Brand Congruence in Interpersonal Relations: A Social Network Analysis PETER H.

8/14/2019 Brand Congruence in Interpersonal Relations: A Social Network Analysis PETER H.

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Brand Congruence in Interpersonal Relations: A Social Network AnalysisAuthor(s): Peter H. Reingen, Brian L. Foster, Jacqueline Johnson Brown, Stephen B. SeidmanSource: The Journal of Consumer Research, Vol. 11, No. 3 (Dec., 1984), pp. 771-783Published by: The University of Chicago PressStable URL: http://www.jstor.org/stable/2489067

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772 THE JOURNAL OF CONSUMER RESEARCHREFERENCE GROUP INFLUENCEAND BRAND CHOICE

Much of the extant literature on reference groups'influence on consumer brand choice falls into twomajor research streams, which can be distinguished interms of methodology and conceptual foci: informalgroup studies and perceived influence studies.Informal Group Studies

The informal group studies by Stafford (1966), Witt(1969), and Witt and Bruce (1970, 1972) have incommon an attempt to relate group cohesiveness tobrand choice congruence within groups. In these stud-ies, group membership was determined by first askinga set of subjects to nominate others (e.g., friends,relatives, or neighbors), and then by obtaining partic-ipation of the nominees. These studies assert thatinformal groups exert influence toward congruenceon member brand choices (e.g., Stafford 1966) andthat the extent of influence varies with group cohe-siveness (Witt 1969) and the nature of the product(Witt and Bruce 1970, 1972). However, the evidencein support of the informal group influence hypothesisis contradictory. For example, Hansen (1969) wasunable to support the existence of a relationshipbetween group cohesiveness and brand congruence,and Ford and Ellis (1980) were unable to replicate theStafford (1966) findings.Perceived Influence Studies

The perceived influence studies by Bearden andEtzel (1982) and Park and Lessig (1977) employedsurvey methodology to assess various types of perceivedreference group influence across products. Based onthe work by Deutsch and Gerard (1955), Jahoda(1972), and Kelman (1961), Park and Lessig developeda scale to measure informational, utilitarian, andvalue-expressive reference group influence. Subjectswere asked to assume that an individual had decidedto purchase a product but had not yet decided whichbrand of the product to buy. They then were givenverbal descriptions of situations representing the dif-ferent kinds of reference group influence. Finally, theywere asked to indicate for each product to what extenteach situation was relevant to his or her brand choice.Overall, the Park and Lessig (1977) findings suggestgreater susceptibility to reference group influence forstudents than for housewives.

Using the framework originally proposed by Bourne(1957), Bearden and Etzel (1982) expanded upon Parkand Lessig's work in an excellent study which inves-tigated when reference groups exert influence. Forpublicly consumed products, it was hypothesized thatreference group influence for the brand of the productshould be strong because brand consumption will beseen by others, whereas for privately consumed prod-ucts, influence should be weak because brand con-sumption will be inconspicuous. As in the Park andLessig (1977) study, subjects were asked to indicatetheir agreement with statements manifesting the typesof reference group influence as they applied to productor brand selection decisions. The results supportedBearden and Etzel's hypothesis about differences inperceived reference group influence between publiclyand privately consumed products.Finally, Moschis (1976) employed Festinger's (1954)theory of social comparison to explain why informalgroups influence purchasing behavior.2 Group influ-ence was determined by having subjects indicate theirextent of agreement with statements such as "Manycosmetic items I own are similar to those of myfriends" (p. 242). Although Moschis found that "in-'formalgroups exert a great influence on their members'purchasing behaviors" (p. 240), it is apparent that noactual informal groups were examined in his study.Limitations of Previous Studies

These studies have yielded important insights intoreference group influences on consumer behavior andhave identified an important area for research. Nev-ertheless, they suffer from several limitations whichrender suspect certain aspects of the produced evi-dence.

Group Definition. One major problem with theinformal group studies by Stafford (1966), Witt (1969),and Witt and Bruce (1970, 1972) centers aroundgroup definition. Since a group consisted of a nomi-nator and several nominees in those studies, it ispossible that the selection procedure yielded groupswhich were diverse in basic sociological structure. Forexample, in one case a group might consist of individ-uals, each of whom is tied to every other in a socialrelation (e.g., friendship), while in another instancethe nominator might be tied to every nominee, butthe nominees may not be tied to each other. Thesetwo structures have completely different sociologicalmeanings. The first case illustrates a basic structurewidely discussed in sociology-the clique. For somepurposes, the second example may not qualify as aninformal group at all in the sociological sense: mostpersons, for instance, are either not interdependent orcompletely unaware of each other's existence.

"reference group" has become established by long usage, so it isemployed here. However, for the informal group studies examinedlater, the groups should have characteristics similar to more tradi-tionally defined groups. Although there is a lack of agreement aboutwhat does and does not constitute a group, it is generally suggestedthat several persons can be considered a group when they areinterdependent or are aware of each other (Ford and Ellis 1980).2 Since the Moschis (1976) study did not examine actual brandchoices, it is classified here as a perceived influence study.


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NETWORKANALYSIS OF BRAND CONGRUENCE 773That the second case is not an unlikely phenomenonis suggested by Ford and Ellis (1980) who, in theirreplication study of Stafford (1966), found that at leastfour of their 10 groups had members who did notknow the other group members (p. 131 .3 Also, Witt

(1969, note 2) points out that his group selectionprocedure may have yielded "groups" that were ref-erents for the nominator but not for the other mem-bers. It is unlikely that meaningful data are obtainedwhen there is substantial heterogeneity in the natureof the units due to the concept of group being poorlydefined. In fact, in these previous informal groupstudies, some groups may not have been groups atall-even under very relaxed conditions for whatconstitutes such a structure. A more appealing strategy,both conceptually and statistically (in the sense ofminimizing extraneous sources of systematic varianceand error variance arising from an imprecise groupdefinition), would be to assess brand congruence ingroups whose sociological and formal structural prop-erties are systematically and precisely controlled.

Influence Assessment. A second major problemwith several of the informal group studies relates tohow informal group influence is assessed. Stafford(1966), for instance, suggests that informal groupinfluence is demonstrated when within-group brandchoices are similar, but when the groups vary amongthemselves (p. 71). This may not hold in general.Consider the following scenario. All group membersand all groups agree on the same brand "X." Accordingto the Stafford criterion, there would be no informalgroup influence. Missing, however, are comparisonsbetween persons who are in a group and those whoare in no group. In a second scenario, imagine thatsuch controls are available. Suppose further that allpersons who are not in a group choose brand "Y."The inferences about group influence resulting fromthe two scenarios would be diametrically opposed. Wesuggested that a more convincing case can be madefor or against the informal group hypothesis by com-paring the brand choices within a group against thechoices of individuals who are in a different groupand in no group. In short, informal group studieswhich examine choice behavior only within/acrossgroups contain a serious design flaw: group influenceis an intragroup phenomenon, so its presence orabsence is not directly testable through intergroupmethods (Ford and Ellis 1980).Perceived Influence. Although the perceived influ-ence studies by Bearden and Etzel (1982), Moschis(1976), and Park and Lessig (1977) have yielded

important information on various types of influenceand on when/why reference groups may affect buyerbehavior, by their very nature they only suggest thepossibility of reference group influence, since no directevidence is provided.Types of Social Relations. There is an additionalshortcoming in the literature which is common toboth research streams: the investigators assumed thatcertain types of social relationships form the basis forreferencegroup influence. Friends, relatives, neighbors,or fellow students may or may not be the referents ofan individual employed in brand decision-making forthe products examined in the Hansen (1969), Moschis(1976), Stafford (1966), Witt (1969), and Witt andBruce (1970, 1972) studies. Similarly, an individual'sfellow workers may or may not be the appropriatereferents for pool tables in Bearden and Etzel's work(1982, p. 187). It would seem advisable, therefore, toexamine brand congruence in basic sociological struc-

tures that arise from different types of social relation-ships. One may find brand congruence for breadamong family members, for example, but such con-gruence is less likely in a group of acquaintances whoplay touch football. Thus, the type of social relation-ships under investigation may be an important pre-dictor of brand congruence.A second reason why an examination of the effectof type of social relation on brand congruence maybe important concerns the notion of brand visibility.In the traditional approach, a private product is op-erationally defined as one used at a person's residence(Bearden and Etzel 1982, p. 186). Since brand con-sumption of such a product would not be sociallyconspicuous, it is argued that purchasing behavior islargelygoverned by attributes rather than by influencesof others (Bourne 1957). However, there is a potentialproblem with this traditional argument. It fails to takeinto account the effect of social interaction on brandvisibility. Social relationships may channel opportu-nities for observation of brand choice, and they mayprovide a stimulus for brand-related verbal commu-nications. That is, social relations may make brandchoice behavior visible even for "private" products.For example, one may find brand congruence amongmembers of a group of frequently interacting friendseven for "private" products such as laundry detergent,kitchen soap, and refrigerators, which the literature todate claims are not subject to group influence (e.g.,Assael 1981, pp. 332-333). Thus conspicuousness, astraditionally defined, may not necessarily be a goodpredictor of brand congruence.

OVERVIEWAlthough group influences on consumer behaviorare commonly judged to be pervasive (e.g., Zaltmanand Wallendorf 1983, p. 197), the previous discussion

3Perhaps this is a reason why Ford and Ellis (1980) failed toreplicate the Stafford data. Stafford (1966, p. 70) claims that hisgroups consisted of women who were friendly toward each otherand who interacted among each other, but no direct data arefurnished.


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774 THE JOURNAL OF CONSUMER RESEARCHsuggests that the evidence produced to date is lessthan compelling and is sometimes even contradictory.To summarize the arguments presented thus far, theprevious literature suffers from:

1. Imprecisedefinition(determination)of groups2. Questionablemeasurementof brandcongruenceef-fects3. Lack of a systematicattemptto examine the brandcongruence notion across different types of basicstructure(e.g., "true cliques" and other "clique-like" structures)4. Inadequate attention to the way congruence mayvaryacross different ypes of social relationships5. A tendency o see perceived eference roup nfluenceas evidence for direct influence.

The most general goal of the present study is toaddress these shortcomings by examining brand con-gruence among individuals in empirical systems ofsocial relationships-what Radcliffe-Brown (1965, p.190) called "the network of actually existing rela-tions"-using recently developed techniques for socialnetwork analysis. The study is exploratory in nature.Although it was expected to yield important substantiveinsights, the emphasis of the research was on illustrat-ing how the limitations in previous investigations canbe effectively addressed with social network analysis.Our primary goal was to make a methodologicalcontribution to the study of consumer sociologythrough an exemplary application of formal algorithmsfor network analysis.The overall research strategy was as follows: statedbrand choices (and preferences) of individuals in aspecified social relationship were compared with thoseof individuals who were not in that social relation.The comparison was carried out across various typesof social relation (e.g., friendship, roommate) andacross a series of tangible/intangible products (e.g.,shampoo, TV show). Moreover, analysis focused onbrand congruence within several kinds of basic socio-logical structures or groups. Before this analysis isdescribed in more detail, some general comments onthe network analysis of social structure will be helpful.Network Analysis of Social Structure

Anthropologists, sociologists, and other social sci-entists have been concerned with precisely the kindsof methodological problems that arise in the consumerbehavior literature reviewed here. In fact, a classicproblem in social science concerns the relationshipbetween individual behavior (e.g., individuals' socialdecisions) and social structure (e.g., the nature of thesocial networks in which individuals find themselves).In many diverse contexts, a prerequisite to addressingthe relationship between individual behavior and social

structure is finding a precise and general way ofrepresenting properties of social structure. Some ofthe most promising results in this area have come tobe called "social network analysis," which is beingcarried out by researchers in sociology, anthropology,psychology, communications, mathematics, and otherfields.The basic ideas behind social network analysis havebeen present in social anthropology and sociology formany years in the writings of Radcliffe-Brown (1965),Nadel (1957), and others. In general, network analysisprovides a formal and precise way of defining termslike "relation," "clique," and "group""so that theycan be applied unambiguously to data on populationsof individuals. Several formalisms have been adoptedby social scientists, including various statistical andalgebraic techniques (see Burt 1980 and Knoke andKuklinski 1982 for recent reviews). The most widelyused, however, is graph-theoretic.In Foster and Seidman's (1981, 1983) graph-theo-retic method-the one adopted here-graphs are usedto represent relationships among individuals. A graphis simply a set of points, some or all of which arejoined by lines. In general, points represent individuals,and each line represents a relationship between a pairof individuals it joins. Each graph represents a singlerelation. A series of graphs may be used to representdifferent relations by having the lines in each graphcorrespond to a specified kind of dyadic relationship(e.g., each line represents a friendship tie in one graph,an employer/employee relation in another, and soon). It is in these graphs that features of social structure(including cliques and other groups) are defined usingconcepts from the mathematical theory of graphs.To use this formalism in social research, it isnecessary to identify patterns in graphs which corre-spond to meaningful sociological properties of thesociety represented by graphs. There are many waysto do so; one could, for instance, see if a graph istransitive or not, whether it is centralized or not, andso on. The theoretical problem of interest here, how-ever, concerns whether or not membership in socialgroups such as cliques is associated with greater brandchoice similarity, and the analytical task is to identifysubsets of graphs which correspond to meaningfulsocial groups.In the Foster and Seidman (1981) method, suchgroups and other social units are called basic structuralunits (or BSUs); in their general, abstract form, theyare called basic structures. An example of a BSU issuggested by a widely used notion in sociology, theclique. The first attempt to make a formal, graph-theoretic definition of clique was by Luce and Perry(1949), who defined a clique as a maximal completesubgraph of a graph-that is, the largest possible setof points of a graph such that each point is tied by aline to every other point. Such basic structures-maximal complete subgraphs-have several important


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776 THE JOURNAL OF CONSUMER RESEARCHdifferent methodological considerations. First, an ex-perimental design is probably not possible, since thepresent state of knowledge is insufficient to produce acompelling design for the issues we have identified.Second, a survey would not be very useful, since it isnot possible to get fine-grained data on most socialnetwork properties through samples. This is so becausewe would be sampling relationships, not individuals.At the present time, data on individual choices cansupport inferences about only the crudest networkproperties, not the properties of interest to us here.What is needed is very detailed information on asmall, natural community of some sort: this will helpus to avoid some of the pitfalls in the earlier studies,albeit at the cost of experimental controls and of alarge universe that would allow us to generalize to avariety of other cases.Subjects and Procedure

Subjects were 49 members of a sorority at a largeSouthwestern state university. Of the total number ofsubjects, 37 (75.5 percent) lived in the sorority houseand 35 (71.4 percent) were at least sophomores. Thesubjects were enrolled in various majors, with businessconstituting the largest single category (30.5 percent).The sorority was paid one dollar for each member'sparticipation.Subjects responded to a self-administered question-naire at one of their monthly meetings. Since sororitypolicy prohibited nonmembers from attending themeeting, some control over questionnaire administra-tion had to be sacrificed. The sorority president had,however, been carefully instructed to follow certainprocedures to minimize contamination of data (e.g.,due to interactions between subjects while completingthe task). The response quality of data obtained wasjudged to be at least satisfactory.Instrument

The instrument first provided some general instruc-tions and a brief cover for the study. This was followedby a strongly stated promise of confidentiality, sincethe subject was required to reveal not only her ownname but also those of individuals she interacted within various types of social relationships.Subjects were asked to furnish names of individualsfor the social relationships shown in the Exhibit.6

EXHIBITSOCIAL RELATIONSHIPS

Description Code Word1. A person's roommate. Roommate2. A person's neighbor(s) who lives adjacent

to her. Adjacent3. A person's neighbor(s) across the hall

who live(s) no farther away than theneighbor(s) living in rooms adjacent toher. Neighbor

4. With whom a person usually plays sports. Sports5. With whom a person usually studies. Study6. With whom a person usually eats her

meals (breakfast, lunch and/or dinner). Meals7. With whom a person usually shares a

bathroom at the same time. Bathroom8. With whom a person usually parties or

goes out with. Party9. A person's closest friends. Friend

10. With whom a person usually discusses avery personal problem. Problem

These were chosen to cover a broad spectrum ofimportant relations arising from spatial proximity,special occasions, and affective bonds. The subjectswere instructed to list names of individuals who wereeither within or outside of the sorority, since con-straining subjects to list only sorority members wouldproduce "artificial" social networks. A total of 568different individuals was named.Finally, for each of the products listed in Figure C,subjects were asked to furnish the name both of thebrand they usually buy/consume and of the brandthey prefer whether or not they buy/consume theproduct. Information on preferredbrands was obtainedin an effort to control indirectly for gifts and forconsumption patterns developed prior to joining thesorority. Under such conditions, congruence on brandsactually consumed may not be found, while congru-ence on preferred brands may be observed.The products listed in Figure C were selected froma preliminary list of 55 products.7 A pretest wasconducted on a convenience sample of 198 subjectssimilar to those in the study. These subjects ratedeach product on a five-point "private/public con-sumption" scale based on Bearden and Etzel's (1982)'For example, the roommate, adjacent, and neighbor namesfurnished by the subjects allowed for an internal check. Theinformation on roommate and adjacent had complete inter-subjectagreement, and the information on neighbor (the operationalizationof which was more difficult to comprehend-see Exhibit) had 88percent agreement. Furthermore, no overlap of membership acrosscliques should have occurred for bathroom, and no cliques shouldhave existed for neighbor and adjacent. These results were obtained.6 Names of persons with whom a subject had carried on a lengthyconversation during the previous 24 hours were also obtained.However, this social relation was eliminated from consideration.

The data were generatedduring the sorority'smonthly meeting;thus the informationon conversationwasjudgedto be less mean-ingful.7 Due to high degreesof nonusageamong subjects,data obtainedon home computers,cars, tennis racquets,and video gamesare notreported.


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NETWORK ANALYSIS OF BRAND CONGRUENCE 777FIGURE C

SUMMARY OF RESULTSProducts #1 #2 #3 #4 #5 #6 #7 #8 #9 10 #1 #12 #13 #14 #1 5 16Relations Shampoo Tootipaste Detrgeret Magazirne TVShow SodaPop Calculator Camera WrlstWatch Pizza Beer Sport TenniaShoe Jeans Restaurant Shirt/BlouseRelations D P C D P C D P C D P C D P C D P C D P C D P C D P C D P C D P C D P C D P C D P C D P C D P C

Roommate AV./ v L13,0,01 P XAdjacent A X XX

[23,2(12),0] P XA _Z__Z_I __Z ?1/__ -2 11 v-r7- ,11Neighbor A _ _ x

E35,23(49),0] p _ xx Z- A ASports A _ A- - I- k_Z- PV VV PV kV

(I17,0,0] p _zz_zz_zZ_ _ z/ [/_z/ z // 1l l // I/ V / V/ 1lStudy A X VI_z_Z I1 _ A I / M _[21,0,3(9)] P z__Z__Z-_ZC Z- A _Z-_Z / I/ IA I I/ I1 V1 1Meals A _ _ X x[96,92(183),29(68)] P _ I I I I IBathroom A X I xx xx xx _ xx[32,2(12),5(21)] p x XXParty A(62,15(59),16(51)J p _ xFriend A IXXXX

[57,4(25),7(24)] P _Problem A[47,3(16),4(15)] P _

x =p C 0.0005xx = P C 0.0001NOTE: Products #1 through #6 were "private" products; products #7 through #16 were "public" products. Based on the pretest data, products are listed from most private to mostpublic. Products #1 through #4 and #12 through #16 deviated from the scale midpoint by at least 0.5. Numbers in brackets under relations show the number of dyads, 2-plexes, andcliques, respectively. Numbers in parentheses within brackets show the number of pairs for 2-plexes and cliques, respectively. Empty cells indicate nonsignificant findings (p > 0.0005).Diagonal lines in cells indicate no 2-plex or clique substructures. D = dyad, P = 2-plex, C = clique, A = actual brand, P = preferred brand.

formulations. The final selection of products wasgoverned first by the requirement that brand con-sumption of each was likely to be visible in at leastone of the social relationships (e.g., bathroom/sham-poo, TV/roommate, beer/party). Second, the tradi-tional argument that greater brand congruence isexpected for "publicly" than for "privately" consumedproducts was incorporated into the study by includingproducts which clearly fell (>3 ? 0.5) in either theprivate or public direction of the scale in the pretest(see note for Figure C). It bears repeating that thetraditional scaling of a product's conspicuousness wasundertaken primarily to illustrate its shortcomings asa predictor of brand congruence in the absence ofcontrolling social relations. As already discussed, effectswere expected for "public" as well as for "private"products, as determined by the pretest.Data Analysis

After coding the data, analysis was performed withSONET-1 (Foster and Seidman 1978; Seidman andFoster 1979), a package of computer programs forgraph-theoretic analysis of social structure. The datafor each social relation were first submitted to MAT-COMP, which constructs a sociomatrix to representthe graph for each relation. MATCOMP then searchesfor connected components (i.e., largest possiblesubgraphs such that any two of its points are joinedby a path) in the graphs. Relations were symmetrized(e.g., persons A and B are in a social relation if at

least one chooses the other) for several reasons. First,it is commonly found (as in the present study) thatfew if any social relations in a clique, for example,are symmetric (i.e., that every person chooses eachother). This may lead to unwarranted conclusions byignoring structure present in a social system. Second,there is no compelling theoretical reason to assumethat choices have to be symmetric for influence tooccur.The MATCOMP output was then submitted toSTRUCT, which searches for cliques and 2-plexes.The details are unimportant for our present purposes,but for cliques the algorithm searches for sets of pointssuch that each point is connected to every other point,whereas for 2-plexes it determines basic structureswith n points such that each point is adjacent to atleast n - 2 others but not to every other point. Thedata are output in a manner that allows each personto be matched with the cliques (2-plexes) of which sheis a member. This information is then entered in an"attribute file" along with some basic demographicsand brand choices. These attribute files, along withan adjacency matrix of all ones, are input to a programcalled CAT3 which does a series of pairwise searchesto determine whether or not each pair of individualsis in a clique (2-plex) together, makes the same brandchoice, and so on.The output of CAT3 is a subset of the adjacencymatrix, containing ones only in cells where, say,common brand choice occurs. These subset adjacencymatrices are input to a program called STAT which


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778 THE JOURNAL OF CONSUMER RESEARCHtransforms the data to make them suitable for cate-gorical data analysis. Our data did not lend themselvesto multivariate approaches to categorical data analysis(e.g., logit-type modeling) that would have enabled usto draw inferences beyond what is reported here andto subject the brand congruence hypothesis to a stron-ger test. The data were strongly nonindependent andunbalanced-e.g., many pairs were in the same BSUfor more than one type of social relation, dyads incliques formed a subset of the entire set of dyads, andpairs were in a clique for one social relation but in a2-plex for another. A large number of zero counts(when no cliques and/or 2-plexes were found) posedan additional limitation.It was therefore decided to separately examine thenonempty cells of Figure C through a series of 2 X 2contingency tables, one dimension being "in a com-mon BSU/not in a common BSU" and the otherdimension being "common brand choice/not commonbrand choice." The frequencies in the tables werebased on pairwise comparisons. Thus, the same unitof analysis was employed for each of the types of basicstructure, making statistical analysis more feasible.Statistical tests employing Chi-square were run sepa-rately for each cell in the 10 (relations) X 2 (actual/preferred brand choices) X 3 (dyad, clique, 2-plex)X 16 (products) overall data matrix. A total of 960tests was possible, but 736 were actually performed,since for five of the 10 social relations no cliques or2-plexes existed. In the case of clique or 2-plex overlap(when a pair of individuals was in more than oneclique or 2-plex for a social relation), a pair wascounted only once.

RESULTSFigure C summarizes the (corrected for continuity)Chi-square results of comparing the brand congruenceof co-members and non-co-members in a specifiedtype of BSU in a specified social relation. Data dis-cussion and interpretation are restricted to those testswhich were significant at p c 0.0005 or p < 0.0001 toguard against the increased probability of findingsignificant results due to the large number of tests.8

Brand Congruence EffectsOf the 736 statistical tests, 26 were significant at p

c 0.0005 and 13 of them were significant at p c 0.0001.Percentage differences were also examined; all of the

significant results were in the predicted direction. Theaverage raw effect (percent brand congruence for per-sons in a BSU minus percent brand congruence forpersons not in one) was 28.9 percent across thesignificant findings (range: 11.8 percent for study/shampoo/dyad to 50.5 percent for friend/pizza/2-plex). Overall, these findings support the expectationof significant brand congruence effects for several ofthe cells in Figure C, even when stringent statisticalcriteria are applied.Also in accord with expectations, significant productresults appear to be dependent on the type of socialrelation and type of basic structure (e.g., pizza/neigh-bor/2-plexes). Although we cannot be certain on thebasis of the present data, this suggests an explanationfor the tendency of the brand congruence efforts to beclustered in only a few products, e.g., TV show, pizza,and restaurant.

Determinants of Brand Congruence Effects:Exploratory AnalysisTo address these questions, attention was focusedon the extent to which the product and type of socialrelationship affected the findings. Although formalstatistical procedures had to be largely abandoned atthis point in favor of a more descriptive approach dueto the data limitations already specified, this lessformal analysis yielded several important insights.Conspicuousness Criterion. As expected, the tra-ditional prediction that the most pervasive brandcongruence would occur with the "public" productsdoes not appear to be consistent with our findings.

The previous literature suggests that brand congruenceeffects would be especially strong for "public" productssuch as clothing and beer (Assael 1981, pp. 332-333)as well as for wristwatches (Bearden and Etzel 1982,p. 190). Yet, none of our findings were statisticallysignificant for these products: on the contrary, signif-icant findings were obtained for "private" productssuch as shampoo and toothpaste. It would be difficultto argue that products such as shampoo and toothpasteare more conspicuous across the various types ofsocial relationships than are products such as runningshoes, jeans, shirt/blouse, wristwatch, and beer, butthis is not to suggest that conspicuousness is unnec-essary for brand congruence to occur. Products wereselected so that their consumption was likely to bevisible in at least one of the types of relation (e.g.,shampoo/bathroom). However, the conspicuousnesscriterion appears to be insufficient to account for thestudy's findings, even when the effect of type of socialrelation on brand visibility is taken into account.

Overlap. That being so, attention was directed athow cliques (or other BSUs) were joined together byoverlapping membership and how BSUs in differentsocial relations intersected. Discussion is limited to

8 Due to nonindependenceacross tests, an exact p = value forthe familyof tests could not be determined.Thelevel of significanceof p ? 0.0005 was judged to be a reasonablecompromisebetweenthe exploratorynatureof the study on one hand, and extremelyconservativestandardson the other. Note that for many of thecells in FigureC significanteffects should not be expectedon apriorigrounds.


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NETWORK ANALYSIS OF BRAND CONGRUENCE 779FIGURED

SIGNIFICANTBRAND AGREEMENTIN FRIENDSHIPCLIQUES45 10 -44 38510

13 ~1010o10 92 190

0 ~~~~~~10 6

299 379 399 / 408

10

401 511340 18NOTE:The number along a solid line indicates actual brand agreement in a clique pair for product #10 (pizza). The following are cliques: (2, 13, 75, 94); (2, 13, 94, 529); (18, 340, 529);(44, 45, 75); (92, 190, 385); (299, 379, 401); and (399, 408, 511).

cliques, because the sheer number of dyads made fordifficult interpretation and graphical depiction, andbecause an analysis of overlap for 2-plexes yieldedessentially the same conclusions as for cliques. Over-lapping clique membership in a given relation isimportant because it provides insights into how brandcongruence within cliques is transmitted outside thecliques. And intersection of cliques within differentrelations is important sociologically because such''overlap" may suggest especially cohesive groupingsof individuals-a property which previous researchsuggests is related to brand congruence (e.g., Stafford1966; Witt 1969).Figure D shows overlap of individuals in differentfriendship cliques along with the members' pairwisecongruent brand choices for pizza (raw effect = 36.2percent). Four of the seven cliques overlap (i.e., atleast one member belongs to more than one clique);overlapping cliques account for 100 percent of thepairwise congruence data for pizza. Figure D is anextreme example in which overlap of individualsacross cliques completely spanned the brand congru-ence effect for one product. In general, clique overlapof individuals for a type of social relation could not

account for all of the data. For example, bathroomcliques did not overlap, yet significant findings wereobtained.Friendship cliques (2, 13, 75, 94) and (2, 13, 94,529) together form a 2-plex, and these cliques werefurther examined to obtain insights into the effects onbrand choice of intersections across different socialrelations. The substructure (2, 13, 94, 529) was foundto be a clique for the social relations friend, meal,party, and problem and the substructure (2, 13, 75,94) was found to be a clique for friend, meals, andparty. Figure E shows this clique overlap across rela-tions graphically, along with information on actualbrand congruence for each pair. Congruence is shownfor all products to generate exploratory insights. Pair-wise brand agreement varied from one product toanother even though these cliques were probably co-hesive. At one extreme, there was complete within-pair and across-pair agreement for the products pizzaand running/tennis shoe. At the other extreme, not asingle pair agreed on actual brand choices for shampoo,magazine, and camera. Clearly, the relationship be-tween clique co-membership and congruent brandchoice depends heavily on the product.


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780 THE JOURNAL OF CONSUMER RESEARCHFIGURE

OVERALLRANDAGREEMENTSNTHREEMULTIPLEXLIQUES3 6 10 13 316

529

2 5 10 13 14| / \ p2 8 10 13 14|....._.._.._._._._... ------.___ _------- -- ------~~~~f131~~~~1>.73 10 11 13 15| j 0

L10 13 ;2 .._...__.__::__.__ 94 10 11 13 15||910 12 13 | 2 3 7 10 13 14

Party relations in clique (2, 13, 75, 94, 529)*-----------------riend n Meal n Party n Problem relations in clique (2, 13, 94, 529)-------- Friend n Meal n Party relations in clique (2, 13, 94, 75)NOTE: Numbers in a rectangle indicate actual brand agreements in a clique pair for the relations as specified above. These numbers correspond to the products listed in Figure C. Forexample, the pair 529/75 agrees on brand choices for products 10 and 13, the pair 2/75 agrees on brand choices for products 10 and 13, etc.

It should be emphasized, however, that clique in-tersection across several social relations was relativelyunusual. There were only three other cliques whichshowed overlap across at least three social relations.Nor is it suggested that intersection across differentrelations is necessarily important. Counter examplesare easy to find; for instance, bathroom cliques showedvirtually no overlap across relations, but significantbrand congruence effects.This sort of intersection has been widely discussed(sometimes called multiplexity, sometimes many-strandedness), and we thought it important to furtherexamine the data with an eye to such intersections.Pairwise brand agreement for all products was com-

pared between multiplex cliques (i.e., intersectionacross at least three social relations) and cliques thatwere relation-specific. The five cliques previouslyidentified met the criterion of multiplex cliques, andthere were seven cliques which were not only relation-specific but which also had pairs that were pairs foronly that specific relation. For both actual and pre-ferred brands, there was significantly greater overallbrand congruence for multiplex cliques (X2 = 10.99,p < 0.01, x2 = 10.42, p < 0.01, respectively). It shouldbe noted, however, that this overall result is dispro-portionately accounted for by cliques (2, 13, 94, 529)and (2, 13, 75, 94) and their complete agreement forthe products pizza and running/tennis shoe.


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NETWORK ANALYSIS OF BRAND CONGRUENCE 781DISCUSSION

In the interpretation and discussion of these findings,it is necessary to carefully balance the study's strengthsand limitations, since it is exploratory and had a non-experimental design. On the one hand, the sororitysurely has characteristics that differentiate it fromother social systems, such as neighborhoods, colleaguesat work, or bridge clubs. For example, brand choicebehavior may be unusually visible, and there may bemore joint consumption behaviors across a widerrange of products than would be expected for othersocial systems. On the other hand, this limitation iscompensated for by maintaining much greater controlon the kinds of relations and social groups than isusually present. The sorority setting limits thestraightforward application of results to other cases inmuch the same way and for analagous reasons thatexperimental results are difficult to generalize. Yet thereal issue here is the controlled selection of relations,products, and social structures. It is in this sense thatthe study is most profoundly exploratory: its majorsubstantive contribution is that variation in types ofrelations and group is important and appears to inter-act with type of product to produce brand congruence.It may well be possible to return to broader-basedsurvey methodology to address the problem of gener-alizability or to engage in experimental work to dealwith causality issues when the fundamental dynamicsrelating different kinds of relations, structures, andproducts are better understood, but a great deal moreexploratory work is needed in this area before thatwill be productive.9It is also worth emphasizing that the method ofanalysis employed here was exploratory in the sensethat it is not wholly sufficient in itself to address thebrand congruence question. Rather, it illustrates thepoint that other analyses have missed important di-mensions of brand congruence by ignoring crucialcomplexities of social structure. To draw inferencesbeyond what is reported here and to subject the brandcongruence hypothesis to a stronger and generallymore sufficient test through multivariate approachesto categorical data analysis would require a morecomplex design. For example, types of social relationand product could be randomized across different butmatched social systems (e.g., several similar neighbor-hoods) to deal with the problem of non-independencewhich limited our approach to data analysis. Of course,

this would have increased the complexity of the datastructure greatly, thus limiting its use as illustration.Overall, the results described here strongly suggestthat brand congruence depends heavily on a complexmix of type of product, type of social relation, andtype of social structural unit. In general, of course,the fact that we found significant brand congruenceeffects confirms previous findings of studies dealingwith the impact of informal groups on member brandchoices (Stafford 1966; Witt 1969; Witt and Bruce1970; Witt and Bruce 1972).1o This is importantbecause we used a very different and more validmeasure of social structure than did previous studies.It is also important because previous studies have notsystematically examined types of social relation andbasic structure, and their methodologies have beenfound to be suspect on several other grounds.Our results also support the more specific, earlierfindings of a correlation between group cohesivenessand member brand choice, in that we found signifi-cantly greater overall brand congruence for multiplexcliques than for relation-specific cliques. Although wedid not directly measure cohesiveness, it seems plau-sible that multiplex groups-i.e., cliques which occurin several different relations-are mQrecohesive thanthose which are specific to a single relation. Still, notall multiplex cliques showed brand congruence, andnot all brand congruence occurred in multiplex cliques.And in any case, congruence varied by product. Clearlythere remains a great deal to explain.Much of the uncertainty revolves around the natureof product and the notion of product visibility. Thetraditional conspicuousness hypothesis appears to be

9Although he study shareswith previous nformalgroup studiesthe problems of generalizabilityand causality, it should be re-emphasizedthat its basic goal was to illustratehow other majorlimitationsin previousinvestigationscan be effectively addressedwithsocial networkanalysis.Social network tudies typicallysufferfrom these problems because social systems tend to have someunique characteristicsand membersin voluntarysocial systemstend to have more similarpersonalattributes.

10No judgment is made on the pervasiveness of the brandcongruencephenomenonfoundin the study. Persuasiveargumentscould be advanced on both sides of the issue. On one hand, thefindingscould be interpretedas suggesting hat brand congruenceis not as pervasiveas previous studies might imply. The currentresearch ocused on primary nformal groups-the type of groupgenerally suggested to have the strongest influence on memberbehavior.The subjectswere students,who have been found to bemore susceptible to reference group influence (Park and Lessig1977). Note further that (based on previous studies) the socialsystem environmentwas one which allowed for strong visibilityofbrandconsumptionacrossa wide arrayof products.Yet relativelyfew of the tests were significant.On the other hand, it could be argued that the current studyunderstates he case of brand congruence or sociallyrelated ndi-viduals.The statistical tandardswere quite conservative,yet manytests survived them. (For the reader who wishes to applya moreconventionallevel of statistical significance,127 of the cells weresignificantat p ? 0.05.) It could also be pointed out that manycells in the design should not be significanton a priori grounds(e.g., bathroom/calculator, ports/detergent, tc.) and that brandchoice behaviorwas perhaps nfluencedby previoussocial interac-tion. Finally, the insignificant effects for many products do notnecessarily mply that referencegroup nfluencewas not operating.A person may have many referencegroups (Shibutani 1955), andthe study may not have capturedthe relevant ones in its list ofsocial relations.


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782 THE JOURNAL OF CONSUMER RESEARCHinsufficient and too imprecise to account for ourfindings: significant effects were sometimes observed,but in many instances they were not found (e.g.,jeans, shirt/blouse, tennis/running shoe). Perhapsworse, the conspicuousness hypothesis in its originalform may be virtually untestable in correlationalstudies, since type of relation is uncontrolled andsome social relations may allow for brand identificationfor products generally judged to be private. Even whenone defines a public product as one that is publicacross many social relations, the present data do notappear to support the proposition that brand congru-ence will necessarily follow.There are other ways in which the existing literatureseems to fail to explain the present findings. What,for example, may explain the fact that in our study,the products TV show, restaurant, and pizza accountedfor the majority of the significant findings? It isdifficult to account for this in the literature. In onediscussion that addresses this kind of issue, Robertson(1971) maintains that products low in visibility, com-plexity, and perceived risk and high in testability areless susceptible to personal influences than are productshigh in visibility, complexity, and perceived risk andlow in testability. Yet it would be difficult to arguethat TV show choice (for which significant brandcongruence effects were found) is higher in visibility,complexity, and perceived risk and lower in testabilitythan is wristwatch brand choice (for which no signif-icant brand congruence effects were obtained).We suggest something more like the following. It islikely that for products such as TV show, restaurant,and pizza, joint brand consumption in interpersonalsettings is a more frequent phenomenon than it is forproducts such as watch, jeans, shirt/blouse, and soon. Joint brand consumption may be preceded byinterpersonal decision making ("What do you wantto watch?" "Where do you want to go?") among theindividuals who comprise a certain basic structure fora type of social relation. As far as the significantfindings for shampoo and magazine are concerned,shared brand consumption is also a possibility in thesocial system under investigation. lPerhaps joint consumption settings (many of whichmay be preceded by interpersonal decision making)are particularly important loci of influence. Beforeaccepting that possibility, however, it should be notedthat interpersonal brand agreement is not necessarilydue to influence. Although previous investigators haveattributed brand congruence to informal group influ-ence, it is conceivable that brand congruence may bedue to interpersonal similarity. This similarity amonggroup members may manifest itself in greater brand

congruence; thus it may be an alternative explanationto the results obtained here and in previous informalgroup studies.This alternative interpretation cannot be entirelydiscounted, but several aspects of the data render itless plausible. First, it would be difficult to explain bya similarity argument why congruence effects werelimited to only certain cells of the overall data matrix.For example, significant results were obtained in thefriend/pizza cells. If similarity in brand decisionsresulted primarily from shared personal attributes,why were the results for all the other products insig-nificant? Second, the previous analysis on multiplexcliques revealed no brand agreements for several prod-ucts. The extent of shared personal attributes shouldbe especially strong for members of multiplex cliques.Finally, it is important to recognize that brandcongruence effects were limited to certain products,types of social relation, and types of basic structureinterdependencies. Although the present data do notallow us to provide specific insights into the workingof these interdependencies, they suggest that types ofsocial relations may channel joint/shared consumptionprocesses (e.g., roommate/TV show; neighbor/pizza).What is common to all of these observations is thedifficulty encountered in addressing them without theuse of sensitive, precise, and computable measures ofsocial structure such as those used in network analysis.At least three capabilities are needed: (1) to work withmany relations-singly and in combination, (2) towork with different types of social units whose prop-erties have solid justification in social theory, and (3)to relate both of these analytically and conceptuallyto the properties of products under investigation. Ofcourse, this program is demanding in its data require-ments, and ingenuity in research design and datacollection are necessary. We suggest that social networkanalysis can provide valuable conceptual and com-putational foundations for carryingfurther the programwe have outlined in this study.[Received November 1983. Revised August 1984.]

II We examined he distributions f brandchoicesfor the productsand found the shape of the distributionsunable to account for theeffects.

REFERENCESAlba, Richard D. (1973), "A Graph-Theoretic Definition ofa Sociometric Clique," Journal of Mathematical Soci-ology, 3, 113-126.Asch, S. E. (1953), "Effects of Group Pressure Upon theModification and Distortion of Judgments," in GroupDynamics, eds. D. Cartwright and A. Zander, NewYork: Harper & Row.Assael, Henry (1981), Consumer Behavior and MarketingAction, Boston, MA: Kent.Bagozzi, Richard P. (1981), "Attitudes, Intentions, andBehavior: A Test of Some Key Hypotheses," Journalof Personality and Social Psychology, 41, 607-627.Bearden, William 0. and Michael J. Etzel (1982), "ReferenceGroup Influence on Product and Brand Purchase De-


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Brand Congruence in Interpersonal Relations: A Social Network Analysis PETER H.

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