How to Make Brand Communities Work: Antecedents and Consequences of Consumer Participation

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How to Make BrandCommunities Work:Antecedents and Consequencesof Consumer ParticipationDavid M. Woisetschläger a , Vivian Hartleb b &Markus Blut aa University of Dortmund,b University of Muenster,Version of record first published: 12 Dec 2008.

To cite this article: David M. Woisetschläger , Vivian Hartleb & Markus Blut (2008):How to Make Brand Communities Work: Antecedents and Consequences of ConsumerParticipation, Journal of Relationship Marketing, 7:3, 237-256

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How to Make Brand Communities Work:Antecedents and Consequences of Consumer

Participation

David M. WoisetschlagerUniversity of Dortmund

Vivian HartlebUniversity of Muenster

Markus BlutUniversity of Dortmund

ABSTRACT. The majority of brand community literature deals with theexploration of the nature of brand communities and the measurement ofcommunity effects. However, existing literature on how to implement andto manage company-run brand communities is rare. In the present article,we conceptualize drivers and consequences of consumer brand communityparticipation and empirically test our model with a data set of 1,025 mem-bers of a virtual brand community. Results indicate that identification withcommunity, satisfaction with community, and degree of influence explainmost of the variance in consumer participation. Moreover, positive influ-ences of participation on recommendation behavior, brand image of the

David M. Woisetschlager is Assistant Professor of Services Management, Uni-versity of Dortmund, Dortmund, Germany.

Vivian Hartleb is Research Assistant, Marketing Center Muenster, Universityof Muenster, Germany.

Markus Blut is Assistant Professor of Marketing, University of Dortmund,Germany.

Address correspondence to: David M. Woisetschlager, University of Dortmund,Otto-Hahn-Str. 6, Dortmund, Germany. (E-mail: [email protected].)

Journal of Relationship Marketing, Vol. 7(3), 2008Available online at http://www.haworthpress.comC© 2008 by The Haworth Press. All rights reserved.

doi: 10.1080/15332660802409605 237

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238 JOURNAL OF RELATIONSHIP MARKETING

community sponsor, and intention to continue community membership canbe confirmed.

KEYWORDS. Brand community, consumer participation, brand image,word–of–mouth, community loyalty

INTRODUCTION

Within the past decade the Internet has become one of the most importantand most commonly used communication media (Lagrosen, 2005). It of-fers boundless possibilities for information and communication exchangewithout any geographical restrictions. Especially over the past few years,groups with common interests or problems have increasingly been orga-nizing themselves into blogs or virtual communities (e.g., Apple, HarleyDavidson, Saab, Tom Petty, Xena)—a phenomenon that is of interest toboth academic research and marketing practice (Carlson, Suter, & Brown,2008). According to Boorstin (1973), consumers with similar norms, val-ues, and habits (e.g., the consumption of the same brand or product) formgroups called communities of consumption. A special kind of communityof consumption is a brand community, which is defined as “a specialized,non-geographically bound community, based on a structured set of so-cial relationships among admirers of a brand” (Muniz & O’Guinn, 2001,p. 412). Unlike the much broader concept of communities of consumption,the center of a brand community is the brand itself; therefore, consumersjoin these communities to exchange experiences with other like-mindedpeople fascinated by a specific brand.

Two main streams of research can be identified from the existing brandcommunity literature: first, studies in which the nature of brand communi-ties is explored and, second, studies that deal with measurement of the out-comes of customers’ brand community engagement. Muniz and O’Guinn(2002) as well as Schau and Muniz (2002)are among the earliest proponentscontributing to the first stream of research. Whereas Muniz and O’Guinnassessed the three core components of brand communities as (a) “con-sciousness of kind,” (b) “shared rituals and traditions,” and (c) “a senseof moral responsibility” and identified brands as a social phenomenon,Schau and Muniz (2002) analyzed several brand communities and re-vealed four types of relationships between individual identity and commu-nity membership: (a) subsumed identity, (b) super member, (c) community

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Woisetschlager, Hartleb, and Blut 239

membership as identity component, and (d) multiple memberships. Fol-lowing the customer-centric model of brand community of McAlexander,Schouten, and Koenig (2002), Ouwersloot and Odekerken-Schroder (2008)segmented brand community members into four categories based on con-sumption motivation: (a) enthusiasts, (b) users, (c) behind-the-scenes, and(d) not-me. Other starting points to explore the nature of brand commu-nities have been personal self-exhibition in front of other consumers inthe context of a convenience product brand community (Cova & Pace,2006), anti-brand communities (Hollenbeck & Zinkhan, 2006), the con-sumer quest for authenticity (Leigh, Peters, & Shelton, 2006), the roleof social environments (Luedicke, 2006), rumor in brand communities(Muniz, O’Guinn, & Fine, 2006), and social versus psychological brandcommunities (Carlson et al., 2008).

In contrast to these studies, the second stream of research examinesthe outcomes of customers’ engagement within a brand community. Forinstance, analyses of brandfests (McAlexander et al., 2002; Schouten,McAlexander, & Koenig, 2007) have revealed that greater integration ina brand community increases customer loyalty and that transcendent cus-tomer experiences lead to stronger relationships with the brand, the prod-uct, the hosting company, and other customers. In the automobile context,Algesheimer, Dholakia, and Herrmann (2005) showed that among otherfacets, brand relationship quality leads to greater brand loyalty intentionsand community engagement to greater membership continuance inten-tions. Furthermore, McAlexander, Kim, and Roberts (2003) analyzed theimpact of satisfaction, brand community integration, and consumer experi-ences on customer loyalty in a casino. McAlexander, Koenig, and Schouten(2004) examined how the nature of relationships among students affectsstudents’ long-term loyalty to their university. In a study about antecedentsand purchase consequences of customer participation in small-group brandcommunities, Bagozzi and Dholakia (2006) suggested that social identityand group behavior are key explanatory variables of brand behavior, andin another study 1 year later Hickman and Ward (2007) analyzed the in-fluence of social identification on group behavior in the context of internaland external trash talk. Casalo, Flavian, and Guinalıu (2007) detected, forexample, that participation has a positive influence on consumer commit-ment to the brand, and satisfaction with previous interactions increases thelevel of trust.

Although consequences for marketing management can be derivedfrom the findings of most of the studies described above, little is writtenabout how to successfully implement and manage a company-run brand

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community (Carlson et al., 2008). From a managerial point of view, com-panies are confronted with the increasing popularity of (virtual) brandcommunities so that both management of a brand community implementedby the consumers and the implementation of a brand community by thecompany itself are now more important. It seems surprising that a lot ofcompanies are not aware of the phenomenon of brand communities, asonly a few of them have integrated these into their marketing mix (Cova& Pace, 2006; McAlexander et al., 2002). If community platforms are setup, they are mostly driven by the ideas of advertising agencies and aregenerally seen as part of a short-term campaign, not as strategic long-terminvestment. It seems, up to now, that the potential of brand communitieshas been underestimated in marketing practice.

In this article, we focus on a company that is aware of the potentialof brand communities. The company bought the naming rights to one ofthe biggest football stadiums in Germany and implemented its own virtualbrand community on the Internet as “virtual football stadium,” especiallyfor fans of the local football team. In this article, we (a) conceptualizefactors that contribute to successful consumer participation in the brandcommunity; (b) investigate the impacts of consumer participation on com-munity loyalty, word of mouth, and brand image perception; and (c) ex-amine moderator variables influencing the relationship between consumerparticipation and the associated consequences.

The theoretical framework of our study is based primarily on socialidentity theory (SIT) and the concept of psychological sense of commu-nity (PSOC). Both are frequently employed in the existing literature on(virtual) communities in general as well as on brand communities in par-ticular (Bhattacharya, Rao, & Glynn, 1995; Carlson et al., 2008; Obst,Zinkiewicz, & Smith, 2002a, 2002b, 2002c). In the following sections, weintroduce the theoretical basis of our study and then derive our hypothesesbased on theory and existing (brand) community literature. Finally, wetest our empirical model using a data set of 1,025 members of this vir-tual brand community and discuss our findings and directions for furtherresearch.

THEORETICAL BACKGROUND AND HYPOTHESISDEVELOPMENT

Within the discipline of community psychology, the concept of PSOChas become one of the major bases for analyzing interpersonal relationships

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(Carlson et al., 2008; Chavis & Pretty, 1999). Obst et al. (2002a, 2002b,2002c) extended this concept with aspects of social identity based on SIT.Besides social identity, PSOC comprises other elements such as the build-ing of a corporate feeling, friendship, trust, support, and the satisfactionof needs. In this context, a brand can thus be seen as linking consumerswith similar passions. Communities distinguish themselves from othercommunities by their passion for a particular brand. Following Sarason(1977), sense of community is the

perception of similarity with others, an acknowledged interdepen-dence with others, a willingness to maintain this interdependence bygiving to or doing for others what one expects from them, the feelingthat one is part of a larger dependable and stable structure. (p. 157 )

McMillan and Chavis (1986) conducted the most influential study of PSOC(Obst et al., 2002a). They argued that PSOC consists of four elements:membership, influence, integration and fulfillment of needs, and sharedemotional connections (McMillan & Chavis, 1986). Building on this studyand on a revised version of PSOC by McMillan (1996), Obst et al. (2002a,2002b, 2002c) combined this concept with SIT. They pointed out thatidentification with the community is an essential element of PSOC andreferred to SIT as a suitable theoretical background (Obst et al., 2002a). SITargues that the self-concept of a person is made up of two different aspectsof identity: personal identity and social identity (Lantz & Loeb, 1998;Tajfel & Turner, 1986; Turner & Oaks, 1989). Personal identity consists ofspecific characteristics, such as talents and interests. Social identity “is theperception of belonging to a group with the result that a person identifieswith that group (i.e., I am a member)” (Bhattacharya et al., 1995, p. 47).More relevant to this study, consumers who identify themselves with abrand and a brand community, respectively, classify themselves and otherconsumers as being a group member (in-group) or as not being a groupmember (out-group; Hickman & Ward, 2007). The phenomenon describedby SIT has been observed in brand communities, for example in terms of“oppositional brand loyalty” as described by Muniz and O’Guinn (2001)and “internal and external trash talk and Schadenfreude” as analyzed byHickman and Ward.

In line with PSOC and SIT, we assume that establishing a success-ful brand community depends on participation of community members(Casalo et al., 2007). Especially in virtual communities, there are manyways of participating and interacting with other community members,

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FIGURE 1. Conceptual Model.

CONSEQUENCES

BrandImage

Word ofMouth

CommunityLoyalty

ConsumerParticipation

ANTECEDENTS

CommunitySatisfaction

CommunityIdentification

Degree ofInfluence

H1

H2

H3

H4

H5

H6

ConsumerParticipation

XInteractionPreference

H7

H9

H8

such as through chats, boards, or news groups. These forms of interactionenable consumers to share information about the brand and the product.Furthermore, consumers also lend support to one another when faced withproblems and thereby develop social bonds. Hence, if companies intendto establish a brand community, they have to ensure participation of com-munity members. Against this background, our conceptual model capturesantecedents of consumer participation, consequences of consumer par-ticipation, and moderator variables influencing the relationship betweenconsumer participation and the associated consequences (see Figure 1).

Antecedents of Consumer Participation

We posit that a community member’s participation is affected by identi-fication with the brand community, satisfaction with the brand community,and the perceived degree of influence opportunities. There are three majorreasons why we study these potential antecedents. First, these variables arerecognized as being powerful drivers for ensuring a brand community’s

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customer participation (Algesheimer et al., 2005; Nambisan & Baron,2007; von Loewenfeld, 2006). Second, management can influence thesethree variables, and, therefore, the variables could be used to establish asuccessful brand community. Finally, although these variables are con-sidered to be crucial for brand community success, the consequences forbrand community management have not been studied extensively before.

Influence of community identification on consumer participation. Thefirst important antecedent of brand community participation is social iden-tity. It is defined as “the perception of belonging to a group with the resultthat a person identifies with that group” (Bhattacharya et al., 1995, p. 47).Social identity primarily comprises the feeling of belonging to a group(Bhattacharya et al., 1995) and is closely connected to one of the mostimportant elements of communities: consciousness of kind. “Conscious-ness of kind is the intrinsic connection that members feel towards oneanother and collective sense of difference from others not in the commu-nity” (Muniz & O’Guinn, 2001, p. 413). Carlson et al. (2008) argued thatidentification is important for developing a psychological sense of brandcommunity. The consequence of self-categorization to a particular vir-tual brand community is a positive distinction of the community’s values,norms, and behaviors toward other communities, which thereby results inan increase in group members’ self-esteem (Turner, 1987). Therefore, weassume that community identification is inextricably linked with consumerparticipation.

Further studies support this assumption: Algesheimer et al. (2005)showed that brand community identification has a positive impact oncommunity engagement. In their study about antecedents and purchaseconsequences of customer participation in small-group brand communi-ties, Bagozzi and Dholakia (2006) found that social identity has a positiveimpact on desire to participate in both Harley riding groups and non-Harleyriding groups. Hence, we propose that identification with a group resultsin active community interaction and hypothesize the following:

H1: Community identification has a positive influence on consumerparticipation.

Influence of community satisfaction on consumer participation. Thesecond important antecedent of brand community participation is satisfac-tion with the community. Satisfaction is an overall evaluation of perfor-mance, and it is based on prior experiences (Anderson & Fornell, 1994).Two conceptualizations of customer satisfaction exist in the literature:

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(a) transaction-specific and (b) overall satisfaction (Cronin & Taylor, 1994).In our research, we focus on overall satisfaction, because it is a better pre-dictor of a community’s past, current, and future performance. Based onPSOC, community members strive for fulfillment of their needs. As a pre-requisite of being actively participating members, community membershave to evaluate their membership positively (McMillan & Chavis, 1986).

Existing findings in the virtual community literature confirm the im-pact of satisfaction with the community on community participation. Forexample, Casalo et al. (2007) showed that in virtual brand communities,satisfaction with the community has an indirect effect on community par-ticipation. Furthermore, de Valck, Langerak, Verhoef, and Verlegh (2007)distinguished between four dimensions of community members’ satisfac-tion: satisfaction with (a) member-to-member interaction, (b) organizer-to-member interaction, (c) organizer-to-community interaction, and (d) thecommunity site. These dimensions have been found to influence members’visit frequency. Nambisan and Baron (2007) and Lin (2006) found a posi-tive effect between satisfaction and customer participation in a communitycontext. Hence, we propose that identification with a group results in activecommunity interaction and hypothesize the following:

H2: Community satisfaction has a positive influence on consumerparticipation.

Influence of consumers’ perceived degree of influence on consumerparticipation. The third important factor that contributes to communityparticipation is the perceived degree of influence on the community. Thisis defined as an individual’s need to have some control and influence(Obst et al., 2002a). As noted before, degree of influence is one of thefour dimensions of PSOC (McMillan & Chavis, 1986). It is closely re-lated to the concept of self-efficacy; therefore, people perceiving a highdegree of influence should be more willing to engage in the community(Bandura, 1986). Yet this linkage was investigated empirically only by vonLoewenfeld (2006), who supported our assumption. Hence, we proposethat the degree of influence with a group results in active communityparticipation and hypothesize the following:

H3: The degree of influence in the community has a positive influenceon consumer participation.

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Consequences of Consumer Participation

We posit that community member participation affects community loy-alty, word of mouth, and the image of the community presenter’s brand.Again, we have three reasons for studying these consequences. First,these consequences are outcomes of community member engagement(Algesheimer et al., 2005; Kim & Jung, 2007; Muniz & Schau, 2007).Second, they are important outcomes for companies intending to establishnew brand communities. Finally, although these variables are consideredto be crucial for brand community success, empirical studies testing theimpact of consumer participation on these consequences and, in particular,on the sponsor’s brand image are largely lacking.

Influence of consumer participation on brand image. One importantoutcome of community participation represents the community presenter’sbrand image, which is defined as the perceptions about a brand as reflectedby the brand associations held in consumer memory (Keller, 1993). Instudies analyzing brand communities, it has been argued that customerempowerment and consumer-generated content may be of high relevancefor increasing brand image (Cova & Pace, 2006; Muniz & Schau, 2007).These community activities may be community member integration, whendeveloping innovations together with the company (Fuller, Jawecki, &Muhlbacher, 2007), or cooperative development of advertising campaigns(Muniz & Schau, 2006, 2007). Muniz and Schau (2006) argued that mem-bers of the community act as marketing consultants, brand managers,salespeople, copywriters, product engineers, service technicians, and pric-ing specialists. Most of this research assuming a positive effect of customerinteraction on brand image is qualitative in nature, and quantitative studiesanalyzing the effect are still lacking (Muniz & Schau, 2007). Accordingto PSOC, customer engagement within the community results in positiveemotions toward the brand. Hence, we hypothesize the following:

H4: Consumer participation has a positive influence on brand image.

Influence of consumer participation on community loyalty and word ofmouth. Further potential outcomes of community participation are com-munity loyalty and word of mouth (Kim & Jung, 2007). Loyalty is anoverall attachment or deep commitment to a product, service, brand, ororganization (Oliver, 1999). The more common manifestations of loyaltyare recommendation behavior and patronage intention (Dwyer, Schurr,& Oh, 1987; Fornell, 1992; Zeithaml, Berry, & Parasuraman, 1996). In a

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brand community context, Algesheimer et al. (2005) showed that a strongercommunity engagement leads to stronger membership continuance andcommunity recommendation intentions. Bagozzi and Dholakia (2006) as-sessed a significant indirect effect of desire to participate on brand loyalty.Jang, Ko, and Koh (2007) as well as Casalo et al. (2007) found that partic-ipation contributes positively to the community commitment of members.In the context of brandfests, Schouten et al. (2007) showed that transcen-dent customer experiences can strengthen a person’s ties to a communityand therefore lead to greater loyalty. According to SIT, interaction withother members leads to a strengthening of in-group consciousness. Hence,we propose that community participation has a positive effect on commu-nity members’ loyalty intentions and on their word-of-mouth behavior andhypothesize the following:

H5–6: Consumer participation has a positive influence on communityloyalty (H5) and word-of-mouth behavior (H6).

Moderating Effect of Interaction Preference

In the existing brand community literature, little attention is paid to fac-tors determining the effectiveness (i.e., consequences) of customer partici-pation. It is likely that the strength of the relationships between communityparticipation and consequences of community participation is moderatedby other variables. In marketing research, existence of moderators has beendiscussed as the rule and not the exception (Ping, 1995). A customer’s in-teraction preference might be one of these factors influencing the strengthand/or the direction of customer participation effectiveness. Interactionpreference is defined as the prevailing tendency of an individual to inter-act with relative strangers (i.e., people they have never met offline) in anonline environment (Wiertz & de Ruyter, 2007). When customers have ahigh preference for interacting within the community, we assume customerparticipation to have a stronger effect on word-of-mouth behavior, brandimage, and community loyalty. If one compares two participating com-munity members, one having a high preference for interaction with otherpeople in general and the other having no such preference, the first personis much more likely to recommend the brand community (perceive a fa-vorable brand image/stay loyal) because he or she receives more benefitsfrom participating in the community. Hence,

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H7–9: The higher the interaction preference, the greater the positiveeffect of consumer participation on word-of-mouth behavior (H7),brand image (H8), and community loyalty (H9).

METHODOLOGY

Questionnaire Development and Pretesting

We tested our hypotheses in an online study using a Web survey de-sign. The online questionnaire was pretested by 20 German undergraduatemarketing students. The pretest was intended to refine the questionnaire,especially with regard to question content, wording, format, and layout.

Measures

We measured attitude-related variables, except for community loyalty,with multi-item scales. Community loyalty was measured by using onesingle item adapted from Algesheimer et al. (2005). Although multi-itemscales are generally preferred, the latest studies support the use of single-item scales for loyalty-related research (LaBarbera & Mazursky, 1983;Lemon, White, & Winer, 2002; Mittal, Ross, & Baldasare, 1998; Rossiter,2002). Furthermore, we took five items that are regularly used in theliterature (Woisetschlager, 2007; Woisetschlager, Michaelis, & Backhaus,in press) to measure brand image. Word of mouth was measured by using ascale from Zeithaml et al. (1996). Interaction preference was measured byusing an established scale from Wiertz and de Ruyter (2007). Participation,degree of influence, as well as identification and satisfaction with the virtualcommunity were adapted from von Loewenfeld (2006). Table 1 providesa description of the items used to measure the constructs.

All items were measured by using 7-point Likert-type scales with an-chors of 1 = strongly agree and 7 = strongly disagree. Measurementreliability of the reflective constructs was examined through a confirma-tory factor analysis. It can be noted that composite reliabilities for allconstructs exceeded. 6, the generally recommended threshold (Bagozzi &Yi, 1988). Moreover, discriminant validity between the constructs is given,because none of the squared correlation coefficients between any of theconstructs exceeded the average variance extracted for a construct (Fornell& Larcker, 1981). Results of correlation analysis are depicted in Table 2.

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TABLE 2. Correlations Between Constructs

Construct 1 2 3 4 5 6 7

1. Participation —2. Identification with

Virtual Community .784 —3. Satisfaction with

Virtual Community .635 .730 —4. Degree of Influence .698 .751 .694 —5. Word of Mouth .678 .736 .719 .657 —6. Brand Image .435 .493 .577 .497 .551 —7. Interaction Preference .747 .644 .503 .540 .550 .360 —

AVE .680 .753 .784 .632 .735 .800 .740

Sample and Data Collection

Data were collected via the Internet. The questionnaire was e-mailed toall registered members of the virtual brand community. At the time whenthe survey started, a total of 8,361 users were registered. Of the users, 21.7%were female and 78.3% were male. Registered members were on average26.32 years old (SD = 11.42) and had been members for 4.66 months(SD = 2.94). A total of 1,025 members participated in the survey, equal-ing a response rate of 12.26%. Of the participants, 24.1% were femaleand 75.9% were male. The respondents were on average 26.03 years old(SD = 11.84) and had been members for 4.72 months (SD = 3.24). Ac-cording to these descriptive statistics, the sample was comparable to thepopulation of all registered members.

RESULTS

We used structural equation modeling to test the hypothesized direct andmoderating effects. The model fits the data well. The comparative fit indexwas .925, the Tucker–Lewis index was .917, the root mean square errorof approximation was .073, and the standardized root-mean-square resid-ual was .083. Table 3 shows the parameter estimates of our model. Pathcoefficients between participation and the three independent constructsidentification with virtual community, satisfaction with virtual commu-nity, and degree of influence were positive and statistically significant atthe .01 level. Regarding the consequences, the path coefficients between

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TABLE 3. Results of the Basic Model With Direct Effects

Direct EffectModel

Hypothesis Construct λ t

Participation (r2) .726H1 Identification with virtual community .567∗∗∗ 11.901H2 Satisfaction with virtual community .095∗∗∗ 2.432H3 Degree of influence .254∗∗∗ 5.507

Word of Mouth (r2) .531H4 Participation .729∗∗∗ 20.650

Brand Image (r2) .230H5 Participation .480∗∗∗ 12.996

Community Loyalty (r2) .471H6 Participation .687∗∗∗ 21.079

Goodness-of-fit statisticsComparative fit index .925Tucker–Lewis index .917Root mean square error of approximation .073Standardized root-mean-square residual .080

∗∗∗p < .01.

participation and word of mouth, brand image, and community loyaltywere positive and significant at the .01 level.

Identification with virtual community had the strongest effect on par-ticipation (λ = .567, p < .01), followed by perceived degree of influ-ence (λ = .254, p < .01) and satisfaction with virtual community (λ =.095, p < .01). Hence, hypotheses H1 through H3 were supported by ourfindings. Our model explained 72.6% of the variance in the participationconstruct. Investigating the consequences, we have to sum up that partici-pation had the strongest effect on word-of-mouth behavior (λ = .729, p <

.01), followed by community loyalty (λ = .687, p < .01) and brand image(λ = .480, p < .01). Thus, hypotheses H4 through H6 were supported byour findings. The derived model explained about 53.1% of the variance inword of mouth (brand loyalty = 47.1%; brand image = 23.0%).

In order to test the moderating influences proposed in hypotheses H7

through H9, we used multigroup structural equation modeling. Mediansplits based on the values of the moderator variables were used to createthe groups. A chi-square difference test was conducted for the possiblemoderator effects by comparing a restricted and a nonrestricted model.Chi-square differences with three degrees of freedom (critical chi-square

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TABLE 4. Results of Multigroup Analysis

Hypothesis Interaction Preference High Low �χ2 (df = 1)

H7 Participation → Word of mouth .662 .624 8.177∗∗∗H8 Participation → Brand image .499 .273 5.502∗∗H9 Participation → Community loyalty .615 .570 1.291

� χ2 (df = 3) 16.138∗∗∗

∗∗p < .05 ∗∗∗p < .01.

value [df = 3, p = .05] = 7.81) were assessed. After confirming a gen-eral moderating effect, we compared two models that differed only inone effect as suggested by our hypotheses. A moderating effect would bepresent when the improvement in chi-square moving from the restricted tothe nonrestricted model is significant, meaning the chi-square differencebetween the two models (and one degree of freedom) is larger than 3.84(p = .05). Results in Table 4 show that interaction preference had a signif-icant impact on the participation–word-of-mouth linkage (at the .01 level).For respondents with high interaction preference the link was stronger, giv-ing support for H7. Regarding the link between participation and brand im-age, a significant positive moderating effect of interaction preference wasfound (at the .01 level), supporting H8. Contrary to our expectations, inter-action preference was not found to moderate the participation–communityloyalty linkage; hence, H9 had to be rejected.

DISCUSSION, LIMITATIONS, AND FURTHER RESEARCH

Results of our empirical analysis reveal that most of the variance inparticipation can be explained by three factors: identification, satisfaction,and degree of influence. Marketing management has to keep these factorsin mind when new features for the community are developed. First, whena company sets up a company-driven community, homogeneous membersshould be grouped into subcommunities to increase the identification ofcommunity members with the community. This could be accomplished bysending automated introductions of members to other members, dependingon their profile match. Second, when implementing a virtual brand com-munity, companies should focus on providing interaction elements to theusers. In fact, successful online communities (e.g., business communitiessuch as XING.com and LinkedIn.com, or communities for social ex-changes such as friendster.com and facebook.com) provide many valuable

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and adaptable examples of how to stimulate interaction between membersof the community. The more satisfied the community members are, themore willing they will be to keep the community alive through interactingwith other members. Third, the more open the platform is to user-generatedcontent, the more community members will contribute to the community.

From a management perspective, online communities are implementedfor several reasons. A company’s brand image is enhanced by havingcustomers exchange with like-minded people in a setting in which thebrand is embedded. Our results demonstrate that active members of thecommunity tend to evaluate the community presenter’s brand image morefavorably. This fact should be an incentive to marketing managers to investin a virtual community. Furthermore, when marketing managers intend toincrease brand community size, they can acquire new members throughrecommendations of existing members. To ensure the long-term success ofthe community, companies can increase community members’ willingnessto stay loyal to the community by engaging members.

Regarding the moderating effect of interaction preference, communitymanagement can use this personal characteristic to cluster communitymembers and design specific actions to increase word-of-mouth behaviorof groups, being sensitive for interacting with others. Similarly, positiveeffects of community participation on brand image should be realized.

Besides these managerial implications, future research should consideranalyzing the effects of implementing features on the change in evaluationof the drivers of community interaction over time. Longitudinal researchdesigns would allow for the monitoring of attitudes and behavior of users.As a result, membership exits could be forecasted and member clustersbased on attitudes and usage could be built. Further personal character-istics such as age, income, and gender should be tested on the consumerparticipation–outcome linkage. How to generate business with a contentand loyal virtual community provides another fruitful avenue for research.Finally, future research should focus on the question of how business of-fers could be communicated to the community without leading to adversereactions from users.

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Documents

How to Make Brand Communities Work: Antecedents and Consequences of Consumer Participation