1

Complementary or Similar? The Impact of Concept Combination Styles on

Evaluations of Co-branded Partnerships

VANITHA SWAMINATHAN*

ZEYNEP GÜRHAN-CANLI

UMUT KUBAT

CEREN HAYRAN

*Vanitha Swaminathan is Associate Professor of Marketing, Katz Graduate School of

Business, University of Pittsburgh, 344 Mervis Hall, Pittsburgh, PA 15260. Phone: (412)

648 1579.Fax: (412) 648 1693.Email: vanitha@katz.pitt.edu. Zeynep Gürhan-Canli is

Migros Professor of Marketing, Koc University, Rumeli Feneri Yolu, Sariyer, Istanbul,

Turkey. Phone: +90 (212) 338 1784. Fax: + 90 (212) 338 1642. Email: zcanli@ku.edu.tr.

Umut Kubat is a post-doctoral fellow at Koç University Graduate School of Business.

Email: ukubat@ku.edu.tr. Ceren Hayran is PhD student in Marketing at Koc University,

Rumeli Feneri Yolu, Sariyer, Istanbul, Turkey. Email: chayran@ku.edu.tr. The authors

gratefully acknowledge a research grant from the International Business Center at the

Katz Graduate School of Business and the Migros Chair at Koc University. The authors

acknowledge the help of Hristina Dzhogleva, Doctoral Candidate in Marketing, Katz

Graduate School of Business, University of Pittsburgh and thank Chris Janiszewski for

his comments on an earlier version of this manuscript.

2

This research examines consumers’ reactions to co-branded partnerships that feature

brands with either complementary or similar attribute levels, both of which are common

in the market place. The results demonstrate that consumers’ evaluations vary as a

function of concept combination style (property mapping or relational linking) and

whether co-branded partners have complementary or similar attributes. Specifically,

when property mapping is used, co-branded partnerships with complementary (vs.

similar) attribute levels are evaluated more favorably. In contrast, when relational linking

is used, co-branded partnerships with similar (vs. complementary) attribute levels are

evaluated more favorably. The results also reveal that the type of advertising and the

breadth of the host brand (broad versus narrow) influence the extent to which consumers

are likely to utilize property mapping or relational linking in evaluating co-branded

partnerships.

Keywords: co-branding, concept combination, property mapping, relational linking

Co-branding, or the use of two or more brand names on one product is a popular

brand strategy (Blackett and Boad 1999; Kumar 2005; Monga and Lau-Gesk 2007; Rao,

Qu, and Ruekert 1999; Simonin and Ruth 1998). By presenting two brand names on one

product, marketers are borrowing equity from partner brands. Therefore, co-branding is

expected to lead to more positive responses from consumers than if the new product is

marketed with a single name. Apple embarked on their co-branding with Nike in order to

take music and sport to a new level. The co-branded Nike-iPod Sport Kit includes a chip

which is embedded inside Nike shoes; the chip communicates with iPod and iPhone

apparels and thereby adds superior benefits to a work out experience. Luxury mobile

phone brand Vertu and luxury sports car brand Ferrari are currently in their sixth year of

co-branding partnership in launching a series of limited edition Vertu Ferrari phones. The

partnership has been considered a success for both brands in terms of reaching luxury

seeker consumers (King 2013; Luxury Daily News 2013).

A brand can choose to partner with another brand that has either complementary

or similar attribute levels. For instance, the co-branded alliance between McDonald’s

(associated with products which have good taste but are perceived as unhealthy) and

Healthy Choice (which provides health benefits but may not be too tasty) to introduce

McDeli healthy sandwiches involves complementary brands at the attribute level. In

contrast, Häagen-Dazs chose to introduce a line of ice cream cordials with other super-

premium brand names (e.g., Häagen-Dazs and Bailey’s). In this case, Häagen-Dazs and

Bailey’s have similar salient attributes (e.g., rich and creamy taste, luxurious). Going

back to the introductory examples, Nike iPod Sport Kit creates additional benefits to both

brands combining the different expertise of the partnering brands - sports and fun -

4

forming an attribute-complementary partnership. On the other hand, Ferrari Vertu

partnership combines the partnering brands’ similar prestige and luxury attributes, hence

is an attribute-similar partnership. Extant research does not examine when attribute-

complementary or attribute-similar partnership strategies can be more effective in

enhancing consumers’ evaluations. Our first major contribution is to develop an

integrated framework that identifies conditions under which complementary (vs. similar)

attribute levels are evaluated more favorably.

Further, extant research does not clarify why consumers may evaluate

complementary (vs. similar) partnerships differently. We use the theoretical lens of

concept combination literature to clarify processes underlying evaluations of co-branded

partnerships. Specifically, previous research (e.g., Gagne and Shoben 1997; Wisniewski

1996) identifies two processes that underlie how two concept combinations are

interpreted. The first process (i.e., property mapping) involves consumers’ mapping of

salient attributes from one partner onto the other partner. The second process (i.e.,

relational linking) involves consumers’ evaluations of how the two brands in an alliance

are related. Extant research (e.g., Desai and Keller 2002; Park, Jun, and Shocker 1996;

Samu, Krishnan, and Smith 1999; Simonin and Ruth 1998) has examined each of these

processes separately. However, there is no theoretical framework that examines both

property mapping and relational linking within a single study. By examining these two

processes within a single study, this research provides insight into both when and why

certain types of co-branded partnerships can result in more favorable evaluations.

Although the impact of concept combination styles is important from a theoretical

perspective, it is also important to examine consumer contexts that may elicit a greater

5

preference for complementary combinations versus similar combinations. Extending

previous research, we identify two contexts that can elicit either one or the other process.

First, the type of advertising can elicit a process that results in either relational linking or

property mapping. Second, drawing on previous research on branding (e.g., Meyvis and

Janiszewski 2004), we demonstrate that brands with varying levels of category

associations can have varying levels of success with either complementary or similar

combinations.

We conduct four studies to test our conceptual framework. In the first study, we

manipulate concept combination styles (property mapping or relational linking) based on

the method suggested by Wisniewski (1996) and examine how evaluations of co-branded

partnerships vary as a function of concept combination style and attribute-

complementarity. In the second study, we replicate the results from Study 1 using

different set of brands. We also examine the processes in greater detail by analyzing

cognitive responses. The third study manipulates concept combination style realistically

using an advertisement. The fourth study examines how concept combination styles are

activated when the host brand in a co-branded partnership is narrow (i.e., the brand is

associated with similar product categories) or broad (i.e., the brand is associated with

different product categories).

In sum, this research advances our understanding of processes underlying

consumers’ evaluations of co-branded partnerships, an important tool in the management

of brand equity. In doing so, this research not only extends prior research on co-branding

(Desai and Keller 2002; Park, Jun, and Shocker 1996; Samu, Krishnan, and Smith 1999;

Simonin and Ruth 1998), but also contributes to the emerging literature on processing of

6

composite products within the consumer behavior literature (Janiszewski and Van

Osselaer 2000; Moreau, Markman, and Lehmann 2001; Rajagopal and Burnkrant 2009).

Theoretical Background

Attribute-Complementary versus Attribute-Similar Co-branding

When two brand names are used on a product, the host or the host brand typically

refers to the primary product within which the modifier or partner brand resides. A co-

branded partner or the modifier brand can have either complementary or similar attribute

levels with the host brand. An attribute-complementary co-branded partnership is

defined as a type of partnership wherein: (1) Both host and partner brands have a

common set of relevant attributes; (2) the host and partner brands differ in attribute

salience such that attributes not salient to one are salient to the other; (3) the (host or

partner) brand for which the attribute is salient has a higher rating than the (host or

partner) brand for which the attribute is not salient (Park, Jun, and Shocker 1996). In

contrast, an attribute-similar co-branded partnership is defined as a partnership wherein:

(1) Both host and partner brands have a common set of relevant attributes; (2) two (host

and partner) brands are similar in attribute salience such that attributes salient to one are

also salient to the other; (3) the (host and partner) brands have similar high ratings on the

same salient attributes. It should be noted that there are two different perspectives that

define complementary partnerships. One perspective is the view put forth by Park, Jun,

and Shocker (1996) as described above. In contrast, complement has been defined

7

somewhat differently by Aaker and Keller (1990) and Simonin and Ruth (1998). Aaker

and Keller (1990) define complement as whether the products can be used together in

certain usage situations in a complementary way (such as downhill skis and ski wear).

Simonin and Ruth (1998) refer to the product categories complementing each other such

as microprocessors used in cars. In this research, we use attribute-level complementarity

as defined by Park, Jun, and Shocker (1996).

Park, Jun, and Shocker (1996) found that attribute-complementary co-branded

combination led to more favorable evaluations than attribute-similar co-branded

combination. In a related research on co-branding, Simonin and Ruth (1998) examined

the effect of fit (brand and product) on evaluations of the co-branded partnership. They

found that fit has a significant positive impact on evaluations. In co-branding context,

product fit refers to the relatedness of product categories and brand fit refers to the

similarity and consistency of partnering brand images such as McDonald’s partnering

with a high-share, high-quality brand of cola (akin to an attribute-similar co-branded

partnership strategy). Thus, based on past research, one may conclude that there are two

distinct ways by which co-branded strategies can be successful with respect to brand

attributes of the constituent brands. Based on Park, Jun, and Shocker (1996), one may

argue that co-branded strategies will be successful when a brand chooses a highly

complementary partner. Further, based on Simonin and Ruth (1998), it appears that co-

branded strategies may succeed when a brand chooses a highly similar partner. Are there

conditions when either of these two strategies is more likely to succeed? We turn to

recent research in concept combinations to examine this issue.

8

Concept Combinations

Recent research in cognitive psychology has pointed to the critical role played by

concept combination styles (property mapping and relational linking) on the manner by

which individuals process combinations of concepts (Gagne and Shoben 1997; Gerrig

and Murphy 1992; Hampton 1987; Smith, Osherson, Rips, and Keane 1988; Wisniewski

1996). Wisniewski (1996) examined a large sample of people’s interpretations of novel

combinations with the goal of identifying significant phenomena associated with

conceptual combination. People’s interpretations were of two types—property mapping

and relational linking—between the modifier and host concepts. Property mapping

involved one or more properties of the modifier concept being applied to the host

concept. In the case of relational linking, the focus is on relationships among objects

where each of the entities may play different thematic roles.

A key assumption in the property mapping style of concept combination is that

host brand is comprised of slots and fillers (e.g., the concept apple has a color slot with

either red or green fillers). When individuals combine or integrate the concepts to come

up with the composite concept using property mapping, the modifier in a conceptual

combination selects one or more slots in the host to be specified by values provided by

the modifier (Smith et al. 1988). Therefore, property mapping simply maps the properties

of the modifier onto the host. Based on property mapping, the concept zebra tablecloth

can be interpreted as a tablecloth which has zebra stripes. Park, Jun, and Shocker (1996)

focused on property mapping type of concept combination. Using property mapping,

9

Godiva cake mix by Slim-Fast (co-branding example used in Park, Jun, and Shocker’s

research) can be interpreted as a delicious cake mix with health benefits.

In contrast, research by Gagne and Shoben (1997) suggests that concept

combinations can also rely on relational linking. According to this view, the concepts

within a combination are interpreted based upon a plausible relation between the modifier

and host. For example, based on relational linking, holiday tablecloth is a concept which

may be interpreted as a tablecloth used on holidays. Much of the concept combination

literature (e.g., Gagne and Shoben 1997) suggests that a key feature of relational linking

is that concepts should belong to somewhat similar categories (not overlapping

categories) and should be capable of having a plausible relationship role.

To illustrate these issues further, consider the case of Godiva cake mix by Slim-

Fast. When property mapping takes place, consumers may map onto Godiva Chocolate

the properties of Slim-Fast (e.g., low calorie) and the tendency may be to think of this

combination as a type of Godiva chocolate but with some health benefits. Therefore, in

attribute-complementary co-branded partnerships (e.g., Godiva by Slim-Fast) when

property mapping is the processing strategy, the overall evaluation of the co-branded

product increases relative to an attribute-similar co-branding strategy (e.g., Godiva by

Häagen-Dazs). In contrast, under relational linking conditions, the focus is on how the

two entities are related functionally, socially, or situationally (Ahluwalia 2008). In the

context of co-branded products, this may lead to a greater focus on why the two brands

are featured together in an attempt to clarify how they are related (Rajagopal and

Burnkrant 2009). In sum, both property mapping and relational linking styles of concept

combination can co-exist, and depending on which concept combination strategy is used,

10

can result in different interpretations of the composite concept. These varying

interpretations will result in different evaluations of attribute-complementary and

attribute-similar co-branded partnerships.

When property mapping takes place, consumers focus on the salient attributes of

the host brand (i.e., the slots) and the manner by which the secondary partner brand acts

as a filler and changes the values of these attributes. The result of such mapping brings to

the forefront issues related to how brands complement each other. Such mapping may

result in a highly complementary co-branded partnership being viewed as superior to a

highly similar co-branded partnership. The secondary partner brand modifies and

increases the performance evaluation of the host’s weak attributes in a complementary

combination. In an attribute-similar partnership, the secondary partner brand has only a

limited role, given that the host brand also has similar strengths. Consequently, we expect

that when consumers engage in property mapping, they will have more favorable

evaluations of the co-branded partnership for attribute-complementary (vs. attribute-

similar) co-brands.

When consumers engage in relational linking, they focus on possible relationships

between the co-branding partners. For example, they are likely to evaluate different types

of relational links between the two brands such as similarity of users, plausibility of

relationships based on time and place, or commonalities based on usage-situation or

functional overlap. Consequently, when consumers engage in relational linking, co-

branded partnerships featuring attribute-similar (vs. attribute-complementary) brands are

likely to be evaluated more favorably, because consumers can easily relate two similar

brands functionally, socially, or situationally. That is, because of the inherent similarity in

11

attribute levels of the two brands and high overall similarity or consistency, attribute-

similar partnerships are generally seen as more cohesive and thus, easier to relate

compared to attribute-complementary partnerships. In contrast, in attribute-

complementary co-branded partnerships, the featured brands possess low consistency or

similarity. Thus, it becomes relatively difficult to relate the two brands and come up with

different types of relations involving two dissimilar brands. Prior research suggests that

perceived difficulty with which information can be retrieved about a target affects

judgment (Schwarz et al. 1991; Tybout et al. 2005; Wänke, Bohner, and Jurkowitsch

1997). For example, Wänke, Bohner, and Jurkowitsch (1997) showed that consumers had

lower brand evaluations when they found it difficult (vs. easy) to come up with reasons

for why they preferred a brand. Consistent with this reasoning, we expect that under

relational linking, consumers should find it easier to relate co-branded partners when the

partners have similar (vs. complementary) attribute levels. Consequently, we expect that

similar (vs. complementary) co-brands should lead to more favorable evaluations when

consumers engage in relational linking. Thus, we hypothesize the following:

H1: In the case of property mapping, attribute-complementary (vs. attribute-

similar) co-branding should lead to higher (lower) evaluations of the co-

branded partnership. In the case of relational linking, attribute-similar (vs.

attribute-complementary) co-branding should lead to higher (lower)

evaluations of the co-branded partnership.

Study 1

12

Method

In order to test hypothesis 1 and build upon previous research findings, we

selected brands used by Park, Jun, and Shocker (1996). We selected cake mixes as the co-

brand partnership category and used Godiva, Slim-Fast, and Häagen-Dazs as the three

brands. Specifically, Godiva by Slim-Fast formed an attribute-complementary

partnership, whereas Godiva by Häagen-Dazs formed an attribute-similar co-branded

partnership. Consistent with our expectations, a pretest revealed a higher complementary

relation between Godiva and Slim-Fast relative to Godiva and Häagen-Dazs (please see

table 1).

____________________

Insert table 1 about here

____________________

A total of 101 undergraduate students participated in a 2 (attribute-

complementarity: complement or similar) X 2 (concept combination style: property

mapping or relational linking) between-subjects design. We primed concept combinations

and asked respondents to write down how they interpreted these combinations. After the

priming task, respondents expressed their evaluations of certain brands (including the

target partnering brands) and then read about a new co-branded partnership. In order to

ensure that motivation level was kept constant and high, participants were told their

opinions were very important. Attitudes toward the co-branded partnership were

measured following the participants’ exposure to the co-branding information.

Participants expressed their evaluations according to four items, each measured on a five-

point scale. The items were anchored by high quality–low quality, good–bad, favorable–

13

unfavorable, positive–negative. Participants also indicated prior category usage in the

partnership category.

We used the priming task suggested by Wisniewski and Love (1998) to prime

either relational linking or property mapping. The priming task involved presenting

respondents with a set of concept combinations. In the case of relational priming,

participants provided interpretations for twelve concepts that primarily had a relational

link (e.g., clothing truck, dollar bill beggar, grocery bicycle, girlfriend insult, holiday

tablecloth). In the case of property priming, respondents provided an interpretation for

twelve concepts that primarily had a property mapping relationship (e.g., bus truck, skunk

beggar, motorcycle bicycle, razor insult, zebra tablecloth). A complete list of concepts

used in the priming procedure is provided in the Appendix.

Manipulation Check. Responses to the priming task were coded by two research

assistants. An interpretation was scored as a relevant relation if it referred to the relation

for which a pair of combinations was matched (e.g., holiday tablecloth is described as a

tablecloth to be used on holidays). An interpretation was scored as other relation if it

referred to the relation between the constituents, but not to the one on which a pair of

combination was matched (e.g., umbrella tree is an umbrella used on the beach). An

interpretation was scored as property if it attributed a property of one constituent to

another (e.g., zebra tablecloth is described as a tablecloth with zebra stripes). An

interpretation was scored as other if it did not fit into one of these three categories.

Two research assistants who did not know the purpose of the study examined

each interpretation and classified it into one of four categories as described above. The

agreement between research assistants was high (94%) and disagreements were resolved

14

by discussion. As expected, those in the relational priming condition reported a

significantly higher number of relational interpretations relative to property

interpretations (7.5 vs. 1.35; t(99) = 12.0; p < .01). In addition, those in the property

priming condition reported a significantly higher number of property interpretations

relative to relational interpretations (7.8 vs. .79; t(99) = 19.1; p < .01). This pattern

suggests that the priming of type of concept combination was successful.

Results and Discussion

Co-branded Partnership Evaluations. We ran a 2 (processing style) X 2

(attribute-complementarity) ANOVA on partnership evaluations (α = .93). Prior attitudes

toward both the partner brands and prior category usage were included as covariates. We

used prior brand attitudes and category usage as covariates in the analyses because they

can have direct effects on brand partnership evaluations. This approach is also consistent

with previous research (e.g., Simonin and Ruth 1998).

An ANOVA on the evaluations of the co-branded partnership reveals significant

main effects of concept combination style (F(1, 94) = 5.98, p < .05) and complementarity

(F(1, 94) = 5.90, p < .05). The effect of prior host brand attitude was also significant (F(1,

94) = 4.98, p < .05). These effects are qualified by a significant two-way interaction

between concept combination style and attribute-complementarity (F(1, 94) = 26.75, p <

.001). Consistent with hypothesis 1, planned contrasts revealed that under property

mapping, evaluations are more favorable when there is attribute-complementary (vs.

attribute-similar) co-branding (3.44 vs. 2.87; F(1, 94) = 4.03, p < .05). In contrast, under

15

relational linking, evaluations are lower for attribute-complementary (vs. attribute-

similar) co-branding (2.86 vs. 4.45; F(1, 94) = 26.75, p < .01).

In separate analyses, we ran the preceding analysis after including two-way

interactions of the host brand attitude with processing and complementarity as well as

category usage with concept combination and complementarity. None of the interactions

involving host brand attitude and category experience came out to be significant. Because

the inclusion of two-way interactions did not materially change our results, we chose the

more parsimonious specification described earlier.

The results of this study demonstrate that concept combination style moderates

the effect of attribute-complementary or attribute-similar co-branded partnership on co-

branded partnership evaluations. Specifically, we found that consumers have more

favorable reactions to a complementary partnership when they engage in property

mapping. In contrast, attribute-similar co-branded partnership leads to more favorable

responses under relational linking.

Study 2

The results from study 1 provide support for our hypothesis. In order to test for

robustness, we sought to replicate the results from study 1 using a different set of brands.

Further, we expand the set of dependent variables to provide additional evidence for the

hypothesized effect.

Method

16

A total of 117 undergraduate students participated in one of four conditions in a 2

(attribute-complementarity: complement or similar) X 2 (concept combination style:

property mapping or relational linking) between-subjects design. Prior attitudes toward

both the partner brands and prior category usage were measured and included as

covariates. Students participated for either a $ 3 cash incentive or course credit. As in

study 1, concept combination style was primed based on Wisniewski and Love (1998)

(see the Appendix for the primed items). The procedure was similar to the procedure used

in study 1. In addition, participants wrote down their thoughts after they evaluated the co-

brand. At the end of the study, participants responded to an open-ended suspicion probe.

None of the participants guessed the link between priming task and subsequent co-

branding study.

Independent Variables

Attribute-Complementarity. The target co-brands featured brands with

complementary (Hershey’s by Healthy Choice) or similar (Hershey’s by Oreos) attribute

levels. We conducted a check of the manipulation to determine if the featured co-branded

combinations were indeed perceived as having complementary or similar attribute levels.

We collected ratings of the Hershey’s, Oreos, and Healthy Choice brands on each of the

following eight attributes: low calorie, low fat, good value, convenience, good taste,

package, richness, and luxury. Hershey’s brand had significantly higher evaluations

relative to Healthy Choice on good taste and richness, whereas Healthy Choice had

17

significantly higher evaluations on low calorie and low fat (see table 1 for actual values).

In contrast, there were no significant differences in evaluations between Hershey’s and

Oreos on all attributes (except for attractive package). The lack of a significant difference

on almost all attributes can be interpreted as support that Hershey’s with Oreos is

perceived as an attribute-similar co-branded partnership whereas Hershey’s with Healthy

Choice is perceived as an attribute-complementary co-branded partnership.

Concept Combination Style. A manipulation check was performed on responses to

the priming task using a coding procedure as described in study 1. The agreement

between the research assistants was high (92%) and disagreements were resolved by

discussion. As expected, those in the relational priming condition reported a significantly

higher number of relational interpretations relative to property interpretations (8.5 vs. .60;

t(115) = 11.14; p < .01). In addition, those in the property priming condition reported a

significantly higher number of property interpretations relative to relational

interpretations (7.0 vs. .60; t(115)= 11.2; p < .01). This pattern suggests that the priming

of concept combination styles was successful.

Results

Attitudes toward the co-branded partnership were measured following the co-

branding information using similar items as in study 1 (α = .95). The means and standard

deviations for the various conditions are presented in table 2.

___________________

Insert table 2 about here

___________________

18

Co-branded Partnership Evaluations. A 2 (attribute-complementarity) x 2

(concept combination style) between subjects ANOVA on the evaluations of the co-

branded partnership revealed a significant main effect of host brand attitude (F(1, 110) =

82.13, p < .01). Importantly, the two-way interaction between concept combination style

and attribute-complementarity was also significant (F(1, 110) = 15.37, p < .001).

Consistent with hypothesis 1, planned contrasts revealed that under property mapping,

evaluations are more favorable when there is attribute-complementary (versus attribute-

similar) co-branding (4.08 vs. 3.69 t(110) = 2.14, p < .05). In contrast, under relational

linking, planned contrasts revealed that evaluations are lower when there is attribute-

complementary (versus attribute-similar) co-branding (3.58 vs. 4.13; t(110) = 3.46, p <

.001). These results suggest that attribute-complementary co-branded partnership is more

successful in property mapping conditions, whereas attribute-similar co-branded

partnership is more successful in relational linking conditions.

In separate analyses, consistent with Study 1 results, we ran the preceding

analysis after including two-way interactions of the host brand attitude with processing

and complementarity as well as category usage with concept combination and

complementarity. None of the interactions involving host brand attitude and category

experience came out to be significant. As before, because the inclusion of two-way

interactions did not materially change our results, we chose the more parsimonious

specification described earlier.

Cognitive Responses. To provide provide further evidence that attribute mapping

and relational linking processes are the primary reasons for the results, we examined

cognitive responses. We focus on positive and negative attribute-related thoughts, in

19

order to create a valenced index of attribute-related thoughts; we also create a valenced

index of relational thoughts. The valenced indices can be thought of as ancillary

dependent variables to provide additional support for our hypothesized effect.

Two independent coders rated the responses as positive attribute-related thoughts

(e.g., Hershey’s brownie mix by Oreos is tasty) or negative attribute-related thoughts

(e.g., Hershey’s brownie mix by Oreos has high calories). Further, coders were asked to

identify any positive or negative relational thoughts. These relational thoughts include

positive thoughts about simultaneity of time/place usage (e.g., Hershey’s and Oreos

brownies are delicious after dinner) and positive thoughts about usage occasion (e.g., I

might use this [Hershey’s brownie mix by Oreos] for a special occasion or gift; I would

take this [Hershey’s brownie mix by Healthy Choice] instead of a meal), or negative

relational thoughts (e.g., I would not use this [Hershey’s brownie mix by Healthy Choice]

on a daily basis). Based on this, we created a net-valenced index of attribute-related

thoughts (i.e., positive attribute-related thoughts minus negative attribute-related

thoughts) and separate net-valenced index of relational thoughts (i.e., positive relational

thoughts minus negative relational thoughts). The coders were in agreement 95% of the

time. Any coding disagreements were resolved through discussion.

An ANOVA on the valenced index of attribute-related thoughts revealed no

significant main effect of concept combination style (F(1, 110) = 2.29, NS), although

attribute-complementarity was significant (F(1, 110) = 7.30, p < .01). Further, the impact

of prior host brand attitude was significant (F(1, 110) = 10.43, p < .01) and the partner

brand attitude was also significant (F(1, 110) = 18.9, p < .01). Importantly, the two-way

interaction between type of concept combination and attribute-complementarity was also

20

significant (F(1,110) = 5.23, p < .01). Planned contrasts revealed that under property

mapping, attribute-related thoughts were significantly more positive for attribute-

complementary (vs. attribute-similar) co-brands (.80 vs. .09; t(1, 110) = 3.33, p < .001).

In contrast, under relational linking, the valenced index of attribute-related thoughts did

not vary as a function of attribute-complementarity (.17 vs. .23; t(110) = 0.34, NS).

An ANOVA on the valenced index of relational thoughts revealed significant

main effects of concept combination style (F(1, 110) = 7.6, p < .01) and attribute-

complementarity (F(1, 110) = 16.6, p < .001). Further, the impact of prior host brand

attitude (F(1, 110) = 19.9, p < .001) and the partner brand attitude (F(1, 110) = 12.3, p <

.001) were significant. The impact of prior experience was also significant (F(1, 110) =

54.3, p < .001). Importantly, the two-way interaction between concept combination style

and attribute-complementarity was also significant (F(1,110) = 23.1, p < .001). Planned

contrasts revealed that under property mapping, the valenced index of relational thoughts

did not vary across attribute-complementary and attribute-similar co-branding (.32 vs.

.18; t(110) = 1.34, NS). Under relational linking, the valenced index of relational

thoughts was more negative for attribute-complementary (vs. attribute-similar) co-

branding (-.36 vs. .19; t(110) = 5.71, p < .001). The results using valenced indices of

attribute-based thoughts and relational thoughts are consistent with our hypothesized

results regarding co-brand evaluations, and provide further support for the role of

attribute mapping and relational linking in influencing cobrand evaluations.

Discussion. Consistent with our hypothesis, it appears that property mapping

increases the evaluations of attribute-complementary co-branding whereas relational

linking enhances the evaluations of attribute-similar co-branding. A second key objective

21

of this research is to examine the conditions under which consumers use either of these

two concept combination styles. The next two studies identify real-world conditions

(based on advertising and brand breadth) under which either of these processing styles is

used.

Study 3

Study 3 followed a 2 (attribute-complementarity: complement vs. similar) x 2

(concept-combination style: property mapping vs. relational linking) between-subjects

design. Participants (n = 124) were recruited using an online panel and asked to complete

the study online in exchange for a small payment. We used cake mixes as the co-branded

partnership category and Hershey’s, Oreo, and Honey-Maid as the three brands.

Participants’ experience in the co-branded partnership category of cake mixes was

measured and used as a covariate in the analysis. In this study, we did not measure

participants’ prior brand attitudes since we manipulated concept combination style using

an advertisement, immediately after which respondents indicated their evaluations of the

co-branded partnership. Measuring prior brand attitudes right before the presentation of

co-branded could have increased participants’ sensitivity to brand attitudes because,

unlike in the first two studies, there was no time lag between measurement of prior brand

attitudes and exposure to co-branded partnership.

Attribute-Complementarity. The target co-brands featured brands with

complementary (Hershey’s by Honey Maid) or similar (Hershey’s by Oreos) attribute

levels. We collected a separate pretest (N=124) in order to determine if the featured co-

22

branded combinations were indeed perceived as having complementary or similar

attribute levels. We collected ratings of the Hershey’s, Oreos, and Honey Maid brands on

each of the following eight attributes: low calorie, low fat, good value, convenience, good

taste, package, richness, and luxury. Consistent with the manipulation, Hershey’s brand

had significantly higher evaluations relative to Honey Maid on good taste, attractive

package, convenience, richness, and luxury whereas Honey Maid had significantly higher

evaluations on low calorie and low fat. There were no significant differences in

evaluations between Hershey’s and Oreos on all attributes (except for good value). The

lack of a significant difference on almost all attributes can be interpreted as support that

Hershey’s with Oreos is perceived as an attribute similar co-branded partnership whereas

Hershey’s with Honey Maid is perceived as an attribute-complementary co-branded

partnership. The results of this pretest are presented in Table 3.

___________________

Insert table 3 about here

___________________

Concept Combination Style. We manipulated concept combination by varying the

procedure from the first two studies. In order to elicit relational linking and property

mapping with a manipulation based in a more realistic consumer setting, we gave

participants one of two types of advertisements which were designed to prime either

relational thoughts or property-based thoughts. In the relational linking condition,

participants were presented with an advertisement the headline of which emphasized the

occasions on which the co-branded product may be consumed (Relational Linking Ad1;

the headlines used in the ads were as follows: “A unique combination of chocolate and

23

cookies (crackers) in the new Hershey’s Cake Mix by Oreo (Honey Maid). Suits every

occasion. You will like it no matter whether it is a dessert for your weekday dinner, an

afternoon snack, or a sweet Sunday breakfast” for the attribute-similar (attribute-

complementary) co-branded partnership). In contrast, participants in the property

mapping condition were presented with an advertisement the headline of which

highlighted the combination of the attributes of the two co-brands (Property Mapping

Ad2; the headlines used in the ads were as follows: “The rich taste of Hershey’s and the

delicious savor (low calories) of Oreo (Honey Maid). Introducing the new cake mixes

Hershey’s Cake Mix by Oreo (Honey Maid)” for the attribute-similar (attribute-

complementary) co-branded product).

Results and Discussion

We excluded participants who failed to respond correctly to the Instructional

Manipulation Check item (Oppenheimer, Meyvis, and Davidenko 2009). In total we had

113 participants.

Co-branded Partnership Evaluations. We controlled for participants’ experience

in co-brand partnership category (i.e. cake mixes) and estimated an ANOVA using the

attribute-complementarity condition, the concept-combination style condition, and their

interaction to predict participants’ evaluations of the co-branded partnership. Results

revealed only a significant interaction of attribute-complementarity and concept-

combination style (F(1, 106) = 7.55, p < 0.01). Planned contrasts showed that when

property mapping advertisement was used, participants in the attribute-complementary

24

condition had more favorable evaluations of the co-branded product than those in the

attribute-similar condition (5.97 vs. 5.20, t(106) = 1.98, p <.005). On the contrary, when

participants were presented with the relational linking advertisements, the evaluations of

the attribute-similar co-branded product were more favorable than those of the attribute-

complementary one, albeit at the 10% level of significance (5.65 vs. 4.94, t(106) = 1.90, p

= 0.06).

Discussion. In sum, Study 3 replicated the results obtained in the first two studies

using realistic marketing stimuli, thus strengthening the managerial and practical

relevance of our findings. More specifically, we showed that marketers can impact

consumers’ evaluations of the new co-branded products using subtle marketing cues such

as advertisement headlines designed to prime property mapping or relational linking

concept-combination style. Our results reveal that the property mapping concept-

combination style leads to more favorable evaluations for attribute-complementary co-

branded products, while the relational linking concept-combination style tends to work

better for attribute-similar co-branded partnerships.

The next study examines the role of brand breadth in influencing co-brand

evaluations, based on how consumers process information with regard to broad brands

and narrow brands. In doing so, this next study offers another factor that could result in

differing propensities by consumers to engage in property mapping or relational linking

processes, following exposure to information regarding a co-branded product.

Study 4

25

Broad versus Narrow Brands

This study tests whether the host brand breadth can moderate the impact of

attribute-complementarity on co-branding partnership evaluations. Brand breadth refers

to the extent to which a brand is associated with similar product categories (narrow) or

different product categories (broad). Category associations form an important part of

consumers’ perceptions of a brand. In fact, some products leverage such category

associations in an effort to establish their superiority over competitors. For example,

Campbell’s ad slogan “Never Underestimate the Power of Soup” highlights Campbell’s

category membership in the soup category. For such brands, category associations are

strong and consistent; consistent associations can facilitate recall of the brand when the

category is cued (Anderson and Spellman 1995).

Other brands that have partnerships in multiple (and seemingly unrelated) product

categories may have diffuse or inconsistent category associations (i.e., broad brands).

Such diffuse category associations imply that a brand is only weakly linked to a particular

category, thus, there are fewer salient category associations that can limit the accessibility

of brand benefits (Meyvis and Janiszewski 2004). On the contrary, when a brand is

closely linked to a single category, brand benefits are less accessible and prone to

interference from non-brand associations (e.g., category associations). It is important to

indicate that we use brand breadth (broad versus narrow) as in the meaning of ‘variance

of product categories’ (Boush and Loken 1991; Meyvis and Janiszewski 2004), rather

than ‘the number of product categories associated with a brand’.

26

When category associations are unavailable, more focus is aimed at

differentiating benefits associated with a brand. For example, Kleenex has a portfolio of

products including facial tissues, napkins and wipes. Although Kleenex brand’s key

benefit is softness, its strong association with the category of ‘cleansing paper products’

could interfere with its softness association. Similarly, Crest has a portfolio of products

including toothpaste, toothbrush and white strips. Although Crest brand benefits involve

cleaning and whitening, its association with the superordinate category of ‘dental hygiene

products’ may hinder recall of its brand-level benefits. This type of interference is akin to

the ‘cue overload effect’ (e.g., Mueller and Watkins 1977; Watkins 1977). In support of

this, Meyvis and Janiszewski (2004) demonstrated that category associations by

hindering the accessibility of benefit associations can weaken the ability of a narrow

brand to introduce brand extensions, relative to a broad brand without competing

category-level associations.

In this way, the salience of category associations can have a moderating effect on

the impact of attribute-complementarity. In a co-branding context, when category

associations are salient, more thoughts will be directed to the overall category and will

result in less emphasis being placed on attribute-level complementarity. This increase in

salience of category associations in the context of the narrow brand will result a greater

proportion of thoughts being generated in regard to how the partners’ respective

categories work together. Thus, these category associations are likely to ‘interfere’ with

brand-specific associations, resulting in more “top-down processing” of category-level

benefits, usage occasions and user types. Consequently, the attention shifts away from

attribute-level processing to examining relationships among categories. This will lead to

27

an increase in evaluation of the attribute-similar co-branded partnership relative to the

attribute-complementary co-branded partnership. Conversely, when consumers are

exposed to host brands with a broad portfolio, the attention will shift to brand-specific

associations. This increase in focus on brand-specific associations will result in an

increase in focus on how the focal host brand can benefit from allying with the secondary

partner. As a result, an attribute-complementary co-brand will be preferred.

In order to manipulate brand breadth, we use the approach suggested by Meyvis

and Janiszewski (2004). We use a fictitious brand, which has a presence in three product

categories. In the narrow brand condition, the host brand was associated with three

closely-linked product categories. In the broad brand portfolio condition, the host brand

was associated with three dissimilar product categories. Presumably, the broad brand will

have fewer category-specific associations than the narrow brand, thereby limiting the

category accessibility. Because of limited category-specific associations, the focus will

shift to the brand-specific associations and how the brand can benefit from the co-

branded partnership. As a result of this, those who are asked to evaluate a partnership of a

broad brand will have a greater preference for an attribute-complementary co-branded

product.

H2: For a narrow host brand with strong category-specific associations,

attribute-similarity (vs. attribute-complementarity) will result in more

favorable evaluations of the co-branded partnership. For a broad host

brand with weak category-specific associations, attribute-complementarity

(vs. attribute-similarity) will result in more favorable evaluations of the

co-branded partnership.

28

Method

Eighty one participants were randomly assigned to a 2 (host brand breadth: broad

versus narrow) X 2 (attribute-complementarity: complementary or similar) between

subjects design. The dependent variables were identical to those used in the previous

studies. Participants first indicated their evaluations of several brands including the co-

branded partner brands as part of an ostensibly unrelated study. Next, participants were

provided information about a new (fictitious) host brand (called Via), which had either a

complementary partner or a similar partner. In the narrow brand condition, we told

participants that the host brand has a presence in three similar product categories (i.e.,

cake mixes, bread mixes and flour). In the broad brand condition, we told participants

that the host brand has a presence in three dissimilar product categories (i.e., cake mixes,

toaster pastries and salad dressings). In order to check whether the manipulation is

successful, we asked respondents to express their agreement with two statements “this

brand manufactures a broad variety of products”; “this brand manufactures a narrow

range of products (reverse coded)” (1 = strongly disagree and 7 = strongly agree). These

statements are averaged (r = .98). An ANOVA reveals that in the broad condition, the

brand is perceived to be associated with a greater variety of products (4.5 vs. 3.3),

(F(1,79) = 25.88, p < .001). In both cases, respondents are given a cover story indicating

that the host brand is planning to introduce a new product, brownie mixes. The new

product has a co-branding partner, which is either an attribute-complementary or an

attribute-similar partner (i.e., Nestle Deluxe or Nestle Lite).

29

We provided the following information for the fictitious host brand (good taste =

3; richness = 3; low calorie = 7; low fat = 7; good value = 3; attractive package = 3;

convenience = 3; luxury = 3). These ratings indicate that the host brand is associated with

health benefits, indicating an attribute-similar co-branded partnership with Nestle Lite. In

addition, these ratings are dissimilar to how Nestle Deluxe is perceived, indicating an

attribute-complementary co-branded partnership.

.

Results

Co-branded Partnership Evaluations. An ANOVA on evaluations of the co-

branded partnership (α = .89) reveals significant main effects of attribute-

complementarity (F(1,76) = 6.37, p < .05), and prior partner brand attitude (F(1, 76) =

6.18, p < .01). The two-way interaction between host brand portfolio breadth and co-

branding strategy was also significant (F(1, 76) = 36.27, p < .001). Consistent with

hypothesis 2, planned contrasts reveal that in the broad host brand condition, evaluations

are significantly higher when there is attribute-complementary (vs. attribute-similar) co-

branding (5.28 vs. 3.67, t(76) = 6.02, p < .0001). In contrast, in the narrow host brand

condition, planned contrasts reveal that brand evaluations are significantly lower when

there is attribute-complementary (vs. attribute-similar) co-branding (4.34 vs. 5.00; t(76) =

2.53, p < .05). These results suggest that attribute-complementary co-branded partnership

has a positive impact when the host brand is broad, whereas attribute-similar co-branded

partnership has a positive impact when the host brand is narrow. A summary of the

results is presented in table 4.

30

___________________

Insert table 4 about here

___________________

Relational Links and Attribute Perceptions. In study 2, we examined the role of

attribute-related thoughts and relational thoughts as ancillary dependent variables in order

to provide additional evidence of the role of processing in influencing co-brand attitude.

In this study, we used more direct measures of relational links and attribute perceptions.

We posit that relational links and attribute perceptions will demonstrate a pattern

similar to those observed for co-branded partnership evaluations. We examined relational

links by asking participants to indicate their level of agreements with the following three

statements on 7-point scales: “It makes sense to have Nestle Deluxe as a partner for the

new Via by Nestle Deluxe brand.” “It was easy to see how VIA and Nestle Deluxe are

related in many ways.” “I was able to come up with different ways in which the VIA by

Nestle Deluxe can be used.” These three statements were averaged (α = .66) to form a

relational linkage index. The results for relational linkage index indicate that in the

narrow brand condition, relational links are significantly higher in the attribute-similar

(versus attribute-complementary) condition (4.93 vs. 4.23; t(76) = 2.43, p < .05). In

contrast, in the broad brand conditions, perceived relational links do not vary as a

function of attribute-complementarity (4.53 vs. 4.70; t(76) = 0.80, NS). These results

indicate that when relational linking takes place (as in the narrow brand condition),

relational links are enhanced when the two partners have similar (rather than

complementary) attributes.

31

We examined attribute perceptions by asking participants to rate the performance

of the co-branded partnership on 7-point scales. Specifically, we asked participants to rate

whether the partnership has high or low attribute values for eight attributes (good taste,

richness, low fat, low calorie, good value, attractive packaging, convenience and luxury).

We focused on attribute ratings about taste (good taste and richness perceptions; r= .95).

In the narrow brand condition, ratings were not significantly different for the attribute-

similar and attribute-complementary conditions (4.62 vs. 4.13; t(76) = 1.26, NS).

However, in the broad brand condition, ratings were significantly lower when the co-

branded partner was attribute-similar (versus attribute-complementary) (3.47 vs. 4.76;

t(76) = 3.25, p < .01). Recall that in this study, the attribute-similar combination is a low

fat-low taste combination whereas the attribute-complementary combination offers both

health and taste. Therefore, it is meaningful that under property mapping (i.e., under

broad brand condition), attribute ratings vary when there is attribute-complementary co-

branding, but not when there is attribute-similar co-branding.

Mediation Analysis. We ran two models to test whether attribute perceptions and

relational linkage index would mediate the effects of complementarity and brand breadth

on co-branded partnership evaluations. In the first model, we wanted to determine

whether the indirect effect of complementarity on co-branded partnership evaluations

through attribute perceptions depended on brand breadth. We tested for the conditional

direct, conditional indirect, and conditional total effects of complementarity on

evaluations of co-branded partnerships through attribute perceptions as brand breadth

changes using a conditional process model (Hayes 2012).

32

The results revealed that the interaction effect of complementarity and brand

breadth on attribute perceptions was significant (b = 1.67, p < .005). The effect of

attribute perceptions on evaluations of co-branded partnerships, when we held brand

breadth and complementarity constant, was also significant (b = .32 p < .001), suggesting

that the first stage of the mediation model (complementarity-attribute ratings) is

moderated. The conditional indirect effect of complementarity on co-branded partnership

evaluations through attribute perceptions was significant in the broad host brand

condition, with a 95% CI (bootstrap confidence interval) wholly above zero [.11, .77]. In

the narrow host brand condition, the indirect effect was not different from zero, as

evidenced by a CI that straddles zero [–.53, .07]. In the broad brand condition, the direct

interaction effect of complementarity and brand breadth on evaluations of co-branded

partnership was statistically significant (b = 1.30, p < .001), meaning that even after

accounting for attribute perceptions , the effect of complementarity had a significant

positive effect on co-branded partnership evaluations in the broad brand condition. These

results indicate a partial mediation. These results are summarized in Figure 1.

___________________

Insert Figure 1 about here

___________________

We ran a second model to further identify the process mechanisms by which

complementarity and brand breadth influenced co-branded partnership evaluations. For

this purpose, we tested whether relational linkage index would mediate the effects of

complementarity and brand breadth on co-branded partnership evaluations, using a

conditional process model (Hayes 2012). The results revealed that the interaction effect

33

of complementarity and brand breadth on relational linkage index was significant (b =

.86, p < .05). The effect of relational linkage index on co-branded partnership

evaluations, when we held brand breadth and complementarity constant, was also

significant (b = .34 p < .001), suggesting that the first stage of the mediation model

(complementarity-relational linkage index) is moderated. The conditional indirect effect

of complementarity on co-branded partnership evaluations through relational linkage

index was significant in the narrow host brand portfolio condition, with a 95% CI

(bootstrap confidence interval) above zero [-.54,-.05]. In the broad host brand condition,

the indirect effect was not different from zero, as evidenced by a CI that straddles zero [–

.11, .36]. In the narrow brand condition, the direct interaction effect of complementarity ×

brand breadth on co-branded partnership evaluations was not statistically significant (b =

-.50, NS), meaning that after accounting for relational linkage index, the effect of

complementarity did not have a significant effect on co-branded partnership evaluations

in the narrow brand condition. These results are summarized in Figure 2.

___________________

Insert Figure 2 about here

___________________

Summary. The results of this study suggest that host brand breadth influences the

extent to which consumers are likely to utilize relational linking or property mapping in

evaluating a co-branded partnership. We found that when consumers were exposed to

host brands with strong (consistent) category associations, these category associations

tend to induce a relational linking strategy. As a result, attribute-level complementarity

was less valued and co-brands involving attribute-similar partners were preferred. In

34

contrast, when consumers were exposed to host brands with weak (inconsistent) category

associations, there is limited interference to the attribute-level processing. As a result, the

more complementary brands were preferred.

We also find evidence of mediation, with property mapping and relational linking

mediating the impact of complementarity on co-branded partnership evaluations, but

under specific levels of host brand breadth. We find evidence of partial mediation in the

case of property mapping, such that the conditional indirect effect of complementarity on

co-branded partnership evaluations through attribute perceptions was significant in the

broad host brand condition; however, there was also a direct impact of complementarity

in this condition (along with attribute perceptions), indicating partial mediation. Further,

the conditional indirect effect of complementarity on co-branded partnership evaluations

through relational linkage index was significant in the narrow host brand condition,

indicating that relational linking is a mediator of the impact of complementarity on co-

branded partnership evaluations, but only in the narrow host brand condition. These

results along with the results for the preceding three studies provide strong support for the

hypothesized effects. We discuss implications of these findings in the next section.

General Discussion

Previous research on co-branding examined whether evaluations of co-branded

partnerships vary based on the level of product and brand fit between the partners, prior

brand familiarity (Simonin and Ruth 1998), attribute-complementarity (Park, Jun, and

Shocker 1996), quality signaling attributes of partnering brands (Rao, Qu and Ruekert

1999) and type of learning (Janiszewski and van Osselaer 2000). Our research builds on

35

this stream of research by demonstrating that the type of concept combination plays an

important role in understanding processes underlying consumer evaluations of co-brands.

Our contributions can be summarized as follows.

First, previous research has alluded to different types of processing based on

either property mapping (Park, Jun, and Shocker 1996) or relational linking (e.g., Desai

and Keller 2002; Samu, Krishnan, and Smith 1999; Simonin and Ruth 1998). Different

from previous research, we manipulate the type of concept combination style (i.e.,

property mapping or relational linking) and demonstrate its important moderating role in

influencing co-brand evaluations. In doing so, our findings clarify processes underlying

evaluations of co-branded partnerships. Specifically, we find that when property mapping

is used, attribute-complementary co-brands are more successful; when relational linking

is used, attribute-similar co-brands are more successful. Importantly, we showed that

property mapping or relational linking led to hypothesized effects by analyzing cognitive

responses, attribute perceptions and perceptions of relational linkages.

Second, we contribute to the emerging consumer behavior literature on processing

of composite products. According to Janiszewski and Van Osselaer (2000) co-brands do

not necessarily induce more favorable evaluations than the constituent brands

individually do, especially when they are established brands. Our theoretical framework

suggests conditions by which this problem may be overcome; co-brands are able to

induce favorable evaluations when the form of processing employed is compatible with

the concept combination style of the partnership. Our study also adds to prior research

that examined ways to overcome the single category problem of products with attributes

from various product categories (Moreau, Markman, and Lehmann 2001; Rajagopal and

36

Burnkrant 2009). The results are compatible with Rajagopal and Burnkrant’s (2009)

findings that under property mapping processing, consumers take into account both the

host and the modifier brand attributes of hybrid products due to the attribute transfer in

between; under relational linking processing, only the host brand attributes are taken into

consideration since no properties are transferred from the modifier to the host brand.

We examine the real-world implications of processing styles by investigating

whether certain consumer behavior contexts elicit one or the other form of processing

(i.e., attribute mapping or relational linking). We specifically showed how advertisements

can induce favorable evaluations for different co-brands by priming the form of

processing within the ad content. When property mapping is primed in the ad, attribute-

complementary co-brands are favored more than attribute-similar co-brands. On the

contrary, priming relational linking in the ad leads to more favorable evaluations for

attribute-similar (vs. attribute-complementary) co-brands. Our findings further contribute

to the emerging research on co-brand advertising, which has examined the determinants

of advertising effectiveness (Samu, Krishnan, and Smith 1999), effects of a partner at

different levels of cognitive elaboration or argument strength (Gammoh, Voss, and

Chakraborty 2006) and the role of audio-visual ad cues on consumers’ perceptions of

partnering brand associations (Wang and Muehling 2010).

We also demonstrated that brand breadth influences the preference for either

property mapping or relational linking. For narrow brands, relational linking is more

likely and similar combinations will result in better evaluations of the co-branded

partnership. For broad brands, property mapping is more likely and can lead to better

partnership evaluations. While much of the extant research has focused on brand breadth

37

in the context of brand partnerships (e.g., Boush and Loken 1991; Meyvis and

Janiszewski 2004), this research demonstrates that brand breadth can moderate

evaluations of co-branded products by eliciting different processing mechanisms.

The results in this research have various managerial implications. We highlighted

several examples in the introduction section, which demonstrate that practitioners are

likely to utilize both complementary and attribute-similar co-branded partnership

strategies. However, the extant literature has been silent regarding when either of these

strategies is likely to be more effective in strengthening consumers’ co-brand evaluations.

The key conclusion from the first two studies is that concept combination styles affect

which co-branding strategy is likely to be more effective. We propose that

complementary co-brands have higher chances of success when consumers are provided

with property mapping processing cues in evaluating the partnership; similar partnerships

are likely to succeed when consumers are provided with relational linking processing

cues.

Studies 3 and 4 strengthen the key conclusion while providing interesting findings

for managers. The results suggest ways of how marketers can influence consumers’

evaluations of different co-branded offers. One way is by priming the ideal form of

processing in the co-brand communication. When a co-branded product is new to the

market, advertisement should be designed to prime the form of processing (i.e., attribute

mapping or relational linking) that is compatible with the specific co-brand type (whether

partners are complementary or similar with each other) so that favorable consumer

evaluations can be induced.

38

The results also have implications of partner selection. For broad brands, the ideal

partners are likely to be those that are very complementary or dissimilar to the host brand.

In contrast, for narrow brands, a highly similar partner will be beneficial. Further, in the

case of ingredient co-branding strategies, managers should select partners with similar

attribute profiles; in composite co-branding strategies, managers are better off seeking

complementary partners.

While we conducted our research in the context of food products, we believe our

findings are applicable to other product categories. Nevertheless, future research should

examine other types of products which involve higher levels of technical complexity

(e.g., consumer electronics). In addition, future research can identify other relevant

variables that may influence the utilization of different concept combination styles. For

example, involvement in the product could moderate these effects. In the first two

studies, motivation was kept high by informing subjects that their opinions were very

important. Would these results hold if motivation were to be kept low? This is an

interesting question that could not be examined within the scope of the present research.

Further, we do not examine whether the joint impact of processing styles and

complementarity effects would vary across various moderating conditions, e.g., type of

brand personality of the partner brand (exciting versus sincere). However, it is worth

investigating moderating factors as a boundary condition for the findings presented here.

In doing so, a richer theory of co-brand strategies could be developed.

Finally, an extension study can examine how the attribute-complementarity and

similarity of partnering brands may affect a multiple partnership strategy. Voss and

Gammoh (2004) showed that although brand alliances composed of two brands induced

39

more favorable evaluations compared to a single brand, brand alliances composed of

three brands were less favored. Electronic products with similar brand attributes (e.g.,

Sony PDA, HP printers and a compatible fictitious camera brand) were used in the

research. It is worth exploring whether using different forms of processing (i.e., attribute

mapping or relational linking) may affect the outcome. Would the results differ if

relational linking processing was used? Can multiple (rather than two) attribute-

complementary partners induce more favorable evaluations when property mapping

processing is primed? These are interesting directions for future research on this topic.

40

REFERENCES

Aaker, David and Kevin L. Keller (1990), “Consumer Evaluations of Brand

Extensions,” Journal of Marketing, 54 (January), 27- 41.

Ahluwalia, Rohini (2008), “How Far Can a Brand Stretch? Understanding the

Role of Self-Construal,” Journal of Marketing Research, 45 (June), 337-

50.

Anderson, Michael C. and Barbara A. Spellman (1995), "On the Status of

Inhibitory Mechanisms in Cognition: Memory Retrieval as a Model Case,"

Psychological Review, 102 (January), 68-100.

Apple Press Info (2013), “Nike and Apple Team Up to Launch Nike+iPod”

(accessed October 26, 2013), [available at

http://www.apple.com/pr/library/2006/05/23Nike-and-Apple-Team-Up-to-

Launch-Nike-iPod.html].

Blackett, Tom and Robert W. Boad (1999), Co-branding: The science of alliance.

Palgrave Macmillan.

Boush, David M. and Barbara Loken (1991), “A Process-Tracing Study of Brand

Extension Evaluation,” Journal of Marketing Research, 28 (February), 16-

28.

Desai, Kalpesh K. and Kevin L. Keller (2002), “The Effects of Ingredient

Branding Strategies on Host Brand Extendibility,” Journal of Marketing,

66 (January), 73-93.

41

Gagne, Christina L. and Edward J. Shoben (1997), “Influence of Thematic

Relations on the Comprehension of Modifier-Noun Combinations,”

Journal of Experimental Psychology, 23 (January), 71-87.

Gammoh, Bashar S., Kevin E. Voss, and Goutam Chakraborty (2006), “Consumer

Evaluation of Brand Alliance Signals,” Psychology & Marketing, 23 (6),

465-486.

Gerrig, Richard J. and Gregory L. Murphy (1992), “Contextual Influences on the

Comprehension of Complex Concepts,” Language and Cognitive

Processes, 7, 205-30.

Hampton, James A. (1987), “Inheritance of Attributes in Natural Concept

Conjunctions,” Memory & Cognition, 15 (1), 55-71.

Hayes, A. F. (2012), “PROCESS: A Versatile Computational Tool for Observed

Variable Mediation, Moderation, and Conditional Process Modelling.

http://www.afhayes.com/ public/process2012.pdf. accessed on 8/13/2012.

Janiszewski, Chris and Stijn M.J. Van Osselaer (2000), “A Connectionist Model

of Brand--Quality Associations,” Journal of Marketing Research, 37

(August), 331-50.

King, Jen (2013), “Vertu and Ferrari Continue Partnership with New Limited-

Edition Smartphone” (August 13), (accessed October 30, 2013), [available

at http://www.luxurydaily.com/vertu-and-ferrari-continue-partnership-

with-new-limited-edition-smartphone/].

Kumar, Piyush (2005), “The Impact of Cobranding on Customer Evaluation of

Brand Counterextensions,” Journal of Marketing, 69 (July), 1-18.

42

Meyvis, Tom and Chris Janiszewski (2004), “When Are Broader Brands Stronger

Brands? An Accessibility Perspective on the Success of Brand

Extensions,” Journal of Consumer Research, 31 (2), 346-57.

Monga, Alokparna Basu and Loraine Lau-Gesk (2007) "Blending Cobrand

Personalities: An Examination of the Complex Self," Journal of

Marketing Research, 44 (August), 389-400.

Moreau, C. Page, Arthur B. Markman, and Donald R. Lehmann (2001), “'What Is It?'

Categorization Flexibility and Consumers' Responses to Really New Products,”

Journal of Consumer Research, 27 (March), 489-98.

Mueller, Christian W. and Michael J. Watkins (1977), "Inhibition from Part-Set Cuing: A

Cue-Overload Interpretation," Journal of Verbal Learning and Verbal Behavior,

16 (December), 699-709.

Oppenheimer, Daniel M., Tom Meyvis and Nicolas Davidenko (2009), "Instructional

Manipulation Checks: Detecting Satisficing to Increase Statistical Power,"

Journal of Experimental Social Psychology, 45 (July), 867-72.

Park, C. Whan, Sung Youl Jun, and Allan D. Shocker (1996), “Composite

Branding Alliances: An Investigation of Extension and Feedback Effects,”

Journal of Marketing Research, 33 (November), 453-66.

Rajagopal, Priyali and Robert E. Burnkrant (2009), “Consumer Evaluations of

Hybrid Products,” Journal of Consumer Research, 36 (August), 232-41.

Rao, Akshay, Lu Qu and Robert W. Ruekert (1999), “Brand Alliances as

Information About Unobservable Product Quality,” Journal of Marketing

Research, 36 (May), 258-68.

43

Samu, Sridhar, H. Shanker Krishnan, and Robert E. Smith (1999), “Using

Advertising Alliances for New Product Introduction: Interactions Between

Product Complementarity and Promotional Strategies,” Journal of

Marketing, 63 (January), 57-74.

Schwarz, Norbert, Herbert Bless, Fritz Strack, Gisela Klumpp, Helga Rittenauer-

Schatka, and Annette Simons (1991), “Ease of Retrieval as Information:

Another Look at the Availability Heuristic,” Journal of Personality and

Social Psychology, 61 (August), 195-202.

Simonin, Bernard L. and Julie A. Ruth (1998), “Is a Company Known by the

Company It Keeps? Assessing the Spillover Effects of Brand Alliances on

Consumer Brand Attitudes,” Journal of Marketing Research, 35

(February), 30-42.

Smith, Edward E., Daniel N. Osherson, Lance J. Rips, and Mark Keane (1988),

“Combining Prototypes: A Selective Modification Model,” Cognitive

Science, 12 (4), 485-527.

Tybout, Alice M., Brian Sternthal, Prashant Malaviya, Georgios A. Bakamitsos,

and Se-Bum Park (2005), “Information Accessibility as a Moderator of

Judgments: The Role of Content versus Retrieval Ease,” Journal of

Consumer Research, 32 (June), 76-85.

Voss, Kevin E. and Bashar S. Gammoh (2004), “Building Brands Through Brand

Alliances: Does a Second Ally Help?” Marketing Letters, 15 (2),

147−159.

44

Wang, Alex and Darrel D. Muehling (2010), “The Effects of Audio-Visual and

Visual-Only Cues on Consumers' Responses to Co-branded

Advertising," Journal of Marketing Communications, 5 (December), 307-

324.

Wänke, Michaela, Gerd Bohner, and Andreas Jurkowitsch (1997), “There are

Many Reasons to Drive a BMW: Does Imagined Ease of Argument

Generation Influence Attitudes?” Journal of Consumer Research, 24

(September), 170-78.

Watkins, Michael J. (1977), “The Intricacy of Memory Span,” Memory &

Cognition, 5 (5), 529-34.

Wisniewski, Edward J. (1996), “Construal and Similarity in Conceptual

Combination,” Journal of Memory and Language, 35 (June), 434-53.

Wisniewski, Edward J. and Bradley C. Love (1998), “Relations versus Properties

in Conceptual Combination,” Journal of Memory and Language, 38

(February), 177-202.

45

TABLE 1

Pretests on Attribute Perceptions in Study 1 and Study 2

Godiva

SlimFast

Häagen Dazs

t-value:

Godiva

vs.

Slimfast

t-value:

Godiva

vs.

Häagen

Dazs

Good Taste 5.63 4.43 5.57 3.09*** 0.18 ns

Richness 5.46 4.28 5.24 2.95*** 0.60ns

Low Calorie 3.89 5.22 4.13 -3.08*** 0.55ns

Low Fat 3.54 5.09 4.09 -3.72*** -1.38ns

Good Value 4.33 4.59 4.33 -0.62ns

0.00ns

Attractive Package 4.83 4.17 4.63 1.67* 0.52ns

Convenience 4.20 4.65 4.98 -1.18ns

-2.21**

Luxury 5.57 3.87 4.93 2.30*** 0.82ns

Hershey’s

Healthy

Choice Oreos

t-value:

Hershey’s

vs.

Healthy

Choice

t-value:

Hershey’s

vs. Oreos

Good Taste 6.23 3.10 5.92 4.90*** 1.67ns

Richness 5.91 3.20 5.90 5.46*** 0.20ns

Low Calorie 2.51 5.30 2.56 -7.98*** -0.32ns

Low Fat 2.41 4.15 2.65 -2.48** -0.47ns

Good Value 5.14 4.90 4.83 0.64ns

1.28ns

Attractive Package 4.67 5.30 5.26 -0.25ns

1.96*

Convenience 5.56 4.10 5.30 0.24ns

0.87ns

Luxury 4.07 4.05 4.22 0.08ns

-0.32ns

Note: scales range from 1=extremely low performance to 7=extremely high performance

*** p<.01; ** p<.05; * p<.10; ns: not significant

46

TABLE 2

Study 2: Means and Standard Deviations

Co-branded Partnership Evaluations

Relational

Property

Attribute complementary co-branded partnership

3.58

(0.45)

4.08

(0.64)

Attribute similar co-branded partnership

4.13

(0.65)

3.69

(0.55)

Valenced Index

of Attribute-Related Thoughts

Attribute complementary co-branded partnership

.17

(0.85)

.80

(1.38)

Attribute similar co-branded partnership

.23

(0.62)

.08

(0.48)

Valenced Index

of Relational Thoughts

Attribute complementary co-branded partnership

-.36

(0.50)

.32

(0.76)

Attribute similar co-branded partnership

.19

(0.35)

.18

(0.50)

47

TABLE 3

Study 3: Attribute Perceptions (n=124)

Hershey’s

Honey Maid Oreos

t-value:.

Hershey’s

vs. Honey

Maid

t-value:

Hershey’s

vs. Oreos

Good Taste 6.12 5.14 5.87 4.21*** -1.05ns

Richness 6.18 4.85 5.97 6.58*** -1.04ns

Low Calorie 2.30 4.03 2.29 -7.12*** -0.07ns

Low Fat 2.39 4.27 2.33 -7.66*** -0.24ns

Good Value 4.83 4.50 4.38 1.50ns

-2.01*

Attractive Package 5.12 4.45 4.94 2.98***

-.82ns

Convenience 5.86 5.21 5.65 3.41***

-0.27ns

Luxury 4.89 3.47 4.40 5.01*** -1.59ns

Note: scales range from 1=extremely low performance to 7=extremely high performance

*** p<.01; ** p<.05; * p<.10; ns: not significant

48

TABLE 4

Study 4: Means and Standard Deviations

Co-branded Partnership Evaluations

Narrow

Brand

Broad

Brand

Attribute complementary co-branded

partnership

4.34

(0.96)

5.28

(0.95)

Attribute similar co-branded partnership

5.00

(0.80)

3.67

(0.68)

Index of Attribute Perceptions

Attribute complementary co-branded

partnership

4.62

(1.14)

3.47

(0.83)

Attribute similar co-branded partnership

4.13

(1.46)

4.76

(1.10)

Index of Relational Linkages

Attribute complementary co-branded

partnership

4.23

(1.07)

4.70

(0.96)

Attribute similar co-branded partnership

4.93

(0.68)

4.53

(0.89)

*Note: The means presented here are not raw means but adjusted means from the analysis

of variance

49

FIGURE 1

Study 4: The Effect of Attribute Complementarity is Mediated by Attribute Related

Thoughts and Moderated by Brand Breadth

FIGURE 2

Study 4: The Effect of Attribute Complementarity is Mediated by Relational

Linkage Index and Moderated by Brand Breadth

Attribute

Complementarity

Attribute

Related

Thoughts

Co-branded

Partnership

Evaluations

cꞌ = .1.90**, SE = .37

c = .53*, SE = .26

** p<.01

* p<.05

Brand

Breadth

b = .32**, SE = .07

Attribute

Complementarity

Relational

Linkage

Co-branded

Partnership

Evaluations cꞌ = 2.13**, SE = .37

c = .30*, SE = .19

** p<.01

* p<.05

a = .86*,

SE = .41

Brand

Breadth

b = .34**, SE = .10

50

APPENDIX

Priming Procedure

Property Primes

Bus Truck

Skunk Beggar

Motorcycle Bicycle

Razor Insult

Umbrella Tree

Zebra Tablecloth

Feather Shoes

Sleeping Pill Sermon

Bullet Sprinter

Roller Coaster Dinner

Butcher Surgeon

Book Computer

Relational Primes

Clothing Truck

Dollar Bill Beggar

Grocery Bicycle

Girlfriend Insult

Fruit Tree

Holiday Tablecloth

Motorcycle Shoes

Adultery Sermon

Adidas Sprinter

Birthday Dinner

Kidney Surgeon

Kitchen Computer