main Effects for Dependent Measures
Goal-congruent Extension
Goal-incongruent Extension
No Message
F-stat
Goalincongruent
vs.
No Message
25.65A
NS
4.7 v. 4.1
2.37 v. 2.34
22.12A
NS
4.0 v. 4.1
2.37 v. 2.34
NS
NS
3.0 v. 2.6
2.44 v. 2.51
6.07C
15.18A
3.0 v. 2.8
2.44 v. 2.55
NS
30.55A
2.6 v. 2.8
2.51 v. 2.55
NS
NS
4.7 v. 4.3
2.34 v. 2.33
18.44A
NS
4.7 v. 3.3
2.33 v. 2.33
37.84A
NS
4.3 v. 3.3
2.34 v. 2.33
22.32A
NS
2.7 v. 2.6
2.44 v. 2.51
NS
15.62A
2.7 v. 2.7
2.44 v. 2.56
NS
19.96A
2.6 v. 2.7
2.51 v. 2.57
NS
9.07B
OPS
RT
4.0 v. 3.4
2.34 v. 2.33
18.90A
NS
4.0 v. 3.5
2.34 v. 2.35
18.14A
NS
3.4 v. 3.5
2.34 v. 2.35
NS
NS
2.6 v. .2
2.42 v. 2.48
4.33C
18.31A
2.6 v. 2.4
2.42 v. 2.50
NS
18.83A
2.2 v. 2.4
2.48 v. 2.53
NS
7.24C
US
RT
4.3 v. 3.9
2.34 v. 2.33
17.23A
NS
4.0 v. 3.6
2.32 v. 2.32
22.00A
NS
3.9 v. 3.6
2.33 v. 2.32
4.16C
NS
1.8 v. 2.0
2.43 v. 2.50
NS
9.03B
1.8 v. 1.7
2.43 v. 2.55
NS
15.15A
2.0 v. 1.7
2.50 v. 2.55
NS
8.57B
MS
RT
4.5 v. 4.1
2.31 v. 2.32
8.86B
NS
4.5 v. 4.1
NS
9.90B
4.1 v. 4.1
2.32 v. 2.32
NS
NS
3.7 v. 3.8
2.44 v. 2.48
NS
5.44C
3.7 v. 3.7
2.44 v. 2.55
NS
18.53A
3.8 v. 3.7
2.48 v. 2.55
NS
14.96B
Aextn
RT
4.6 v. 4.2
2.34 v. 2.36
9.62B
NS
4.6 v. 3.9
2.34 v. 2.35
41.95A
NS
4.2 v. 3.9
2.36 v. 2.35
11.85B
NS
2.6 v. 2.5
2.42 v. 2.51
NS
7.03C
2.6 v. 2.6
2.42 v. 2.47
NS
7.53B
2.5 v. 2.6
2.47 v. 2.48
NS
NS
Dependent
Goal congruent
vs.
Measures
Goalincongruent
GOF
RT
4.7 v. 4.0
2.37 v. 2.37
Ideals
RT
Goalcongruent vs.
F-stat
Goal-congruent
vs.
F-stat
Goalincongruent
F-stat
Goalincongruent
vs.
No Message
Goalincongruent vs.
F-stat
No Message
F-stat
NOTE: GOF = goodness-of-fit, OPS = overall perceived similarity, US = usage similarity, MS = manufacturing similarity, Aextn = attitude toward the extension, RT = reaction time.
See Table One for descriptions of each of these variables.
A p<.001
B p<.01
C p<.05
NS = not significant
43
APPENDIX 1
Goal-congruent Extension
Reebok has decided to introduce a new Fall line of merchandise. We are interested in your opinion
concerning Reebok’s choice of new products using the Reebok brand name. One of the product
categories that they are considering is a line of cotton Spandex athletic wear.
The type of athletic wear is made of cotton Spandex material for aerobics, basketball, cycling, and
running. This cool, stay-dry cotton Spandex material ensures maximum comfort with double needle
seams. The aerobic wear includes interchangeable pieces in many different patterns and colors. The
cycling clothes are designed for anatomical fit, full polypropylene pads, drawstring waist and leg
grippers for maximum comfort. The basketball and running clothes are designed with inside
drawstring waist for maximum freedom of movement and Coolmax lining to wick away moisture.
This type of athletic wear is designed to be worn by the serious athlete when exercising at home
or at the health club. This line of exercise wear will be sold in sporting good stores as well as
department stores and specialty athletic stores. Each piece has the Reebok logo embroidered on it to
ensure quality athletic wear. It is designed to compete with well known brands such as Nike, Speedo,
Side One, Descente, and others.
Goal-incongruent Extension
Reebok has decided to introduce a new Fall line of merchandise. We are interested in your opinion
concerning Reebok’s choice of new products using the Reebok brand name. One of the product
categories that they are considering is a line of dress leather shoes.
This line of leather shoes would be for both men and women. They would be made of soft leather and
deerskin with padded leather insoles. They are a great alternative to the traditional shoes because they
would come in colors that you can mix and match with your entire wardrobe. These shoes are designed
to complete the fashionable wardrobe. They are fashioned as a stylish, quality shoe to wear with a
certain outfit and versatile enough to wear in both casual and formal situations. They will come in
many different colors including the more traditional black and brown colors for men as well as women.
This type of leather dress shoe is designed to be high quality, stylish, and colorful. They will be
sold in sporting goods stores as well as in the more traditional department and shoe stores. The
Reebok log will be stamped on the sole of their shoes as a mark of distinction. They are designed to
compete with such brands as Bally, Bandolino, and Cole-Haan for women. For men, they are designed
to compete with brands such as Murphy’s Cole-Haan, and Bally.
APPENDIX 2
Examples of the Message Stimuli
45