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The owner's edge: Brand ownership influences causal maps
Journal of Business Research 62 (2009) 339–344
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Journal of Business Research
The owner's edge: Brand ownership influences causal maps Johan van Rekom a,⁎, Peeter W.J. Verlegh b,1, Robert Slokkers c,2 a b c
Department of Marketing Management, Room T10-18, Rotterdam School of Management, Erasmus University Rotterdam, P.O. Box 1738, 3000 DR, The Netherlands Department of Marketing Management, Room T10-14, Rotterdam School of Management, Erasmus University Rotterdam, P.O. Box 1738, 3000 DR, The Netherlands LogiMark, Van Gijnstraat 17, 2288 GB Rijswijk, The Netherlands
A R T I C L E
I N F O
Article history: Received 1 May 2007 Received in revised form 1 February 2008 Accepted 1 June 2008 Keywords: Brand maps Cognitive structure Expertise Ownership Snowboards
A B S T R A C T Understanding the coherence between the attributes of a brand is a key asset for marketers managing brand equity. This study proposes consumer causal maps as a powerful instrument to achieve this purpose. These maps shed light on how different consumer groups think about the brand. Compared to non-owners, brand owners have been able to develop more expertise regarding the specific brand, which leads them to have more extensive causal maps. An exception occurs for the category leader, for which owners and non-owners have equally extensive maps. The surprising finding of this study is that the leading brand seems to encompass the ingredients for the causal maps of the other brands in the category. The results highlight how management should address owners and non-owners differently, in particular if a brand is far from category leadership. © 2008 Elsevier Inc. All rights reserved.
1. Introduction To achieve a favorable position in consumers' minds, brands distinguish themselves on attributes that are relevant to their customers or target groups. Marketers should not address brand attributes in isolation but rather look at the entire network of attributes (Keller, 2003; John, Loken, Kim and Monga, 2006). This helps them to create a coherent set of brand attributes that positively differentiates a brand from its competitors. To some extent, marketers can manage consumer perceptions of a brand's attributes and their interrelations. However, consumers continuously interact with the brand and reflect on it. Insight into consumer perceptions of the networks of brand attributes is therefore of utmost importance. Understanding the pattern of relations between associations helps marketers come to grips with and capitalize upon their brand equity (Keller, 2003). Cognitive maps form a key instrument for this purpose. They help managers gain insight into how brand associations imply others. Such maps not only convey important brand associations (like the more traditional associative networks maps — cf. John et al., 2006), but also show how associations are connected with each other. Murphy and Medin (1985) argue that connections between elements of a belief structure often constitute causal relations. Causal accounts are particularly compelling as explanations (Keil, 2006). The vast majority
⁎ Corresponding author. Tel.: +31 104081967; fax: +31 104089011. E-mail addresses: [email protected] (J. van Rekom), [email protected] (P.W.J. Verlegh), [email protected] (R. Slokkers). 1 Tel.: +31 104082732. 2 Tel.: +31 703070684. 0148-2963/$ – see front matter © 2008 Elsevier Inc. All rights reserved. doi:10.1016/j.jbusres.2008.06.007
of humans' everyday explanations involve notions of cause and effect, and when an explanation contains both causal and non-causal elements, the causal ones tend to dominate patterns of judgment (Murphy and Medin, 1985; Keil, 2006). Causal maps are efficient means of organizing and understanding consumer worlds (Anderson, Lepper and Ross, 1980; Chater and Oaksford, 2006), and thus offer a more focused instrument than general associational maps. Cognitive maps, thus, offer particularly useful insight to marketers. They are helpful in understanding how consumers think, and in identifying consumer core associations. Centrality in such a structure points to the features that are most pivotal to the overall brand image (Henderson, Iacobucci and Calder, 1998). These most essential features drive brand image (John et al., 2006), and play a crucial role in creating and maintaining brand equity (De Chernatony, 2001). Causal maps show how brand features depend upon each other, and point to those features that make the brand what it is — in other words, its essence (Van Rekom, Jacobs and Verlegh, 2006). Unfortunately, methods for producing brand maps have been slow to emerge (John et al., 2006). The dominant stream of research still focuses on associative networks (Loken, 2006). Causal brand maps are only a recent phenomenon (see Van Rekom et al., 2006), which suggests that scholars and practitioners have been underutilizing a potentially very insightful research instrument. The current study contributes to this emerging literature by being the first to compare causal maps for multiple brands in a category. In addition, this study compares causal maps of brand owners to those of non-owners, which is the basis for important consumer insights, as well as examining the role of consumer characteristics (i.e., brand ownership) in determining these maps. Brand ownership affects consumers' knowledge and understanding of a brand. Using the brand allows consumers to learn about it, and
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increasing complexity of the consumer cognitive structure regarding that brand's attributes.
develop a deeper understanding of the relationships among a brand's attributes (Alba and Hutchinson, 1987). The main question of this study is how brand ownership affects causal maps of brands. This study reviews the extant literature on the effect of consumer expertise on cognitive structure, develops hypotheses and tests those in an empirical study.
H2. The more skilled respondents are in performing the productrelated tasks successfully, the more elaborate their causal maps of the brand will be.
2. The relation between brand ownership and cognitive structures
3. Methods
The amount, content and organization of product knowledge differ greatly between experts and novices (Mitchell and Dacin, 1996). Experience plays an important role in the development of cognitive structures (Zinkhan and Braunsberger, 2004). Brand owners are likely to differ from non-owners in terms of a greater liking, familiarity and involvement with the brand (Kirmani, Sood and Bridges, 1999). In this way, brand owners are in a favorable starting position to become brand experts, and the differences between brand owners and nonowners are likely to resemble the differences between experts and novices. What effects does this have on their cognitive structures? First of all, experience leads to stronger brand associations and richer cognitive structures (Kirmani et al., 1999). John et al. (2006) find that consumers who are more familiar with a brand have brand maps with more associations, more relationships, and more indirect links between these associations. Motorcycle experts store attribute information about brands and models of motorcycles at more concrete levels than novices (Mitchell and Dacin, 1996). They often have very complex linkages in their cognitive maps. Because experts believe they know “how things work”, they are much less likely to engage in comparisons between brands, and focus more on one brand. For instance, Mitchell and Dacin's (1996) experts make much fewer itemby-item comparisons of individual motorcycle attributes. Comprehension differences arise because experts are able to perceive how the different attributes relate to each other (Alba and Hutchinson, 1987). By consequence, experts are more likely to elaborate on newlylearned information and connect new facts to previously learned facts. As the knowledge within their cognitive structures is more interconnected, experts are better able to understand how physical attributes of a motorcycle relate to performance (Mitchell and Dacin, 1996). This latter argument suggests that the key distinction between experts and novices may be in understanding the causal relations between attributes and performance. This argument is in line with the aforementioned dominance of causal relations in human thinking (Murphy and Medin, 1985; Keil, 2006) and Ahn's (1998) argument that the key to understanding how people think about categories, and by extension brands, is the understanding of the pattern of causal relations between their features. Although these authors provide ample support for the notion that cognitive structures for brands are richer and more integrated for experts than for novices, this notion has not been studied in the notion of causal structures. Research so far has only focused on associational structures in general, in spite of John et al.'s (2006) call to delve deeper into the nature of these relationships. This study will test the hypothesis that brand owners have a more developed causal structure.
Snowboard brands provide the field for testing the hypotheses. Snowboarding is a relatively young industry, with sufficient variation between more and less established brands. Snowboarding has such an appeal to part of the population (Howe, 1998) that a reasonable number of “experts” is likely to arise, which can be contrasted with a sufficient number of non-experts. Moreover, in a flat and snowless country like the Netherlands, the population of snowboarders has little other choice than using a very limited number of indoor sports centers, which facilitates reaching a representative part of the snowboarding population. The purpose of this empirical research project is to establish the causal maps of owners and non-owners of snowboard brands and test hypotheses concerning these maps. Although in the past sometimes the Kelly Repertory Grid has served to infer implicit causal structures (Fransella, Bell and Bannister, 2004), and Sirsi et al. (1996) built a group cognitive map using extensive qualitative interviews, the only method that focuses on directly establishing and comparing individual's causal maps is Van Rekom et al.'s (2006) two-phase method of assessing causal structure. A first qualitative research phase is necessary to establish the features of snowboard brands that are relevant to this population. The outcomes of this first phase serve as an input into the quantitative questionnaire which allows for testing hypotheses 1 and 2. The first research phase consists of interviewing fifty snowboarders at a large and well-known indoor sports center in the Netherlands. This center is one of the most popular national venues for snowboarding. The company reports 1.2 million visitors per year. The interviews take place in the main lobby and in the restaurant of the venue, and last about 5 min. Respondents indicate which brands they know on a list of brands available in the Netherlands. They then mention those characteristics that come up first for each of the brands. The four best-known brands are Burton, recognized by all 50 respondents, Forum, recognized by 38, and Nitro and Salomon, both recognized by 34 respondents. The characteristics that come up most often were, in descending order of mentions, “high quality” (47 mentions), “hardcore” (29 mentions), “strong image” (26), “cool” (21), “trendy” (14), “strong boards” (13), “beautiful” (13), “value for money” (13) and “innovative” (12 mentions). This procedure gives the four best-known brands and the nine most widely recognized features. Because the second research phase must establish the complete causal structure between them, adopting more features or more brands might make the questionnaire for the subsequent phase too lengthy. This second phase consists of a survey among 200 snowboarders. Again, indoor sport centers provide effective access to the snowboarding population, taking full advantage of the strengths of intercept interviews in controlling self-selection bias. The interviewers approach snowboarders at the entrance in the same sports center as the pretest, and in a competing center. Visitors randomly receive one of the four versions (one for each brand). They fill out the questionnaires in the presence of the interviewer, who is available all the time for clarifications. On average, respondents take about 20 min to complete the questionnaire. First, respondents rate the importance of each of the nine attributes important on a seven-point scale, ranging from 1 = completely unimportant to 7 = very important. Next, respondents indicate to what extent each of the nine attributes applies to each of the four brands on a seven-point scale, ranging from 1 = does not apply at all to
H1. If respondents own a brand, or have owned the brand in the past, their causal structure regarding that brand is more elaborate than if they have never owned that brand. So far, discussion has focused on ownership as source of expertise. Although ownership may represent an important aspect of expertise, the owner should also be successful in acquiring the skills to be a successful user of the product — which is the original way Alba and Hutchinson (1987) defined “expertise”. Usage skill may result in a further elaboration of a consumer causal structure, on top of ownership alone. Both factors contribute to the more intense experience with a brand. Therefore, both should contribute to an
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Fig. 1. The causal structures for each of the brand-ownership combinations.
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7 = applies completely. The remaining part of the questionnaire is brand-specific for Burton, Forum, Nitro or Salomon. The identification of the causal structure among these nine brand attributes relies upon the method developed by Van Rekom et al. Van Rekom et al. (2006), and the questionnaire follows their model. The questionnaire includes nine pages, one for each attribute, on which consumers rate their perception of the relations between that attribute and the other eight. The order is randomized. Each page contains eight statements like this: Burton is [attribute A], because Burton is [attribute B]. For example, the page for the feature “Cool” includes eight statements like “Burton is cool because Burton is hardcore”. For each combination, respondents indicate whether the suggested causal relation is correct (coded as “1”), whether no connection exists between the proposed cause and effect (coded as “0”), or whether the proposed cause inhibits rather than causes the effect (coded as “−1”). Then, for each respondent, each attribute's causal status is the straightforward sum of all the ratings that respondent gives to the relations where that attribute is suggested as the cause. A validity check on this relatively new method would be desirable. In their detergent study, Van Rekom et al. (2006) find a substantial correlation (0.49, p b 0.001) between the degree to which an attribute caused other attributes and that attribute's perceived necessity. Replication of their research in this completely different context would provide an interesting validity check on the method. Respondents answered the question: “Would Burton still be Burton if this attribute was lacking?” on a seven-point scale, ranging from 1 (yes, it is still absolutely Burton) to 7 (no, it is no longer Burton). A higher score means that a feature is more essential to the brand. Michel and Ambler (1999) propose this scale as a direct measure of brand essence. Finally, respondents indicate their snowboarding skills on a sevenpoint scale (“1” = novice, “7” = professional) and they indicate what brand of snowboard they currently have, what brand they had before, and their age and gender. The computation of a new variable, “ownership” serves to trace the effects of ownership on cognitive structure. A value of “1” for this variable implies that the respondent owns or has owned that brand, and a value of “0” implies, that the respondent never owned the brand. The final step involves the calculation of the measure of cognitive complexity for each respondent, by counting the total number of non-zero relations in a respondent's causal matrix. 4. Results The left pane of Fig. 1 shows the causal structures for respondents who never owned a snowboard of the respective brand. The right pane shows the structures for those who own or have owned the brand (henceforth the “owners”). These maps build upon the average ratings for each possible causal relation, applying a cut-off point of 0.60, which implies that the figures only show relations with which at least 60% of the respondents agree. The selection of a reasonable cut-off point keeps the figures informative, and follows recommenTable 1 Regression coefficients for elaboration of causal brand maps Independent variables
Constant
Snowboarding skills
R2
Burton Forum Nitro Salomon
Non-owners
Owners
0.45 0.62 0.72 0.73
0.57 0.66 0.60 0.77
All correlations are significant at p b 0.001.
dations of Van Rekom et al. (2006). Fig. 1 shows an overall pattern with a striking exception: in all cases, the owners' cognitive structures contain more relations and more attributes, except for Burton. The top panes of Fig. 1 show how the non-owners' structure includes one more attribute than the Burton owners' – “hardcore”, on top – and more causal relations. Fig. 1 suggests heterogeneity between brands. Therefore, for each brand a separate regression serves to test Hypotheses 1 and 2. The bottom row of Table 1 shows the overall significance, calculated according to Rosenthal's (1991) principles for calculating overall effects. Ownership is paired with increased complexity of causal structures. This finding supports H1, although the effect varies strongly by brand. The effect is significant for Salomon and Forum, for which owners on average distinguish 7 (Forum) or 8 (Salomon) causal relations more than non-owners. For Nitro the difference is equal to four, which is still considerable, but no longer significant. For Burton, the difference almost disappeared. The test of hypothesis 2 turns out more homogeneous across the four brands. Contrary to the second hypothesis, an increase in snowboarding skills is paired with a decrease in the complexity of cognitive structure: One scale point increase in snowboarding skills on average corresponds to 2.5 less causal relations. The lower row in Table 1 shows that the overall effect size is significant at p = 0.001. Effect sizes do not differ by brand (χ2(3) = 0.68, p = 0.88, see Rosenthal, 1991: 74). These cognitive structures help identify the pivotal elements in respondents' causal structures. Each respondent has rated each brand attribute on both the total number of other features the attribute causes and its perceived necessity. These ratings allow for computing for each respondent a correlation between the nine features' causal status and their perceived necessity (Van Rekom et al., 2006). Rosenthal (1991) suggest subjecting these correlations to a Fisher-Z transformation in order to arrive at an average correlation across all respondents. Retransforming the average Fisher-Z value into the corresponding correlation coefficient gives a group-level correlation coefficient (Rosenthal, 1991). Table 2 shows, how for each of the eight groups of Fig. 1 these overall correlations range from 0.45 for the nonowners of Burton to 0.77 for the owners of Salomon. All coefficients are significant (p b .001).Using a similar method Van Rekom et al. (2006) obtain a correlation coefficient of 0.49. Table 2 also extends to their results. Whereas Van Rekom et al. (2006) limit themselves to brand-customers, this study shows that this principle holds for noncustomers as well. The replication of their positive correlation points to the validity of the causal structures in this research, and shows that causal structures indeed help trace the pivotal elements in respondents' cognitive representations of the brand. 5. Discussion
Brand Burton Forum Nitro Salomon Overall effect sizea
Ownership
Table 2 Overall correlations between causal status and perceived necessity for each of the eight subgroups
44.3 30.0 32.4 24.4
ß raw
ß stand.
p
ß raw
ß stand.
p
−0.98 7.38 4.21 8.27 0.25
− 0.04 0.35 0.16 0.41 0.001
0.79 0.01 0.27 0.00
−2.73 −2.57 −2.21 −2.51 −.23
−0.25 −0.30 −0.16 −0.27 0.001
0.11 0.03 0.25 0.04
0.07 0.17 0.06 0.24
Raw = raw regression coefficients, Stand. = standardized regression coefficients. a Overall effect sizes and significances have been calculated according to Rosenthal (1991: 19 and p. 87).
This is the first study to show that brand owners have more elaborate causal brand structures than non-owners. A notable exception is the leading brand in the industry, Burton, for which the impact of ownership appears negligible. This can be due to the dominant position of this brand in the market. Burton is the only brand which is familiar to 100% of respondents in the pretest (the other 3 brands are familiar to about 70% of respondents).
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Fig. 1 shows how the structure for Burton, for owners as well as for non-owners is richer than any other structure. Burton seems to be a good instance of a strongly category-dominant brand, enjoying widespread customer recognition and a substantial market share (Herr, Farquhar and Fazio, 1996). In other words, Burton appears to be the most prototypical of the four snowboard brands. Being prototypical is a typical advantage of successful first-to-market entrants (Carpenter and Nakamoto, 1989). Later entrants into a market will call to mind previous entrants. Consumers will then construct their representations of these later entrants with reference to the already existing brand (Zhang and Markman, 1998: 424). These results suggest that the more prototypical a brand, the more elaborate its causal structure. Conversely, a brand that is less prototypical for a category has fewer associations, and a larger difference between owners and non-owners. The relationship with the time of market entry for the respective brands is telling: Burton started in 1977 (Howe, 1998), and is the most prototypical brand. Nitro started in 1990, and Forum and Salomon entered the snowboard business only in 1997. The ranking of the entry in the market closely corresponds to the impact of ownership on causal structure, as indicated by the regression coefficients for ownership in Table 1. The less prototypical a brand is, the steeper the regression slope for ownership becomes. Fig. 1 shows how the causal maps of the other brands look like fragments of the more complete causal map of Burton. The conclusion seems warranted that its core associations dominate the category. A relation between cognitive structure and category structure is in line with the work of scholars who investigated the effect of order of market entrance on cognition. Carpenter and Nakamoto (1989) find that product ideals tend to follow the pioneering brand. Zhang and Markman (1998) argue that early entrant can maintain their positions if they remain superior to later entrants on important features. In such a situation later entrants will first be compared to the early entrant. Being the category prototype, a successful earlier entrant can continue to dominate the category. (cf., Rosa, Judson and Porac, 2005). The data suggest that Burton may be an example of a prototype that has managed to maintain its position. Indeed, Donnelly (2006) observes that founder/owner Jake Burton is often recognized as the inventor of contemporary snowboarding, and that this image in part explains the brand's 40% share in the international snowboarding market.
Fig. 2. Overall pattern of ratings of the four brands on the nine features.
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Table 3 Overall degree to which features are important and apply to each brand Importance
Quality Hardcore Image Cool Trendy Strong Beautiful Value for money Innovative
Degree to which attributes apply to each brand Burton
Forum
Nitro
Salomon
Mean (s.d)
Mean (s.d)
Mean (s.d)
Mean (s.d)
Mean (s.d)
6.69 (0.48) 3.53 (1.33) 4.47 (1.30) 3.93 (1.61) 3.10 (1.48) 6.27 (0.92) 5.38 (1.04) 5.94 (1.12) 5.34 (1.20)
6.43 (0.91) 5.28 (1.18) 6.79 (0.47) 5.95 (0.95) 5.71 (1.06) 6.15 (0.88) 6.11 (0.96) 5.34 (1.11) 6.47 (0.78)
5.09 (1.24) 6.14 (1.23) 5.41 (1.36) 5.90 (1.44) 5.75 (1.14) 5.00 (1.32) 5.62 (1.10) 4.15 (1.33) 5.25 (1.13)
5.45 (0.94) 4.68 (1.41) 5.07 (1.07) 5.18 (1.15) 4.69 (1.2) 5.50 (0.91) 5.46 (1.08) 5.40 (1.01) 4.71 (1.21)
5.93 (1.14) 3.23 (1.36) 4.33 (1.30) 3.47 (1.50) 3.45 (1.23) 5.93 (0.98) 4.47 (1.33) 5.30 (1.06) 4.80 (1.39)
The numbers in brackets represent standard deviations.
If this prototype effect holds, consumers should – in line with Carpenter and Nakamoto's argument – see the leading brand as providing superior performance on the attributes that matter to them. A closer look at the respondents' answers to the questions to what degree each of the nine features applied to each of the brands confirms this notion: Fig. 2 visualizes how Burton seems to incorporate a kind of category ideal: the solid line representing Burton is mostly on top. Burton is equal or superior on six out of nine attributes (Table 3). Only on “hardcore” and “trendy” is it outperformed by Forum, but the average importance ratings in Table 3 make clear that these were the two least important features, below the midpoint of the importance scale. Nitro outperforms Burton in “value for money”, but this difference is not significant (t = −0.66, p = 0.51). Fig. 2 shows the overall pattern. As any study, this research has its weaknesses. Proposing a complete matrix of associations may induce people to think up more relations than a research technique without any aid that could control for completeness (cf. Sirsi, Ward and Reingen, 1996). Even though the four interviewers monitored and motivated respondents, it is possible that some nay-saying has influenced ratings of some of the suggested relations, and that skilled snowboarders are significantly more critical about the proposed relationships. Such a process should not invalidate the findings, however. This study focuses on one product category only, which may lead to concerns about generalizability. Although the correlations in Table 2 are similar to those obtained by van Rekom et al. (2006) in a different product category (detergents), further replication is needed to generalize and establish these findings. The results point to promising opportunities for further research. This study uncovers an intriguing link between consumers' causal brand maps and the structure of the product category. The “prototype effect” provides an interesting avenue for further study. Future research may measure perceptions of prototypicality among consumers, and test whether these scores can explain the findings. A further opportunity would be to compare the causal structures of consumer representations of the respective brands with the discourse consumers and producers develop around the brands, in particular their introductions (cf. Rosa et al., 2005). Such a finding would show how such discourse crystallizes in consumer causal structures, and what it means for the development of the image of a brand. For managers, this study points to the rich possibilities of causal brand mapping. Fig. 1 highlights how causal structures differ between owners and non-owners, which implies that these consumers should be targeted quite differently. The contrast between the causal structures in Fig. 1 and the brand ratings in Fig. 2 is enlightening: A direct reliance on differences with competitors (in Fig. 2) might lead Burton to focus on “great image” as its major advantage over competitors, whereas the causal maps in Fig. 1 show that Burton's real edge is “innovativeness”, which positively affects many of the
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other attributes of the brand. Fig. 1 tells managers which features exactly depend upon “innovativeness”, in the eyes of different market segments. These concrete results offer a golden opportunity to tailor brand communication strategies to the needs of specific segments, while keeping an eye on the overall consistency of the brand concept. Fig. 1 also shows how brands should target owners and nonowners. It visualizes for instance the striking difference between nonowners and owners of Forum: non-owners think very abstractly about this brand, whereas owners relate it to more tangible properties. The results suggest that the discrepancy between owners and non-owners decreases with the brand's position in the category leadership. The maps themselves allow managers to build up refined marketing strategies, capitalizing on these insights in consumer reasoning. In sum, this study presents a revealing method to analyze how different groups think about brands. The most intriguing finding is that the causal structure of the most prototypical brand seems to provide a “mother structure” for other brands in the category. This finding should stimulate marketers to reflect on the position of their brand within consumers cognitive causal structures for the relevant product category. References Ahn WK. Why are different features central for natural kinds and artifacts?: the role of causal status in determining feature centrality. Cognition 1998;69(2):135–78. Alba Joseph W, Wesley Hutchinson J. Dimensions of consumer expertise. J Consum Res 1987;13(3):411–54. Anderson Craig A, Lepper Mark R, Ross Lee. Perseverance of social theories: the role of explanation in the persistence of discredited information. J Pers Soc Psychol 1980;39:1037–49 December. Carpenter Gregory S, Nakamoto Kent. Consumer preference formation and pioneering advantage. J Mark Res 1989;26:285–98 August. Chater Nick, Oaksford Mike. Mental mechanisms: speculations on human causal learning and reasoning. In: Fiedler K, Juslin P, editors. Information sampling and adaptive cognition. Cambridge: Cambridge University Press; 2006. p. 210–36. De Chernatony Leslie. From brand vision to brand evaluation. Strategically building and sustaining brands. Oxford: Butterworth Heinemann; 2001.
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Journal of Business Research
The owner's edge: Brand ownership influences causal maps Johan van Rekom a,⁎, Peeter W.J. Verlegh b,1, Robert Slokkers c,2 a b c
Department of Marketing Management, Room T10-18, Rotterdam School of Management, Erasmus University Rotterdam, P.O. Box 1738, 3000 DR, The Netherlands Department of Marketing Management, Room T10-14, Rotterdam School of Management, Erasmus University Rotterdam, P.O. Box 1738, 3000 DR, The Netherlands LogiMark, Van Gijnstraat 17, 2288 GB Rijswijk, The Netherlands
A R T I C L E
I N F O
Article history: Received 1 May 2007 Received in revised form 1 February 2008 Accepted 1 June 2008 Keywords: Brand maps Cognitive structure Expertise Ownership Snowboards
A B S T R A C T Understanding the coherence between the attributes of a brand is a key asset for marketers managing brand equity. This study proposes consumer causal maps as a powerful instrument to achieve this purpose. These maps shed light on how different consumer groups think about the brand. Compared to non-owners, brand owners have been able to develop more expertise regarding the specific brand, which leads them to have more extensive causal maps. An exception occurs for the category leader, for which owners and non-owners have equally extensive maps. The surprising finding of this study is that the leading brand seems to encompass the ingredients for the causal maps of the other brands in the category. The results highlight how management should address owners and non-owners differently, in particular if a brand is far from category leadership. © 2008 Elsevier Inc. All rights reserved.
1. Introduction To achieve a favorable position in consumers' minds, brands distinguish themselves on attributes that are relevant to their customers or target groups. Marketers should not address brand attributes in isolation but rather look at the entire network of attributes (Keller, 2003; John, Loken, Kim and Monga, 2006). This helps them to create a coherent set of brand attributes that positively differentiates a brand from its competitors. To some extent, marketers can manage consumer perceptions of a brand's attributes and their interrelations. However, consumers continuously interact with the brand and reflect on it. Insight into consumer perceptions of the networks of brand attributes is therefore of utmost importance. Understanding the pattern of relations between associations helps marketers come to grips with and capitalize upon their brand equity (Keller, 2003). Cognitive maps form a key instrument for this purpose. They help managers gain insight into how brand associations imply others. Such maps not only convey important brand associations (like the more traditional associative networks maps — cf. John et al., 2006), but also show how associations are connected with each other. Murphy and Medin (1985) argue that connections between elements of a belief structure often constitute causal relations. Causal accounts are particularly compelling as explanations (Keil, 2006). The vast majority
⁎ Corresponding author. Tel.: +31 104081967; fax: +31 104089011. E-mail addresses: [email protected] (J. van Rekom), [email protected] (P.W.J. Verlegh), [email protected] (R. Slokkers). 1 Tel.: +31 104082732. 2 Tel.: +31 703070684. 0148-2963/$ – see front matter © 2008 Elsevier Inc. All rights reserved. doi:10.1016/j.jbusres.2008.06.007
of humans' everyday explanations involve notions of cause and effect, and when an explanation contains both causal and non-causal elements, the causal ones tend to dominate patterns of judgment (Murphy and Medin, 1985; Keil, 2006). Causal maps are efficient means of organizing and understanding consumer worlds (Anderson, Lepper and Ross, 1980; Chater and Oaksford, 2006), and thus offer a more focused instrument than general associational maps. Cognitive maps, thus, offer particularly useful insight to marketers. They are helpful in understanding how consumers think, and in identifying consumer core associations. Centrality in such a structure points to the features that are most pivotal to the overall brand image (Henderson, Iacobucci and Calder, 1998). These most essential features drive brand image (John et al., 2006), and play a crucial role in creating and maintaining brand equity (De Chernatony, 2001). Causal maps show how brand features depend upon each other, and point to those features that make the brand what it is — in other words, its essence (Van Rekom, Jacobs and Verlegh, 2006). Unfortunately, methods for producing brand maps have been slow to emerge (John et al., 2006). The dominant stream of research still focuses on associative networks (Loken, 2006). Causal brand maps are only a recent phenomenon (see Van Rekom et al., 2006), which suggests that scholars and practitioners have been underutilizing a potentially very insightful research instrument. The current study contributes to this emerging literature by being the first to compare causal maps for multiple brands in a category. In addition, this study compares causal maps of brand owners to those of non-owners, which is the basis for important consumer insights, as well as examining the role of consumer characteristics (i.e., brand ownership) in determining these maps. Brand ownership affects consumers' knowledge and understanding of a brand. Using the brand allows consumers to learn about it, and
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increasing complexity of the consumer cognitive structure regarding that brand's attributes.
develop a deeper understanding of the relationships among a brand's attributes (Alba and Hutchinson, 1987). The main question of this study is how brand ownership affects causal maps of brands. This study reviews the extant literature on the effect of consumer expertise on cognitive structure, develops hypotheses and tests those in an empirical study.
H2. The more skilled respondents are in performing the productrelated tasks successfully, the more elaborate their causal maps of the brand will be.
2. The relation between brand ownership and cognitive structures
3. Methods
The amount, content and organization of product knowledge differ greatly between experts and novices (Mitchell and Dacin, 1996). Experience plays an important role in the development of cognitive structures (Zinkhan and Braunsberger, 2004). Brand owners are likely to differ from non-owners in terms of a greater liking, familiarity and involvement with the brand (Kirmani, Sood and Bridges, 1999). In this way, brand owners are in a favorable starting position to become brand experts, and the differences between brand owners and nonowners are likely to resemble the differences between experts and novices. What effects does this have on their cognitive structures? First of all, experience leads to stronger brand associations and richer cognitive structures (Kirmani et al., 1999). John et al. (2006) find that consumers who are more familiar with a brand have brand maps with more associations, more relationships, and more indirect links between these associations. Motorcycle experts store attribute information about brands and models of motorcycles at more concrete levels than novices (Mitchell and Dacin, 1996). They often have very complex linkages in their cognitive maps. Because experts believe they know “how things work”, they are much less likely to engage in comparisons between brands, and focus more on one brand. For instance, Mitchell and Dacin's (1996) experts make much fewer itemby-item comparisons of individual motorcycle attributes. Comprehension differences arise because experts are able to perceive how the different attributes relate to each other (Alba and Hutchinson, 1987). By consequence, experts are more likely to elaborate on newlylearned information and connect new facts to previously learned facts. As the knowledge within their cognitive structures is more interconnected, experts are better able to understand how physical attributes of a motorcycle relate to performance (Mitchell and Dacin, 1996). This latter argument suggests that the key distinction between experts and novices may be in understanding the causal relations between attributes and performance. This argument is in line with the aforementioned dominance of causal relations in human thinking (Murphy and Medin, 1985; Keil, 2006) and Ahn's (1998) argument that the key to understanding how people think about categories, and by extension brands, is the understanding of the pattern of causal relations between their features. Although these authors provide ample support for the notion that cognitive structures for brands are richer and more integrated for experts than for novices, this notion has not been studied in the notion of causal structures. Research so far has only focused on associational structures in general, in spite of John et al.'s (2006) call to delve deeper into the nature of these relationships. This study will test the hypothesis that brand owners have a more developed causal structure.
Snowboard brands provide the field for testing the hypotheses. Snowboarding is a relatively young industry, with sufficient variation between more and less established brands. Snowboarding has such an appeal to part of the population (Howe, 1998) that a reasonable number of “experts” is likely to arise, which can be contrasted with a sufficient number of non-experts. Moreover, in a flat and snowless country like the Netherlands, the population of snowboarders has little other choice than using a very limited number of indoor sports centers, which facilitates reaching a representative part of the snowboarding population. The purpose of this empirical research project is to establish the causal maps of owners and non-owners of snowboard brands and test hypotheses concerning these maps. Although in the past sometimes the Kelly Repertory Grid has served to infer implicit causal structures (Fransella, Bell and Bannister, 2004), and Sirsi et al. (1996) built a group cognitive map using extensive qualitative interviews, the only method that focuses on directly establishing and comparing individual's causal maps is Van Rekom et al.'s (2006) two-phase method of assessing causal structure. A first qualitative research phase is necessary to establish the features of snowboard brands that are relevant to this population. The outcomes of this first phase serve as an input into the quantitative questionnaire which allows for testing hypotheses 1 and 2. The first research phase consists of interviewing fifty snowboarders at a large and well-known indoor sports center in the Netherlands. This center is one of the most popular national venues for snowboarding. The company reports 1.2 million visitors per year. The interviews take place in the main lobby and in the restaurant of the venue, and last about 5 min. Respondents indicate which brands they know on a list of brands available in the Netherlands. They then mention those characteristics that come up first for each of the brands. The four best-known brands are Burton, recognized by all 50 respondents, Forum, recognized by 38, and Nitro and Salomon, both recognized by 34 respondents. The characteristics that come up most often were, in descending order of mentions, “high quality” (47 mentions), “hardcore” (29 mentions), “strong image” (26), “cool” (21), “trendy” (14), “strong boards” (13), “beautiful” (13), “value for money” (13) and “innovative” (12 mentions). This procedure gives the four best-known brands and the nine most widely recognized features. Because the second research phase must establish the complete causal structure between them, adopting more features or more brands might make the questionnaire for the subsequent phase too lengthy. This second phase consists of a survey among 200 snowboarders. Again, indoor sport centers provide effective access to the snowboarding population, taking full advantage of the strengths of intercept interviews in controlling self-selection bias. The interviewers approach snowboarders at the entrance in the same sports center as the pretest, and in a competing center. Visitors randomly receive one of the four versions (one for each brand). They fill out the questionnaires in the presence of the interviewer, who is available all the time for clarifications. On average, respondents take about 20 min to complete the questionnaire. First, respondents rate the importance of each of the nine attributes important on a seven-point scale, ranging from 1 = completely unimportant to 7 = very important. Next, respondents indicate to what extent each of the nine attributes applies to each of the four brands on a seven-point scale, ranging from 1 = does not apply at all to
H1. If respondents own a brand, or have owned the brand in the past, their causal structure regarding that brand is more elaborate than if they have never owned that brand. So far, discussion has focused on ownership as source of expertise. Although ownership may represent an important aspect of expertise, the owner should also be successful in acquiring the skills to be a successful user of the product — which is the original way Alba and Hutchinson (1987) defined “expertise”. Usage skill may result in a further elaboration of a consumer causal structure, on top of ownership alone. Both factors contribute to the more intense experience with a brand. Therefore, both should contribute to an
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Fig. 1. The causal structures for each of the brand-ownership combinations.
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7 = applies completely. The remaining part of the questionnaire is brand-specific for Burton, Forum, Nitro or Salomon. The identification of the causal structure among these nine brand attributes relies upon the method developed by Van Rekom et al. Van Rekom et al. (2006), and the questionnaire follows their model. The questionnaire includes nine pages, one for each attribute, on which consumers rate their perception of the relations between that attribute and the other eight. The order is randomized. Each page contains eight statements like this: Burton is [attribute A], because Burton is [attribute B]. For example, the page for the feature “Cool” includes eight statements like “Burton is cool because Burton is hardcore”. For each combination, respondents indicate whether the suggested causal relation is correct (coded as “1”), whether no connection exists between the proposed cause and effect (coded as “0”), or whether the proposed cause inhibits rather than causes the effect (coded as “−1”). Then, for each respondent, each attribute's causal status is the straightforward sum of all the ratings that respondent gives to the relations where that attribute is suggested as the cause. A validity check on this relatively new method would be desirable. In their detergent study, Van Rekom et al. (2006) find a substantial correlation (0.49, p b 0.001) between the degree to which an attribute caused other attributes and that attribute's perceived necessity. Replication of their research in this completely different context would provide an interesting validity check on the method. Respondents answered the question: “Would Burton still be Burton if this attribute was lacking?” on a seven-point scale, ranging from 1 (yes, it is still absolutely Burton) to 7 (no, it is no longer Burton). A higher score means that a feature is more essential to the brand. Michel and Ambler (1999) propose this scale as a direct measure of brand essence. Finally, respondents indicate their snowboarding skills on a sevenpoint scale (“1” = novice, “7” = professional) and they indicate what brand of snowboard they currently have, what brand they had before, and their age and gender. The computation of a new variable, “ownership” serves to trace the effects of ownership on cognitive structure. A value of “1” for this variable implies that the respondent owns or has owned that brand, and a value of “0” implies, that the respondent never owned the brand. The final step involves the calculation of the measure of cognitive complexity for each respondent, by counting the total number of non-zero relations in a respondent's causal matrix. 4. Results The left pane of Fig. 1 shows the causal structures for respondents who never owned a snowboard of the respective brand. The right pane shows the structures for those who own or have owned the brand (henceforth the “owners”). These maps build upon the average ratings for each possible causal relation, applying a cut-off point of 0.60, which implies that the figures only show relations with which at least 60% of the respondents agree. The selection of a reasonable cut-off point keeps the figures informative, and follows recommenTable 1 Regression coefficients for elaboration of causal brand maps Independent variables
Constant
Snowboarding skills
R2
Burton Forum Nitro Salomon
Non-owners
Owners
0.45 0.62 0.72 0.73
0.57 0.66 0.60 0.77
All correlations are significant at p b 0.001.
dations of Van Rekom et al. (2006). Fig. 1 shows an overall pattern with a striking exception: in all cases, the owners' cognitive structures contain more relations and more attributes, except for Burton. The top panes of Fig. 1 show how the non-owners' structure includes one more attribute than the Burton owners' – “hardcore”, on top – and more causal relations. Fig. 1 suggests heterogeneity between brands. Therefore, for each brand a separate regression serves to test Hypotheses 1 and 2. The bottom row of Table 1 shows the overall significance, calculated according to Rosenthal's (1991) principles for calculating overall effects. Ownership is paired with increased complexity of causal structures. This finding supports H1, although the effect varies strongly by brand. The effect is significant for Salomon and Forum, for which owners on average distinguish 7 (Forum) or 8 (Salomon) causal relations more than non-owners. For Nitro the difference is equal to four, which is still considerable, but no longer significant. For Burton, the difference almost disappeared. The test of hypothesis 2 turns out more homogeneous across the four brands. Contrary to the second hypothesis, an increase in snowboarding skills is paired with a decrease in the complexity of cognitive structure: One scale point increase in snowboarding skills on average corresponds to 2.5 less causal relations. The lower row in Table 1 shows that the overall effect size is significant at p = 0.001. Effect sizes do not differ by brand (χ2(3) = 0.68, p = 0.88, see Rosenthal, 1991: 74). These cognitive structures help identify the pivotal elements in respondents' causal structures. Each respondent has rated each brand attribute on both the total number of other features the attribute causes and its perceived necessity. These ratings allow for computing for each respondent a correlation between the nine features' causal status and their perceived necessity (Van Rekom et al., 2006). Rosenthal (1991) suggest subjecting these correlations to a Fisher-Z transformation in order to arrive at an average correlation across all respondents. Retransforming the average Fisher-Z value into the corresponding correlation coefficient gives a group-level correlation coefficient (Rosenthal, 1991). Table 2 shows, how for each of the eight groups of Fig. 1 these overall correlations range from 0.45 for the nonowners of Burton to 0.77 for the owners of Salomon. All coefficients are significant (p b .001).Using a similar method Van Rekom et al. (2006) obtain a correlation coefficient of 0.49. Table 2 also extends to their results. Whereas Van Rekom et al. (2006) limit themselves to brand-customers, this study shows that this principle holds for noncustomers as well. The replication of their positive correlation points to the validity of the causal structures in this research, and shows that causal structures indeed help trace the pivotal elements in respondents' cognitive representations of the brand. 5. Discussion
Brand Burton Forum Nitro Salomon Overall effect sizea
Ownership
Table 2 Overall correlations between causal status and perceived necessity for each of the eight subgroups
44.3 30.0 32.4 24.4
ß raw
ß stand.
p
ß raw
ß stand.
p
−0.98 7.38 4.21 8.27 0.25
− 0.04 0.35 0.16 0.41 0.001
0.79 0.01 0.27 0.00
−2.73 −2.57 −2.21 −2.51 −.23
−0.25 −0.30 −0.16 −0.27 0.001
0.11 0.03 0.25 0.04
0.07 0.17 0.06 0.24
Raw = raw regression coefficients, Stand. = standardized regression coefficients. a Overall effect sizes and significances have been calculated according to Rosenthal (1991: 19 and p. 87).
This is the first study to show that brand owners have more elaborate causal brand structures than non-owners. A notable exception is the leading brand in the industry, Burton, for which the impact of ownership appears negligible. This can be due to the dominant position of this brand in the market. Burton is the only brand which is familiar to 100% of respondents in the pretest (the other 3 brands are familiar to about 70% of respondents).
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Fig. 1 shows how the structure for Burton, for owners as well as for non-owners is richer than any other structure. Burton seems to be a good instance of a strongly category-dominant brand, enjoying widespread customer recognition and a substantial market share (Herr, Farquhar and Fazio, 1996). In other words, Burton appears to be the most prototypical of the four snowboard brands. Being prototypical is a typical advantage of successful first-to-market entrants (Carpenter and Nakamoto, 1989). Later entrants into a market will call to mind previous entrants. Consumers will then construct their representations of these later entrants with reference to the already existing brand (Zhang and Markman, 1998: 424). These results suggest that the more prototypical a brand, the more elaborate its causal structure. Conversely, a brand that is less prototypical for a category has fewer associations, and a larger difference between owners and non-owners. The relationship with the time of market entry for the respective brands is telling: Burton started in 1977 (Howe, 1998), and is the most prototypical brand. Nitro started in 1990, and Forum and Salomon entered the snowboard business only in 1997. The ranking of the entry in the market closely corresponds to the impact of ownership on causal structure, as indicated by the regression coefficients for ownership in Table 1. The less prototypical a brand is, the steeper the regression slope for ownership becomes. Fig. 1 shows how the causal maps of the other brands look like fragments of the more complete causal map of Burton. The conclusion seems warranted that its core associations dominate the category. A relation between cognitive structure and category structure is in line with the work of scholars who investigated the effect of order of market entrance on cognition. Carpenter and Nakamoto (1989) find that product ideals tend to follow the pioneering brand. Zhang and Markman (1998) argue that early entrant can maintain their positions if they remain superior to later entrants on important features. In such a situation later entrants will first be compared to the early entrant. Being the category prototype, a successful earlier entrant can continue to dominate the category. (cf., Rosa, Judson and Porac, 2005). The data suggest that Burton may be an example of a prototype that has managed to maintain its position. Indeed, Donnelly (2006) observes that founder/owner Jake Burton is often recognized as the inventor of contemporary snowboarding, and that this image in part explains the brand's 40% share in the international snowboarding market.
Fig. 2. Overall pattern of ratings of the four brands on the nine features.
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Table 3 Overall degree to which features are important and apply to each brand Importance
Quality Hardcore Image Cool Trendy Strong Beautiful Value for money Innovative
Degree to which attributes apply to each brand Burton
Forum
Nitro
Salomon
Mean (s.d)
Mean (s.d)
Mean (s.d)
Mean (s.d)
Mean (s.d)
6.69 (0.48) 3.53 (1.33) 4.47 (1.30) 3.93 (1.61) 3.10 (1.48) 6.27 (0.92) 5.38 (1.04) 5.94 (1.12) 5.34 (1.20)
6.43 (0.91) 5.28 (1.18) 6.79 (0.47) 5.95 (0.95) 5.71 (1.06) 6.15 (0.88) 6.11 (0.96) 5.34 (1.11) 6.47 (0.78)
5.09 (1.24) 6.14 (1.23) 5.41 (1.36) 5.90 (1.44) 5.75 (1.14) 5.00 (1.32) 5.62 (1.10) 4.15 (1.33) 5.25 (1.13)
5.45 (0.94) 4.68 (1.41) 5.07 (1.07) 5.18 (1.15) 4.69 (1.2) 5.50 (0.91) 5.46 (1.08) 5.40 (1.01) 4.71 (1.21)
5.93 (1.14) 3.23 (1.36) 4.33 (1.30) 3.47 (1.50) 3.45 (1.23) 5.93 (0.98) 4.47 (1.33) 5.30 (1.06) 4.80 (1.39)
The numbers in brackets represent standard deviations.
If this prototype effect holds, consumers should – in line with Carpenter and Nakamoto's argument – see the leading brand as providing superior performance on the attributes that matter to them. A closer look at the respondents' answers to the questions to what degree each of the nine features applied to each of the brands confirms this notion: Fig. 2 visualizes how Burton seems to incorporate a kind of category ideal: the solid line representing Burton is mostly on top. Burton is equal or superior on six out of nine attributes (Table 3). Only on “hardcore” and “trendy” is it outperformed by Forum, but the average importance ratings in Table 3 make clear that these were the two least important features, below the midpoint of the importance scale. Nitro outperforms Burton in “value for money”, but this difference is not significant (t = −0.66, p = 0.51). Fig. 2 shows the overall pattern. As any study, this research has its weaknesses. Proposing a complete matrix of associations may induce people to think up more relations than a research technique without any aid that could control for completeness (cf. Sirsi, Ward and Reingen, 1996). Even though the four interviewers monitored and motivated respondents, it is possible that some nay-saying has influenced ratings of some of the suggested relations, and that skilled snowboarders are significantly more critical about the proposed relationships. Such a process should not invalidate the findings, however. This study focuses on one product category only, which may lead to concerns about generalizability. Although the correlations in Table 2 are similar to those obtained by van Rekom et al. (2006) in a different product category (detergents), further replication is needed to generalize and establish these findings. The results point to promising opportunities for further research. This study uncovers an intriguing link between consumers' causal brand maps and the structure of the product category. The “prototype effect” provides an interesting avenue for further study. Future research may measure perceptions of prototypicality among consumers, and test whether these scores can explain the findings. A further opportunity would be to compare the causal structures of consumer representations of the respective brands with the discourse consumers and producers develop around the brands, in particular their introductions (cf. Rosa et al., 2005). Such a finding would show how such discourse crystallizes in consumer causal structures, and what it means for the development of the image of a brand. For managers, this study points to the rich possibilities of causal brand mapping. Fig. 1 highlights how causal structures differ between owners and non-owners, which implies that these consumers should be targeted quite differently. The contrast between the causal structures in Fig. 1 and the brand ratings in Fig. 2 is enlightening: A direct reliance on differences with competitors (in Fig. 2) might lead Burton to focus on “great image” as its major advantage over competitors, whereas the causal maps in Fig. 1 show that Burton's real edge is “innovativeness”, which positively affects many of the
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other attributes of the brand. Fig. 1 tells managers which features exactly depend upon “innovativeness”, in the eyes of different market segments. These concrete results offer a golden opportunity to tailor brand communication strategies to the needs of specific segments, while keeping an eye on the overall consistency of the brand concept. Fig. 1 also shows how brands should target owners and nonowners. It visualizes for instance the striking difference between nonowners and owners of Forum: non-owners think very abstractly about this brand, whereas owners relate it to more tangible properties. The results suggest that the discrepancy between owners and non-owners decreases with the brand's position in the category leadership. The maps themselves allow managers to build up refined marketing strategies, capitalizing on these insights in consumer reasoning. In sum, this study presents a revealing method to analyze how different groups think about brands. The most intriguing finding is that the causal structure of the most prototypical brand seems to provide a “mother structure” for other brands in the category. This finding should stimulate marketers to reflect on the position of their brand within consumers cognitive causal structures for the relevant product category. References Ahn WK. Why are different features central for natural kinds and artifacts?: the role of causal status in determining feature centrality. Cognition 1998;69(2):135–78. Alba Joseph W, Wesley Hutchinson J. Dimensions of consumer expertise. J Consum Res 1987;13(3):411–54. Anderson Craig A, Lepper Mark R, Ross Lee. Perseverance of social theories: the role of explanation in the persistence of discredited information. J Pers Soc Psychol 1980;39:1037–49 December. Carpenter Gregory S, Nakamoto Kent. Consumer preference formation and pioneering advantage. J Mark Res 1989;26:285–98 August. Chater Nick, Oaksford Mike. Mental mechanisms: speculations on human causal learning and reasoning. In: Fiedler K, Juslin P, editors. Information sampling and adaptive cognition. Cambridge: Cambridge University Press; 2006. p. 210–36. De Chernatony Leslie. From brand vision to brand evaluation. Strategically building and sustaining brands. Oxford: Butterworth Heinemann; 2001.
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