Consumer perceptions of co-branding alliances: Organizational dissimilarity signals and brand fit

Abstract

This study explores how consumers evaluate co-branding alliances between dissimilar partner firms. Customers are well aware that different firms are behind a co-branded product and observe the partner firms’ characteristics. Drawing on signaling theory, we assert that consumers use organizational characteristics as signals in their assessment of brand fit and for their purchasing decisions. Some organizational signals are beyond the control of the co-branding partners or at least they cannot alter them on short notice. We use a quasi-experimental design and test how co-branding partner dissimilarity affects brand fit perception. The results show that co-branding partner dissimilarity in terms of firm size, industry scope, and country-of-origin image negatively affects brand fit perception. Firm age dissimilarity does not exert significant influence. Because brand fit generally fosters a benevolent consumer attitude towards a co-branding alliance, the findings suggest that high partner dissimilarity may reduce overall co-branding alliance performance.

Full text

Original Article
Consumer perceptions of
co-branding alliances:
Organizational dissimilarity
signals and brand fit
Received (in revised form): 15th July 2016
Carolin Decker
is a Professor of management and organization at the University of Bremen, Germany. Prior to this appointment, she was
an Assistant Professor at WHU -- Otto Beisheim School of Management. She received her Ph.D. in management in 2007
and her post-doctoral lecture qualification in 2014 from Freie Universita¨t Berlin. Her research interests include the
governance of inter-organizational relationships, family businesses and family offices, and organizational decline and
recovery.
Annika Baade
is a Ph.D. candidate in management at the University of Bremen, Germany. She received her M.Sc. degree in management
from WHU -- Otto Beisheim School of Management in Vallendar, Germany, in 2015. Her research interests lie at the
intersection of inter-organizational partnerships, marketing strategy, branding, and licensing.
ABSTRACT This study explores how consumers evaluate co-branding alliances
between dissimilar partner firms. Customers are well aware that different firms are
behind a co-branded product and observe the partner firms’ characteristics. Drawing
on signaling theory, we assert that consumers use organizational characteristics as
signals in their assessment of brand fit and for their purchasing decisions. Some
organizational signals are beyond the control of the co-branding partners or at least
they cannot alter them on short notice. We use a quasi-experimental design and test
how co-branding partner dissimilarity affects brand fit perception. The results show
that co-branding partner dissimilarity in terms of firm size, industry scope, and
country-of-origin image negatively affects brand fit perception. Firm age dissimilarity
does not exert significant influence. Because brand fit generally fosters a benevolent
consumer attitude towards a co-branding alliance, the findings suggest that high
partner dissimilarity may reduce overall co-branding alliance performance.
Journal of Brand Management (2016) 23, 648–665. doi:10.1057/s41262-016-0013-5;
published online 25 August 2016
Keywords: co-branding alliances; brand fit; consumer attitude; signaling theory;
consumer perceptions; quasi-experiment
Correspondence:
Carolin Decker, Department of
Management and Organization,
Faculty 7: Business Studies and
Economics, University of
Bremen, Wilhelm-Herbst-Straße
5, 28359 Bremen, Germany
E-mail: Carolin.Decker@uni-
bremen.de
ª2016 Macmillan Publishers Ltd. 1350-231X Journal of Brand Management Vol. 23, 6, 648–665
www.palgrave.com/journals

INTRODUCTION
Co-branding alliances, which are a ‘strategy
of presenting two or more independent
brands jointly on the same product or ser-
vice’ (Erevelles et al,2008, p. 940), have
become increasingly popular in recent
decades (Ahn and Sung, 2012; Baxter and
Ilicic, 2015; Besharat and Langan, 2014;
Helmig et al,2008). Prior research has
mainly been concerned with the drivers of
customer evaluations of co-branding alli-
ances (Gammoh and Voss, 2011), such as
perceived partner brand fit (Park et al,
1996; Simonin and Ruth, 1998; Van der
Lans et al,2014). Both customer perception
and strategic motives drive co-branding
alliance formation (O’Dwyer et al,2011),
which may result in partnerships of dis-
similar firms. Organizational dissimilarities
refer to considerable and perceivable dif-
ferences in the dimensions of the organi-
zations’ company profiles, such as date of
establishment, country-of-origin, size, and
industry. These visible dissimilarities serve
as signals (Connelly et al,2011), which
affect consumers’ brand fit perceptions
(Ahn and Sung, 2012) and their attitudes
towards co-branding alliances (Ashton and
Scott, 2011; Simonin and Ruth, 1998).
Although the understanding of organiza-
tional dissimilarity signals on consumer
perception is vital to ensure co-branding
alliance performance, our knowledge on
this topic is limited. Using a quasi-experi-
mental approach, we examine how co-
branding alliances involving dissimilar partners
affect consumer-brand fit perceptions.
In this study, a co-branding alliance
means that, first, two or more independent
partner firms form the alliance. Second, all
brands involved receive significant cus-
tomer recognition and remain independent
throughout the medium to long-term
partnership. Third, its net value does not
suffice to justify the formation of a joint
venture or the establishment of a new
brand. Fourth, both brand names appear on
the common physical product (Blackett
and Russell, 1999;Se
´ne
´chal et al,2014).
Our study makes two contributions:
First, we add to the understanding of co-
branding alliance formation, consumer
evaluation, and performance by identifying
organizational antecedents of perceived
brand fit, which have not yet been
addressed in past customer perspective
research. From a firm’s perspective, these
organizational characteristics reflect strate-
gic motives for the formation of co-
branding alliances and partner selection
(Oeppen and Jamal, 2014), such as the
access to complementary resources (Chung
et al,2000; Wernerfelt, 1984), the devel-
opment of new customer segments (Har-
rigan and Newman, 1990; O’Dwyer et al,
2011), and the entry into new geographical
markets (Glaister and Buckley, 1996;
Reuer et al,2011). As many studies use
signaling theory ‘to explain the effective-
ness of brand alliances with respect to
consumers (…), it seems logical to inves-
tigate the sender side of the signaling
phenomenon’ (Gammoh and Voss, 2011,
p. 83). We examine the co-branding part-
ners’ combined organizational characteris-
tics and their impact on consumers’
assessments. Second, our study provides
new insights into how the partner firms
convey both intended and unintended
signals to the customers. The interplay of
their organizational characteristics and the
importance of these characteristics to their
customers affect individual perceptions of
brand fit and attitudes towards the alliance.
The remainder of this study is organized as
follows: first, we review previous research on
co-branding alliances. Second, drawing on
signaling theory, we outline five hypotheses.
Third, we elaborate on the chosen methods
and present our results. Finally, we discuss
our findings and outline implications for
future research and management.
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PRIOR RESEARCH
Co-branding alliances have primarily been
studied from a marketing and brand man-
agement perspective (Bengtsson and Ser-
vais, 2005; Besharat and Langan, 2014;
Gammoh and Voss, 2011). This perspec-
tive explores the effects of consumer per-
ceptions of co-branding alliance partners,
such as brand and product fit, brand
awareness, quality perception, brand atti-
tude, brand equity, and brand credibility on
performance (Aghdaie et al,2012; Levin
et al,1996; Park et al,1996;Se
´ne
´chal et al,
2014; Simonin and Ruth, 1998; Swami-
nathan et al,2015; Washburn et al,2004).
Findings illustrate that, first, perceived
brand and product category fit between
alliance partners (for example, Baumgarth,
2004; Simonin and Ruth, 1998) and fit
between the co-brands and product cate-
gories with the new product (for example,
Bouten et al,2011) are highly important.
Second, consumer attributes, such as self-
complexity (Monga and Lau-Gesk, 2007),
brand loyalty (Swaminathan et al,2012),
involvement (Samuelsen et al,2015; Wal-
chli, 2007), consumer-brand identification
(Xiao and Lee, 2013), gender (Lau and
Phau, 2010), age (Charry and Demoulin,
2014), as well as brand attributes, such as
complementarity and similarity (Swami-
nathan et al,2015), moderate the relation-
ship between a co-branded offering and
co-branding alliance performance. Third,
spillover effects are especially likely in co-
branding alliances with high brand and
product fit and asymmetric brand equity
distributions (Simonin and Ruth, 1998;
Swaminathan et al,2012). Finally, co-
branding alliances effectively enhance
consumer evaluations of co-brand quality
and credibility (Rao et al,1999; Voss and
Tansuhaj, 1999). They have a positive
signaling effect (Aghdaie et al,2012).
While ‘customer perspective’ research
places the customer as the receiver of signals
at center stage, studies adopting a ‘firm
perspective’ focus on the sender’s side.
Consistent with research on the formation
of strategic alliances, they explore, for
instance, key motives (Al Khattab, 2012;
O’Dwyer et al,2011), alliance experience
and governance choices (Cavazos and
Varadarajan, 2012;Liet al,2010;Sauve
´e
and Coulibaly, 2010), and access to the
partner’s customers and resources (Leu-
thesser et al,2003;O’Dwyeret al,2011).
There are differences between these
research streams. First, co-branding research
is more concerned with brand-related risks,
such as partner brand performance (Abra-
hams and Granof, 2002), decreasing con-
sumer orientation (Rindfleisch and
Moorman, 2010), or brand equity dilution
(Herm, 2014), than with the strategic and
behavioral risks of alliance formation, such as
opportunism (Parkhe, 1993)orknowledge
leakage (Kale et al,2000). Second, in addition
to, for example, resource endowments, prior
ties, partner fit, partner status and reputation
(Beckman et al,2004;Chunget al,2000;
Gulati, 1998; Varadarajan and Cunningham,
1995), brand-related aspects, such as brand
reputation and brand product quality, play a
prominent role in co-branding partner
selection (Gammoh and Voss, 2011). Market
uncertainty differently affects governance
choices in strategic and co-branding alliances.
In strategic alliances, partner opportunism,
market uncertainty, and competition
enhance the likelihood of equity-based
governance (Dyer et al,2004;Gulati,1998).
Conversely, the likelihood of equity-based
governance in co-branding alliances will be
lower if market uncertainty increases (Li et al,
2010).
In our hypotheses, we combine both
strands of literature and emphasize the firm
perspective by identifying co-branding
partners’ potentially dissimilar organiza-
tional characteristics. We consider the
customer perspective by relating these
Decker and Baade
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organizational characteristics to consumers’
assessments of brand fit and attitudes
towards co-branding alliances.
THEORY AND HYPOTHESES
Signaling theory
According to signaling theory, firms will
achieve favorable consumer perceptions
and will positively affect consumer deci-
sion-making at the point of purchase, if
they convey relevant information and
reduce firm--consumer information asym-
metry. Two brand names with similar or
complementary attributes on a single pro-
duct imply that a firm borrows equity from
the partner firm’s brand (Rao and Ruekert,
1994; Spence, 1973; Swaminathan et al,
2015). Customer perspective research sug-
gests that co-branding alliances serve as
intended market signals of innovation,
product quality, and credibility (Rao et al,
1999). The perception of a high level of
brand fit drives consumer affect (Baum-
garth, 2004;Se
´ne
´chal et al,2014; Simonin
and Ruth, 1998). Consumers may react
more positively to the combination of two
brands than if a product reveals a single
brand (Swaminathan et al,2015).
In contrast to other types of alliances, in
co-branding alliances, customers are well
aware that different companies are behind
the product (Newmeyer et al,2014). They
can observe salient organizational charac-
teristics of the co-branding partners. Based
on these signals, customers form corporate
associations. They use them for the assess-
ment of the value of the cooperation of
these firms on the brand and product level
(Brown and Dacin, 1997). Customers’
attitudes towards co-branding alliances will
be more positive, if the partner firms fit
well together and their perceived similarity
is high (Se
´ne
´chal et al,2014).
Some signals are beyond the control of
the co-branding partners (Bangerter et al,
2012). Organizational characteristics are a
case in point. Co-branding partners may
have dissimilar organizational characteris-
tics (De Man, 2013) that can hardly be
manipulated. They often unintentionally
affect customers’ brand fit perceptions and
attitudes (Connelly et al,2011;Gu
¨rhan-
Canli and Batra, 2004). Because the simi-
larity of co-branding partners leads to the
perception of a higher brand fit (Simonin
and Ruth, 1998), we argue that firms with
dissimilar organizational characteristics in
terms of size, age, industry scope, and
country-of-origin image, which cannot be
aligned on short notice, provide potentially
unintended market signals and, in turn,
achieve lower brand fit evaluations.
Firm size
The number of alliance formations
between large and small firms is steadily
growing (Mellewigt and Decker, 2014;
Yang et al,2014). For smaller firms, which
often lack brand awareness, market power,
and financial resources, forming alliances
with large, established corporations often
represents the only way to get rapid access
to necessary resources at relatively low costs
while remaining independent (Dyer and
Singh, 1998; Rothaermel, 2001). Allying
with an established firm enhances a new
venture’s legitimacy and quality perception
(Stuart et al,1999). Large, mature firms
enter into strategic alliances with small
firms and start-ups to benefit from their
product innovativeness and adaptability
(King et al,2003). Therefore, large, estab-
lished corporations and small start-ups
enter alliances because of their comple-
mentary resources that, among other
things, result from the organizations’ dif-
ference in size.
Information about size is publicly avail-
able, so that consumers are knowledgeable
about the organizational dissimilarity in co-
branding alliances between large and small
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firms. If consumers, who have limited
cognitive capacity to process new infor-
mation (Payne, 1982), evaluate brands,
they tend to rely on signals that firms send
to reduce information asymmetry (Spence,
1973). The evaluation of a co-branding
alliance is more complex than the evalua-
tion of a single brand. Consumers try to
reduce the cognitive effort by actively
searching for signals and relying on their
knowledge about the two brands involved.
Because this knowledge includes informa-
tion about characteristics of the firms
behind the brands, co-branding alliances
between large and small firms send a dis-
similarity signal. As firm size cannot easily
be manipulated on short notice and brand
managers might not consider organizational
characteristics as co-branding alliance sig-
nals, firm size dissimilarity might be an
unintended signal.
Dissimilarity signals, either intended or
unintended, represent a higher cognitive
effort to consumers than similarity signals.
This higher level of cognitive effort frus-
trates them and evokes negative affect (Ahn
and Sung, 2012; Garbarino and Edell,
1997). Consequently, signals of firm size
dissimilarity are evaluated less favorably
than firm size similarity signals.
H1 High firm size dissimilarity of co-
branding alliance partners is nega-
tively related to customer brand fit
perception.
Firm age
Despite their innovative capacity, new
ventures often lack knowledge and capa-
bilities required for the commercialization
of their ideas, ‘such as marketing, com-
peting manufacturing, and after sales sup-
port’ (Colombo et al,2006, p. 1166). By
forming partnerships with established firms,
young firms can overcome the liability of
newness and resource constraints and
benefit from reputational spillover effects
(Baum et al,2000). They thereby achieve
external legitimacy (Dacin et al,2007;
Singh et al,1986). Alliances between young
firms with new brands and established
companies with well-known brands
enhance the small brand’s quality percep-
tion and brand awareness (Fang and Mis-
hra, 2002). Established firms often suffer
from a decreasing innovativeness (Das and
He, 2006), because their mature organiza-
tional structure frequently lacks flexibility
and hampers sustained product innovation
(Dougherty and Hardy, 1996). Therefore,
they form alliances with young firms to
explore new growth opportunities by
exploiting the younger partners’ techno-
logical competencies (Colombo et al,2006;
Reuer and Tong, 2010; Shan et al,1994).
Firm age significantly influences the
corporate social responsibility perception of
stakeholders (Dilling, 2011). Therefore, we
assume that firm age is well recognizable by
consumers. Moreover, consumers tend to
be more familiar with established than with
new brands, because the likelihood that, for
example, they have touchpoints or have
tried a product that is available for more
than ten years is higher than for a product
that has recently been launched (Jacoby
et al,1977). In addition, the ‘larger the
number of cues […] the greater the likeli-
hood that the information can be recalled’
(Keller, 1993, p. 5) and the lower is the
cognitive effort required for evaluation and
decision-making. If consumers evaluate a
co-branding alliance with a high firm age
dissimilarity, they will be able to recall a
high number of brand attributes for the
established co-branding partner, while
lacking such brand associations for the new
brand. This difference in the number of
recallable brand attributes for the co-
branding partners sends a (mainly unin-
tended) dissimilarity signal to consumers
and makes it more difficult for them to
establish a cognitive link between the new
and the established brand (Ahn and Sung,
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2012). This difficulty enhances their frus-
tration and negatively affects their brand fit
perceptions (Ahn and Sung, 2012; Gar-
barino and Edell, 1997).
H2 High firm age dissimilarity of co-
branding alliance partners is nega-
tively related to customer brand fit
perception.
Industry scope
Firms generally enter alliances with firms
from different product categories and
industries to gain access to new customer
groups and enhance brand awareness
(Abratt and Motlana, 2002; Ahn et al,2009;
Gammoh et al,2006; Smarandescu et al,
2013). As partners in these inter-industry
alliances have a different industry or pro-
duct category focus, their industry scopes
are dissimilar. Because consumers are
knowledgeable about firms’ industry scope,
so that they, for example, associate Porsche
with sports cars or Beiersdorf with skin care
products, they are also likely to recognize
industry scope dissimilarity in inter-indus-
try co-branding alliances.
If consumers evaluate alliances between
brands that are associated with different
product categories and serve different
consumer needs, they have problems to
align the co-branding partners’ brand
attributes (Smarandescu et al,2013; Zhang
et al,2002). Ahn et al (2009) suggest that a
high perceived ‘match-up,’ which ‘refers to
consumer perceptions of the degree of
relevance or correspondence between two
paired product categories’ (p. 479) results
in more positive consumer evaluations.
Vice versa, industry scope dissimilarity sig-
nals ‘(for example, the co-branding
between a clothing brand and an automo-
tive brand) demand excessive processing to
resolve the discrepancy’ (Ahn and Sung,
2012, p. 422). They hence lead to less
favorable brand fit perceptions.
H3 High industry scope dissimilarity of
co-branding alliance partners is neg-
atively related to customer brand fit
perception.
Country-of-origin image
Alliances can be used to introduce brands
and products to new geographical regions
and markets (Abratt and Motlana, 2002;
Lee et al,2013; Ueltschy and Laroche,
2011). International co-branding alliances
represent a widely adopted strategy in
today’s increasingly global business envi-
ronment (Li and He, 2013). Firms ally with
foreign brands, headquartered in different
countries (Bluemelhuber et al,2007)in
order to avoid market entry barriers
(Glaister and Buckley, 1996; Reuer et al,
2011), to reduce costs of doing business
abroad (Hymer, 1960/1976), and to
decrease the liability of foreignness (Za-
heer, 1995). Forming partnerships with
local firms can help overcome consumer
animosity towards foreign brands (Fong
et al,2014; Li and He, 2013; Voss and
Tansuhaj, 1999). Local brands enter inter-
national co-branding alliances to benefit
from the foreign partner’s investments and
technology (Abratt and Motlana, 2002;
Gre˛bosz and Otto, 2013).
Consumers take the country image into
account when they evaluate a product
(Essoussi and Merunka, 2007; Hong and
Wyer, 1989; Koschate-Fischer et al,2012)
and a co-branding alliance (Bluemelhuber
et al,2007). Brands’ country images can
have positive or negative effects on pur-
chase intentions (Josiassen, 2011). Co-
branding alliances between partners that are
both associated with a positive country
image are more favorably evaluated by
consumers than co-branding partnerships
between one brand with a positive and one
with a negative country image (Lee et al,
2013). This finding might be explained by
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a negative spillover effect from the brand
with the negative country image on the
perception of the co-branding alliance,
resulting in a lower perception of overall
co-branded product quality.
Consumer ethnocentrism research asserts
that consumers use domestic standards as a
reference point in the evaluation of foreign
products (Balabanis and Diamantopoulos,
2004). Cultural attributes, such as language,
religion, social norms, and beliefs, guide
consumers’ preferences especially regarding
consumer goods, everyday choices, and
social interactions (Ghemawat, 2001).
Foreign products that come from countries
with a high cultural similarity to the home
country tend to be evaluated more favor-
ably than products from culturally dissimi-
lar countries (Sharma et al,1995).
Consumers attribute to countries with a
low cultural distance to their home country
a more positive image than to countries
with a high cultural distance. If the per-
ceived cultural distance between interna-
tional co-branding partners is low, it does
not challenge a consumer’s general beliefs
or cultural identity (Ghemawat, 2001).
Conversely, the matching of the country
images of co-branding partner brands with
a high cultural distance requires a higher
cognitive effort, which result in less
favorable brand fit assessments (Ahn and
Sung, 2012; Garbarino and Edell, 1997).
H4 High country-of-origin image dis-
similarity of co-branding alliance
partners is negatively related to cus-
tomer brand fit perception.
Consumer attitudes towards co-
branding alliances
Previous research on co-branding has tes-
ted the effect of brand fit perception on the
consumer evaluation of the co-branding
alliance (Arnett et al,2010; Baumgarth,
2004; Dickinson and Barker, 2007; Lafferty
et al,2004; Simonin and Ruth, 1998)asan
indicator for overall co-branding alliance
performance. Generally, a higher level of
perceived brand fit results in more positive
consumer evaluations in terms of consumer
attitude towards the co-branding alliance
(Graeff, 1997). Consumer attitude towards
brands and co-branding alliances, which is
‘defined as consumers’ overall evaluations
of a brand’ (Keller, 1993, p. 4), directly
affects consumer actions, decision-making,
and behavior (Dickinson and Heath, 2006).
To investigate whether consumer-brand
fit perception has implications for con-
sumer decision-making and ultimately for
co-branding alliance performance, we
include the following hypothesis:
H5 Brand fit perception is positively
related to consumer attitude towards
the co-branding alliance.
METHODOLOGY
Research design
We used a quasi-experimental design.
Respondents received a questionnaire
comprising a set of hypothetical vignettes
that they had to assess. Vignettes are sce-
narios comprising ‘short descriptions of a
person or a social situation, which contain
precise references to what are thought to be
[…] important factors in decision-making
or judgment-making processes of the
respondents’ (Alexander and Becker, 1978,
p. 94). The scenarios described our unit of
analysis -- co-branding alliances -- and a
limited set of dimensions -- the indepen-
dent variables. Each scenario represented a
unique combination of different dimen-
sions (Atzmu
¨ller and Steiner, 2010). We
used a full factorial design (Karren and
Barringer, 2002). The scenario universe of
this study representing all combinations of
four dimensions’ variations comprised 16
scenarios. We described hypothetical co-
branding alliances (Ahn and Sung, 2012)to
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‘avoid any additional brand associations
aside from those presented in the scenario’
(Kalafatis et al,2012, p. 627). We omitted
real brand names in order to avoid framing
effects and cognitive biases resulting from
respondents’ experiences with a brand or
with real marketing situations (Jun et al,
2005; Zhang and Taylor, 2001).
Such a design offers several advantages.
First, researchers can control the indepen-
dent variables, while excluding external
factors that might distort assessments
(Aguinis and Bradley, 2014; Ashill and
Yavas, 2006). Second, the design allows for
simultaneous testing of individual effects of
multiple factors on a dependent variable
(Groß and Bo
¨rensen, 2009; Sauer et al,
2009). Third, because factorial research
employs scenarios as stimuli, which
describe a specific decision problem and
require a lower cognitive effort of respon-
dents, it is more likely that respondents
grasp the decision problem correctly and
focus on the variables tested in factorial
research than in standardized direct-ques-
tion-based surveys (Groß and Bo
¨rensen,
2009; Weber, 1992). Fourth, all respon-
dents receive the same set of standardized
stimuli, which increases the replicability of
results (Alexander and Becker, 1978).
The research design addresses consumers’
perceptions in general, so that students rep-
resent relevant and suitable respondents
(Fang et al,2013; Gammoh et al,2006;
Thompson and Strutton, 2012). We col-
lected data in two German universities in
February 2015. One university was a small,
private business school offering bachelor and
master study programs in management,
whereas the other was a public university in
Northern Germany providing a wide range
of study programs in various disciplines. The
questionnaires included a cover page with
guidelines and a definition of co-branding
alliances and 16 scenarios. The sequence of
scenarios was varied randomly across ques-
tionnaires. Out of 200 originally spread
questionnaires, we received 126 usable
questionnaires (2,016 observations), yield-
ing a response rate of 63 percent.
Variables and measures
The scenarios described co-branding alli-
ances in terms of the partner firms’ size, age,
industry scope, and country-of-origin. The
variables were all defined by two levels rep-
resenting either high or low (or no, respec-
tively) co-branding partner dissimilarity. An
irregular number of levelsmay have distorted
results (Karren and Barringer, 2002).
Firm size (dis-)similarity was measured
based on the alliance partners’ annual
turnover and employees (Mellewigt and
Decker, 2014). Partners with low firm size
dissimilarity have a comparable annual
turnover and number of employees. The
high dissimilarity scenario describes an
alliance between a large and a small firm.
We used significant differences in turnover
(more than 1 billion Euros versus less than
10 million Euros) and number of employ-
ees (more than 1,000 versus less than 50
employees).
Firm age was captured by the number of
years since foundation (Mellewigt and
Decker, 2014). Partners with low firm age
dissimilarity have been founded approxi-
mately at the same time. An alliance with
high firm age dissimilarity comprises an
established firm and a start-up.
The industry scope dimension had to fulfill
two criteria. First, the industry had to be
popular for co-branding alliances and,
second, respondents should feel comfort-
able with the products. The consumer
goods industry was selected for partners
with low industry scope dissimilarity. High
industry scope dissimilarity was inspired by
the example of Walt Disney and Car-
refour’s private label. It describes a part-
nership between a firm engaged in
consumer goods and a firm operating in the
media industry.
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The dimension country-of-origin image
should involve a noticeable cultural distance
between co-branding partners with high
dissimilarity. Hence, real countries were
used in the scenarios. Because the study was
conducted in Germany, for low or no
country-of-origin dissimilarity, both part-
ners were defined to be German firms. For
high dissimilarity, the country-of-origin of
company A was Japan, company B was a
German firm. These countries were selected
due to the significant cultural differences
between them and the well observable cul-
tural distance (Ghemawat, 2001; Hall and
Soskice, 2001; Hofstede, 2001).
We conducted a pretest with ten profes-
sionals with different backgrounds (re-
searchers, students, Ph.D. students, doctors,
and lawyers) and of different ages to ensure
that the scenarios were easy to understand
and perceived as relevant. It showed that all
participants clearly perceived the intended
differences between the scenarios, because all
cues had been manipulated on just two levels,
namely either high or low dissimilarity.
We asked our respondents to assess all
scenarios based on two single items refer-
ring to brand fit perception (‘I perceive the
co-branding alliance as positive’) and con-
sumer attitude towards the co-branding
alliance (‘The partner firms complement
each other’). These single items differ from
the multi-item scales originally suggested
by Simonin and Ruth (1998) because of
the results of our pretest. This pretest had
revealed that we had to adapt the scales for
brand fit perception and consumer attitude,
because the participants did not perceive
the five items adopted from Simonin and
Ruth (1998) as distinct. Based on their
feedback, we transformed them into two
clear statements and six-point rating scales
(ranging from 1 =‘strongly disagree’ to
6=‘fully agree’).
We included control variables regarding
consumers’ characteristics and attitudes.
Age and gender affect perceptions and
purchasing decisions. Consumers’ capaci-
ties to absorb and process information on
products and their preferences differ
depending on their age (Charry and
Demoulin, 2014; Czellar, 2003; de Faul-
trier et al,2014). According to selectivity
theory, men and women use different
strategies to process information on prod-
ucts. Because women have a lower elabo-
ration threshold and are more likely to
relate their existing knowledge to new
information, they will be more likely to
perceive a fit between two brands on the
same product than men (Lau and Phau
2010). Furthermore, when consumers
evaluate a co-branded product, they try to
categorize it based on contextual factors
(Bouten et al,2011). It is possible that
brand fit perceptions will be more
Table 1: Correlations
Variables 1 2 3 4 5 6 7 8
1 Brand fit 1.000
2 Consumer attitude 0.713*** 1.000
3 Gender -0.048** -0.033 1.000
4 Age 0.096*** 0.035 0.039* 1.000
5 Import. country-of-
origin
-0.029 -0.011 0.065** 0.132*** 1.000
6 Importance firm age 0.034 0.037* 0.004 0.045** 0.226*** 1.000
7 Importance firm size 0.064** 0.048** -0.065** -0.162*** 0.085*** 0.448*** 1.000
8 Importance brands 0.065** 0.047** -0.070** 0.041* 0.133*** 0.163*** 0.252*** 1.000
Note:N=2,016 vignettes provided by 126 individuals.
Signicance levels: *p\0.100; **p\0.050; ***p\0.001.
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favorable, if the characteristics of the
organizations involved in a co-branding
alliance are relevant to consumers (Sa-
muelsen et al,2015). Therefore, we con-
sider the importance of brands, firm size,
firm age, and country-of-origin in our
analysis.
An examination of the bivariate corre-
lations reported in Table 1indicates that
gender and age are significantly correlated
with brand fit perception. The importance
of firm size and brands is significantly
correlated with both brand fit perception
and attitude towards the co-branding alli-
ance. The importance of firm age is sig-
nificantly related to the attitude towards
the co-branding alliance. The importance
of country-of-origin is negatively corre-
lated with both dependent variables,
though not significantly. Tests of our
hypotheses with and without the afore-
mentioned control variables yielded iden-
tical results.
RESULTS
Descriptive findings
Most of the respondents studied manage-
ment, 45 percent were enrolled in other
programs, such as industrial engineering or
computer science. On average, the
respondents were 23 years old. Among
them, 58 percent were male. Levene’s test
showed no significant differences in terms
of age and gender between students from
the two universities, indicating homo-
geneity of variances. Descriptive statistics
are reported in Table 2.
The respondents assessed the importance
of brands as high (mean =4.333). v
2
tests
indicated that brands were more important
to students with a major than to those with
a minor in management or to those
enrolled in other programs (v
2
(5) =
19.962, p B0.001). Brands were slightly
more important to students from the small,
private university than to students from the
bigger, public university (v
2
(5) =12.822,
p\0.050).
Variance inflation factors (VIFs) were
well below the conservative threshold of 5
(Menard, 1995, p. 66), indicating no
problem of multicollinearity (highest value:
importance of size =1.37).
Manipulation checks
To assess the effectiveness of the manipu-
lations, we conducted a one-way ANOVA
with, first, brand fit perception and second,
consumer attitude toward the co-branding
alliance as the experimental factors. The
overall F-value for brand fit was significant
(F(4,2011) =23.05, p=0.00). Tukey
post hoc tests revealed that the mean scores
for low versus high dissimilarity in size
(M=3.968 vs. M=3.656), industry
(M=3.929 vs. M=3.695), and country-
of-origin image (M=4.010 vs.
M=3.615) were significant. They were
not significant for age (M=3.813 vs.
M=3.811). The overall F-value for con-
sumer attitude was also significant
(F(4,2011) =17.44, p=0.00). Tukey
post hoc comparisons indicated significant
differences between low versus high dis-
similarity in size (M=3.886 vs.
M=3.519) and country-of-origin image
(M=3.867 vs. M=3.538), but not in age
(M=3.684 vs. M=3.721) and industry
(M=3.726 vs. M=3.679).
Test of hypotheses
We used OLS regressions with robust
standard errors. We clustered the observa-
tions at the individual level, because each
respondent assessed several scenarios.
Moreover, the variables represent factors
on the alliance and the individual level.
Table 3shows the results.
In line with Hypothesis 1, high firm size
dissimilarity is negatively related to cus-
tomer brand fit perception. Hypothesis 2
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asserts that firm age dissimilarity negatively
affects brand fit. The results do not support
this hypothesis. The coefficient is negative
as expected but insignificant. High industry
scope dissimilarity and high country-of-
origin image dissimilarity both have a sig-
nificant negative impact on customer brand
fit perception, supporting Hypotheses 3
and 4.
Consistent with previous studies
(Bluemelhuber et al,2007; Simonin and
Ruth, 1998) and supporting Hypothesis 5,
brand fit nurtures consumer attitude
towards a co-branding alliance. In addition,
high firm size dissimilarity negatively affects
consumer attitude, while high industry
scope dissimilarity fosters it.
DISCUSSION
Based on signaling theory, we hypothe-
sized that high partner dissimilarity in terms
of firm size, firm age, industry scope, and
country-of-origin image negatively affects
brand fit perception. We introduced dis-
similarity signals on the organizational level
Table 2: Descriptive statistics
Stimuli
Firm size dissimilarity
Low: Company A and company B have a similar annual turnover and a similar number of employees
High: Company A is with more than 1,000 employees and an annual turnover of over €1 billion a big enterprise.
Company B is with less than 50 employees and an annual turnover of less than €10 million a small business
Firm age dissimilarity
Low: Company A and company B were founded approximately at the same time
High: Company A is an established business that was founded more than 10 years ago. Company B is a start-up that
was founded within the last 3 years
Industry scope dissimilarity
Low: Company A and company B are both operating in the consumer goods industry
High: Company A operates in the media industry. Company B is specialized in consumer goods
Country-of-origin image dissimilarity
Low: Company A and company B are both German businesses
High: Company A is a Japanese business. Company B is a German business
Variable Mean SD Minimum Maximum
Consumer evaluations
Brand fit perception 3.812 1.324 1 6
I perceive the co-branding alliance as positive. (1 =‘disagree’, …,6=‘agree’)
Consumer attitude 3.702 1.357 1 6
The partner firms complement each other. (1 =‘disagree’, …,6=‘agree’)
Control variables
Age
in years
22.651 2.140 18 29
Importance country-of-origin 3.937 1.385 1 6
1 (‘not important’), …, 6 (‘very important’)
Importance firm age 2.635 1.245 1 6
1 (‘not important’), …, 6 (‘very important’)
Importance firm size 3.063 1.379 1 6
1 (‘not important’), …, 6 (‘very important’)
Importance brands 4.333 1.148 1 6
1 (‘not important’), …, 6 (‘very important’)
Gender
Male/female Male:
58 %
Female:
42 %
Note: N =2,016 vignettes provided by 126 individuals.
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to the field of co-branding, which have not
yet been addressed in previous customer
perspective research.
Contributions
Our results make three contributions. First,
we identified antecedents on the organi-
zational level to consumer-brand fit per-
ception. These have implications for co-
branding alliance formation, consumer
evaluation, and co-branding alliance per-
formance. Our finding that there is a
negative relationship between the co-
branding partners’ combined organizational
characteristics of firm size, industry scope,
and country-of-origin image dissimilarity
and consumer-brand fit perception suggests
that, in addition to brand-related factors,
organizational characteristics affect con-
sumer assessments of co-brands. Organiza-
tional dissimilarity results from strategic
alliance formation motives, such as access
to complementary resources (Chung et al,
2000; Wernerfelt, 1984), new customer
segments (Harrigan and Newman, 1990;
O’Dwyer et al,2011), and new geograph-
ical markets (Glaister and Buckley, 1996;
Reuer et al,2011). Co-branding alliance
formation between firms with a heteroge-
neous organizational structure make sense
from a strategic perspective. However, it
sends a potentially unintended dissimilarity
signal to consumers, which adversely affects
brand fit perception. Brand fit perception,
on the other hand, drives consumer atti-
tude towards the alliance (Arnett et al,
2010; Baumgarth, 2004; Dickinson and
Barker, 2007; Lafferty et al,2004; Simonin
and Ruth, 1998) and decision-making
(Dickinson and Heath, 2006). Using the
antecedents of brand fit perception as
control variables in the models testing
consumer attitudes toward co-branding
alliances, we see that high industry scope
dissimilarity nurtures them, but high firm
size dissimilarity affects them negatively.
Consumers appreciate and understand the
potentially complementary effects of dif-
ferent industrial backgrounds involved in
the development and commercialization of
a joint product. They do not see
Table 3: Regression analyses
Variables Brand t perception Consumer attitude
Model 1 Model 2 Model 3 Model 4
Constant 2.031** (0.620) 2.502*** (0.632) 1.385** (0.422) 1.403** (0.423)
Gender -0.110 (0.110) -0.110 (0.110) 0.003 (0.070) 0.002 (0.070)
Age 0.071** (0.026) 0.071** (0.026) -0.243 (0.017) -0.024 (0.017)
Importance country-of-origin -0.052 (0.045) -0.052 (0.045) 0.012 (0.025) 0.012 (0.025)
Importance firm age 0.002 (0.048) 0.002 (0.048) 0.019 (0.021) 0.019 (0.031)
Importance firm size 0.069 (0.044) 0.069 (0.044) -0.013 (0.028) -0.013 (0.028)
Importance brands 0.053 (0.052) 0.053 (0.052) 0.001 (0.035) 0.002 (0.035)
H1: Firm size dissimilarity -0.312*** (0.065) -0.139** (0.042)
H2: Firm age dissimilarity -0.003 (0.061) 0.040 (0.044)
H3: Industry scope dissimilarity -0.233** (0.074) 0.123* (0.062)
H4: Country-of-origin image dissimilarity -0.394*** (0.073) -0.041 (0.045)
H5: Brand fit perception 0.736*** (0.029) 0.731*** (0.030)
F2.70** 10.17*** 102.34*** 82.21***
R
2
0.022 0.066 0.510 0.515
Adj. R
2
0.019 0.061 0.509 0.513
Note:N=2,016 observations adjusted to 126 individual-level clusters. Robust standard errors in parentheses are reported
below the coefcients.
Signicance levels: *p\0.100; **p\0.050; ***p\0.001.
Perceptions of co-branding alliances
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complementarities, efficiency gains, or
quality improvements in co-branding alli-
ances between firms of different sizes.
Overall, our results indicate that consumers
are well aware of the firms behind a co-
branded product (Newmeyer et al,2014)
and that dimensions of organizational dis-
similarity of co-branding partners differ-
ently affect brand fit perception and
consumer attitude.
Second, this study reveals the potential
of extending co-branding alliance research
beyond the brand level. It adds to the
understanding of co-branding alliances as a
multi-dimensional construct (Oeppen and
Jamal, 2014). We considered both the firm
and the brand level in our study. Our
results emphasize the importance of
including multiple levels of analysis in co-
branding research (Hitt et al,2007).
Third, contrary to Hypothesis 2, the rela-
tionship between firm age dissimilarity and
brand fit perception is insignificant though
negative as expected. Prior research asserts
that consumers face difficulties in evaluating
co-branding alliances between young and
established brands, because they lack brand
associations with the less familiar start-up
brand (Keller, 1993). Our non-finding may
be due to today’s business environment, in
which start-ups can rapidly gain a high level
of brand awareness through various online
channels, affiliates, and social media (Chaffey
et al,2009). Examples of established firms that
are known for sustained innovation, such as
General Electric, Siemens, and Sony, rebut
the assumption that age decreases innovation.
The arguments that consumers are less
familiar with start-up brands (Keller, 1993)
and that new brands are perceived to have a
higher innovative potential than established
firms (Das and He, 2006) might be outdated.
Moreover, compared to the other organiza-
tional characteristics included in our analysis,
firm age was of minor importance to
respondents.
Limitations and directions
for future research
The limitations that we see, may trace
promising avenues for future research.
First, we used a full factorial survey con-
sisting of 16 vignettes, which is well below
the recommended maximum of 80 vign-
ettes per questionnaire (Aiman-Smith et al,
2002). Nevertheless, respondents reported
fatigue while assessing the vignettes. To
avoid respondent overload and increase
respondent’s motivation to participate in
the study, further policy capturing research
should adopt a fractional approach instead
(Graham and Cable, 2001).
Second, we used a sample of German
students. Due to their study programs, the
possibility that participants were sensitized
to topics, such as co-branding, cultural
distance between alliance partners, and
alliance partner fit, cannot be excluded.
Studies in other contexts could increase the
generalizability of our results by validating
them with a bigger, more diverse consumer
sample in terms of age, professional back-
ground, nationality, and brand awareness
(Aiman-Smith et al,2002).
Third, Ahn and Sung (2012) criticize the
measurement of partner brand fit as a uni-
tary construct. They suggest that research-
ers should differentiate between functional
fit (fit between the brands’ product cate-
gories) and symbolic fit (the brands’ con-
cept consistency). Future studies could test
whether and to what extent organizational
dissimilarity signals differently affect con-
sumer perceptions of these brand fit
dimensions, consumers’ attitudes toward
co-branding alliances, and their purchasing
decisions.
Fourth, we tested a co-branding scenario
between partners that were, first, either
operating in the consumer goods or the
media industry and, second, based in either
Germany or Japan. Future co-branding
studies testing our hypotheses in other
Decker and Baade
660 ª2016 Macmillan Publishers Ltd. 1350-231X Journal of Brand Management Vol. 23, 6, 648–665

industry and country-of-origin constellations
could provide further insights. In addition,
attitudes towards firms, brands, industries,
and countries may evolve over time because
of accumulated consumer experiences. A
cross-sectional dataset cannot depict the
development of brand fit perception and
consumer attitude over time. It also raises
endogeneity concerns. Researchers should
develop designs involving the collection of
longitudinal data in order to consider the
dynamics of brand fit perceptions and atti-
tudes and strengthen the direction of causality
(Meier et al,2016).
Finally, in line with previous studies (for
example, Baumgarth, 2004; Gammoh and
Voss, 2011; Rao et al,1999; Simonin and
Ruth, 1998), we analyzed co-branding
alliances from a customer perspective.
However, co-branding alliances are not
always formed with the consumer in mind
(O’Dwyer et al,2011) and one-sided per-
formance evaluations may not fully capture
co-branding alliance success. Future studies
could include internal performance indi-
cators based on secondary data on co-
branding alliances instead of purely focus-
ing on key informants. Moreover, our
study design excludes the possibility of co-
branding alliance failure. It draws on the
assessment of currently (at least hypotheti-
cally) existing co-branding alliances. To
avoid a potential survivor bias, researchers
could follow recommendations by Meier
et al (2016) and compare evaluations of
successful and failed co-branding alliances.
Managerial implications
From a managerial perspective, our results
provide implications for co-branding alli-
ance formation and communication. First,
marketing managers, besides carefully
forming co-branding alliances with partners
that fit based on strategic considerations,
should assess whether such firm perspec-
tive-driven co-branding alliances make
sense from a customer perspective (Ahn
and Sung, 2012; Arnett et al,2010). Given
the finding that brands are important to
consumers, the formation of a co-branding
alliance that is strategically sound but does
not satisfy customers, co-branding alliance
success and long-term brand performance
could be compromised.
Second, taking into account that orga-
nizational dissimilarity between co-brand-
ing partners can usually not be avoided as
some characteristics cannot be altered on
short notice, managers should ensure that
they sufficiently communicate and explain
the co-branding alliance to consumers to
assist them in cognitively processing the
potential partner dissimilarity signals (Ahn
and Sung, 2012; Samuelsen et al,2015). A
marketing campaign that highlights the co-
branding partner brands’ matching attri-
butes might reduce a consumer’s dissimi-
larity perception resulting in a higher level
of brand fit perception and a more favor-
able attitude towards the alliance.
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