Evaluations of Co-Brands: A Two-Country Comparison

This paper explores consumer reactions to a brand alliance, with perceptions of the parent brands, perceived fit between the brands and fit between product categories as the drivers. Drawing on previous work on co-brands (Simonin and Ruth, 1998; Baumgarth, 2000), two simultaneous studies of four consumer brand pairings were conducted in the UK (n=122) and Italy (n=125) using respondents from an online panel. Important differences between the studies are identified and possible cultural explanations for deviant outcomes are discussed.
JEL ClassificationM31

Full Article

1. Introduction

The popularity of co-branding (also referred to as ‘brand alliances’) as a brand management strategy is well documented (Helmig et al., 2008). Marketers are increasing their use of co-brands as a way to break through ad clutter and leverage marketing spend; Datamonitor reported that co-branding almost doubled in early 2014 compared to previous years (Schultz, 2014). Co-brands combine the competencies and reputations of two brands to create a new product (Park et al., 1996). Past research has identified important determinants of consumer attitudes to cobrands, such as familiarity with the parent brands (Levin and Levin, 2000), the perceived quality of the partners (Rao and Ruekert, 1994), and their relative brand equity (Washburn et al., 2000). Research on co-branding developed from a burgeoning literature on brand extensions, applying characteristics associated with extension success (strong parent brand quality perceptions, the complementarity between the parent and extension product categories) to a brand alliance scenario. Simonin and Ruth (1998) draw on information integration theory and presented a structural model that relates alliance perceptions to pre-existing parent brand attitudes and the fit (both product-wise and brand-wise) between the parents, and incorporates feedback effects from the alliance back to the parent brands. They found familiarity moderates the strength of relationship between constructs, and that partner brands were not necessarily affected equally by participation in a particular alliance. A query on Google Scholar reveals more than 1800 references to Simonin and Ruth (1998), referred to hereafter as S&R, making it one of the most widely cited studies in the co-branding literature.

A few researchers have the applied the S&R model, considering additional drivers and/or ignoring the feedback effects. Ruth and Simonin (2003) applied the model to sponsored events, adding country of origin as a factor. Lafferty, Goldsmith and Hult (2004) applied the original S&R model to cause-related alliances, confirming the importance of pre-existing attitudes toward a cause and a brand on the alliance perceptions, and identifying the fit between the cause and the brand name (rather than the product category) as a necessary antecedent for a successful campaign. Baumgarth (2004) attempted to replicate S&R, looking at car + stereo co-brands, and cereal + chocolate. He found that pre-existing attitudes were less influential, and brand fit more impactful than the S&R findings. These differing results were put down to differences in operationalization in the co-brand evaluation, and to cultural difference between the Baumgarth studies (in Germany) and the original S&R study in the U.S. Subsequently, Helmig, Huber and Leeflang (2006) modified the S&R model adding additional personal variables that influence behavioural intention. They found support for the main relationships, with product fit more influential than brand fit. Bluemelhuber, Carter and Lambe, (2008) considered cross-national brand alliances, adding country-of-origin fit as an antecedent of alliance attitudes. All relationships were supported, with brand fit more influential than product fit on co-brand perceptions. Recently, Bouten, Snelders and Hultink (2011) also expanded fit to include the match between the new product offering and the parent brands; the results suggest brand fit dimensions to be a greater influence than other factors on co-brand evaluations.

These finding suggest questions remain about the relative importance of product fit and brand fit to co-branding endeavours, and the impact of culture on co-branding evaluations. Heeding calls for more replication work in the managerial sciences (e.g. Hubbard and Armstrong, 1994; Easley et al., 2000; Evanschitzky et al., 2007) this paper looks at co-brand perceptions using the S&R framework for four global brand pairings in two countries, Italy and the UK. The research looks at alliance perceptions only and does not consider spill over effects. The study contributes to our understanding of brand alliances in two ways; it provides additional empirical evidence for a widely cited research model, and it considers how cultural differences might impact on brand alliance perceptions. By testing the same brand pairings simultaneously in two countries, a direct comparison can be done.

The paper is organized as follows. The literature review summarises the brand alliance literature from a demand (i.e. customer) perspective, followed by a discussion of the S&R and Baumgarth (2004) studies. Cross-cultural consumer behaviour is then briefly discussed, followed by a short overview of the design methodology. The final section presents the results of the two country studies, comparing against previous research and drawing on Hofstede’s theory of national culture (Hofstede, 2001) when analysing the results. Methodological limitations and areas for future research are identified.

2. Literature Review

2.1. Brand Alliances

The theoretical foundations of consumer perceptions of brand alliances developed from consideration of brand extensions (e.g. Aaker and Keller, 1990) and are based on theories on signalling (Rao and Ruekert, 1994; Rao et al., 1999), and attitude formation (e.g. Anderson, 1981; Hillyer and Tikoo, 1995). Signalling theory suggest that because firms hold different information to buyers it needs to find way to communicate this information to them. Research on attitude formation suggests that people interpret and integrate new information with existing beliefs; pre-existing, salient and accessible brand attitudes and close, observable cues influence consumer perceptions of a brand partnership (Petty and Cacciopio, 1986; Lynch et al.,1991), A review of the empirical literature (see Table 1 for a summary) highlights a few key points. First, the extent which consumers perceive two product categories as complementary and well matched (i.e. product fit), and the congruence of brand associations such as quality or brand personality (brand fit), have a positive influence on brand alliance perceptions (3 citations here). The relative impact of brand and product fit has been explored across a range of characteristics, such ingredient branding (Desai and Keller, 2002; Radighieri et al., 2013); functional vs expressive brands (Lanseng and Olsen, 2012); search vs. experience goods (Washburn et al., 2000); cause-related alliances (Lafferty et al, 2004; Ruth and Simonin, 2003) and trans-national brand pairings (Bluehelhuber et al., 2008; Han and Hongwei, 2013; Lee et al., 2013). Recent papers have developed the fit construct beyond simple product and brand metrics (Bouten et al., 2011; Lanseng and Olsen, 2012; Xiao et al., 2014).

Second, studies have also considered how consumer attitudes toward an alliance ‘spill over’ and influence post exposure attitudes toward the partner brands (e.g. Bengtsson and Servais, 2005; Cunha et al., 2014; Simonin and Ruth, 2008). Overall, the findings suggest general positive outcomes for parent brands (e.g. Washburn et al., 2000; Swaminathan et al., 2012), but several studies suggest these benefits are asymmetrical (Laffery et al., 2004; Simonin and Ruth 1998; Radigieri et al., 2013) and negative spillover is possible (Votolato and Unnava, 2006; Radigieri et al., 2013). The impact of personality variables have also been considered Finally, the review highlights the broad range of products (e.g. cars, food products, bicycle seats, personal electronics, luggage, clothing, health & beauty) and brands (e.g. Heineken, Sony, Calvin Klein, Evian, Gucci, Corona, etc.) studied. However, most research was conducted in the US (26 of 32 studies in Table 1), no multi-country studies were identified.

Table 1. Empirical literature on consumer evaluations of co-brands (brand alliances)

Study Products & Brands considered Findings
Ahn et al., 2009 (Korea) Levis jeans – Samsung Sense computer;Levis jeans – Motorola computer If consumers perceive a harmony across paired products or brands, they are more likely to engage in the association process of evaluating the brand alliance
Baumgarth, 2004(Germany) 4 car brands/ 4 consumer electronic brands; 4 cereal brands/4 chocolate brands Replication of S&R found lower significance of brand attitudes toward the individual brands for the co-brand evaluations, and greater importance of brand fit as factor.
Besharat, 2010(USA) Blue-tooth (Blackberry/ Hitachi) enabled sunglasses (Ralph Lauren/ Police) Presence of at least one high-equity brand in co-brand leverages consumers’ evaluations of a new product
Bluehelhuber et al., 2008 (USA) Car brands (BMW/Kia) + stereo brands (Sony/Apex/fictitious brand) Extension of S&R analysing transnational brand alliances –when brand familiarity decreases, positive influence of fit on a brand alliance increases, and is greater than that of brand fit.
Bouten et al., 2011(Netherlands) bicycle seat (Batavus/Maxi Cosi/ Sparta and hand vacuum cleaner (Swiffer/ Duracell/ Sorbo) Extension of S&R – added two new fit measures (new product/product fit and new product/brand fit)
Cunha et al., 2014(USA) cereals, brownies & cookies Well-known brand can weaken or strengthen the association between the less-known brand and the co-branding outcomes, depending on when product information is provided.
Desai and Keller, 2002(USA) bath soap, cough syrup Where product attributes are dissimilar from parent brand, ingredient branding results in more favourable evaluations over self-brand ingredients.
Fang et al., 2013(USA) Fictitious digital cameras Both a BA and a warranty were significant signals of product quality. No advantage to having both over just one.
Gammoh et al., 2006 (USA) Digital camera (fictitious brand) + PDA (Sony) Brand ally is an endorser of the primary brand i) when cognitive elaboration is low and ad is strong; ii) when cognitive elaboration is high and the ad is weak and the ally is reputable.
Geylani et al., 2008 (USA) Fictitious brands, luggage and clothing Not in a brand’s best interest to choose highest performing alliance partner. An alliance can increase parent brand attribute perceptions, but also uncertainty about the brands
Li and He, 2013(Taiwan) beer flavored tea product by Heineken (Netherlands) and Uni-President (Taiwan) Brand order and consumers’ beliefs about the appropriateness and morality of buying foreign-made products moderate brand attitude effects
Helmig et al., 2006(Germany) fruit juice (Hohes C/ Granini, Punica/Valensina) +yogurt brands (Mueller/ Danone/ Ehrmann/Bauer) Extension of S&R – adds buying intention and personal variables that affect buying intention Product fit has strongest effect on behavioural intention.
James, 2005; James et al., 2006 (UK) PDA (Filofax/Sony/ Calvin Klein); phone watch (Swatch /Sony/ British Telecom); sun lotion for hair (Vidal Sassoon/Ambre Solaire /Benetton) Mouthwash (Crest/Oral B/Sure) Brand fit is important; alliances with poor overall attitudes were often linked to associations of attributes of the original parent branded product. Managers should focus on finding a similarity between brand alliance partners in brand personality as well as concrete dimensions
Lafferty et al., 2004(USA) Causes: American Red Cross /Famine Relief Fund; water: Evian/Naya; soup: Campbells/ Healthy Choice Cause benefits more than product from alliance; fit between partners plays a pivotal role in consumer acceptance of the alliance as plausible and familiarity with the cause improves effectiveness
Lanseng and Olsen, 2012(Norway) Functional: Krystal detergent/ Clinomyn toothpaste/ Philips TV/ IF life insurance. Expressive: Pepsi/ Gucci sunglasses/ D&G jeans / Corona beer Both product category fit and brand concept consistency influence consumer evaluation. Product category fit is important in only functional & mixed brand concept-based alliances, not expressive brand alliances
Lebar et al., 2005 (USA) Internet survey, nationally representative sample Joint branding campaigns help to increase a brand’s perceived differentiation, but also sometimes harm perceived knowledge and esteem in the process.
Lee et al., 2013(USA) Car/Car stereo: BMW/Japanese car stereo, BMW/Mexican car stereo Positive attitudes when images of countries involved are both favourable. Partner with less favourable country image can leverage Country of origin fit to gain favourable brand image and consumer product evaluation.
Levin et al.,1996 (USA) Brownies (Betty Crocker/ Mrs Bakewell) +chocolate chips(Nestles/ “Rich”) The ingredient brand had larger impact on the co-brand evaluation than the host brand. Host brands were rated lower if the ingredient brand pairing was not well known.
Levin and Levin 2000; Levin, 2002 (USA) Restaurants When one brand is ambiguous, quality is inferred when brands are considered to be similar; specific attribute values and global evaluations of quality are assimilated from the better known ‘context’ brand
Park et al., 1996 (USA) Slim-Fast/Chocolate cakemix/Godiva Brands with complementary attributes yield a better composite extension (header + modifier) than a direct extension of the header brand. Complementary brands yields better results than highly favourable brands that are not complementary.
Radighieri et al., 2013 (USA) Phones (Nokia/Aduiovox) and cameras (Kodak/Vivitar) Successful alliance positively affects both parent brands but the positive feedback is much more substantial for the weaker (vs stronger) brand. When an alliance fails, a strong ingredient brand is the only parent brand somewhat protected.
Rao et al., 1999 (USA) real/fictitious TV brand alliances If a product has an important unobservable attribute, partnering with a brand that has a reputation to uphold delivers higher consumer quality perceptions of the product.
Rodrigue and Biswas, 2004 (USA) Doritos tortilla chips + partner (Olean cooking oil / Kraft brand cheese) Brand pre-attitudes have a positive effect on alliance attitudes, with positive spill over effects and perceptions of quality, WTP and purchase intention. Resource dependency moderates effects on ally; contract exclusivity moderates effects on host brand
Ruth and Simonin, 2003(USA) Coca-Cola + cosponsor (US: Breyers ice cream/ Jack Daniels whiskey/ Bank of New York/ Marlboro) (Japanese: Meiji/ Suntory/ Bank of Japan/ Fuji) Sponsor brand nationality and complementarity of products also affect cobrand perceptions.
Simonin and Ruth (S&R) 1998(USA) Car (Ford/ Toyota/ VW/ Hyundai) + microprocessor (Motorola/ Fujitsu/ Siemens/ Samsung); NW Airlines + Visa; Disney + major retailer Looks at individual brand attitudes, product fit, and brand fit as important inputs to brand alliance attitude, with feedback from alliance to individual brands. Familiar brands have a greater impact on BA, but unfamiliar brands benefit from more spill-over effect.
Swaminathan et al., 2012(USA) AC Nielsen scanner panel data. Line extensions with ingredient branded products Eg: Betty Crocker cake mix w/ Hershey’s Choc Consumers who trial the co-branded product are more likely to purchase both host and ingredient brands; effect is greater among prior non-loyal users and when there is greater perceived fit between host and ingredient brand.
Voss and Gammoh, 2004 (USA) Fictitious digital camera brand with Sony (PDA) and HP (Printers) Single brand ally significantly increased perceived quality and hedonic and utilitarian attitudes. Second ally did not further increase evaluations.
Votolato and Unnava, 2006 (USA) fictitious clothing brands Negative spill-over from partner to host brand occurred only when host was viewed as equally culpable for an offence.
Washburn et al., 2000(USA) Potato chip: Ruffles/fictitious brand BBQ sauce: Maulls/fictitious brand Co-branding positively affected subsequent brand equity ratings. Brand names particularly important when claims are difficult to evaluate prior to purchase.
Washburn et al., 2004(USA) Paper towels + disinfectant (Bounty/ Mr Clean, Bounty/ Defense, Spirit/Mr Clean, Spirit/ Defense Co-branding elevates the perceived equity of both partner brands. Having a high equity partner enhances pre-trial evaluation of experience and credence attributes that are relevant to the high-equity partner.

2.2. Simonin&Ruth (1998) and Baumgarth (2004)

Simonin and Ruth (1998) was the first study to simultaneously consider co-brand evaluation and spill over effects, as well as the fit between brands and products (with brand familiarity as a moderating factor). The hypotheses were tested based on a co-brand of a car brand (Ford, Toyota, Volkswagen, Hyundai) and a microprocessor brand (Motorola, Fujitsu, Siemens, Samsung), resulting in 16 different brand alliances. The co-brand combinations were based on participants being familiar with the car brands, but having differing levels of brand familiarity for the microprocessors. In total, 350 university students and staff participated in a study where the co-brand was presented through an advertisement. The hypotheses of the spill-over effects as well as the co-brand evaluation were tested by means of a comprehensive causal model. To assess its robustness with other types of alliances, S&R then tested the model with two further alliances, Northwest Airlines/Visa and Disney/retailer. The results supported all hypothesized relationships. An indicator of S&R’s impact on the literature is the high frequency of citation in later co-brand papers, and six papers from Table 1 apply or extend the S&R model.

Arguing that the validity of S&R’s results should be validated in other cultural contexts, Baumgarth (2004) performed a direct replication of S&R in Germany, using well known car brands (BMW, VW, Opel and Porsche), and consumer electronic (audio) brands that were either high familiarity (Sony, Blaupunkt) or low familiarity (Aiwa, Bang & Olufson). An extended replication was conducted for cereal brands (high for Kellogg’s and Dr Oeker Vitalks; low for Kolln Flocken and Seitendbacher) and chocolate brands (high for Lika and Ritter Sport; low for Exzet). This study was intended to identify variance due to brand familiarity across both partners, and test the S&R model with fast-moving consumer good (FMCG) products, which is where the majority of real co-brands reside. The test of S&R in another cultural context and with FMCG products was intended to improve the generalization of the model.

A comparison of S&R (1998) and Baumgarth (2004) for the direct replication showed significant differences, with only half of the original eight relationships supported. Three out of the four supported hypotheses focused on spill over effects. Only brand fit was a significant influence on the brand alliance for the automotive/audio brand pairings. (Note for the cereal + chocolate co-brand, all relationship were supported). The main differences between the studies were the lower significance of brand attitudes towards the individuals brands for the co-brand evaluation, and the higher significance of brand fit in Baumgarth’s study over S&R. Possible reasons for the differences were hypothesized to be the slightly different operationalizations of co-brand evaluations between the studies or cultural differences. Baumgarth then devotes substantial discussion to operationalization differences, but culture is not addressed. We now briefly consider dimensions of culture and their relationship with branding strategy.

2.3. Cross-Cultural Consumer Behaviour and Branding

Most aspects of consumer behaviour are culture bound and much research on cross-cultural consumer behaviour and issues of global branding have used the Hofstede dimensional model of national culture (Hofstede, 1980; 2001). The model has been used to explain differences of the concepts of self, personality and identity, which in turn explain variation in branding strategy and communications. Differences in perception and information categorization, and the social processes that fuel motivation and emotion have also been explained by the model (de Mooij and Hofstede, 2011). Reasons for the widespread adoption of Hofstede’s classification of culture lies in the large number of countries measured (82 to date), the numerous comparative studies/replications that support his findings, and the simplicity of his dimensions which are accessible to a wide audience. Comparison of different models from an international marketing strategy perspective indicates that more recent cultural frameworks (e.g. Schwartz’s, GLOBE) provide limited advancements compared with Hofstede’s original work (Magnusson et al., 2008).

The Hofstede model distinguishes cultures according to five dimensions: power distance, individualism/collectivism, masculinity/femininity, uncertainty avoidance, and long- vs. short-term orientation. Power distance can be defined as ‘the extent to which less powerful members of a society accept and expect that power is distributed equally’ (De Mooij and Hofstede, 2011). In large power distance cultures, social status must be clear so that others cans show proper respect, and global brands serve that purpose. In individualistic cultures, one’s identity is the person, and is considered to have a ‘low context’ style centred around explicit verbal communications, that are succinct and to the point. By contrast, collectivistic cultures are based on the social system to which they belong, and avoiding loss of face is important. Collectivistic cultures are high-context, with an indirect style of communications that is built around relationship-building and trust. For masculine societies, performance and achievement are important and achievement must be demonstrated, so status brands or products are important to show ones/ success (De Mooij and Hofstede 2002), which feminine societies are caring for others and quality of life, and are less brand-conscious. Uncertainty avoidance (UA) can be defined as ‘the extent to which people feel threatened by uncertainty and ambiguity and try to avoid these situations’. In high UA cultures, there is a need for rules and formality to structure life; searching for truth and a belief in experts are important here. High UA people are less open to change, and have lower rates of innovation adoption. Long-versus short-term orientation is the extent to which a society exhibits a pragmatic future-orientated perspective rather than a conventional historic or short-term point of view. Long-term orientation implies investment in the future, perseverance, thrift, ordering relationships by status, having a sense of shame ; short-term orientation focuses on personal steadiness, stability, happiness and respect for tradition.

Brands are augmented products with values or personal traits added through communication strategy. Studies have confirmed that different cultural conditions lead consumers to different brand evaluations (Aaker, Benet-Martinez and Garolera, 2001; Kocak et al., 2007), and consumers across cultures may attribute different brand personalities to one and the same global brand. For example, the Red Bull brand has been marketed with a consistent brand identity, but consumers from different cultures attribute different personalities to the brand (Fosch et al., 2008). A commercial cross-cultural brand value study that compared personalities attributed to highly valued global brands across cultures found differences that aligned on Hofstede’s dimensions of power distance and uncertainty avoidance (De Mooij, 2010). The mechanisms by which these associations are formed are also influenced by culture, reflecting variations in motivations, emotions, and mental processes (Aaker and Maheswaran, 1997; de Mooij and Hofstede 2011; Malai and Speece, 2005). In brand extension research, Monga and John (2007) relied on cultural differences in thinking style (i.e. holistic vs analytical) to explain the greater perceived fit and more favourable brand evaluations among East Asians compared to Westerners. In general, multi-country replications of brand extension models reveal significant differences to due culture (Aaker and Keller, 1993; Bottomley and Doyle 1996; Bottomley and Holden 2001). To date, no multi-country studies of cobranding have been identified. Although positioned as a direct replication of S&R (1998), the Baumgarth (2004) study in Germany considered culture-specific brands and contained subtle differences in the cobrand category (microprocessors vs audio electronics) that might have impacted the results.

This study seeks to address this gap by applying the S&R model (without spill over effects) simultaneously in two countries (See Figure 1). By using the same product categories and global brands, a clear cross-cultural comparison can be done. The validity of the S&R model in other cultural contexts is particularly important as organizations continue to expand co-branding activities across borders (a recent example is Starbucks + Spotify). The findings of Baumgarth (2004) and the discussion above suggests it is logical to assume that culture influences customer perceptions of the parent brands and moderates perceived product and brand fit. Hofstede’s framework will be applied as a theoretical lens to consider differences in findings between the countries.

Figure 1. Theoretical framework

3. Method

The design of the study was similar to the S&R (1998) and Baumgarth (2004) studies. The UK and Italy were chosen as the population domains for the sample. A small pre-test (n=30) was performed individually in each country to identify the common products and brands for the main study, with only high familiarity brands selected. Four brand alliances of a host brand (A) and a partner brand (B) were devised: McDonalds (restaurant) + Lindt (chocolate); Colgate (toothpaste) + Mentos (mints); Kellogg’s Special K (cereal) + Mueller (yogurt), and Pepsi (soft drink) + Red Bull (energy drink). The variables were operationalized in order to correspond closely to S&R (1998) and Baumgarth (2004). Measures were assessed through seven-point bipolar semantic differential scales, including measures of attitudes toward each partner brand and the brand alliance, as well as brand fit and product fit. Familiarity was operationalized as a single item scale (e.g. Bergkvist and Rossiter, 2007; Droley and Morrison, 2001; Fuchs and Diamantopolous, 2009). The sample was created using an online panel with UK (n=122) and Italian (n=125) respondents.

4. Results

We used partial least squares (PLS) to test our model. PLS simultaneously estimates the measurement and the causal model. However, Hulland (1999) suggests interpreting the model in two stages, looking at the measurement model first and then assessment of the structural model.

4.1. Measurement Model

All factor loadings on the (intended latent variable are significant and bigger than 0.7 (Fornell and Larcker, 1981), and the squared-multiple correlations indicate item reliability. The average variance extracted (AVE) from each variable is bigger than 0.5 (Bagozzi and Yi, 1988), thus supporting the existence of convergent validity. Discriminant validity was evaluated by comparing the AVE of each construct and the variance shared between such constructs and other constructs in the model (Table 2).

Table 2. Correlations, AVE and Reliability statistics

Factors 1 2 3 4 5 6 7 CR AVE
[1] AttitudesA .952 .967 .906
[2] AttitudesB .194 .954 .968 .909
[3] Product Fit .183 .143 .948 .946 .898
[4] Brand Fit .119 .095 .826 .887 .879 .787
[5] FamiliarityA .115 .003 .010 .030 - - -
[6] FamiliarityB .219 .304 .049 .082 .430 - -
[7] AttitudesAB .327 .137 .387 .500 .042 .050 .926 .948 .858
[1] AttitudesA .983 .967 .906
[2] AttitudesB .376 .993 .968 .909
[3] Product Fit .377 .187 .951 .946 .898
[4] Brand Fit .305 .135 .855 .958 .879 .787
[5] FamiliarityA .421 .232 .046 .001 - - -
[6] FamiliarityB .299 .464 .059 .093 .622 - - -
[7] AttitudesAB .647 .640 .542 .542 .211 .314 .986 .948 .858

Note: Numbers in boldface indicate the square root of the AVE. No correlation is greater than the corresponding square root of AVE, confirming discriminant validity

4.2. Main Model

The results are presented in Table 3. The results show pre-existing brand attitudes influence attitude towards the co-branded products for both countries. Interestingly, the influence of the host brand was much stronger in Italy, while the partner brand was a stronger influence with UK respondents. Product fit was a significant influence on co-brand perceptions in Italy, but not for UK respondents. Brand fit had no main effects for either cohort, but a significant interaction effect between brand fit and familiarity of the partner brand was observed for the Italian respondents.

Table 3. Results of the Partial Least Squares Analysis

UK Italy
Path coefficient (t-value) f2 Path coefficient (t-value) f2
AttitudesA difference of coefficients sig at 5% 0.164 (2.09)* 0.05 0.343 (4.39)*** 0.28
AttitudesB difference of coefficients sig at 1% 0.744 (11.85)*** 0.98 0.458 (6.11)*** 0.51
Product fit -0.063(0.52) 0.01 0.275 (2.89)** 0.08
Brand fit 0.135 (1.46) 0.00 0.121 (1.17) 0.01
AttitudesA * FamiliarityA -0.102 (0.89) 0.01 -0.013 (0.14) 0.00
AttitudesB * FamiliarityB 0.035 (0.41) 0.00 -0.024 (0.17) 0.00
Brand fit * FamiliarityA 0.053 (0.46) 0.00 -0.106 (0.79) 0.01
Brand fit * FamiliarityB -0.001 (0.05) 0.00 0.236 (1.76)* 0.07
R2, Adj R2 0.575; 0.536 0.754; 0.732
Q2 0.458 0.675

5. Discussion and Conclusions

5.1. Theoretical Contributions

The results suggest that culture influences the relative impact of pre-existing brand attitudes and fit measures on alliance perceptions. For Italian respondents, the parent brands have similar levels of influence on alliance perceptions, and fit between the product categories is also a significant factor. For the UK sample, the partners’ impact on the brand alliance is lop-sided, and fit was not significant. Considering these results, Hofstede’s model of culture provides some insight into differences in branding perceptions and categorization for the two samples. Using Hofstede’s framework, Italy and the UK are substantively different on the dimensions of uncertainty avoidance (Italy high/UK low) and indulgence (Italy low/UK high). Cultures of strong uncertainty avoidance (such as Italy), are less comfortable with uncertainty and ambiguity, and rely on rules and formality to guide them. The findings suggest the Italian respondents apply equal consideration to brands, and that categorization of the products (complementarity, consistency) is a clear heuristic. As the fit between brands is a more ambiguous and intangible assessment, its lack of significance may reflect Italian respondents discomfort with the metric. However, the significant interaction between brand fit and familiarity for the partner brand indicates that where familiarity with the partner brand is high, the Italian cohort did consider brand fit as important to co-brand perceptions. In contrast, UK respondents gave substantively more weight to the partner brand perceptions over the host in determining their view of the brand alliance; surprisingly, neither brand nor product fit influenced perceptions. These results suggest that if a respondent had a positive view of partner brands Lindt, Mentos, Mueller and Red Bull, and somewhat a positive view of the parent brands, the alliance would be viewed positively, regardless of whether the products and brands were considered a good match. These findings are substantively different from the results of Simonin and Ruth (1998) and Baumgarth (2004). One possible rationale for this is the ubiquity of new product introductions and brand alliance activity in the UK. In 2014, 3000 branded FMCG product ranges were launched in the UK. As a “high” indulgent society (see, UK respondents are more likely to be optimistic, impulsive and possess a “give it a go” attitude. These characteristics may translate into a more positive attitude toward brand alliances, regardless of fit.

5.2. Limitations and Future Research Directions

In summary, this study highlights interesting differences between countries in terms of brand alliance perceptions, and we believe is the first paper to consider the same brand alliance perceptions across two countries simultaneously. However, a number of limitations exist. Both surveys were conducted under conditions of high involvement so validity under low involvement is questionable. The brands selected were all well-known fast-moving consumer goods; future studies should explore less established brands and other product categories; The operationalization of fit was broad and does not take into account recent extensions to the fit construct (e.g. Bouten, Snelders and Hultink, 2011); The countries studied (UK, Italy) shared some similar cultural characteristics (individualism, masculinity, long-term orientation), future research should explore differences in brand alliance perceptions across countries with broader range of cultural characteristics. The difference in findings between the two samples highlights the need for more cross-cultural replication research on co-branding.


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Kingston Business School, United Kingdom

Kingston Business School, United Kingdom


Mark Anderson, Kingston Business School, London, Kingston upon Thames, United Kingdom

Article History

Received: July 18, 2015
Accepted: October 1, 2015
Available Online: October 11, 2015

Cite Reference

Anderson, M. and Martins Da Silva, P., 2015. Evaluations of Co-Brands: a Two-Country Comparison. Expert Journal of Marketing, 3(2), pp. 51-61

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