J PROD INNOV MANAG 2013;30(S1):126–141
© 2013 Product Development & Management Association
DOI: 10.1111/jpim.12067
The Effects of Brand Metaphors as Design Innovation: A Test
of Congruency Hypotheses*
Charles H. Noble, Mark N. Bing, and Elmira Bogoviyeva
Metaphors are a common tool in brand design, from the original, enticing Apple logo to the classic animalistic hood
ornament of a Jaguar automobile. Metaphors are a powerful marketing tool as an efficient way to convey a great deal
of meaning to consumers, including expressing product benefits, points of differentiation (e.g., “Iron Mountain’s” name
and logo, intended to express its superiority in data and document safekeeping), and even brand personality. The
perspective taken here is that when applied to products, metaphors also serve as a form of design innovation. This study
examines the interactions and effects of various applications of brand metaphor (linguistic, visual, and symbolic) and
the forms those metaphors can take (human, animal, or nonmetaphoric) in influencing important outcomes including
brand vividness, brand differentiation, and consumer preference. Based on two experiments across multiple product
categories with 424 subjects, we find that the consistency of brand metaphor application and the use of animal-based
metaphors in particular have significant influence on key outcomes. Implications for brand management and design
innovation through the more effective use of design metaphors are considered, as are implications for theory and future
research in the area.
A
fundamental goal of most marketing and product development efforts is to achieve separation from the competition (or “differentiation”)
in the marketplace and in the minds of consumers. This
form of competitive advantage is based on this premise that occupying a unique space in a consumer’s
mind by developing a product image that is vivid,
distinctive, and promises unique benefits will enhance
desirability.
For some time, metaphors have been used as an
effective tool in brand and product development and
in understanding consumer thought processes (Zaltman
and Zaltman, 2008). Simply put, “a metaphor describes
one thing in terms of another, frequently providing a
better picture than can a straight literal description”
(McWilliam and Dumas, 1997, p. 271). Metaphors have
been applied in several ways in marketing, such as in the
cultivation of a brand personality (Ang and Lim, 2006).
For example, the metaphoric apple logo of Apple Inc.
concisely conveys a sense of familiarity, a nonthreatening
nature (particularly desirable in a high-technology consumer good), and even enticement (encouraging one to
“take a bite”). Metaphors are also closely tied to the field
Address correspondence to: Charles H. Noble, College of Business
Administration, The University of Tennessee—Knoxville, 310 Stokely
Management Center, Knoxville, Tennessee 37996-0530. E-mail: cnoble@
utk.edu. Tel: 865-974-9450.
* The authors appreciate the artistic support of Minu Kumar in making
this work possible.
of product design and innovation because, for example,
the personal meanings that are stimulated by good design
can be effected by powerful metaphors (Verganti, 2011).
Metaphors are often based on animals, birds, insects,
and other fauna found in nature as well as on human
beings, such as the design of a “smiling” grill on the front
of an automobile (with smiling being a uniquely human
gesture) (Aggarwal and McGill, 2007). In this research,
we refer to these choices as metaphor types.
Metaphor types can be applied in different ways. Linguistic metaphors are the most traditional, broadly
defined as the representation of one thing in terms of
something else, often using an analogy or an implicit
comparison (Capelli and Jolibert, 2009). Common terms
such as “price war” and “product life cycle” are fundamentally metaphor based. While the metaphor has its
roots as a linguistic convention, so-called visual metaphors are increasingly common, particularly in product
design innovation, described as the representation of a
person, place, thing, or idea by way of a visual image that
suggests a particular association or point of similarity
(McQuarrie and Mick, 1996). For example, the color
green is increasingly used in product packaging to
help convey the environmentally friendly nature of an
enclosed product. A third type of metaphor considered
here, symbolic metaphors, use markings, logos, or other
visual symbols which may be a minor part or not even
attached to the product itself to convey information to
suggest an association or point of similarity. For example,
BRAND METAPHORS AS DESIGN INNOVATION
the Great Seal of the United States is a symbolic metaphor which conveys a great deal of meaning, including
the central position of a bald eagle (a metaphor for
strength) clutching an olive branch and 13 arrows in its
talons, those symbols representing a balance between
peace and war (Patton, 1987). This study uses the phrase
“brand metaphor applications” to refer to all of these
types: linguistic, visual, and symbolic. Linguistic metaphors are reflected in the name chosen for a product,
visual in its physical form, and symbolic in the logo used
to represent the product graphically.
Metaphors can be a powerful option in a product
designer’s tool kit, and represent a form of design innovation. Metaphors are closely aligned with the “mystique
and holistic appeal” (Noble, 2011, p. 391) that is often the
goal of design innovation and can be used effectively to
develop impactful brands and memorable customer experiences (Luchs and Swan, 2011). Further, several authors
have equated the design innovation process to, “. . .
developing marketing programs to position products in
consumers’ minds, especially with respect to competitive
products” (e.g., Townsend, Montoya, and Calantone,
2011), a goal that is often achieved through effective
metaphor usage. Therefore, the use of brand metaphors
in product development is really an exercise in design
innovation.
BIOGRAPHICAL SKETCHES
Dr. Charles H. Noble (PhD, Arizona State University) is currently the
Proffitt’s Professor of Marketing and PhD Program Director at The
University of Tennessee in Knoxville. He is also a Vice President of the
Product Development and Management Association. His research interests focus generally on design and development processes, as applied to
both products and services. He has published in Journal of Marketing,
Strategic Management Journal, Journal of the Academy of Marketing
Science, Sloan Management Review, Journal of Product Innovation
Management, IEEE Transactions on Engineering Management, and
many others.
Dr. Mark N. Bing (PhD, University of Tennessee) is an associate professor of management at the University of Mississippi. He has published
numerous articles in journals such as Journal of Applied Psychology,
Organizational Behavior and Human Decision Processes, Organizational Research Methods, Journal of Management, Journal of Organizational Behavior, Journal of Vocational Behavior, Journal of
Personality Assessment, and Academy of Management Learning and
Education. His research areas include human resource selection,
personality measurement, personality test faking, test development
and validation, counterproductive workplace behavior, and research
methods.
Dr. Elmira Bogoviyeva (PhD, University of Mississippi) is an assistant
professor of marketing at KIMEP University (Kazakhstan). She received
her Ph.D. from the University of Mississippi. Her research areas include
brand development and management, product development and innovation, social media, perception of time, and temporal orientation.
J PROD INNOV MANAG
2013;30(S1):126–141
127
Despite the potential positive influence of brand metaphors in design innovation, several knowledge gaps exist
regarding their effects. For example, there is a lack of full
understanding of how brand metaphor types and applications interact to influence important marketplace and
consumer outcomes such as brand vividness, brand differentiation, and consumer choice. In addition to these
linkages, we also investigate in this study the fundamental notion of consistency in brand metaphor application.
While some successful products such as the Jaguar automobile display consistency across these application possibilities (e.g., the distinctive Jaguar hood ornament/logo,
its cat-like product form, and the name itself), other
seemingly successful products show less of this sort of
consistency (e.g., the Volkswagen Beetle, which has a
bug-like name and form but no corresponding logo). The
extent to which consistency is an important issue in metaphor application is a theoretical and managerial issue that
warrants attention. In sum, this study investigates the
following questions surrounding metaphor-based design
innovations:
1. Generally, how do different types and applications
of brand metaphors influence brand vividness, brand
differentiation, and consumer preference?
2. Are human reactions to brand metaphor types primarily driven by familiarity, such that human-based metaphors result in more vividness than those which are
animal based, which in turn are more vivid than no
metaphor at all?
3. Among applications of brand metaphors (linguistic,
visual, and symbolic), how does consistency of metaphor usage influence outcomes?
4. Is brand vividness an essential link between brand
metaphors and important outcomes such as brand differentiation and consumer preference?
Figure 1 summarizes this research project’s hypotheses in the form of a causal model.
Literature Foundations
Brand Metaphors and Design Innovation
The word “metaphor” originates from the Greek
metapherein, meaning “to carry over,” or “to transfer”
(Hunt and Menon, 1995). Metaphors have long been of
interest in marketing, both as branding and design tools
and in understanding consumer reactions to various phenomena (e.g., Cotte, Ratneshwar, and Mick, 2004;
McQuarrie and Phillips, 2005). Zaltman (1996) suggested that communication in society is mostly nonver-
128
J PROD INNOV MANAG
2013;30(S1):126–141
C. H. NOBLE ET AL.
Personality
Congruence
Brand Metaphor Type
- human
- animal (fauna)
- nonmetaphor
H8
Product
Category
Involvement
H1 (abcd)
H2
Public
Consumption
H6
Brand
Vividness
H3
H4
Brand Metaphor
Applications
- linguistic (name)
- visual (form)
- symbolic (logo)
Brand
Differentiation
H7
H5
Consumer
Preference
Category
Knowledge
Animistic (often anthropomorphic)
interpretation
Figure 1. The Influence of Varying Brand Metaphor Types and Applications on Brand Vividness, Brand Differentiation, and
Consumer Preference
bal, and that at least two thirds of all social meaning
is exchanged nonverbally, often through images. He
stressed that metaphor is central to cognition and that the
representation of one thing in terms of another is fundamental to thinking and knowing. Cornelissen (2003) used
metaphor-based techniques for describing managerial
issues of corporate identity and relationship marketing.
As a design innovation, metaphoric forms can influence
perceptions of functional performance and other key consumer variables (Hoegg and Alba, 2011).
Metaphor use has also been tied to various brand
issues. For example, Aggarwal and McGill (2007)
provide a detailed examination of the relationships
people build with brands, treating them as live creatures
having souls, with reference to animism. The concept of
brand personality is largely based on animistic metaphor
thinking, with three out of five brand personality dimensions found by Aaker (1995) (e.g., sincerity, competence,
sophistication) to be clearly anthropomorphic. In sum,
there are different types of metaphors (e.g., human,
animal, inanimate object) which can be used in various
ways, such as in linguistic, visual, and symbolic applications. As we discuss next, these metaphors (when used
effectively in branding) may be interpreted as animistic
or, more specifically at times, as anthropomorphic, and
influence consumer perceptions of the brand itself and
purchase preferences.
Animism and Anthropomorphism
The term animism is derived from the Latin word anima,
meaning breath or soul (Garretson and Niedrich, 2004).
In early civilizations, it was a common belief that a soul
or spirit existed in every object, even if the object was
inanimate. While a metaphor can be based on an inanimate object (e.g., Prudential Insurance’s long-standing
“Get a piece of the rock” campaign), many powerful
metaphor applications are based on living, nonhuman
creatures—what we classify as “fauna” for this research.
Anthropomorphism is a somewhat more specific
concept, involving the attribution of human qualities to
nonhuman things, whether animate or inanimate (Kiesler,
2006; Landwehr, McGill, and Herrmann, 2011). Guthrie
(1993, 1997) suggests at least three psychological foundations for this phenomenon. First, he emphasized the
importance of “familiarity” in explaining the power of
anthropomorphism. Familiarity theory is based on a cognitive process of building mental maps of the world by
using familiar objects as reference points, with human
references being the most frequent and comfortable.
Second is the idea that people seek emotional comfort
when encountering the unknown, and seeing and describing things similar to people reduces that discomfort.
Finally, game theory is the basis for the “best bet” phenomenon which suggests, among other things, that
BRAND METAPHORS AS DESIGN INNOVATION
people will perceive it less risky and thus more desirable
to interpret the world in human terms when faced with
uncertainty (Guthrie, 1997).
Brand Vividness
A fundamental goal of brand management is to develop a
brand that is perceived by consumers as vivid, with vividness defined as “emotionally interesting, concrete, and
imagery provoking” (Nisbett and Ross, 1980, p. 45). The
concept of vividness largely has its roots in the information processing literature. From this perspective, vivid
information attracts more attention than pallid and
abstract stimuli, thereby increasing message scrutiny and
persuasion (Chang and Lee, 2010). Thus, vivid stimuli
carry disproportional weight in shaping attitudes and
opinions (Nisbett and Ross, 1980), particularly in fuzzy
or indistinct situations (Slovic, 1993).
Based on these views and on insights from familiarity
theory and emotional satisfaction (Guthrie, 1997), we
expect there to be ties between metaphor use and vividness. Specifically, we expect that various metaphor types
will trigger animistic and possibly anthropomorphic
interpretation processes, which result in perceptions of
vividness. Therefore, our first hypothesis is as follows:
H1: There will be a positive relationship between metaphor type and brand vividness. Specifically, when a
human or animal metaphor is perceived in a brand,
brand vividness will be higher than when no metaphor is
used.
We expect this phenomenon will hold across all potential brand metaphor applications such that:
H1a: There will be a positive relationship between metaphor presence in a brand name and brand vividness.
H1b: There will be a positive relationship between metaphor presence in a brand symbol (or logo) and brand
vividness.
H1c: There will be a positive relationship between metaphor presence in a brand form and brand vividness.
Animal-based metaphors can certainly trigger emotional and cognitive responses in consumers (e.g., the
Aflac duck has dramatically increased consumer
awareness of a largely business-to-business insurance
company). However, we expect based on familiarity
theory (Guthrie, 1993) that anthropomorphic (i.e.,
human) metaphors will resonate even more strongly with
consumers. There seems to be a tacit belief in this relationship in practice as, for example, even the earliest film
J PROD INNOV MANAG
2013;30(S1):126–141
129
representations of robotic automatons from the 1950s
depicted them as humanoid, whether helpful or threatening, with the filmmaker’s intent to stir the strongest possible emotional reaction. More importantly, research and
theory has supported this view.
In advertising research, animistic metaphors have been
found to be influential (Garretson and Niedrich, 2004),
but anthropomorphic metaphors may be particularly
powerful (Blanchard and McNinch, 1984). According to
the theory of familiarity (Guthrie, 1997), people use
themselves as models of the world, and have higher preference for “humanoid” objects. Visually, human-like
objects are assumed to have physical characteristics
similar to humans—two arms, two legs, two eyes, an
upright posture, etc. While some animals such as nonhuman primates (e.g., apes) would approximate those qualities, most other fauna (animals) do not. Considering that
humans are largely visual processors of information
(Lakoff and Johnson, 1980), we expect that proximity to
humanness in a brand metaphor will be strongly connected to response variables such as vividness, and
therefore:
H1d: Human metaphor types (names, forms, and logos)
will be more strongly and positively related to brand
vividness than will animal (fauna) metaphor types which
will, in turn, be more strongly and positively related to
brand vividness than nonmetaphoric brand types.
Consistency in metaphor usage is an issue that has
not received focused research attention. For example,
one might expect that a consistent application of the
same metaphor across name, form, and logo would
create the most powerful impact on a consumer.
However, some of the most powerful brands on the
market violate this principle (e.g., Apple Inc. with a
metaphoric name and logo but no “apple-shaped” products). It may be that one of these three brand metaphor
elements drives perceptions much more strongly than
others, or simply that human cognitive processing does
not require this degree of redundancy and consistency in
order to have a powerful influence. For example,
MacInnis, Shapiro, and Gayathri (1999) demonstrated in
an experimental setting that brand memory is highest
when a brand name is depicted pictorially, and a high
benefit brand name was used. This finding suggests both
that some brand metaphor applications may be more
important than others and that consistency may have a
cumulative or interactive effect.
Consistency of brand metaphor application across
name, form, and logo may also represent a form of repetition. Macklin (1996) reported that in the case of visual
130
J PROD INNOV MANAG
2013;30(S1):126–141
cues used for testing brand memory, the presence of two
cues like color and picture improves brand memory more
than one cue. Klink (2003) experimentally demonstrated
that there is an interrelationship between brand mark
(logo) and brand name, with this synergy influencing
brand meaning, and communication of that meaning. In
sum, we expect that a more consistent application of
brand metaphor elements will create more powerful synergies and reinforcements that will have a stronger influence on consumer outcomes than with one or two
elements alone. Therefore:
H2: Consistent brand metaphor application (across
name, form, and logo) will increase brand vividness
much more so than will individual types or
subcombinations of those types.
Brand Differentiation
The origin of the differentiation concept in marketing
literature goes back to Shaw (1912), who described
product differentiation as meeting human wants more
accurately than competitors that lacked product differentiation. Porter (1985) and Dickson and Ginter (1987)
refined the concept by suggesting that differentiation can
also result from nonproduct elements such as production
processes, human resources, and the sourcing of raw
materials. A recent conceptualization by Vargo and Lusch
(2004) suggests that competitive differentiation is based
on specialized skill sets (a form of “services” in their
conceptualization).
From a branding perspective, vividness should
influence differentiation. Fundamentally, differentiation
requires a competitive reference point, making it a strategic variable. Brand vividness, on the other hand, is
based on a more isolated assessment of a single brand and
the clarity and strength of its meaning. Therefore, we
expect these variables to be distinct and discriminable.
For example, Coca-Cola and Pepsi have undeniably
strong and vivid brands based on their status near the top
of many ranking studies,1 yet a blind taste test often
causes even loyal consumers to have difficulty differentiating between the two, supporting the distinction
between these brand concepts. However, it seems likely
that vividness can serve as an effective point of brand
differentiation and we propose that:
H3: There will be a positive relationship between brand
vividness and brand differentiation.
1
http://www.interbrand.com; for 2009, Coca-Cola ranked #1 and Pepsi
#23 globally.
C. H. NOBLE ET AL.
It is well established that a consumer’s prior knowledge about a product category influences the choices he
or she makes from that category (Alba and Hutchinson,
1987). Knowledgeable consumers have access to category and brand information that they can draw upon in
assessing and evaluating a product (Malaviya and
Sivakumar, 1998). Knowledgeable (i.e., expert) consumers have sophisticated knowledge structures in memory
and can draw upon this knowledge when interacting with
new information in making product evaluations (Sen,
1998). We expect that highly knowledgeable consumers
who perceive a brand to be vivid will experience an
interaction effect such that:
H4: The relationship between brand vividness and brand
differentiation will be moderated by product category
knowledge such that increased category knowledge will
strengthen the positive relationship between vividness
and differentiation.
Differentiation is an essential element of a brand that
makes it noticeable in the marketplace and meaningful to
consumers. Brand differentiation has been studied as a
characteristic of an advertising message and has been
shown to influence persuasion (Stewart, 1986). Carpenter
and Nakamoto (1989) suggest that a unique and differentiated positioning of a brand shifts a portion of the
consumer taste distribution toward the brand and, as a
result, the brand ultimately achieves a higher level of
prominence. According to them, this sort of effective
brand positioning can be powerful enough to even
reduce the inherent advantages of market pioneering
brands (Carpenter and Nakamoto, 1989). Govers and
Schoormans (2005) supported this view in a study of
differentiation based on design, suggesting that a product
perceived to be different from others had a higher consumer preference. Based on these views, we expect the
following main effect:
H5: There will be a positive relationship between brand
differentiation and consumer preference.
More interesting perhaps are some of the factors that
may moderate this direct relationship. Several authors
(e.g., Beatty and Talpade, 1994) have argued that product
category involvement plays an important role in consumer preference formation. Product involvement is
defined as “a person’s perceived relevance of the object
based on inherent needs, values, and interests”
(Zaichkowsky, 1985, p. 32). That personal relevance is
also influenced by the perceiver’s cognitive structure
regarding the product category (Celsi and Olson, 1988).
So, high involvement consumers have strongly held
needs, values, and interests in the product category in
BRAND METAPHORS AS DESIGN INNOVATION
question (Giese, Spangenberg, and Crowley, 1996).
Because these high involvement consumers are more
likely to process relevant information, we expect this
factor to have a moderating effect on the relationship
between brand differentiation and consumer preference:
H6: The relationship between brand differentiation and
consumer preference is moderated by product category
involvement such that higher levels of involvement will
strengthen the positive relationship between brand differentiation and consumer preference.
The nature of the consumption setting (public versus
private) can influence both product choices and the consumption experience. Previous research has shown that
the extent to which consumption is public can influence
variety-seeking behavior (Ratner and Kahn, 2002), as
consumers are influenced by how their choices will be
perceived by others. The theory of reasoned action
(Fishbein and Ajzen, 1975) suggests that behavior is a
function of behavioral intention which, in turn, is predicted by both attitudinal and normative influences. From
this view, an individual’s perceptions of what others think
about him or her act as a subjective norm and a behavioral
influence (Kulviwat, Bruner, and Al-Shuridah, 2009).
Based on the view that public consumers have a desire to
be perceived as distinctive and innovative (Kulviwat
et al., 2009), we expect that differentiated brands will
more strongly influence consumer preference when
goods are considered as public instead of private:
H7: The relationship between brand differentiation and
consumer preference is moderated by the situation of
consumption (public versus private) such that more
public goods will strengthen the positive relationship
between brand differentiation and consumer preference.
People tend to prefer products that match their selfimage. Sirgy (1982) suggested that self-image, when congruent with a product, increased consumer preference
and usage of that product. The congruence between selfimage and product use has also been shown to evoke
emotions in consumers, to increase levels of loyalty and
trust, and to generally have a positive influence on preference (Govers and Schoormans, 2005). In a society in
which one’s product choices are increasingly seen as an
extension of one’s personality, this congruence should
influence preference. We expect that more differentiated
brands create a greater opportunity for a consumer to
make a statement about his or her personality through
use, particularly when there is personality congruence
between the brand and the consumer. Therefore, we
expect:
J PROD INNOV MANAG
2013;30(S1):126–141
131
H8: The relationship between brand differentiation and
consumer preference is moderated by personality congruence such that higher levels of personality congruence will strengthen the positive relationship between
brand differentiation and consumer preference.
Next, we describe two studies designed to test these
hypotheses.
Study 1
The goal of Study 1 was to test the research model displayed in Figure 1 through a combination of experimental
manipulations and survey measures based on variations
in a single product category.
Method
In order to determine the proper applications for this
study, we conducted a pretest in which several product
categories were considered which would be both familiar
to the subject group and which had the potential to
employ human and animal metaphors. For each of
these product categories (e.g., audio speakers, staplers,
juicers, telephones, and robots), three alternatives were
identified—one clearly based on a human metaphor, one
based on an animal metaphor, and one that was not based
on any metaphor at all. Subjects in this pretest were
students of a large public university in the southeastern
United States (n = 102) and each considered one of the
three options for each product category, with the option
and the order of categories randomly assigned. Subjects
completed a seven-item anthropomorphism scale for each
option (coefficient alpha = .822). The scale was developed for the current project based on studies by Garretson
and Niedrich (2004), Hunt and Menon (1995), Lakoff and
Johnson (1980), and McQuarrie and Mick (1996). Based
on familiarity theory and other perspectives on anthropomorphism, we expected that an appropriate set of three
products (in a single category) would include a “human”
metaphor that scored highest on anthropomorphism,
an “animal” metaphor that was next highest, and a
nonmetaphor that was lowest in anthropomorphism. In a
series of paired t-tests, the juicer and robot sets of products met these expectations. Thus, juicers were used as
the context for Study 1, and robots were used as the
context for Study 2.
Study 1 participants consisted of 424 students at a
major public university in the southeastern United States
who received course credit for their participation. The
study employed a 3 (Form: human, animal, nonmetaphor)
132
J PROD INNOV MANAG
2013;30(S1):126–141
Study #1: Juicers
C. H. NOBLE ET AL.
Human
Animal
Nonmetaphor
“Ultra Juice Man”
“Ultra Juice Penguin”
“Ultra Juicer”
Human
Animal
Nonmetaphor
“Mega Robo-Man”
“Mega Robo-Cat”
“Mega Robot”
Form
Logo
Name
Study #2: Robots
Form
Logo
Name
Figure 2. Manipulations (Juicers and Robots)
× 3 (Name: human, animal, nonmetaphor) × 3 (Logo:
human, animal, nonmetaphor) mixed factorial counterbalanced design. Subjects received one juicer scenario, an
example of which is shown in Appendix A. This scenario
described a situation where the subject was shopping for
a new juicer and considering various brands, then offered
a stimulus consisting of a form, logo, and product name.
Figure 2 shows the set of stimuli that were combined to
form the 27 experimental conditions studied.
After considering the scenario, subjects responded to a
series of measures of the model variables, including
brand vividness, brand differentiation, category knowledge, product category involvement, personality congruence, public versus private consumption, and consumer
preference. The definitions, sources, and items for these
measures are shown in Table 1.
Results
We chose to use general linear models (GLMs) and moderated multiple regressions (MMRs) to test the study’s
hypotheses over structural equation modeling (SEM)
analyses because of several disadvantages found within
SEM. First, most methodologists recommend that SEM
should only be used (typically) when the number of
cases, subjects, and/or observations is 200 + (N > 200)
and when the subject-to-variable ratio is at least 10–1
(Bentler and Chou, 1987; Jaccard and Wan, 1996). We
had approximately 15 subjects per cell (424 subjects ÷ 27
cells = 15.7 per cell), and six major variables—name,
form, logo, and gender, age, and year in college as control
variables. Thus, our subject-to-variable ratio was 15-6 per
cell, clearly short of the sample size requirements of
SEM. Also, as multivariate normality is violated when
complex interactions are represented and tested in SEM,
we chose to use these other statistical methods (i.e., GLM
and MMR) over SEM because they are typically preferred for testing interactions (Bing, LeBreton, Davison,
Migetz, and James, 2007).
In the first stage of our causal model, we used a GLM
to analyze the effects of varying brand metaphoric type
(i.e., human, animal, and nonmetaphoric) within the three
brand factors, name, form, and logo, on perceptions of
brand vividness (Cronbach’s alpha = .91) for the juicer
BRAND METAPHORS AS DESIGN INNOVATION
J PROD INNOV MANAG
2013;30(S1):126–141
133
Table 1. Constructs, Scales, and Sources
Construct
Source(s)
Definition
Scale Items
Anthropomorphism
Adapted from
McQuarrie
and Mick
(1996)
The tendency to ascribe not
only life, but also human
characteristics to nonhuman
beings and inanimate
objects.
Brand vividness
Adapted from
Keller and
Block
(1997)
“Intensity of the brand
including the extent to
which the brand is
well-defined, recognizable
and attention-grabbing.”
Brand characterized by
attractiveness and
magnetism.
Brand
differentiation
Adapted from
Song and
Parry
(1997)
Brand perceived to be unique
by consumers on the basis
of combined tangible and
intangible features and
created distinction
associated with brand
experience.
Product category
knowledge
Flynn and
Goldsmith
(1999)
Perceived knowledge and
expertise on product.
Product category
involvement
Beatty and
Talpade
(1994)
The personal relevance and
importance of a category of
goods or services (Park and
Young, 1986).
Brand-Personality
congruence
Sirgy et al.
(1997)
Public / Private
consumption
Kulviwat
et al.
(2009)
Perceived similarity between
individual’s personality and
set of human characteristics
projected by brand.
Self-congruity refers to the
fact that consumers prefer
products associated with an
image that is similar to their
self-concept.
The individual or observed by
other people use of product.
(Agree / disagree regarding the subject product. 7-point scale)
A1. Looks very human.
A2. Looks very realistic.
A3. It would remind me of a real person.
A4. Looks like a living being.
A5. I can relate to it.
A6. I can connect to it.
A7. I can imagine myself talking to it.
(“If this brand were a person, how would you describe it?”) (7-point, semantic differential
scale)
BV1. vivid / not vivid
BV2. well-defined / not well-defined
BV3. lifelike / not lifelike
BV4. intense / not intense
BV5. easy / not easy to imagine
BV6. easy / not easy to relate to
BV7. easy / not easy to picture
BV8. reminds me of something / doesn’t remind me of anything
BV9. exciting / dull
BV10. interesting / boring
BV11. attractive / unattractive
BV12. favorable / unfavorable
BV13. distinctive / not distinctive
(7-point Likert-type scale, “strongly agree / disagree”)
BD1. This brand is different from others
BD2. This brand is unique
BD3. I would be able to recognize the presented brand among others.
BD4. I would say that the presented brand “stands out” from others.
BD5. I would say this brand is not related to others.
BD6. This brand expresses what is unique about its users.
BD7. The brand “speaks” for itself.
(7-point Likert-type scale, “strongly agree / disagree”)
PK1. I feel quite knowledgeable about this product category.
PK2. Among my circle of friends, I am one of the “experts” on this type of product.
PK3. I rarely come across a brand within this product category that I haven’t heard of.
PK4. I know quite a bit about this product category.
PK5. I do not feel knowledgeable about this product category. (r)
PK6. Compared to most other people, I know less about this product category. (r)
PK7. When it comes to this product category, I really don’t know a lot. (r)
PK8. I have heard of most of the new products of this type that are around.
(7-point Likert-type scale, “strongly agree / disagree”)
PI1. In general I have strong interest in this product category.
PI2. This product category is very important to me.
PI3. This product category matters a lot to me.
PI4. I get bored when people talk to me about this product category. (r)
(7-point Likert-type scale, “strongly agree / disagree”)
PC1. I would likely choose this brand if purchasing this type of product.
PC2. This brand is consistent with how I see myself.
PC3. People similar to me would use this brand.
PC4. The brand reflects who I am.
PC5. The brand is very much like me.
PC6. The brand is a mirror image of me.
Consumer
preference
Adapted from
Costley
and Brucks
(1992)
The propensity with which an
individual would choose a
product.
(7-point, semantic differential scale)
PPC1. I would use this product with just [myself/others] in mind.
PPC2. [No one/everyone] would notice me using this product.
PPC3. I would think of [myself/others] when using this product.
PPC4. This product would be interesting only [to me/to others].
PPC5. I think [only I/others] would enjoy using this product.
(7-point Likert-type scale, “strongly agree / disagree”)
CP1. I like this brand.
CP2. This brand pleases me.
CP3. This is a good brand.
CP4. This brand has more pros than cons.
CP5. Given an acceptable price, I would be happy to buy this brand.
CP6. I have a favorable opinion of this brand.
134
J PROD INNOV MANAG
2013;30(S1):126–141
C. H. NOBLE ET AL.
Table 2. Juicer Product Results for Predicting Brand Vividness. Three-Factor Experimental Design of Brand Name
(3 Levels) by Brand Form (3 Levels) by Brand Logo (3 Levels) in the Prediction of Brand Vividness
Name
Nonmetaphoric
Form
Human
Animal
Non
4.75
5.14
4.40
Non
4.27
5.06
4.05
Animal
Logo
Animal
4.75
4.86
4.44
Human
4.78
4.90
4.35
Non
4.89
5.28
4.25
Animal
Logo
Human
4.59
4.92
3.69
Human
4.30
5.14
4.43
Non
4.31
4.98
4.25
Animal
Logo
5.24
4.26
4.10
Human
Note. Each of the three brand factors, name, form, and logo, had three levels of brand metaphoric theme: anthropomorphic, animate (fauna), and
nonmetaphoric. As this experimental design was fully crossed, there were a total of 27 experimental conditions. The numbers within each cell of the table
represent the mean values obtained on the brand vividness scale calculated across all research participants within that particular condition. Brand vividness
was measured with a 13-item scale, and participants responded to each item of the scale using a 7-point semantic differential response option ranging, for
example, from “not vivid” (1) to “vivid” (7). Internal consistency reliability for this scale was .91 for the juicer product.
Three-way congruent scenarios highlighted in bold.
product. Gender, age, and year in college were statistically controlled as covariates in the GLM. As congruency
interaction hypotheses were a priori, we used one-tailed
tests for detecting statistical significance of interactions
(Bing et al., 2007).
The results of this initial GLM analysis are presented
in Table 2. Notice first that within Table 2, we can see that
two of the complete congruency conditions led to the
highest levels of brand vividness. When brand name,
form, and logo were all congruent with a human metaphor theme the mean brand vividness level was 5.24,
whereas when all were congruent with an animal metaphor theme, the mean level was 5.28. Although the effects
of varying the metaphor type for the brand name and
logo were nonsignificant, a significant main effect of
varying metaphor type for the brand form was found
(F(2,387) = 14.52, p < .01). Despite the complexity of
the design, we did generally see that participants
perceived the brand with the animal form as being
more vivid (note the middle row of Table 2 compared
with others). In only one scenario was this finding
inconsistent—the human brand name condition in which
the congruency of human name, human form, and human
logo led to a relatively high level of perceived brand
vividness (M = 5.24). Under this same human brand
name condition, when the logo was changed from human
to animal, the animal form led to a higher level of perceived brand vividness (M = 4.98) in comparison to the
human form (M = 4.31). This pattern resulted in the twoway interaction of brand form and logo for the juicer
product (F(4,387) = 1.96, p = .05, one-tailed), which provided partial support for the congruency hypothesis (H2).
In the second stage of our causal model, we used
MMR to test our hypotheses that brand vividness would
have a positive relationship with brand differentiation
(Cronbach’s alpha = .90) (H3), and that product category
knowledge (Cronbach’s alpha = .87) would moderate the
brand vividness-to-brand differentiation relationship
such that it would become even stronger (i.e., more positive) when product category knowledge increased (H4).
Thus, brand vividness and product category knowledge
were expected to interact in the prediction of brand differentiation for the product. Once again, we controlled
for gender, age, and year in college in this analysis.
For the MMR procedure, we first centered the brand
vividness and product category scale scores to reduce
potential multicollinearity between these predictors and
their respective cross-product, and then multiplied these
centered scale scores to create the cross-product that
serves as the interaction term in the MMR analysis. The
brand differentiation criterion was then regressed onto
the control variables in the first step of the analysis, the
centered predictors in the second step of the analysis, and
the interaction term in the third step of the analysis.
MMR assessed whether or not the interaction term
entered in Step 3 made a unique contribution to the explanation of variance in the criterion (i.e., brand differentiation) above and beyond the controls and the main effects
of the predictors (i.e., brand vividness and product category knowledge) that were entered in Steps 1 and 2,
respectively, and partialled from the interaction term in
Step 3 of the procedure (Cohen and Cohen, 1983). As we
had an a priori interaction hypothesis, the observed alpha
for the interaction term obtained from the MMR analysis
was divided by two to increase statistical power via a
one-tailed test of statistical significance for the interaction (Bing et al., 2007). The results of the MMR analysis
revealed that entry of the control variables on Step 1 did
not produce a significant R2 (.00, p > .05). Entry of the
predictors on Step 2 produced a significant ΔR2 (.18;
BRAND METAPHORS AS DESIGN INNOVATION
F(2,410) = 45.24, p < .01), although only brand vividness
had a significant β-weight (.44; t(410) = 9.50, p < .01).
Entry of the interaction term on Step 3 did not lead to a
significant ΔR2 (.00, p > .05). Therefore, brand vividness
and product category knowledge did not interact to
explain a significant amount of variance in brand differentiation (thus, H4 was not supported). However, brand
vividness did have a strong positive relationship with
brand differentiation (β = .44, p < .01) for the juicer
product in the presence of the control variables and
product category knowledge. Therefore, the main effect
hypothesis for brand vividness in the prediction of brand
differentiation (H3) was supported.
For testing the third stage of our causal model, we also
used MMR. In this third stage, increases in brand differentiation were predicted to lead to increases in consumer
preference (Cronbach’s alpha = .93) (H5), and this positive relationship was predicted to strengthen as product
category involvement (Cronbach’s alpha = .80) increased
(H6), as personality congruence with the product
(Cronbach’s alpha = .92) increased (H8), and as willingness to publicly use the product (i.e., public consumption;
Cronbach’s alpha = .73) increased as well (H7). Once
again, we controlled for gender, age, and year in college
in this analysis. The positive relationship of brand differentiation with consumer preference, along with these
three possible interactions with brand differentiation in
the prediction of consumer preference, were tested using
MMR with control variables entered on the first step,
centered predictors on the second step, and the three
two-way interaction terms on the third step, which were
calculated from centered predictors.
The results of the MMR analysis revealed that entry of
the control variables on Step 1 did not produce a significant R2 (.00, p > .05). Entry of the predictors on Step 2
produced a significant ΔR2 (.57; F(4,408) = 135.07,
p < .01). Entry of the interaction terms on Step 3 also led
to a significant ΔR2 (.01; F(3,405) = 2.07, p = .05, onetailed). Examination of the β-weights on Step 3 revealed
that personality congruence had a strong positive relationship with consumer preference (β = .69, p < .01).
Also, the hypothesized positive relationship between
brand differentiation and consumer preference (H5) was
supported (β = .11, p < .01). However, this positive relationship between brand differentiation and consumer
preference was moderated by personality congruence,
with their interaction term being statistically significant
(H8) (β = .07, p < .05, one-tailed). The interactions predicted between public consumption and brand differentiation (H7), and between product category involvement
and brand differentiation (H6), were nonsignificant.
J PROD INNOV MANAG
2013;30(S1):126–141
135
Study 2
The goal of Study 2 was to replicate Study 1 with a
product category that offered different characteristics. A
juicer may be considered a fairly utilitarian, low involvement product, which may have an effect on the nature of
brand evaluations and the influence of brand metaphors
(Beatty and Talpade, 1994). We desired a more involving
product category for a replication study, and of the
product categories considered and discussed earlier
(e.g., audio speakers, staplers, juicers, telephones, and
robots), robots both met the earlier described tests for
anthropomorphism and were significantly more involving
(Mrobots = 13.79, Mjuicers = 10.77; t = 3.01, p = .035) on a
four-item product category involvement scale (Beatty and
Talpade, 1994).
Method
Study 2 was conducted at the same time as Study 1 using
the same subjects; the two studies were administered in a
random order. Therefore, subjects here were also n = 424
students at a major public university in the southeastern
United States, receiving course credit for their participation. Study 2 also employed a 3 (Form: human, animal,
nonmetaphor) × 3 (Name: human, animal, nonmetaphor)
× 3 (Logo: human, animal, nonmetaphor) mixed factorial
counterbalanced design. Subjects received a scenario
describing the purchase of a robot product consisting of a
form, logo, and product name (see Appendix A). Figure 2
shows the various robot variants.
Results
We analyzed the brand metaphoric data for the robot
product in the exact same manner as previously performed for the juicer product. Thus, in the first stage of
our causal model, we used a GLM to analyze the effects
of varying brand metaphoric theme (i.e., human, animal,
and nonmetaphoric) within the three brand factors (name,
form, and logo) on perceptions of brand vividness
(Cronbach’s alpha = .94) for the robot product. Gender,
age, and year in college were statistically controlled as
covariates in the GLM. Once again, as congruency interaction hypotheses were a priori, we used one-tailed tests
for detecting statistical significance of interactions (Bing
et al., 2007).
The results of this initial GLM analysis are presented
in Table 3. Notice first that within Table 3, we can see that
the pattern of results for the robot product is somewhat
dissimilar from that obtained for the juicer product. The
136
J PROD INNOV MANAG
2013;30(S1):126–141
C. H. NOBLE ET AL.
Table 3. Robot Product Results for Predicting Brand Vividness. Three-Factor Experimental Design of Brand Name
(3 Levels) by Brand Form (3 Levels) by Brand Logo (3 Levels) in the Prediction of Brand Vividness
Name
Nonmetaphoric
Form
Human
Animal
Non
3.69
4.15
3.07
Non
4.57
4.47
3.30
Animal
Logo
Animal
4.28
3.97
3.32
Human
3.47
4.36
3.07
Non
3.59
4.39
3.26
Animal
Logo
Human
4.23
3.99
3.33
Human
3.98
4.04
3.22
Non
4.61
4.97
3.52
Animal
Logo
4.56
4.05
3.07
Human
Note. Each of the three brand factors, name, form, and logo, had three levels of brand metaphoric theme: anthropomorphic, animate (fauna), and
nonmetaphoric. As this experimental design was fully crossed, there were a total of 27 experimental conditions. The numbers within each cell of the table
represent the mean values obtained on the brand vividness scale calculated across all research participants within that particular condition. Brand vividness
was measured with a 13-item scale, and participants responded to each item of the scale using a 7-point semantic differential response option ranging, for
example, from “not vivid” (1) to “vivid” (7). Internal consistency reliability for this scale was .94 for the robot product.
Three-way congruent scenarios highlighted in bold.
highest mean level of brand vividness of 4.97 was
obtained for a partially congruent condition, that of
animal form and logo, but with a human name. The next
highest mean brand vividness level of 4.61 was obtained
by another partially congruent condition, that of human
form and name, but with an animal logo. The complete
congruency condition of human theme led to a mean
brand vividness level of 4.56, whereas when all were
congruent with an animal metaphoric theme the mean
level was 4.39. Clearly, this pattern for the robot product
is somewhat dissimilar from that obtained with the juicer
product. This different pattern may be due to the fact that
robots are often imbued with some inherent humanized
features, and thus are perceived to be innately more
human-like.
For testing the second stage of the causal model for the
robot product, we used the identical MMR procedure that
was performed previously for the juicer product. As
before, brand vividness was expected to have a positive
relationship with brand differentiation (Cronbach’s
alpha = .87), and product category knowledge
(Cronbach’s alpha = .82) was expected to moderate the
brand vividness-to-brand differentiation relationship
such that this relationship was expected to become even
stronger and more positive when product category knowledge increased. Thus, brand vividness and product category knowledge were also expected to interact in the
prediction of brand differentiation for the robot product.
Gender, age, and year in college were controlled for in
this analysis. The results of the MMR analysis revealed
that entry of the control variables on Step 1 did not
produce a significant R2 (.01, p > .05). Entry of the predictors on Step 2 produced a significant ΔR2 (.21;
F(2,407) = 55.02, p < .01), although only brand vividness
had a significant β-weight on Step 2 (.44; t(407) = 9.72,
p < .01). Entry of the interaction term on Step 3 did not
lead to a significant ΔR2 (.01, p > .05). Therefore, brand
vividness and product category knowledge did not interact to explain a significant amount of variance in brand
differentiation, failing to support H4. However, brand
vividness did have a strong positive relationship with
brand differentiation (β = .44, p < .01) for the robot
product in the presence of the control variables and
product category knowledge. Therefore, the main effect
hypothesis for brand vividness in the prediction of brand
differentiation was supported (H3), and these results for
the robot product were nearly identical to those obtained
for the juicer product.
For testing the third stage of our causal model, we
also used MMR. In this third stage, increases in brand
differentiation were predicted to lead to increases in
consumer preference (Cronbach’s alpha = .91), and this
positive relationship was predicted to strengthen as
product category involvement (Cronbach’s alpha = .85)
increased, as personality congruence with the product
(Cronbach’s alpha = .90) increased, and as willingness
to publicly use the product (i.e., public consumption;
Cronbach’s alpha = .69) increased as well. Once again,
we controlled for gender, age, and year in college in this
analysis. The results of the MMR analysis revealed that
entry of the control variables on Step 1 produced a significant R2 (.04, p < .01). Entry of the predictors on Step
2 produced a significant ΔR2 (.50; F(4,405) = 110.86,
p < .01). Entry of the interaction terms on Step 3 also
led to a significant ΔR2 (.01; F(3,402) = 2.33, p < .05,
one-tailed). Examination of the β-weights on Step 3
revealed that product category involvement had a positive relationship with consumer preference (β = .11,
p < .01), as did personality congruence (β = .52,
p < .01), and public consumption (β = .11, p < .01).
BRAND METAPHORS AS DESIGN INNOVATION
Also, the hypothesized positive relationship between
brand differentiation and consumer preference was supported (β = .23, p < .01) (H5). However, this positive
relationship between brand differentiation and consumer
preference was moderated by public consumption, with
their interaction term being statistically significant
(β = .08, p < .05) (supporting H7) and indicating that as
public consumption increased so did the strength of the
positive relationship between differentiation and consumer preference. The interactions predicted between
personality congruence and brand differentiation, and
between product category involvement and brand differentiation, were nonsignificant.
Discussion
Given the large 3 × 3 design here, the extensive set of
variables considered, the validation of the model in two
different contexts, and the range of analysis methods
employed, it would be extremely unlikely to have an
unequivocally clear set of results. Given those considerations, we can report several fairly consistent and, thus,
well-validated findings from these studies that help
advance our understanding of the design of effective
brand metaphors. We consider these findings and their
implications below, organized around several major
themes.
Metaphor Types and Consistency
This study considered the influence of two common types
of brand design metaphors—human and animal—as contrasted with nonmetaphoric applications in influencing
important outcomes such as brand vividness, brand differentiation, and consumer preference. We examined
three major ways in which these metaphors are used—in
the product’s form, name, and logo. Based on various
theoretical perspectives we expected, in brief, that human
metaphors would generally be more influential than
animal which would, in turn, be more influential than the
lack of a metaphor in design. Among the modes of metaphor application, we did not predict pervasive differences
in influence across name, form, and logo but we did
expect that the consistent application of a metaphor
type across these application forms would be a powerful
influence.
On the issue of consistency, our range of analyses
generally supported the value of congruence or the consistent application of a metaphor type across name, form,
and logo. This reinforces some past literature (e.g., Klink,
2003) but also extends that work by considering three
J PROD INNOV MANAG
2013;30(S1):126–141
137
major ways in which brand metaphors are applied. This
suggests that brand managers make a more concerted
effort to extend their metaphor usage even more fully. For
example, this finding suggests that Apple Inc. consider
more nods to its fruit name and logo metaphor in its
product styling. Similarly, the Volkswagen Beetle utilizes
name and form but has no corresponding insect-inspired
logo. Our findings suggest that a more consistent use of
metaphors in brand design may lead to a more vivid
brand that stands out more clearly in the marketplace and
drives consumer preference. Interestingly, while there
may not have been pervasive advantages for consistent
human or animal metaphors over the other (see Tables 2
and 3, for example), these data and other analyses suggest
strongly that either metaphor type, if applied consistently,
is far superior to no metaphor at all. This reinforces the
powerful communication potential of metaphor usage.
Future research should consider so-called “flora,” or the
plant life-based metaphors. This is another seemingly
common metaphor type (e.g., the Olive Garden restaurant’s name and grapevine logo) but research is needed to
understand whether these metaphors exhibit the same
ability to influence as do human- and animal-based
brands. While the principles of consistent messaging
would suggest their potential effectiveness, familiarity
theory would seem to suggest flora-based metaphors
would be less effective (Guthrie, 1997), given their
seeming greater distance from the human form.
Considering the relative influence of metaphor types
(animal versus human) more deeply, some of our analyses suggested that animal metaphors may have somewhat
greater influence than their human counterparts. This was
more apparent in the robot product category. This may be
explained by the common depiction (in reality and in
fiction) of robots as helpful creatures, such as the currently popular Roomba® robotic vacuum cleaner. Combining that helpful connotation with the fact that the most
common animal metaphors are likely dogs and cats (i.e.,
beloved household pets), this combination may generate
a good deal of positive affect for many consumers.
Brand Vividness, Differentiation, and
Consumer Preference
The core links in the causal model here were well supported. Brand vividness was shown to influence brand
differentiation which, in turn, influenced consumer preference. These relationships held across product categories and even generally when including various potential
moderating factors. Our inclusion of brand vividness as
an outcome of brand design metaphors extends prior
138
J PROD INNOV MANAG
2013;30(S1):126–141
research and, by linking to differentiation and preference,
illustrates the importance of this variable in the context of
metaphor interpretation.
We did find evidence to suggest that metaphors
applied to brand form and logo may have a greater impact
than do metaphoric names. This may have implications
for the study of the human processing of metaphors,
perhaps suggesting that in these settings (or at least with
the college-aged sample here), visual processing may be
more powerful than the verbal processing associated with
a brand name. Because name is likely closest to the core
of what was meant by “brand” in the earliest writings in
the field (e.g., Wolfe, 1942), this finding suggests the
growing influence of product design (i.e., form) and
quick visual cues (e.g., logos) in determining preference.
Taken in aggregate, the core of the research model
(Figure 1) was well supported in this work and supports
the need to consider consistent and meaningful metaphors in brand management.
The Influence of Product Type, Personality, and the
Nature of Consumption
Some findings here varied based on product type and
moderating factors. There was a mixed pattern in comparing the results from the juicer and robot categories
(Study 1 and Study 2, respectively). Several relationships
were consistent across categories, such as the greater
influence of “animals” among brand forms. This finding
may relate to the increasing prominence and attachment
to household pets in modern society (Jyrinki and
Leipämaa-Leskinen, 2006), perhaps at the expense of
human connections. It is contrary to the principles of
familiarity theory, however, and thus raises questions that
need further study regarding the proper theoretical perspective for considering how consumers interpret brand
design metaphors.
Among the moderating factors, differences were found
across the two product categories. For juicers, personality
congruence moderated the relationship between brand
differentiation and consumer preference. This suggests,
perhaps surprisingly, that modern consumers consider
more than pure functionality in evaluating even something as seemingly mundane as a juicer. Consumers who
felt the “personality” of the juicer more closely matched
their own were more inclined to prefer that product. Interestingly, this moderating effect was not found in the robot
category, where one might think that a perceived personality match with a robot helper would be more critical.
One might speculate that the tactile and personal relationship a consumer has with a juicer heightens this aware-
C. H. NOBLE ET AL.
ness of fit or personality. A consumer may touch this
object, while surrounded by family, one or more times a
day, leading to a greater sense of connectedness than
more distant objects such as a robot that often sit
untouched in a corner. This finding does highlight the
need to better understand the notion of brand personality
even as applied to the most seemingly mundane items.
The moderating effect of public (versus private) consumption on the relationship between brand differentiation and consumer preference was found for the robot
category but not for juicers. This is not surprising because
consumers viewing a robot as a public good will likely
have it prominently positioned in the home, will use it as
a conversation piece with visitors, and so on. Thus, the
product can create social and self-esteem benefits for the
owner purely from its public nature, increasing the desire
to purchase for those evaluating the product in that way.
Combined, however, these differences do suggest that
product category differences (even if peripheral) do exist
in using brand design metaphors to influence consumers.
Future research needs to explore these generalizability
issues in a more systematic way to broaden our understanding of these phenomena.
Conclusions
It has been established in research and in practice that
metaphors can be quite effective in efficiently conveying
information to the potential consumer. Further, they can
serve as a powerful tool in creating effective design innovations. However, the major areas of application of these
metaphors (to name, form, and logo) have not been
studied in combination until this project. Also, this work
distinguishes between human metaphors (exploring
issues related to anthropomorphism), animal metaphors,
and the absence of any metaphor at all. We also consider
the notion of consistency, the extent to which the same
metaphor type (or lack of one) is carried across name,
form, and logo. The broader nomological model considers the influence of these choices on brand vividness,
differentiation, and consumer preference. The results
largely support the core model, with lesser support for the
proposed moderating factors. Regarding metaphor usage,
we find that human and animal metaphors are both seemingly more effective than no metaphor at all. We also find
general support for the benefits of consistently applying
these metaphors.
For managers, this work has several implications.
First, we generally support the value of metaphors in
brand development and design innovation, at least for the
two major types we have examined here. It seems that
BRAND METAPHORS AS DESIGN INNOVATION
market research into which particular metaphors may
best resonate for a particular product category would be
worthwhile. We did find some differences across product
categories in how consumers evaluate these brands. So,
determining how a brand metaphor’s personality will be
perceived is necessary. Also, it seems that certain goods
are considered more public than others, influencing how
consumers are influenced by the metaphor in making
purchase decisions for that category. Managers should
understand these nuances for their particular brand situation. Finally, this work has cross-functional implications
for new product development. The importance of metaphors in form established here suggests the importance of
the industrial design unit as part of cohesive, strategic
thinking during new product development. Logo development may be conducted internally by a graphic design
unit or perhaps outsourced, but our emphasis on consistency suggests that these groups must be early participants in the process of strategic brand management.
Finally, the need to develop a consistent brand metaphor
name stresses the ongoing importance of a strong marketing group. Early partnership and communication
among these units during the brand and product development process would seem essential for the creation of
cohesive and influential metaphors.
Design innovation has been increasingly discussed as
a cross-functional effort to create products with holistic
and powerful impact on the consumer, and which create
unique meaning which is difficult to replicate by the
competition (Luchs and Swan, 2011). In this view, effective design is more than simply combining form and
function but achieving a higher level of influence, as can
seemingly be achieved through the proper use of brand
metaphors.
Microsoft’s “Windows” (to the world? or to your
computer?), the inviting egg-shape of a Michael Graves
toaster, and the exciting Ferrari “prancing horse” logo
all use metaphors to contribute to building powerful
brands. When metaphors are applied to forms, in particular, the implications for the product development process
are much more significant. Our research stresses the
importance of brand metaphors, particularly when used
strategically and in combination, in order to create differentiated and desirable products in the marketplace.
Appendix A
Experiment 1 Scenario (Juicers)
Below, we describe a scenario of a hypothetical situation.
We would like you to imagine yourself in this situation.
J PROD INNOV MANAG
2013;30(S1):126–141
139
Recently, you graduated from college with a bachelor’s degree and got a job. You found an apartment for
rent, signed a lease, and started organizing and decorating
your new place. As a part of a New Year’s resolution, you
decided to develop a “healthier ”lifestyle, including
getting more physical exercise and eating healthier foods.
While thinking about kitchen appliances to be included in
shopping for your new place, you added a citrus juicer,
knowing that many people think fresh squeezed orange
juice is a very healthy way to start the day. Having no
prior experience of dealing with juicers, you decided to
first to make an initial search on your own. First, you
went to http://www.google.com and performed a search
on the word “juicer,” and examined the results. Your
search resulted in several types of juicer-related links.
These included pictures of juicers, logos of different
juicer brands, and different brand names for juicers. In
examining the results, you were surprised by the number
of different juicers available.
Below, you see the name, logo, and a picture of the
juicer brand listed first in your Google search results.
Experiment 2 Scenario (Robots)
Below, we describe a scenario of a hypothetical situation.
We would like you to imagine yourself in this situation.
Recently, you had a lecture about Japan in your Global
Marketing course. The main part of this lecture was a
presentation on robots used in industrial settings. All
these industrial robots looked gigantic and similar to
computers. You found this to be an interesting discussion.
After the class, you and your classmate continued the
theme of robots by recalling “Star Wars” and other
movies. At one point, you brought to the conversation the
possibility of searching and buying one, as your uncle
promised to pay for a product that you would choose as a
present for your upcoming graduation. Your uncle is a
“tech savvy” guy working as an engineer for a high-tech
company. He would definitely be more in favor of purchasing a technology product over a car, vacation, or
other typical graduation gift. You and your friend decided
to go to the Internet and to search for different types of
robots separately and then to discuss what you found.
Your initial decision was to go to http://www.google.com,
perform a search on the word “robot,” and examine the
results. Your search resulted in several types of robotrelated links. These included pictures of robots, logos of
different robot brands, and different brand names for
robots. In examining the results, you were surprised by
the number of different robots available.
This is a picture of the product listed first in your
Google search results.
140
J PROD INNOV MANAG
2013;30(S1):126–141
C. H. NOBLE ET AL.
References
Guthrie, S. 1993. Faces in the clouds: A new theory of religion. New York:
Oxford University Press.
Aaker, J. L. 1995. Brand personality: Conceptualization, measurement
and underlying psychological mechanisms. Unpublished doctoral
dissertation. Stanford University, Stanford, CA.
Guthrie, S. E. 1997. Anthropomorphism: A definition and a theory. In
Anthropomorphism, anecdotes, and animals, ed. R. W. Mitchell, N. S.
Thompson, and H. L. Miles, 50–58. Albany, NY: State University of
New York Press.
Aggarwal, P., and A. L. McGill. 2007. Is that car smiling at me? Schema
congruity as a basis for evaluating anthropomorphized products.
Journal of Consumer Research 34 (December): 468–79.
Alba, J. W., and J. W. Hutchinson. 1987. Dimensions of consumer expertise. Journal of Consumer Research 13 (March): 411–54.
Ang, S. H., and E. A. C. Lim. 2006. The influence of metaphors and product
type on brand personality perceptions and attitudes. Journal of Advertising 35 (2): 39–53.
Beatty, S. E., and S. Talpade. 1994. Adolescent influence in family decision
making: A replication with extension. Journal of Consumer Research
21 (September): 322–41.
Bentler, P. M., and C.-P. Chou. 1987. Practical issues in structural modelling. Sociological Methods and Research 16: 78–117.
Bing, M. N., J. M. LeBreton, H. K. Davison, D. Z. Migetz, and L. R. James.
2007. Integrating implicit and explicit social cognitions for enhanced
personality assessment: A general framework for choosing measurement and statistical methods. Organizational Research Methods 10 (2):
346–89.
Blanchard, J., and G. McNinch. 1984. The effects of anthropomorphism on
word learning. Journal of Educational Research 78 (2): 105–10.
Capelli, S., and A. Jolibert. 2009. Metaphor’s validity in marketing
research. Psychology and Marketing 26 (12): 1079–90.
Carpenter, G. S., and K. Nakamoto. 1989. Consumer preference formation
and pioneering advantage. Journal of Marketing Research 26 (August):
285–98.
Celsi, R. L., and J. C. Olson. 1988. The role of involvement in attention and
comprehension processes. Journal of Consumer Research 15 (September): 210–24.
Chang, C.-T., and Y.-K. Lee. 2010. Effects of message framing, vividness
congruency and statistical framing on responses to charity advertising.
International Journal of Advertising 29 (2): 195–220.
Cohen, J., and P. Cohen. 1983. Applied multiple regression/correlation
analysis for the behavioral sciences (2nd ed.). Hillsdale, NJ: Lawrence
Erlbaum Associates.
Cornelissen, J. P. 2003. Metaphor as method in the domain of marketing.
Psychology and Marketing 20 (3): 209–25.
Costley, C. L., and M. Brucks. 1992. Selective recall and information use in
consumer preferences. Journal of Consumer Research 18 (March):
464–74.
Cotte, J., S. Ratneshwar, and D. G. Mick. 2004. The times of their lives:
Phenomenological and metaphorical characteristics of consumer
timestyles. Journal of Consumer Research 31 (2): 333–45.
Dickson, P. R., and J. L. Ginter. 1987. Market segmentation, product
differentiation, and marketing strategy. Journal of Marketing 51 (2):
1–10.
Fishbein, M., and I. Ajzen. 1975. Belief, attitude, intention and behavior:
An introduction to theory and research. Reading, MA: Addison-Wesley
Publishing Company.
Flynn, L. R., and R. E. Goldsmith. 1999. A short, reliable measure of
subjective knowledge. Journal of Business Research 46 (1): 57–66.
Garretson, J. A., and R. W. Niedrich. 2004. “Spokes-characters”: Creating
character trust and positive brand attitudes. Journal of Advertising 33
(2): 25–36.
Giese, J. L., E. R. Spangenberg, and A. E. Crowley. 1996. Effects of
product-specific word-of-mouth communication on product category
involvement. Marketing Letters 7 (2): 187–99.
Govers, P. C. M., and R. Schoormans. 2005. Product personality and its
influence on consumer preference. The Journal of Consumer Marketing
22 (4/5): 189–97.
Hoegg, J. A., and J. W. Alba. 2011. Seeing is believing (too much): The
influence of product form on perceptions of functional performance.
Journal of Product Innovation Management 28: 346–59.
Hunt, S. D., and A. Menon. 1995. Metaphors and competitive advantage:
Evaluating the use of metaphors in theories of competitive strategy.
Journal of Business Research 33 (2): 81–90.
Jaccard, J., and C. K. Wan. 1996. LISREL approaches to interaction effects
in multiple regression. Thousand Oaks, CA: Sage Publications.
Jyrinki, H., and H. Leipämaa-Leskinen. 2006. Pets as extended self in the
context of pet food consumption. Advances in Consumer Research –
European Conference Proceedings 7: 543–49.
Keller, P. A., and L. G. Block. 1997. Vividness effects: A resource-matching
perspective. Journal of Consumer Research 24 (December): 295–304.
Kiesler, T. 2006. Anthropomorphism and consumer behavior. Advances in
Consumer Research 33 (1): 149.
Klink, R. R. 2003. Creating meaningful brands: The relationship between
brand name and brand mark. Marketing Letters 14 (3): 143–57.
Kulviwat, S., G. C. Bruner II, and O. Al-Shuridah. 2009. The role of social
influence on adoption of high tech innovations: The moderating effect
of public/private consumption. Journal of Business Research 62: 706–
12.
Lakoff, G., and M. Johnson. 1980. Metaphor we live by. Chicago, IL:
University of Chicago Press.
Landwehr, J. R., A. L. McGill, and A. Herrmann. 2011. It’s got the look:
The effect of friendly and aggressive “facial” expressions on product
liking and sales. Journal of Marketing 75 (3): 132–46.
Luchs, M., and K. S. Swan. 2011. Perspective: The emergence of product
design as a field of marketing inquiry. Journal of Product Innovation
Management 28: 327–45.
MacInnis, D. J., S. Shapiro, and M. Gayathri. 1999. Enhancing brand
awareness through brand symbols. Advances in Consumer Research
26: 601–8.
Macklin, M. C. 1996. Preschoolers’ learning of brand names from visual
cues. Journal of Consumer Research 23 (3): 251–61.
Malaviya, P., and K. Sivakumar. 1998. The moderating effect of product
category knowledge and attribute importance on the attraction effect.
Marketing Letters 9 (1): 93–106.
McQuarrie, E. F., and D. G. Mick. 1996. Figures of rhetoric in advertising
language. Journal of Consumer Research 22 (March): 424–38.
McQuarrie, E. F., and B. J. Phillips. 2005. Indirect persuasion in advertising: How consumers process metaphors presented in pictures and
words. Journal of Advertising 34 (2): 7–20.
McWilliam, G., and A. Dumas 1997. Using metaphors in new brand design.
Journal of Marketing Management 13: 265–84.
Nisbett, R. E., and L. Ross. 1980. Assessing weights to data: The “vividness
criterion.” In Human inference: Strategies and shortcomings of social
judgment, ed. R. E. Nisbett and L. Ross, 42–62. Englewood Cliffs, NJ:
Prentice-Hall.
Noble, C. H. 2011. On elevating strategic design research. Journal of
Product Innovation Management 28: 389–93.
Park, C. W., and S. M. Young. 1986. Consumer response to television
commercials: The impact of involvement and background music on
brand attitude formation. Journal of Marketing Research 23 (1): 11–24.
Patton, J. W. 1987. The real meaning and significance of the great seal
of the United States. Available at: http://jpatton.bellevue.edu/
biblical_economics/greatseal.html
Porter, M. 1985. Competitive advantage: Creating and sustaining superior
performance. New York: Free Press.
BRAND METAPHORS AS DESIGN INNOVATION
Ratner, R. K., and B. E. Kahn. 2002. The impact of private versus public
consumption on variety-seeking behavior. Journal of Consumer
Research 29 (September): 246–57.
Sen, S. 1998. Knowledge, information mode, and the attraction effect.
Journal of Consumer Research 25 (June): 64–77.
Shaw, A. W. 1912. Some problems in market distribution. Quarterly
Journal of Economics 26 (4): 703–65.
Sirgy, M. J. 1982. Self-concept in consumer behavior: A critical review.
Journal of Consumer Research 9 (3): 287–300.
Sirgy, M. J., D. Grewal, T. F. Mangleburg, J. Park, K.-S. Chon, C. B.
Claiborne, J. S. Johar, and H. Berkman. 1997. Assessing the predictive
validity of two methods of measuring self-image congruence. Journal
of the Academy of Marketing Science 25 (Summer): 229–41.
Slovic, P. 1993. Perceived risk, trust, and democracy. Risk Analysis 6:
675–82.
Song, X. M., and M. E. Parry. 1997. The determinants of Japanese new
product successes. Journal of Marketing Research 34 (February):
64–76.
Stewart, D. W. 1986. The moderating role of recall, comprehension, and
brand differentiation on the persuasiveness of television advertising.
Journal of Advertising Research 26 (2): 43–47.
J PROD INNOV MANAG
2013;30(S1):126–141
141
Townsend, J. D., M. M. Montoya, and R. J. Calantone. 2011. Form and
function: A matter of perspective. Journal of Product Innovation Management 28: 374–7.
Vargo, S. L., and R. F. Lusch. 2004. Evolving to a new dominant logic for
marketing. Journal of Marketing 68 (1): 1–17.
Verganti, R. 2011. Radical design and technology epiphanies: A new focus
for research on design management. Journal of Product Innovation
Management 28: 384–88.
Wolfe, H. D. 1942. Techniques of appraising brand preference and brand
consciousness by consumer interviewing. Journal of Marketing 6 (4):
81–87.
Zaichkowsky, J. L. 1985. Measuring the involvement construct. Journal of
Consumer Research 12 (December): 341–52.
Zaltman, G. 1996. Metaphorically speaking: New technique uses multidisciplinary ideas to improve qualitative research. Marketing Research 8
(Summer): 13–20.
Zaltman, G., and L. H. Zaltman. 2008. Marketing metaphoria: What deep
metaphors reveal about the minds of consumers. Cambridge, MA:
Harvard Business School Press.