This article was downloaded by: [2008-2009 Thammasat University] On: 5 June 2010 Access details: Access Details: [subscription number 789376256] Publisher Routledge Informa Ltd Registered in England and Wales Registered Number: 1072954 Registered office: Mortimer House, 3741 Mortimer Street, London W1T 3JH, UK Journal of Relationship Marketing Publication details, including instructions for authors and subscription information: http://www.informaworld.com/smpp/title~content=t792306914 How to Make Brand Communities Work: Antecedents and Consequences of Consumer Participation David M. Woisetschlägera; Vivian Hartlebb; Markus Bluta a University of Dortmund, b University of Muenster, To cite this Article Woisetschläger, David M. , Hartleb, Vivian and Blut, Markus(2008) 'How to Make Brand Communities Work: Antecedents and Consequences of Consumer Participation', Journal of Relationship Marketing, 7: 3, 237 — 256 To link to this Article: DOI: 10.1080/15332660802409605 URL: http://dx.doi.org/10.1080/15332660802409605 PLEASE SCROLL DOWN FOR ARTICLE Full terms and conditions of use: http://www.informaworld.com/terms-and-conditions-of-access.pdf This article may be used for research, teaching and private study purposes. Any substantial or systematic reproduction, re-distribution, re-selling, loan or sub-licensing, systematic supply or distribution in any form to anyone is expressly forbidden. The publisher does not give any warranty express or implied or make any representation that the contents will be complete or accurate or up to date. The accuracy of any instructions, formulae and drug doses should be independently verified with primary sources. The publisher shall not be liable for any loss, actions, claims, proceedings, demand or costs or damages whatsoever or howsoever caused arising directly or indirectly in connection with or arising out of the use of this material. How to Make Brand Communities Work: Antecedents and Consequences of Consumer Participation David M. Woisetschl¨ager Downloaded By: [2008-2009 Thammasat University] At: 13:18 5 June 2010 University of Dortmund Vivian Hartleb University of Muenster Markus Blut University of Dortmund ABSTRACT. The majority of brand community literature deals with the exploration of the nature of brand communities and the measurement of community effects. However, existing literature on how to implement and to manage company-run brand communities is rare. In the present article, we conceptualize drivers and consequences of consumer brand community participation and empirically test our model with a data set of 1,025 members of a virtual brand community. Results indicate that identification with community, satisfaction with community, and degree of influence explain most of the variance in consumer participation. Moreover, positive influences of participation on recommendation behavior, brand image of the David M. Woisetschl¨ager is Assistant Professor of Services Management, University of Dortmund, Dortmund, Germany. Vivian Hartleb is Research Assistant, Marketing Center Muenster, University of Muenster, Germany. Markus Blut is Assistant Professor of Marketing, University of Dortmund, Germany. Address correspondence to: David M. Woisetschl¨ager, University of Dortmund, Otto-Hahn-Str. 6, Dortmund, Germany. (E-mail: [email protected]) Journal of Relationship Marketing, Vol. 7(3), 2008 Available online at http://www.haworthpress.com C 2008 by The Haworth Press. All rights reserved. doi: 10.1080/15332660802409605 237 238 JOURNAL OF RELATIONSHIP MARKETING community sponsor, and intention to continue community membership can be confirmed. KEYWORDS. Brand community, consumer participation, brand image, word–of–mouth, community loyalty Downloaded By: [2008-2009 Thammasat University] At: 13:18 5 June 2010 INTRODUCTION Within the past decade the Internet has become one of the most important and most commonly used communication media (Lagrosen, 2005). It offers boundless possibilities for information and communication exchange without any geographical restrictions. Especially over the past few years, groups with common interests or problems have increasingly been organizing themselves into blogs or virtual communities (e.g., Apple, Harley Davidson, Saab, Tom Petty, Xena)—a phenomenon that is of interest to both academic research and marketing practice (Carlson, Suter, & Brown, 2008). According to Boorstin (1973), consumers with similar norms, values, and habits (e.g., the consumption of the same brand or product) form groups called communities of consumption. A special kind of community of consumption is a brand community, which is defined as “a specialized, non-geographically bound community, based on a structured set of social 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, consumers join these communities to exchange experiences with other like-minded people fascinated by a specific brand. Two main streams of research can be identified from the existing brand community literature: first, studies in which the nature of brand communities is explored and, second, studies that deal with measurement of the outcomes of customers’ brand community engagement. Muniz and O’Guinn (2002) as well as Schau and Muniz (2002)are among the earliest proponents contributing to the first stream of research. Whereas Muniz and O’Guinn assessed the three core components of brand communities as (a) “consciousness of kind,” (b) “shared rituals and traditions,” and (c) “a sense of moral responsibility” and identified brands as a social phenomenon, Schau and Muniz (2002) analyzed several brand communities and revealed four types of relationships between individual identity and community membership: (a) subsumed identity, (b) super member, (c) community Downloaded By: [2008-2009 Thammasat University] At: 13:18 5 June 2010 Woisetschl¨ager, Hartleb, and Blut 239 membership as identity component, and (d) multiple memberships. Following the customer-centric model of brand community of McAlexander, Schouten, and Koenig (2002), Ouwersloot and Odekerken-Schr¨oder (2008) segmented brand community members into four categories based on consumption motivation: (a) enthusiasts, (b) users, (c) behind-the-scenes, and (d) not-me. Other starting points to explore the nature of brand communities have been personal self-exhibition in front of other consumers in the context of a convenience product brand community (Cova & Pace, 2006), anti-brand communities (Hollenbeck & Zinkhan, 2006), the consumer quest for authenticity (Leigh, Peters, & Shelton, 2006), the role of social environments (Luedicke, 2006), rumor in brand communities (Muniz, O’Guinn, & Fine, 2006), and social versus psychological brand communities (Carlson et al., 2008). In contrast to these studies, the second stream of research examines the outcomes of customers’ engagement within a brand community. For instance, analyses of brandfests (McAlexander et al., 2002; Schouten, McAlexander, & Koenig, 2007) have revealed that greater integration in a brand community increases customer loyalty and that transcendent customer experiences lead to stronger relationships with the brand, the product, the hosting company, and other customers. In the automobile context, Algesheimer, Dholakia, and Herrmann (2005) showed that among other facets, brand relationship quality leads to greater brand loyalty intentions and community engagement to greater membership continuance intentions. Furthermore, McAlexander, Kim, and Roberts (2003) analyzed the impact of satisfaction, brand community integration, and consumer experiences on customer loyalty in a casino. McAlexander, Koenig, and Schouten (2004) examined how the nature of relationships among students affects students’ long-term loyalty to their university. In a study about antecedents and purchase consequences of customer participation in small-group brand communities, Bagozzi and Dholakia (2006) suggested that social identity and group behavior are key explanatory variables of brand behavior, and in another study 1 year later Hickman and Ward (2007) analyzed the influence of social identification on group behavior in the context of internal and external trash talk. Casal´o, Flavi´an, and Guinal´ıu (2007) detected, for example, that participation has a positive influence on consumer commitment to the brand, and satisfaction with previous interactions increases the level of trust. Although consequences for marketing management can be derived from the findings of most of the studies described above, little is written about how to successfully implement and manage a company-run brand Downloaded By: [2008-2009 Thammasat University] At: 13:18 5 June 2010 240 JOURNAL OF RELATIONSHIP MARKETING community (Carlson et al., 2008). From a managerial point of view, companies are confronted with the increasing popularity of (virtual) brand communities so that both management of a brand community implemented by the consumers and the implementation of a brand community by the company itself are now more important. It seems surprising that a lot of companies are not aware of the phenomenon of brand communities, as only a few of them have integrated these into their marketing mix (Cova & Pace, 2006; McAlexander et al., 2002). If community platforms are set up, they are mostly driven by the ideas of advertising agencies and are generally seen as part of a short-term campaign, not as strategic long-term investment. It seems, up to now, that the potential of brand communities has been underestimated in marketing practice. In this article, we focus on a company that is aware of the potential of brand communities. The company bought the naming rights to one of the biggest football stadiums in Germany and implemented its own virtual brand community on the Internet as “virtual football stadium,” especially for fans of the local football team. In this article, we (a) conceptualize factors that contribute to successful consumer participation in the brand community; (b) investigate the impacts of consumer participation on community loyalty, word of mouth, and brand image perception; and (c) examine moderator variables influencing the relationship between consumer participation and the associated consequences. The theoretical framework of our study is based primarily on social identity theory (SIT) and the concept of psychological sense of community (PSOC). Both are frequently employed in the existing literature on (virtual) communities in general as well as on brand communities in particular (Bhattacharya, Rao, & Glynn, 1995; Carlson et al., 2008; Obst, Zinkiewicz, & Smith, 2002a, 2002b, 2002c). In the following sections, we introduce the theoretical basis of our study and then derive our hypotheses based on theory and existing (brand) community literature. Finally, we test our empirical model using a data set of 1,025 members of this virtual brand community and discuss our findings and directions for further research. THEORETICAL BACKGROUND AND HYPOTHESIS DEVELOPMENT Within the discipline of community psychology, the concept of PSOC has become one of the major bases for analyzing interpersonal relationships Woisetschl¨ager, Hartleb, and Blut 241 Downloaded By: [2008-2009 Thammasat University] At: 13:18 5 June 2010 (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 building of a corporate feeling, friendship, trust, support, and the satisfaction of needs. In this context, a brand can thus be seen as linking consumers with similar passions. Communities distinguish themselves from other communities by their passion for a particular brand. Following Sarason (1977), sense of community is the perception of similarity with others, an acknowledged interdependence with others, a willingness to maintain this interdependence by giving to or doing for others what one expects from them, the feeling that 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 shared emotional connections (McMillan & Chavis, 1986). Building on this study and on a revised version of PSOC by McMillan (1996), Obst et al. (2002a, 2002b, 2002c) combined this concept with SIT. They pointed out that identification with the community is an essential element of PSOC and referred to SIT as a suitable theoretical background (Obst et al., 2002a). SIT argues that the self-concept of a person is made up of two different aspects of identity: personal identity and social identity (Lantz & Loeb, 1998; Tajfel & Turner, 1986; Turner & Oaks, 1989). Personal identity consists of specific characteristics, such as talents and interests. Social identity “is the perception of belonging to a group with the result that a person identifies with that group (i.e., I am a member)” (Bhattacharya et al., 1995, p. 47). More relevant to this study, consumers who identify themselves with a brand and a brand community, respectively, classify themselves and other consumers as being a group member (in-group) or as not being a group member (out-group; Hickman & Ward, 2007). The phenomenon described by 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 by Hickman and Ward. In line with PSOC and SIT, we assume that establishing a successful brand community depends on participation of community members (Casal´o et al., 2007). Especially in virtual communities, there are many ways of participating and interacting with other community members, 242 JOURNAL OF RELATIONSHIP MARKETING FIGURE 1. Conceptual Model. ANTECEDENTS CONSEQUENCES Community Identification Word of Mouth H4 Downloaded By: [2008-2009 Thammasat University] At: 13:18 5 June 2010 H1 Community Satisfaction H2 Consumer Participation H5 Brand Image H6 H3 Degree of Influence H7 Consumer Participation X Interaction Preference H8 Community Loyalty H9 such as through chats, boards, or news groups. These forms of interaction enable consumers to share information about the brand and the product. Furthermore, consumers also lend support to one another when faced with problems and thereby develop social bonds. Hence, if companies intend to establish a brand community, they have to ensure participation of community members. Against this background, our conceptual model captures antecedents of consumer participation, consequences of consumer participation, and moderator variables influencing the relationship between consumer participation and the associated consequences (see Figure 1). Antecedents of Consumer Participation We posit that a community member’s participation is affected by identification with the brand community, satisfaction with the brand community, and the perceived degree of influence opportunities. There are three major reasons why we study these potential antecedents. First, these variables are recognized as being powerful drivers for ensuring a brand community’s Downloaded By: [2008-2009 Thammasat University] At: 13:18 5 June 2010 Woisetschl¨ager, Hartleb, and Blut 243 customer participation (Algesheimer et al., 2005; Nambisan & Baron, 2007; von Loewenfeld, 2006). Second, management can influence these three variables, and, therefore, the variables could be used to establish a successful brand community. Finally, although these variables are considered to be crucial for brand community success, the consequences for brand community management have not been studied extensively before. Influence of community identification on consumer participation. The first important antecedent of brand community participation is social identity. It is defined as “the perception of belonging to a group with the result that 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 most important elements of communities: consciousness of kind. “Consciousness of kind is the intrinsic connection that members feel towards one another and collective sense of difference from others not in the community” (Muniz & O’Guinn, 2001, p. 413). Carlson et al. (2008) argued that identification is important for developing a psychological sense of brand community. The consequence of self-categorization to a particular virtual brand community is a positive distinction of the community’s values, norms, and behaviors toward other communities, which thereby results in an increase in group members’ self-esteem (Turner, 1987). Therefore, we assume that community identification is inextricably linked with consumer participation. Further studies support this assumption: Algesheimer et al. (2005) showed that brand community identification has a positive impact on community engagement. In their study about antecedents and purchase consequences of customer participation in small-group brand communities, Bagozzi and Dholakia (2006) found that social identity has a positive impact on desire to participate in both Harley riding groups and non-Harley riding groups. Hence, we propose that identification with a group results in active community interaction and hypothesize the following: H1 : Community identification has a positive influence on consumer participation. Influence of community satisfaction on consumer participation. The second important antecedent of brand community participation is satisfaction with the community. Satisfaction is an overall evaluation of performance, and it is based on prior experiences (Anderson & Fornell, 1994). Two conceptualizations of customer satisfaction exist in the literature: Downloaded By: [2008-2009 Thammasat University] At: 13:18 5 June 2010 244 JOURNAL OF RELATIONSHIP MARKETING (a) transaction-specific and (b) overall satisfaction (Cronin & Taylor, 1994). In our research, we focus on overall satisfaction, because it is a better predictor of a community’s past, current, and future performance. Based on PSOC, community members strive for fulfillment of their needs. As a prerequisite of being actively participating members, community members have to evaluate their membership positively (McMillan & Chavis, 1986). Existing findings in the virtual community literature confirm the impact of satisfaction with the community on community participation. For example, Casal´o et al. (2007) showed that in virtual brand communities, satisfaction with the community has an indirect effect on community participation. Furthermore, de Valck, Langerak, Verhoef, and Verlegh (2007) distinguished between four dimensions of community members’ satisfaction: satisfaction with (a) member-to-member interaction, (b) organizerto-member interaction, (c) organizer-to-community interaction, and (d) the community site. These dimensions have been found to influence members’ visit frequency. Nambisan and Baron (2007) and Lin (2006) found a positive effect between satisfaction and customer participation in a community context. Hence, we propose that identification with a group results in active community interaction and hypothesize the following: H2 : Community satisfaction has a positive influence on consumer participation. Influence of consumers’ perceived degree of influence on consumer participation. The third important factor that contributes to community participation is the perceived degree of influence on the community. This is 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 the four dimensions of PSOC (McMillan & Chavis, 1986). It is closely related to the concept of self-efficacy; therefore, people perceiving a high degree of influence should be more willing to engage in the community (Bandura, 1986). Yet this linkage was investigated empirically only by von Loewenfeld (2006), who supported our assumption. Hence, we propose that the degree of influence with a group results in active community participation and hypothesize the following: H3 : The degree of influence in the community has a positive influence on consumer participation. Woisetschl¨ager, Hartleb, and Blut 245 Downloaded By: [2008-2009 Thammasat University] At: 13:18 5 June 2010 Consequences of Consumer Participation We posit that community member participation affects community loyalty, 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 establish new brand communities. Finally, although these variables are considered to be crucial for brand community success, empirical studies testing the impact 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 important outcome of community participation represents the community presenter’s brand image, which is defined as the perceptions about a brand as reflected by the brand associations held in consumer memory (Keller, 1993). In studies analyzing brand communities, it has been argued that customer empowerment and consumer-generated content may be of high relevance for increasing brand image (Cova & Pace, 2006; Muniz & Schau, 2007). These community activities may be community member integration, when developing innovations together with the company (F¨uller, Jawecki, & M¨uhlbacher, 2007), or cooperative development of advertising campaigns (Muniz & Schau, 2006, 2007). Muniz and Schau (2006) argued that members of the community act as marketing consultants, brand managers, salespeople, copywriters, product engineers, service technicians, and pricing specialists. Most of this research assuming a positive effect of customer interaction on brand image is qualitative in nature, and quantitative studies analyzing the effect are still lacking (Muniz & Schau, 2007). According to PSOC, customer engagement within the community results in positive emotions 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 of mouth. Further potential outcomes of community participation are community loyalty and word of mouth (Kim & Jung, 2007). Loyalty is an overall attachment or deep commitment to a product, service, brand, or organization (Oliver, 1999). The more common manifestations of loyalty are recommendation behavior and patronage intention (Dwyer, Schurr, & Oh, 1987; Fornell, 1992; Zeithaml, Berry, & Parasuraman, 1996). In a Downloaded By: [2008-2009 Thammasat University] At: 13:18 5 June 2010 246 JOURNAL OF RELATIONSHIP MARKETING brand community context, Algesheimer et al. (2005) showed that a stronger community engagement leads to stronger membership continuance and community recommendation intentions. Bagozzi and Dholakia (2006) assessed a significant indirect effect of desire to participate on brand loyalty. Jang, Ko, and Koh (2007) as well as Casal´o et al. (2007) found that participation contributes positively to the community commitment of members. In the context of brandfests, Schouten et al. (2007) showed that transcendent customer experiences can strengthen a person’s ties to a community and therefore lead to greater loyalty. According to SIT, interaction with other members leads to a strengthening of in-group consciousness. Hence, we propose that community participation has a positive effect on community members’ loyalty intentions and on their word-of-mouth behavior and hypothesize the following: H5–6 : Consumer participation has a positive influence on community loyalty (H5 ) and word-of-mouth behavior (H6 ). Moderating Effect of Interaction Preference In the existing brand community literature, little attention is paid to factors determining the effectiveness (i.e., consequences) of customer participation. It is likely that the strength of the relationships between community participation and consequences of community participation is moderated by other variables. In marketing research, existence of moderators has been discussed as the rule and not the exception (Ping, 1995). A customer’s interaction preference might be one of these factors influencing the strength and/or the direction of customer participation effectiveness. Interaction preference is defined as the prevailing tendency of an individual to interact with relative strangers (i.e., people they have never met offline) in an online environment (Wiertz & de Ruyter, 2007). When customers have a high preference for interacting within the community, we assume customer participation to have a stronger effect on word-of-mouth behavior, brand image, and community loyalty. If one compares two participating community members, one having a high preference for interaction with other people in general and the other having no such preference, the first person is much more likely to recommend the brand community (perceive a favorable brand image/stay loyal) because he or she receives more benefits from participating in the community. Hence, Woisetschl¨ager, Hartleb, and Blut 247 H7–9 : The higher the interaction preference, the greater the positive effect of consumer participation on word-of-mouth behavior (H7 ), brand image (H8 ), and community loyalty (H9 ). METHODOLOGY Downloaded By: [2008-2009 Thammasat University] At: 13:18 5 June 2010 Questionnaire Development and Pretesting We tested our hypotheses in an online study using a Web survey design. The online questionnaire was pretested by 20 German undergraduate marketing 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 one single item adapted from Algesheimer et al. (2005). Although multi-item scales are generally preferred, the latest studies support the use of singleitem 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 the literature (Woisetschl¨ager, 2007; Woisetschl¨ager, Michaelis, & Backhaus, in press) to measure brand image. Word of mouth was measured by using a scale from Zeithaml et al. (1996). Interaction preference was measured by using an established scale from Wiertz and de Ruyter (2007). Participation, degree of influence, as well as identification and satisfaction with the virtual community were adapted from von Loewenfeld (2006). Table 1 provides a description of the items used to measure the constructs. All items were measured by using 7-point Likert-type scales with anchors of 1 = strongly agree and 7 = strongly disagree. Measurement reliability of the reflective constructs was examined through a confirmatory factor analysis. It can be noted that composite reliabilities for all constructs 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 the constructs exceeded the average variance extracted for a construct (Fornell & Larcker, 1981). Results of correlation analysis are depicted in Table 2. 248 .914 .995 .916 .837 .892 .912 .995 .912 .833 .887 Participation (von Loewenfeld, 2006)a 1. Members of the [Name] community help each other. 2. When I seek for advice, I am likely to find someone supportive in the [Name] community. 3. I found new friends as a result of joining the [Name] community. 4. Friendships in the [Name] community are important to me. 5. Social contacts and friendships are supported by the [Name] community’s offers for interaction. Identification With Virtual Community (von Loewenfeld, 2006)a 1. I see myself as belonging to the [Name] community. 2. The [Name] community plays a part in my everyday life. 3. I see myself as a typical and representative member of the [Name] community. 4. The virtual [Name] community confirms in many aspects my view of who I am. 5. I can identify with the [Name] community. 6. I have strong feelings for the [Name] community. 7. I feel like I belong in the [Name] community. Satisfaction With Virtual Community (von Loewenfeld, 2006)a 1. Overall, the [Name] community meets my expectations. 2. The content of the [Name] community matches exactly with my interests. 3. The [Name] community fulfills my needs. Degree of Influence (von Loewenfeld, 2006)a 1. As a member of [Name] community, I can influence the community as a whole. 2. I am satisfied with the degree of influence to shape the [Name] community. 3. A single member has the chance to be an active part in the [Name] community. Word of Mouth (Zeithaml et al., 1996)a 1. I have said positive things about [Name] community to other people. 2. I have recommended [Name] community to people who seek my advice. 3. I have encouraged other people to join [Name] community. CR2 CA1 Scale/Item TABLE 1. Constructs and Measures Downloaded By: [2008-2009 Thammasat University] At: 13:18 5 June 2010 .735 .632 .784 .753 .680 AVE3 249 — .919 — .917 1 a Measured using 7-point Likert-type scales anchored by 1 = strongly agree, 7 = strongly disagree. Cronbach’s Alpha; 2Composite Reliability; 3Average Variance Extracted. .952 .951 Brand Image (Woisetschlager, 2006; Woisetschlager et al., 2007)a ¨ ¨ 1. [Brand] is trustworthy. 2. [Brand] is reliable. 3. [Brand] is likeable. 4. [Brand] is a very good brand. 5. [Brand] is a very attractive brand. Community Loyalty (Algesheimer et al., 2005)a 1. It would be very difficult for me to leave the [Name] community. Interaction Preference (Wiertz & Ruyter, 2007)a 1. I am someone who enjoys interacting with other community members. 2. I am someone who likes actively participating in discussions with other community members. 3. In general, I am someone who, given the chance, seeks contact with other community members. 4. In general, I thoroughly enjoy exchanging ideas with other community members. CR2 CA1 Scale/Item TABLE 1. Constructs and Measures (Continued) Downloaded By: [2008-2009 Thammasat University] At: 13:18 5 June 2010 .740 — .800 AVE3 250 JOURNAL OF RELATIONSHIP MARKETING Downloaded By: [2008-2009 Thammasat University] At: 13:18 5 June 2010 TABLE 2. Correlations Between Constructs Construct 1 2 3 4 5 6 7 1. Participation 2. Identification with Virtual Community 3. Satisfaction with Virtual Community 4. Degree of Influence 5. Word of Mouth 6. Brand Image 7. Interaction Preference — .784 — .635 .698 .678 .435 .747 .730 .751 .736 .493 .644 — .694 .719 .577 .503 — .657 .497 .540 — .551 .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 to all registered members of the virtual brand community. At the time when the 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 average 26.32 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, equaling a response rate of 12.26%. Of the participants, 24.1% were female and 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). According to these descriptive statistics, the sample was comparable to the population of all registered members. RESULTS We used structural equation modeling to test the hypothesized direct and moderating effects. The model fits the data well. The comparative fit index was .925, the Tucker–Lewis index was .917, the root mean square error of approximation was .073, and the standardized root-mean-square residual was .083. Table 3 shows the parameter estimates of our model. Path coefficients between participation and the three independent constructs identification with virtual community, satisfaction with virtual community, and degree of influence were positive and statistically significant at the .01 level. Regarding the consequences, the path coefficients between Woisetschl¨ager, Hartleb, and Blut 251 TABLE 3. Results of the Basic Model With Direct Effects Direct Effect Model Downloaded By: [2008-2009 Thammasat University] At: 13:18 5 June 2010 Hypothesis Participation (r 2) Identification with virtual community Satisfaction with virtual community Degree of influence Word of Mouth (r 2) Participation Brand Image (r 2) Participation Community Loyalty (r 2) Participation Goodness-of-fit statistics Comparative fit index Tucker–Lewis index Root mean square error of approximation Standardized root-mean-square residual H1 H2 H3 H4 H5 H6 ∗∗∗ Construct λ t .567∗∗∗ .095∗∗∗ .254∗∗∗ 11.901 2.432 5.507 .729∗∗∗ 20.650 .480∗∗∗ 12.996 .687∗∗∗ 21.079 .726 .531 .230 .471 .925 .917 .073 .080 p < .01. participation and word of mouth, brand image, and community loyalty were positive and significant at the .01 level. Identification with virtual community had the strongest effect on participation (λ = .567, p < .01), followed by perceived degree of influence (λ = .254, p < .01) and satisfaction with virtual community (λ = .095, p < .01). Hence, hypotheses H1 through H3 were supported by our findings. Our model explained 72.6% of the variance in the participation construct. Investigating the consequences, we have to sum up that participation 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 by our findings. The derived model explained about 53.1% of the variance in word 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. Median splits based on the values of the moderator variables were used to create the groups. A chi-square difference test was conducted for the possible moderator effects by comparing a restricted and a nonrestricted model. Chi-square differences with three degrees of freedom (critical chi-square 252 JOURNAL OF RELATIONSHIP MARKETING TABLE 4. Results of Multigroup Analysis Interaction Preference High Low χ2 (df = 1) Participation → Word of mouth Participation → Brand image Participation → Community loyalty χ2 (df = 3) .662 .499 .615 16.138∗∗∗ .624 .273 .570 8.177∗∗∗ 5.502∗∗ 1.291 Hypothesis H7 H8 H9 Downloaded By: [2008-2009 Thammasat University] At: 13:18 5 June 2010 ∗∗ p < .05 ∗ ∗ ∗ p < .01. value [df = 3, p = .05] = 7.81) were assessed. After confirming a general moderating effect, we compared two models that differed only in one effect as suggested by our hypotheses. A moderating effect would be present when the improvement in chi-square moving from the restricted to the nonrestricted model is significant, meaning the chi-square difference between 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 significant impact on the participation–word-of-mouth linkage (at the .01 level). For respondents with high interaction preference the link was stronger, giving support for H7 . Regarding the link between participation and brand image, a significant positive moderating effect of interaction preference was found (at the .01 level), supporting H8 . Contrary to our expectations, interaction preference was not found to moderate the participation–community loyalty linkage; hence, H9 had to be rejected. DISCUSSION, LIMITATIONS, AND FURTHER RESEARCH Results of our empirical analysis reveal that most of the variance in participation can be explained by three factors: identification, satisfaction, and degree of influence. Marketing management has to keep these factors in mind when new features for the community are developed. First, when a company sets up a company-driven community, homogeneous members should be grouped into subcommunities to increase the identification of community members with the community. This could be accomplished by sending automated introductions of members to other members, depending on their profile match. Second, when implementing a virtual brand community, companies should focus on providing interaction elements to the users. In fact, successful online communities (e.g., business communities such as XING.com and LinkedIn.com, or communities for social exchanges such as friendster.com and facebook.com) provide many valuable Downloaded By: [2008-2009 Thammasat University] At: 13:18 5 June 2010 Woisetschl¨ager, Hartleb, and Blut 253 and adaptable examples of how to stimulate interaction between members of the community. The more satisfied the community members are, the more willing they will be to keep the community alive through interacting with other members. Third, the more open the platform is to user-generated content, the more community members will contribute to the community. From a management perspective, online communities are implemented for several reasons. A company’s brand image is enhanced by having customers exchange with like-minded people in a setting in which the brand is embedded. Our results demonstrate that active members of the community tend to evaluate the community presenter’s brand image more favorably. This fact should be an incentive to marketing managers to invest in a virtual community. Furthermore, when marketing managers intend to increase brand community size, they can acquire new members through recommendations of existing members. To ensure the long-term success of the community, companies can increase community members’ willingness to stay loyal to the community by engaging members. Regarding the moderating effect of interaction preference, community management can use this personal characteristic to cluster community members and design specific actions to increase word-of-mouth behavior of groups, being sensitive for interacting with others. Similarly, positive effects of community participation on brand image should be realized. 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