an extended search for generic consumer-brand relationships

An Extended Search for GenericConsumer–Brand RelationshipsWolfgang FritzTechnische Universitat Braunschweig

Bettina LorenzVolkswagen Consulting

Michael KempeVolkswagen Financial Services

ABSTRACT

Relatively few empirical studies address the question of generic relationships between consumersand brands. But a relationship-oriented brand communication seems to have become increasinglyimportant to companies. In this article, the authors present details of a study on genericconsumer–brand relationships conducted in Germany. Based on the data of more than 900consumers, four different types of consumer–brand relationships emerge, characterized as “bestfriendship,” “unemotional purpose-based relationship,” “loose contact,” and “happy partnership.” Anextended analysis of the data using advanced statistical methods supports these findings to a highdegree. Furthermore, as the results of the extended analysis also suggest, numerous well-knownbrands often appear within less favorable relationships like “unemotional purpose-basedrelationship” and “loose contact.” These findings indicate important shortcomings ofrelationship-oriented brand management in many companies and suggest the need for further workin this area. © 2014 Wiley Periodicals, Inc.

In recent years, the significance of relationship mar-keting has greatly increased. The central focus here ison the relationship between companies and their cus-tomers. In many markets, however, particularly in thefield of consumer goods, the relationship between con-sumers and brands also plays an important role. Yetempirical studies that focus on these brand relation-ships are still relatively scarce, even though such rela-tionships often form the basis for more comprehensivecustomer relationships and may also have a significanteffect on the value of a brand. Consumer–brand rela-tionships are obviously an important area of researchthat has not heretofore been the subject of many empir-ical studies, especially in Europe. Therefore these rela-tionships are the central focus of this article, which ex-amines in particular the dimensions and types of suchrelationships in two empirical analyses. Furthermore,the article draws conclusions that are relevant to mar-keting research and marketing practice.

CURRENT STATE OF RESEARCH

In German-speaking Europe, some studies take atheory-based look at the role that brands play

in customer relationships in consumer goods mar-kets (e.g., Bruhn, Hennig-Thurau, & Hadwich, 2004;Meffert, 2002). However, only few empirical studieshave been carried out on this topic to date (e.g., Bruhn& Eichen, 2010; FCB Deutschland, 2002). More re-cent studies have focused solely on a few specific as-pects of consumer–brand relationships, for instance,brand love, persons as brands, consequences for cus-tomer value, and for complaint management of the firm(Henkel & Huber, 2005; Huber, Vollhardt, & Vogel,2009; Jodl, 2005; Wenske, 2008).

A relatively larger number of studies have been car-ried out in the English-speaking world (MacInnis, Park,& Priester, 2009). Many of these also analyze impor-tant details of consumer–brand relationships, for in-stance, brand love (Batra, Ahuvia, & Bagozzi, 2012),brand attachment, and brand attitude strength (Park,MacInnis, Priester, Eisingerich, & Iacobucci, 2010) aswell as the transfer of brand personalities to consumers(Park & Roedder, 2010) and other aspects (e.g., Aaker,1996; Aaker, Fournier, & Brasel, 2004; Aggarwal, 2004;Blackston, 1993; Sheth & Parvatiyar, 1995). The mostfrequently cited works are the fundamental studies byFournier (1994, 1998), who identifies a total of 15 dif-ferent types of relationships between consumers and

Psychology & Marketing, Vol. 31(11): 976–991 (November 2014)View this article online at wileyonlinelibrary.com/journal/mar

© 2014 Wiley Periodicals, Inc. DOI: 10.1002/mar.20747

976

brands from an individual consumer’s perspective (forinstance, “best friendship,” “secret affair,” or “enslave-ment”). Since then, other studies about consumer–brand relationships have been carried out on the basisof Fournier’s approach (Fournier, 2009; Ji, 2002; Kates,2000).

Noteworthy among such work is the study by Fritzand Lorenz (2010) which is based on the earlier workof Lorenz (2009). In contrast to Fournier’s work, Fritzand Lorenz (2010) seek to identify comprehensive typesof consumer–brand relationships on a broad empiricalbase; in other words, relationship types that can beconsidered as being representative of larger groups ofconsumers. However, one methodological limitation ofthe study by Fritz and Lorenz (2010) is the rather tra-ditional statistical approach the authors use in orderto determine different types of brand relationships. Amore sophisticated approach could likely aid in fine-tuning earlier findings in this regard. In line with theabove, in this article, first, the most important aspectsof the study by Fritz and Lorenz (2010) are presented.Following that, the details of a finer analysis resultingin greater specificity are furnished. Finally, a discus-sion of the overall findings presents a capstone endingto this article.

THE ORIGINAL STUDY

Conceptual Framework and ResearchPropositions

The article by Fritz and Lorenz (2010) is based on thefundamental creed of relationship-oriented brand re-search, on the assumption that a brand may be re-garded as an active partner in a relationship withthe consumer. This approach is, e.g.., also empha-sized by Aaker, who believes that relationships betweenconsumers and brands can have characteristics simi-lar to interpersonal friendships (Aaker, 1996, p. 160;Hofmeyr & Rice 2002). For Blackston (1993, 2000), in-teraction and reciprocity are the central elements ofsuch relationships; this can be seen not only in con-sumers’ perceptions and behavior toward the brand,but also in the fact that consumers ascribe perceptionsand behavior to the brand itself during their inter-actions with it. Following this perspective, Fritz andLorenz characterize a consumer–brand relationship byrepeated, interrelated, and nonaccidental exchanges ortransactions between a consumer and a brand, whereinthe brand’s behavior is considered as a virtual or quasi-behavior in the subjective view of the consumer (Fritz& Lorenz, 2010, p. 369).

The theoretical basis of the Fritz and Lorenz studyis formed in particular by social psychology approachesto interpersonal relationships, especially of exchange-theory approaches. In this view, social interaction pro-cesses take place as transactions that are evaluated bythe individual participants. Equity-theory approaches

are also taken into consideration; these state that peo-ple in such interactions are not simply following theirown goals, but are also working toward fairly dis-tributed or balanced results. Some specific theories ofexchange and equity are the interdependency theoryby Thibaut and Kelley (1959), the investment modelby Rusbult (1980), the theory of social exchange byHomans (1961) and Blau (1964), the equity theory byWalster, Berscheid, and Walster (1978), and the re-source theory by Foa and Foa (1974). An additionalperspective is found in the theory of social penetra-tion by Altman and Taylor (1973), which allows aninvestigation of various relationship types. Since thestudy focuses on the relationships between only twoparties (consumer and brand) and not on the relation-ships among multiple players, approaches that look atrelationship networks are not included.

On this background, Fritz and Lorenz distinguishnine possible dimensions of consumer–brand relation-ships (Fritz & Lorenz, 2010, pp. 370). These are shownin Table 1 and are briefly explained below.

The significance of the interdependence relationshipdimension is fundamentally derived from the interde-pendence theory by Thibaut and Kelley (1959), alongwith the satisfaction dimension, which is extremely rel-evant to interpersonal relationships and is also empha-sized in the investment model by Rusbult (1980). Thislast model ascribes great importance to commitment asa measure of the bond between two people and is there-fore investigated as another relationship dimension.In addition to commitment, which is a more attitude-related dimension, the consumer’s actual behavior istaken into consideration as an action-related dimen-sion in terms of buying and recommendation behav-ior (Chaudhuri & Holbrook, 2001; Delgado-Ballester &Munuera-Aleman, 2001).

Another significant relationship dimension is brandtrust. This assumption is based on the social ex-change theories by Homans (1961) and Blau (1964).The latter highlights the importance of trust in sym-bolic exchanges, for instance in purchasing branditems.

The affective relationship aspects are speciallytaken into consideration through the dimensions of in-timacy and passion. A theoretical basis for this can befound in resource theory (Foa & Foa, 1974), as wellas in the theory of social penetration by Altman andTaylor (1973). A core assumption of this theory is thatindividuals are constantly discovering more intimateelements of a partner’s personality during the courseof a relationship. It also demonstrates the importanceof the chronology of a relationship. Hence, relationshipduration is considered as a further dimension. Finally,the equity dimension, based on the above-mentionedequity theory by Berscheid and Walster (1978), coversthe aspect of fairness in relationships.

One important question is whether different typesof relationships between consumers and brands can bedistinguished empirically by the relationship dimen-sions outlined above. To this end, Fritz and Lorenz

GENERIC CONSUMER–BRAND RELATIONSHIPS 977Psychology & Marketing DOI: 10.1002/mar

Table 1. Nine Potential Dimensions of Relationships between Consumers and Brands (Fritz and Lorenz, 2010).

Relationship Dimension Content Theoretical Basis

Interdependence Mutual dependence between consumer and brand (seeFournier, 1998) as reflected in the frequency ofinteraction with the brand, the scope and variety ofbrand-related activities (such as use of brandextensions), and the intensity of individualinteraction.

Interdependence theory, Thibaut andKelley (1959)

Relationship duration Absolute amount of time during which therelationship between consumer and brand exists.

Social penetration theory, Altman andTaylor (1973)

Satisfaction Result of a cognitive comparison between expectedand experienced performance. In addition to thesecognitive components, satisfaction also exhibits anaffective component, as in the concept of “customerdelight.”

Interdependence theory, Thibaut andKelley (1959) and Rusbult’s (1980)investment model

Brand commitment Based on Morgan and Hunt (1994), brandcommitment is understood as the consumer’s desireto maintain a long-term relationship with a brand,combined with his/her willingness to make an efforttowards achieving this goal.

Rusbult’s (1980) investment model

Actual behavior For example, it is assumed that the customer’sresponse is composed of buying and word-of-mouthbehavior to a high degree.

Approaches to brand loyalty

Equity According to Walster, Berscheid, and Walster’s (1978)equity theory, equity is defined as the perception ofa balance between rewards and inputs, whererewards are defined as the difference betweenoutcomes and inputs.

Equity theory, Walster, Berscheid, andWalster (1978)

Brand trust According to Morgan and Hunt (1994) brand trustrepresents the level of consumer’s confidence in thebrand’s ability to fulfill his/her expectations. Thisconfidence results from the customer’s projection ofpositive expectations and preconceptions onto thebrand. Brand trust comprises a total of four factors:willingness to resolve problems, benevolence, brandreliability, and integrity.

Social exchange theory, Homans (1961)and Blau (1964)

Passion According to Sternberg, passion is anall-encompassing motivational construct that goesbeyond physical attraction. In describing passion,he refers to Hatfield and Walster’s statementsregarding passionate love:

Resource theory, Foa and Foa (1974)

“The passionate component . . . includes whatHatfield and Walster (1981) refer to as ‘a state ofintense longing for union with the other’” (p. 9;Sternberg, 1986, 122)

Intimacy According to Reis and Shaver’s (1988) intimacy model,intimacy occurs when a person (i.e., the consumer)reveals feelings or information to another person(i.e., the brand). The process is continued if thelistener’s (i.e., the brand’s) response seems to besupportive and sympathetic. Self-disclosure is thusan essential component of intimacy. Anotherimportant aspect is that the disclosing person feelsunderstood, confirmed, and cared for. Thus,intimacy includes both cognitive as well as affectivecomponents.

Social penetration theory, Altman andTaylor (1973)

(2010, p. 371) formulate two fundamental researchpropositions claiming that different types of consumer–brand relationships do exist and that these types differfrom one another empirically with respect to each rela-tionship dimension.

Method

Sample and Analysis. Data were collected via ane-mail–supported online survey of consumers in Ger-many. This type of survey sets up questionnaires on

978 FRITZ, LORENZ, AND KEMPEPsychology & Marketing DOI: 10.1002/mar

Table 2. Demographics of Sample (Fritz and Lorenz, 2010).

Demographics

Percentage ofAdjusted Sample

(n = 986)

ExpectedPercentage (Basis:

Population)

Gender Female 50.0% (493) 51.1% (504)Male 50.0% (493) 48.9% (482)n = 986; χ2 (p = 0.05; df = 1) = 3.84 > χ2 (emp.) = 0.25

Age Under 14 0.0% (0) N/A14–29 31.6% (311) 25.0% (247)30–49 43.4% (428) 45.0% (444)50–64 22.9% (226) 30.0% (296)over 64 2.1% (21) N/An = 986; χ2 (p = 0.05; df = 4) = 9.49 < χ2 (emp.) = 12.06

Education No school-leaving certificate 1.6% (16) 7.0% (69)Lower secondary school 9.3% (91) 36.0% (354)Secondary school leaving certificate, midlevel secondary

school, or similar35.5% (349) 37.0% (364)

College/university 53.7% (528) 19.0% (187)n = 984; χ2 (p = 0.05; df = 3) = 7.81 < χ2 (emp.) = 351.39

the Web and sends links to e-mail addresses, inform-ing targeted addressees of the questionnaires. The on-line panel of Gesellschaft fur Konsumforschung (GfK),one of the biggest market research institutes in Eu-rope, was used to carry out the survey. The data wereanalyzed using SPSS 19.0 and PLS-Graph. A total of1121 respondents took part in the survey, resulting in986 completed questionnaires that could be includedfor further analysis. Table 2 shows the demographicstructure of the sample.

The chi-square test shows that the sample is rep-resentative of the German population in terms ofgender, but not in terms of age and education. Theresulting profile corresponds to an average internetuser, whose demographic profile still differs fromthat of the average population in terms of age andeducation.

Among other things, Table 3 shows the consumer-goods categories and brands included in the study. Con-sumers were assigned to categories and brands at ran-dom. Each consumer responded only to questions aboutone brand he or she had used.

Operationalization and Validation of the Con-structs. The relationship dimensions are theoreti-cal constructs that require operationalization andempirical validation. In order to operationalize thenine relationship dimensions, Fritz and Lorenz (2010)draw upon available and previously tested scales (seeTable A1). Thus the interdependence construct is op-erationalized using the “Relationship Closeness Inven-tory” (RCI) developed by Berscheid, Snyder, and Omoto(1989), which looks at the frequency, number, strength,and duration of interdependencies as fundamental as-pects of close human relationships. Since these as-pects differ in terms of content, while at the sametime (incompletely) determining (or “forming”) the con-struct, this relationship dimension is operationalized as

a formative construct (Diamantopoulos & Winklhofer,2001). Following Berscheid, Snyder, and Omoto (1989,p. 796), however, the relationship duration construct,as the chronological span of the existence of a relation-ship, is operationalized separately in order to recordalso the length of relationships that are not character-ized by a high level of interdependence.

Numerous approaches are used to measure the sat-isfaction construct. For the purposes of the study,existing scales used to measure relationship satis-faction are particularly suitable. Its operationaliza-tion is based on the “global items” of the scaleby Rusbult, Martz, and Agnew (1998), the satisfac-tion scale by Aaker, Fournier, and Brasel (2004),and the inventory of the Relationship AssessmentScale by Hendrick (1988), which was further de-veloped by Sander and Bocker (1993). Due tothe fact that relationship satisfaction is reflectedin the chosen items, the construct is operational-ized reflectively (Diamantopoulos and Winklhofer,2001).

The brand commitment relationship dimensionincludes cognitive, conative, and chronological compo-nents (Aaker, Fournier, & Brasel, 2004; Chaudhuri &Holbrook, 2002; Rusbult, 1983) and is therefore speci-fied as a formative construct. The commitment scales byRusbult (1983) and Rusbult, Martz, and Agnew (1998)stem from the field of relationship psychology and pro-vide the basis for operationalizing the cognitive factor.The conative factor is measured according to customerloyalty research, using central aspects of behavioralintentions (the intention to make a repeat purchaseor a recommendation or to remain loyal to the prod-uct, willingness to withstand adversity). These aspectsare operationalized reflectively using items from brandcommitment or loyalty scales by Aaker, Fournier, andBrasel (2004); Delgado-Ballester, Munuera-Aleman,and Yague-Guillen (2003); and Chaudhuri and Hol-brook (2001). The measurement of the chronological


Table 3. Consumer Goods, Brands, and Number of Respondents (Fritz and Lorenz, 2010).

Product Category Brands and Number of Respondents Absolute Percentage

Clothing Adidas, C&A, Esprit, H&M, Levi’s, Nike 116 11.76%Banks Deutsche Bank, Dresdner Bank, Postbank,

Sparkasse, Volksbank, Raiffeisenbank100 10.14%

Credit cards American Express, MasterCard, Visa 93 9.43%Fast-food restaurants Burger King, Kochloffel, McDonald’s,

Nordsee, Pizza Hut, Subway139 14.10%

Cars Audi, BMW, Ford, Mercedes, Opel, VW 109 11.05%Beverages Coca-Cola, Fanta, Pepsi, Schweppes, Sprite 154 15.62%Cosmetics Dove, Fa, Labello, Nivea, Palmolive, Penaten 130 13.18%Online service providers AOL, Freenet, Google, T-Online, web.de,

Yahoo!145 14.71%

Total 986 100.00%

component of brand commitment uses one centralindicator and refers to Aaker, Fournier, and Brasel(2004); Rusbult (1983); and Rusbult, Martz, and Agnew(1998).

The actual behavior relationship dimension is spec-ified formatively using indicators that include buy-ing and recommendation behaviors. In order to oper-ationalize these aspects, new formulations are used,taking into consideration, for instance, the scalesprovided by Delgado-Ballester, Munuera-Aleman, andYague-Guillen (2003).

Social psychology theory describes many differentapproaches, some quite complex, that can be used tomeasure the equity relationship dimension (van Yperen& Buunk, 1990). In order to record the perceived eq-uity in consumer brand relationships, Fritz and Lorenzselect a global measurement approach that essen-tially follows the Berg and McQuinn (1986) version ofthe Hatfield Global Measure (van Yperen & Buunk,1990), adding in the fairness aspect described by Oliver(1997).

To operationalize the brand trust relationship di-mension, which is also considered to be a complex,multifactor construct (Delgado-Ballester, Munuera-Aleman, & Yague-Guillen 2003; Sirdeshmuhk, Singh,& Sabol, 2002; Morgan & Hunt, 1994), four fac-tors were taken into account—supported by numer-ous studies—that formatively depict the construct: will-ingness to solve problems, goodwill, brand reliability(including competence and credibility), and integrity.The four factors are operationalized reflectively, refer-ring to the scales by Delgado-Ballester and Munuera-Aleman, (2001), Delgado-Ballester, Munuera-Aleman,and Yague-Guillen (2003), Larzelere and Huston(1980); Monga (2002), and Sidershmuhk et al. (2002).

The passion relationship dimension represents acomprehensive motivational construct that is measuredusing the social psychological scales by Sternberg andHatfield (Amelang, 1995; Hatfield, 1988) as well as sub-sequent measures (Hendrick & Hendrick, 1989), par-ticularly the scale for measuring brand affect as devel-oped by Chaudhuri and Holbrook (2001). These scalesinclude a concrete usage-related factor and an abstractemotional factor, representing the two formative indi-

cators of the higher-level construct and are operational-ized by reflective indicators.

A similar approach is used with the intimacy re-lationship dimension, which also represents a com-plex formative construct. According to Reis and Shaver(1988), it comprises the aspects “self-disclosure,” “un-derstanding,” “confirmation resp. acceptance,” and“caring,” that are supplemented by “listening” asa preliminary stage to understanding. The opera-tionalization of these factors is reflective; for “self-disclosure” it refers to Aaker (1996), Aaker, Fournier,and Brasel (2004), and Laurenceau, Feldman Bar-rett, and Pietromonaco (2004) and for “understanding,”“confirmation resp. acceptance,” and “caring” to Stern-berg (1986), Thorbjornsen et al. (2002), and Monga(2002).

In testing the reliability and validity of the mea-surement models empirically, the traditional standardPLS criteria for reflective and formative measure-ment models were used (Anderson & Gerbing, 1991;Bollen & Lennox, 1991; Chin, 1998; Jarvis, MacKen-zie, & Podsakoff, 2003). The results, shown in Ta-ble 4, demonstrate that nearly all the traditional cri-teria of fit are fulfilled. Furthermore, the Fornell–Larcker criterion, which establishes the discriminantvalidity of the reflective measurements of factors, isgiven.

Six of the nine relationship dimensions representformative second-order constructs, since they includeseveral partial dimensions or factors that can be seenas first-order constructs (interdependence, brand com-mitment, behavior, brand trust, passion, and intimacy;see Table 4).

However, these partial dimensions or factors arereflectively specified. According to the systematiza-tion suggested by Jarvis, MacKenzie, and Podsakoff(2003), these measurement models with second-orderconstructs belong to the methodically appropriate TypeII. The empirical findings reveal that second-order con-structs are also validly depicted by their partial dimen-sions (factors), since in every case there are significantweights on the second-order model level with plausi-ble (positive) signs that take on values between 0.43(t = 9.35) and 0.95 (t = 84.79). The variance inflation


Tab

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Table 5. Growth of Heterogeneity and Number ofClusters (Fritz and Lorenz, 2010).

Number ofClusters

HeterogeneityCoefficient (Sum of

Squared Errors)Growth of

Heterogeneity

6 2699.31 145.175 2924.01 224.714 3201.94 277.933 3715.11 513.162 4305.96 590.851 6232.29 1926.33

factor remains significantly below the critical value of10 in every case. Thus there is no multicollinearityproblem. However, there are correlations among thesecond-order constructs showing values of 0.01 to 0.79,with an average correlation value of 0.49. Since theseconstruct correlations are still significantly lower thanthe critical value of 0.90, discriminant validity is given(Herrmann, Huber, & Kressmann, 2006). Thus the fitcriteria for formative measurement models are fulfilledon the second-order construct level.

The following cluster analysis is not affected bythe correlating relationship dimensions, which are in-cluded as clustering variables using their factor values,since most clustering methods do not assume uncorre-lated clustering variables (Milligan, 1996; Milligan &Hirtle, 2003). This also applies if these clustering vari-ables represent complex constructs and the criteria fordiscriminant validity are met.

Results

Determining the Number of Different Relation-ship Types. Fritz and Lorenz (2010) use a traditionalhierarchical cluster analysis to empirically identify re-lationship types in terms of the relationship dimen-sions regarded as clustering variables (Punj & Stewart,1986). Using the single-linkage method, first outliersare identified, in other words cases with characteristicsthat are very atypical for the sample. The squared Eu-clidean distance is selected as a measure of proximity.As a result of this procedure, 37 of the 986 total caseshad to be excluded from further study. Nevertheless,this is unimportant because the cases are distributedevenly among the product categories and brands un-der investigation. Thus 949 cases were finally used forcluster formation.

The traditional cluster analysis combines the Wardprocedure with the k-means method (Scheibler &Schneider, 1985). The preliminary determination of theoptimal cluster number is based on the heterogeneitycoefficients (sum of squared errors). If one look at theirdifferences in Table 5, the advantage of a four clusterssolution is shown: In moving from the four-cluster tothe three-cluster solution, the increase in the sum ofsquared errors nearly doubles.

Table 6. Percentage of Cases Correctly Classified byMultiple Discriminant Analysis (Fritz and Lorenz,2010).

Number of Clusters

Hit Ratio(ClassificationCorrectness)

Three-cluster solution 93.8%Four-cluster solution 95.2%Five-cluster solution 94.9%Six-cluster solution 94.8%

Optimizing the four clusters solution using the k-means method reduces the sum of squared errors by164.76, or 5.1%. Multiple discriminant analyses areperformed for further validation. The four clusters solu-tion is also superior to the alternative solutions in termsof classification correctness for individual discriminantfunctions, as shown in Table 6.

Interpreting the Different Relationship Types. Inorder to characterize the relationship types indicatedby the four clusters in more detail, the relationshipdimensions used as clustering variables are analyzed.Differences in the means of each dimension across thefour clusters are highly informative, as depicted by theprofile graphs in Figure 1.

The four identified relationship types clearly differfrom one another: 53 of a total of 54 mean differencesare significant. The only exceptions are Clusters 1 and2 in terms of “duration.” On the other hand, Cluster 4(n = 128) differs from the other clusters in that all of itsrelationship dimensions are well above average. Thisindicates the presence of a high relationship quality.Clearly, this type of relationship can be characterizedas a very close and trustful type of relationship that ismarked by both passion and intimacy. These charac-teristics indicate a large similarity to an interpersonalpartnership which is also marked by passion, commit-ment, and intimacy. For these reasons, the relationshiptype represented by Cluster 4 can be described as ahappy partnership.

Cluster 1 (n = 328) also shows above-average valuesfor nearly all relationship dimensions. It even has thehighest mean value in terms of relationship duration,along with Cluster 2. Only its “passion” dimension isnotably low. It is therefore a close and extremely long-lasting relationship (its average duration is 10 years ormore), and consumers are quite satisfied with it. Theytrust the brand and feel attached to it, although, unlikeCluster 4, there is no presence of passion. The char-acteristics of this consumer–brand relationship exhibitclear parallels to the friendship as a form of an inter-personal relationship. The latter is also marked by ahigh degree of trust, intimacy, and attachment, alongwith a similarly low degree of passion. In light of thissimilarity, the brand relationship in Cluster 1 can becharacterized as a best friendship.


Figure 1. Profile graphs of the four consumer–brand relationship types (F- and Tukey–Kramer tests, Fritz and Lorenz, 2010).

Cluster 2 (n = 257) is fundamentally different fromthe two previously described clusters. Here, the dimen-sions of interdependence, satisfaction, commitment,behavior, trust, equity, passion, and intimacy are thelowest of all clusters. The only exception is duration,which has the highest value of all relationship types.Thus, Cluster 2 represents a long-lasting but low-quality relationship. This is demonstrated by the factthat consumer satisfaction is relatively low within thistype of brand relationship. This appears contradictoryat the first glance due to the long duration of the re-lationship. However, there are several different expla-nations. It seems likely that these consumers enteredinto the relationship for a specific purpose only, suchas to simplify the acquisition of the particular brand asmuch as possible and thus minimize the time and effortrequired for purchases.

From the interpersonal relationships parallels canbe drawn to a “partnership of convenience” in whichthe participants enter into only to fulfill a specific pur-pose or to benefit from it in some way. Examples ofsuch partnerships include marriages of convenience orflat-sharing communities. In addition, the brand re-lationship observed here remains superficial and ismarked by a low degree of appreciation. In light ofthese comparisons, this relationship type may be inter-preted as an unemotional purpose-based relationship.Although the consumers maintain a long-term relation-ship with the brand, they do so more out of habit thancommitment.

Cluster 3 (n = 236) also represents a superficial rela-tionship type; however, it does not last long. Althoughthe consumer is quite satisfied with the brand, he orshe does not feel attached to it. Aspects of an emotionalrelationship such as intimacy and passion are missing.If these characteristics are transferred to interpersonalrelationships, a similarity is found to loose contacts:You encounter the person in question once in a while,are glad to see him or her, and converse with him or

her about general topics—however, a closer relationshipnever develops. For these reasons, the consumer–brandrelationship represented by Cluster 3 can be best char-acterized as a loose contact.

Finally, it is worth noting that the four clusters alsodiffer in terms of size: While “happy partnerships” rep-resent a rather niche form of relationship at 13.5% ofthe sample, 34.5% of the persons surveyed regardedthe brands they used as friends and are thus classi-fied under the “best friendship” relationship type. Alower percentage of 27.1% is classified as “unemotionalpurpose-based relationship,” followed by “loose contact”with only 24.9%. Overall, the research propositions aresupported empirically. The four relationship types dif-fer significantly from each other along the relationshipdimensions, the only exception being in terms of rela-tionship duration.

AN EXTENDED ANALYSIS

Identifying Relationship Types byAdvanced Clustering Methods

As already mentioned, one methodological shortcom-ing of the Fritz and Lorenz (2010) study is the rathertraditional approach of cluster analysis used to em-pirically identify brand relationship types. Extendingthis traditional approach, in the following an advancedmixture-clustering procedure is chosen in order to val-idate the clustering solution (Wedel & Kamakura,2003). This extended analysis seems necessarybecause mixture clustering provides a superior esti-mation procedure and also because traditional (deter-ministic) clustering neglects the problem of unobservedheterogeneity within the data to a high degree (Franke,Reisinger, & Hoppe, 2009). Mixture-clustering proce-


Table 7. Findings of the Mixture-clustering Procedure (Extended Study).

Number of Clusters Log-Likelihood AIC CAIC MAIC BIC Entropy df

2 –17,479.25 35,000.51 35,170.42 35,021.51 35,149.42 0.896 213 –15,727.75 31,519.50 31,777.19 31,551.50 31,745.19 0.916 324 –15,211.90 30,509.80 30,856.06 30,552.80 30,813.06 0.919 435 –15,004.31 30,116.63 30,551.47 30,170.63 30,497.47 0.898 546 –14,818.86 29,767.73 30,291.15 29,832.73 30,226.15 0.891 65

dures on the other hand take unobserved data hetero-geneity into account (Wedel & Kamakura, 2003).

The findings presented in Table 7 also support thefour-cluster solution. The entropy of the four-cluster so-lution shows the highest value indicating the best sep-aration of the clusters and the information criteria arebetter for the four-cluster solution than for the three-cluster or the two-cluster solution.

The four-cluster solution also fulfills standard cri-teria for heterogeneity and homogeneity. Thus, all ofthe distances between the cluster centers show valuesbetween 1.7 and 5.9 while the average F-value withinthe clusters is 0.51, which in fact indicates a sufficientdegree of homogeneity of the clusters. Hence, it followsthat, along the nine relationship dimensions, the useof traditional and mixture clustering empirically iden-tifies four different clusters representing four differenttypes of relationships between consumers and brands.

A Comparison of the Empirical Findings

In order to decide which of the clustering approachesleads to better results, the criteria for heterogeneityand homogeneity shown in Table 8 are employed toevaluate the four-cluster solutions of both approaches.These criteria are the sum of squared errors (SSW),the remaining sum of squares (RS according to Frankeet al., 2009), the F-value, and the hit ratio of discrimi-nant analysis.

The cluster solution of the traditional k-means algo-rithm fulfills all standard criteria for heterogeneity andhomogeneity. All distances between the cluster centersshow values between 2.2 and 5.2. The hit ratio of thediscriminant analysis is very high, while all F-valueswithin the clusters are between 0.30 and 0.90. Also RSreaches an acceptable level. All in all, this indicates asufficient degree of clusters’ homogeneity.

This is different for the results of the mixture-clustering approach. The distances between the clus-ter centers also show acceptable values between 1.7and 5.9. The average F-value within the clusters ismarginally smaller and the hit ratio of the discriminantanalysis is slightly higher than for the k-means solu-tion. However, single F-values are higher than 1, indi-cating less homogeneity of the clustering result. Thisalso is demonstrated by the higher sum of squared er-rors, which leads to a still acceptable but lower RS valuethan for the k-means solution. In conclusion, despitethe advantages that mixture clustering offers, it obvi-

ously does not lead in any case to a more homogeneoussolution than a traditional clustering approach.

Furthermore, the interpretation of the different clus-ter solutions is considered. Although the advancedmixture-clustering approach supports the four-clustersolution uncovered by the traditional approach in prin-ciple, it reveals some relevant differences, especiallywith regard to the size of the clusters representing thefour types of brand relationships as seen in Table 9.Especially the size of Cluster 2 differs to a great extentbetween the two clustering solutions. Whereas it is thesmallest cluster of the mixture clustering approach, thesize doubles when using the traditional method. Thesize of Cluster 3 also shows a difference between thetwo solutions. While it is the largest of the four clus-ters in mixture clustering, it is much smaller in thetraditional approach.

There are also some differences in the profiles of thefour brand relationship types as shown in Figure 2 com-pared to Figure 1. But, on the other hand, the compari-son also reveals by far more similarities in both profiles.The only relevant exception is the duration dimension,because in this regard the types differ less strongly formixture than for traditional clustering. Neverthelessthe profiles of the other eight dimensions show nearlythe same pattern across the four relationship types inboth kinds of clustering solutions.

Additional Characteristics of RelationshipTypes

Particularly in marketing practice, it is important toask whether brand relationship types appear differ-ently in individual consumer groups and for concretebrands. Such information can help companies to iden-tify market segments with differing brand relationshipsin order to position their brands better in those seg-ments. For this reason, the following analysis tries touncover additional segment-related characteristics ofthe brand relationship types.

In their study, Fritz and Lorenz (2010, p. 382) findthat consumers engaged in favorable types of brandrelationships (“best friendship” and “happy partner-ship”) have to some degree a different demographicprofile than those sharing less favorable relationships(“loose contact” and “unemotional purpose-based rela-tionship”). But two objections can be raised againstthese findings. First, the authors again use a rathertraditional approach for data analysis that offers no


Table 8. Comparison of Cluster Solutions (Extended Study).

Clustering Method

Sum ofSquared

Errors (SSW)

RemainingSum of

Squares (RS)HighestF-value

AverageF-value Hit Ratio

k-Means 3037 0.513 0.940 0.513 94.8%mixture clustering 3430 0.450 1.174 (!) 0.510 96.0%

Note: Sum of squares total (SST) = 6232.29; RS = 1–SSW/SST.

Table 9. Comparison of Cluster Size (Extended Study).

Cluster Cluster Size Cluster SizeCluster No. (Relationship Type) k-Means Mixture Clustering

1 Best friendship 328 (34.6%) 334 (35.2%)2 Unemotional purpose-based relationship 257 (27.1%) 122 (12.9%)3 Loose contact 236 (24.9%) 360 (37.9%)4 Happy partnership 128 (13.5%) 133 (14.0%)

detailed insight into the goodness-of-fit of the appliedmodel (bivariate contingency analysis). Second, onlythree demographic variables are analyzed (gender, in-come, and age) while others are neglected (e.g., educa-tion).

In order to overcome these shortcomings, in this ex-tended analysis the data are reanalyzed by using a si-multaneous multiple logistic regression approach (e.g.,Field, 2009, p. 2009). Moreover, “formal education” isincluded as another demographic variable in the anal-ysis and the basic category of goods the brands belongto (physical products vs. services) is also taken into ac-count. The findings of this extended analysis are pre-sented in Tables 10 and 11.

In contrast to the study by Fritz and Lorenz (2010),the results shown in Table 10 demonstrate that neither

the demographic nor the product-related variables varysignificantly for consumers sharing favorable vs. lessfavorable brand relationships.

However, most of the goodness-of-fit criteria shownin Table 11 indicate that the logistic regression modelas a whole does not hold empirically to a sufficient de-gree and therefore should be rejected. The Hosmer–Lemeshow test shows a nonsignificant chi-squarestatistic and the Cox & Snell R-Square and the Nagelk-erke R-Square are far below an acceptable level of ex-plained variance. The classification power of the modelseems to be nearly arbitrary because of its too smallnumber of correct classifications. It follows that themodel as a whole is not able to explain relevant demo-graphic or product-related differences between favor-able and less favorable consumer–brand relationship

Figure 2. Profile graphs of the four consumer–brand relationship types identified by the mixture-clustering approach (extendedstudy).


Table 10. Logistic Regression Variables (Extended Study).

Variables B SE Wald df Significance Exp(B)

Income –0.036 0.153 0.056 1 0.813 0.964Education –0.028 0.117 0.059 1 0.808 0.972Age –0.002 0.006 0.083 1 0.773 0.998Gender –0.005 0.160 0.001 1 0.973 0.995Type of goods

(physical productvs. service)

0.162 1.134 1.134 1 0.287 1.175

Constant 0.057 0.015 0.015 1 0.904 1.058

Note: Dependent variable: 0 = favorable, 1 = less favorable type of brand relationship. See Table A2 for the operationalizations of the independentvariables.

Table 11. Evaluation of the Logistic Regression Model(Extended Study).

Goodness-of-Fit Criteria

Value ofGoodness-of-Fit

Criteria

Chi-square /df/significance 10.934/8/0.205−2 Log likelihood 969.343Cox & Snell R-Square 0.002Nagelkerke R-Square 0.003Percentage of correct classifications 51.9

Table 12. Relation-Specific Focus of Five GlobalBrands (Extended Study).

BrandNumber of Favorable

Relationships

Number of LessFavorable

Relationships Total

Coca Cola 16 13 29Pepsi 13 17 30McDonald’s 15 9 24Burger King 6 19 25Subway 8 15 23

Note: Reading example: Of 154 respondents of the industry “bever-ages” (see Table 3), 30 are in a relationship with Pepsi. For 13 respon-dents, the brand is a partner in a “best friendship” or “happy partner”relationship, while 17 respondents share an “unemotional purpose-based” or a “loose contact” relationship with the brand.

types. Moreover, the findings indicate that these typesof relationship may occur in each consumer segmentidentified by demographic or product-related variablesand can therefore be seen as generic consumer–brandrelationships that are of general importance for mar-keting and brand management of firms.

Overall Conclusions

According to the findings presented in the last sec-tion, the groups of consumers who share typicalrelationships with their brands tend not to have dif-ferent demographic profiles. With regard to the indi-vidual brands, the dominant notion is that of manybrands appearing simultaneously in multiple relation-ship types. This is important to companies, particularlyin terms of their relationship-oriented brand position-

ing. For instance, the Coca Cola brand is better po-sitioned than its competitor Pepsi, because it is morefrequently found as a partner in favorable than in lessfavorable relationship types. Similarly, McDonald’s isin a better relationship-oriented brand position thanits competitors. This is shown in detail in Table 12 andFigure 3.

Most important for companies is to create and main-tain favorable brand relationships, which refers to the“happy partnership” and “best friendship” relationshiptypes. However, creating and developing these brandrelationships cannot be the only objective of brand man-agement. Another challenge is to improve the less ad-vantageous relationships, the “unemotional purpose-based relationship” and the “loose contact,” wheneverthe company detects such relationships with its brands.Since these two relationship types are characterized bya weaker identification with the brand, there is alwaysa higher risk that the consumer will switch to a com-petitor’s brand what has to be avoided.

Overall, the findings presented here support thegrowing understanding that firms’ traditional brandmanagement is in need of a much broader perspec-tive. In addition to the brand, firms must also focus onthe relationship between the consumer and the brand(Fournier, 2009; MacInnis, Park, & Priester, 2009). Inpractice, this way of thinking has already been adoptedby several companies; Henkel’s Web site, e.g., featuresthe slogan “a brand like a friend.” However, many othercompanies are still far from implementing such a com-prehensive perspective of brand management.

One limitation of the analyses presented here istheir character as descriptive snapshots of the phe-nomena under investigation. In the future, broad em-pirical studies should be carried out to determinewhen and how consumers integrate brands into theirlives, what factors influence their choice of brandrelationships, how consumers develop their chosenbrand relationships and reevaluate or replace themwith other relationship types. Like human relation-ships, the relationships between consumers and brandsmay change over time. One must agree with Fournierthat there is a need to focus more extensively on thedynamics of brand relationships in the future, both inresearch and in practice (Fournier, 2009, p. 15).


Figure 3. Relationship-oriented positioning of five global brands (see Table 12, extended study).

Furthermore, empirical follow-up studies shouldalso use alternative methods of data collection. Thewell-known GfK’s online panel seems to be more repre-sentative for the community of internet users than forthe population as a whole. Despite these limitations,the findings presented here underscore the importanceof a relationship-oriented conception of brand manage-ment in research and practice as well.

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Correspondence regarding this article should be sent to:Wolfgang Fritz, Institute of Marketing, Technische Uni-versitat Braunschweig, Abt-Jerusalem-Str. 4, 38106 Braun-schweig, Germany (w.fritz@tu-braunschweig).

APPENDIX

Table A1. Indicators of Consumer–brand Relationship Dimensions (Fritz and Lorenz 2010).

Construct Factor Item

Interdependence (formative) Frequency I normally use this brand’s products . . . daily/severaltimes a week/once a week/several times a month/oncea month/several times a year/once a year/less thanonce a year.

Variety (reflective) I use this brand’s products in a variety of contexts.(5-point Likert scale)

I would use other products by this brand. (5-point Likertscale)

Strength (reflective) This brand is important to me. (5-point Likert scale)I feel like something is missing when I don’t use this

brand’s products. (5-point Likert scale)The brand plays an important role in my life. (5-point

Likert scale)The brand has some influence over me. (5-point Likert

scale)I am important to this brand. (5-point Likert scale)I have some influence over this brand. (5-point Likert

scale)Relationship duration How long have you been using this brand’s products?

less than one month/less than six months/less thanone year/less than five years/less than 10 years/morethan 10 years

Satisfaction (reflective) I am completely satisfied with this brand. (5-point Likertscale)

My relationship with this brand makes me very happy.(5-point Likert scale)

The brand has exceeded my initial expectations. (5-pointLikert scale)

My relationship with this brand is nearly ideal. (5-pointLikert scale)

Brand commitment (formative) cog.-emotional (reflective) How strongly are you convinced by this brand? (5-pointLikert scale)

How closely connected do you feel to the brand? (5-pointLikert scale)

cog.-nostalgic (reflective) This brand reminds me of things I have done. (5-pointLikert scale)


Table A1. Continued


This brand will always remind me of certain phases ofmy life. (5-point Likert scale)

repeat purchase (reflective) I will buy this brand’s products again. (5-point Likertscale)

I would always recommend this brand to others.(5-point Likert scale)

willingness to withstand adversity(reflective)

I would be prepared to pay a higher price for thisbrand’s products than for comparable products by acompetitor’s brand. (5-point Likert scale)

If this brand were not available in a store, I wouldpostpone my purchase. (5-point Likert scale)

I would keep buying this brand even if it disappointedme. (5-point Likert scale)

intended loyalty (reflective) I am loyal to this product. (5-point Likert scale)The decision to stop using this product would cause

some inconvenience for me. (5-point Likert scale)duration I will continue to use this brand’s products several

years from now. (5-point Likert scale)Equity (reflective) The brand treats me fairly. (5-point Likert scale)

The brand offers me a fair price–performance ratio.(5-point Likert scale)

Brand trust (formative) Reliability (reflective) I trust this brand. (5-point Likert scale)This is a brand that never disappoints me. (5-point

Likert scale)The brand offers me products with consistent quality.

(5-point Likert scale)The brand treats me like a valued customer. (5-point

Likert scale)Goodwill (reflective) The brand’s company policy communicates respect for

the customer. (5-point Likert scale)The brand works to meet customer needs. (5-point

Likert scale)Willingness to solve problems (reflective) The brand will help me resolve any problems I might

have with its products (5-point Likert scale)The brand would compensate me if I had problems

with the product. (5-point Likert scale)The brand works hard to resolve customer problems.

(5-point Likert scale)Integrity (reflective) The brand is sincere in its promises. (5-point Likert

scale)The brand is extremely honest with me. (5-point

Likert scale)The brand is interested in its customers. (5-point

Likert scale)Passion (formative) Concrete factor (reflective) I feel good when I use this brand. (5-point Likert scale)

I would rather use this brand’s products than those ofany other brand. (5-point Likert scale)

Abstract factor (reflective) I think about this brand often during the day. (5-pointLikert scale)

No other brand makes me as happy. (5-point Likertscale)

There is something magical about my relationshipwith the brand. (5-point Likert scale)

The brand is very attractive to me. (5-point Likertscale)

I idealize this brand. (5-point Likert scale)I would feel distressed if this brand did not exist

anymore. (5-point Likert scale)I would be sad if I temporarily had to do without this

brand. (5-point Likert scale)


Table A1. Continued


I see my relationship with this brand as somethingunique. (5-point Likert scale)

I feel like this brand and I were made for each other.(5-point Likert scale)

I have feelings for this brand that I do not have formany other brands. (5-point Likert scale)

Intimacy (formative) Self-disclosure by consumer I can imagine sharing personal information with thisbrand. (5-point Likert scale)

Listening (reflective) I feel like the brand is really interested in me. (5-pointLikert scale)

The brand really listens to what I have to say.(5-point Likert scale)

Comprehension (reflective) I feel like the brand really understands me. (5-pointLikert scale)

I feel like I really understand the brand (5-pointLikert scale)

Acceptance The brand accepts me the way I am. (5-point Likertscale)

Caring (reflective) I can count on this brand when I need it. (5-pointLikert scale)

My relationship to this brand is pleasant. (5-pointLikert scale)

Self-disclosure by brand (reflective) I know a lot about this brand. (5-point Likert scale)I am familiar with the products that this brand offers.

(5-point Likert scale)I am confident that I can describe the brand to

someone who is not familiar with it. (5-point Likertscale)

Actual behavior (formative) Purchasing behavior I normally purchase this brand’s products/services . . .daily/weekly/monthly/several times a year/once ayear/approx. every two to five years/approx. everysix to 10 years/less often/I have only purchased thisbrand’s products/services once.

Recommendation behavior (reflective) I have advised others to use this brand’s products.(5-point Likert scale)

I sometimes defend this brand in conversations.(5-point Likert scale)

Table A2. Operationalization of Independent Regression Variables (Extended Study).

Variable Operationalization

Income Monthly household net income1 = up to 1.000 EUR2 = 1.001 to 4.000 EUR3 = over 4.000 EUR

Education 1 = no or lower secondary school2 = midlevel secondary school3 = secondary school-leaving certificate

Age metric scaleGender 1 = male

2 = femaleType of goods 1 = physical product

2 = service


an extended search for generic consumer-brand relationships

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