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Accepted Manuscript Gratifications of Using Facebook, Twitter, Instagram, or Snapchat to Follow Brands: The Moderating Effect of Social Comparison, Trust, Tie Strength, and Network Homophily on Brand Identification, Brand Engagement, Brand Commitment, and Membership Intention Joe Phua, Seunga Venus Jin, Jihoon (Jay) Kim PII: DOI: Reference: S0736-5853(16)30016-8 http://dx.doi.org/10.1016/j.tele.2016.06.004 TELE 813 To appear in: Telematics and Informatics Received Date: Revised Date: Accepted Date: 13 January 2016 3 June 2016 4 June 2016 Please cite this article as: Phua, J., Jin, S.V., Kim, J., Gratifications of Using Facebook, Twitter, Instagram, or Snapchat to Follow Brands: The Moderating Effect of Social Comparison, Trust, Tie Strength, and Network Homophily on Brand Identification, Brand Engagement, Brand Commitment, and Membership Intention, Telematics and Informatics (2016), doi: http://dx.doi.org/10.1016/j.tele.2016.06.004 This is a PDF file of an unedited manuscript that has been accepted for publication. 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Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. Gratifications of Using Facebook, Twitter, Instagram, or Snapchat to Follow Brands: The Moderating Effect of Social Comparison, Trust, Tie Strength, and Network Homophily on Brand Identification, Brand Engagement, Brand Commitment, and Membership Intention Joe Phua, Ph.D. Assistant Professor Grady College of Journalism and Mass Communication University of Georgia 120 Hooper Street Athens, GA 30602-3018 Email: joephua@uga.edu Phone: (706) 542-4984 Fax: (706) 542-2183 Corresponding Author*: Seunga Venus Jin, Ph.D.* Associate Professor Department of Marketing Communication Emerson College 120 Boylston St, Boston, MA 02116 Email: seunga.venus.jin@gmail.com Jihoon (Jay) Kim, M.A. Ph.D. Graduate Assistant Grady College of Journalism and Mass Communication University of Georgia 120 Hooper Street Athens, GA 30602-3018 Email: jaykim82@uga.edu Phone: (706) 542-4791 1 Gratifications of Using Facebook, Twitter, Instagram, or Snapchat to Follow Brands: The Moderating Effect of Social Comparison, Trust, Tie Strength, and Network Homophily on Brand Identification, Brand Engagement, Brand Commitment, and Membership Intention Abstract Applying uses and gratifications theory (UGT), this study examined consumers’ use of one of four social networking sites (SNSs): Facebook, Twitter, Instagram, or Snapchat, for following brands, and their influence on brand community-related outcomes. Results (N = 297) indicated Snapchat users scored highest for passing time, sharing problems, and improving social knowledge, while Instagram users scored highest for showing affection, following fashion, and demonstrating sociability. Twitter users had highest brand community identification and membership intention, while Instagram users had highest brand community engagement and commitment. Attention to social comparison, SNS trust, tie strength, and homophily also significantly moderated the relationship between frequent use of each SNS to follow brands, and brand community-related outcomes. Implications for future research on SNS users’ goal-directed consumption behaviors are discussed. Keywords: social media; social networking sites (SNSs); uses and gratifications theory (UGT); brand community; brand relationships; social comparison; tie strength; network homophily 2 1. Introduction Social networking sites (SNSs) enable users to create personal profiles, articulate their identities, connect with other users and brands, and view, share, upload and comment on photos, messages, videos and other content posted on their newsfeeds (boyd & Ellison, 2007; Phua & Jin, 2011). SNSs are becoming increasingly ubiquitous in the everyday lives of people worldwide. Among the most popular SNSs as of March 2016 are Facebook (1.56 billion active users), Instagram (400 million active users), Twitter (320 million active users), and Snapchat (200 million active users) (Statista, 2015). Additionally, a 2015 industry report by Social Media Examiner found that over 96% of businesses use SNSs to market their brands and products, due to their ability to increase brand exposure, attract website traffic, develop loyal fans, and gain marketplace intelligence (Stelzner, 2015). At the same time, consumers are increasingly using SNSs to find out about brands and products (Laroche, Habibi, Richard, & Sankaranarayanan, 2012; Lipsman, Mudd, Rich, & Bruich, 2012). Consumers also integrate two or more SNSs as part of their daily activities (Quan-Haase & Young, 2010) and access these SNSs on their mobile devices (Lenhart, Duggan, Perrin, Stepler, Rainie, & Parker, 2015), allowing marketers more touch-points to reach their consumers. Social media activities for a brand can foster the consumer base of the brand (Xie & Lee 2015) and engagement in social media brand communities increases consumers’ purchase expenditures (Goh, Heng, & Lin, 2013). Millions of companies have set up Facebook pages for brand communication purposes and the popularity of social media necessitates theoretical understanding of how social media exposures influence brand-related outcomes (Xie & Lee, 2015). In light of the exponential growth of SNSs and the integral role social media platforms play in brand communication (Xie & Lee, 2015; Goh, Heng, & Lin, 2013), this study aims to 3 provide theoretical explanations for “why” people use SNSs and further elucidate the key motivations for using different SNS platforms in the context of brand communities. To this end, the current research draws from uses and gratification theory (UGT) given the relevance of the theory to the assumption of media users as “active communicators” instead of passive recipients of media forms and contents (Rubin, 2002). Approaching the intersection between consumers’ use of multiple SNSs to find out about brands and the utility of different SNSs for social media marketing, this study applies UGT (Katz, Blumler, & Gurevitch, 1973) to examine consumers’ use of several top SNS platforms to follow brands, gratifications gained from using them, and their influence on brand community-related outcomes. Drawing from UGT and building upon previous empirical findings (Quan-Haase & Young, 2010), the present study posited that frequent users of Facebook, Twitter, Instagram, and Snapchat would derive different gratifications from their use (passing time, showing affection, following fashion, sharing problems, demonstrating sociability, and improving social knowledge) (Quan-Haase & Young, 2010), and also have different impacts on brand communityrelated outcomes (identification, engagement, commitment, and membership intention). The relationship between SNS use and brand community-related outcomes would also be moderated by several intervening variables (e.g., attention to social comparison, SNS trust, tie strength, and network homophily). Overall, the study offers insights into the utility of different SNS platforms for marketing and their influences on consumers’ perceptions of brands they follow. 2. Literature Review 2.1. Social Networking Sites (SNSs) and Brands A major advantage of SNSs over more traditional media (e.g., radio, television) is their capacity for greater user interactivity. When SNS users “like” or “follow” a brand, they will 4 receive updates and posts by the brand on their newsfeed. The users can then “like”, share, or comment on the post, which would further propagate it on their friends’ newsfeeds, whose own interactions with the post would, in turn, be rebroadcast to their networks. Hence, brand content is transmitted in SNSs at a much faster rate and to a much larger and more responsive audience than most traditional media, but at a much lower cost (Qualman, 2013). As such, digital marketers are increasingly incorporating SNSs as an indispensable part of their online brand strategy by raising brand awareness, driving engagement, and increasing conversions for their brands and products. Previous research on SNSs in consumer marketing found increased consumer engagement with brands based on frequency and content of brand pages’ updates (Colliander & Dahlen, 2011; Phua & Ahn, 2014; Tsai & Men, 2013), proliferation of usergenerated content (UGC) (Krishnamurthy & Dou, 2008; Vanden Bergh, Lee, Quilliam, & Hove, 2011), referrals and recommendations (Chatterjee, 2011), identification and membership in brand communities (Christodoulides, Jevons, & Bonhomme, 2012; Kim, Sung, & Kang, 2014), and celebrity-endorsed electronic word-of-mouth (eWoM) (Jin & Phua, 2014; Lee & Youn, 2009). Studies also examined motivations for engagement with SNS advertising content (Chi, 2011; Kwon, Kim, Sung, & Yoo, 2014; Muntinga, Moorman, & Smit, 2011; Taylor, Strutton, & Thompson, 2012), suggesting that SNS users have various motivations (e.g., informationseeking, leisure, etc.) that influence their use of features within one SNS platform as well as across different SNS platforms. The current study attempts to examine whether gratifications of using SNSs significantly differ across four different SNS platforms (Facebook, Twitter, Instagram, and Snapchat), each with unique interactive features and ways for consumers to engage with branded content. 2.2. Uses and Gratifications Theory (UGT) 5 UGT (Katz et al., 1973) is a theoretical framework explaining how and why people actively seek out different media to fulfill their specific needs and wants. UGT posits that the gratifications users receive through the media they select, in turn, satisfy a variety of informational, social, and leisure needs. Key assumptions of UGT are: consumers are goaldirected in their media selection behavior and actively interpret and integrate media messages, including advertisements, within their everyday lives, so as to achieve optimal levels of gratification for their needs and desires (Rubin, 1986). Studies applying UGT have found that consumers actively seek out different media to fulfill their informational, entertainment, social, and escapism needs, with media self-efficacy, habitual behavior, prior attitudes, self-regulation, and other factors moderating their media selections (Dimmick, Chen, & Li, 2004; Ko, Cho, & Roberts, 2005; LaRose & Eastin, 2004). More recently, scholarly research has used UGT to examine consumers’ goal-directed consumption behavior in the context of SNSs (e.g., Chi, 2011; Kwon et al., 2014; Muntinga et al., 2011; Papacharissi & Mendelson, 2011; Taylor et al., 2012). In particular, two trends with regards to SNS use among brand consumers have been identified: (1) the majority of consumers simultaneously use more than one SNS platform because each has its unique features and purposes, and; (2) consumers increasingly embrace SNSs as both a communication channel and an informational tool that help them fulfill their informational, emotional, and social desires when used in tandem (Lenhart et al., 2015; Quan-Haase & Young, 2010). To date, numerous researchers have analyzed motives for using SNSs applying the UGT approach. For instance, Gulnar, Balci, and Cakir (2010) proposed seven motives affecting YouTube and Facebook use: self-expression, media drenching, passing time, information seeking, personal status updating, relationship maintenance, and entertainment. Park, Kee, and Valenzuela (2009) found that four 6 primary needs (socializing, entertainment, self-status seeking, and information) were fulfilled from participating in Facebook groups. Quan-Haase and Young (2010), meanwhile, compared Facebook and instant messaging use, and found that Facebook users derived fun and knowledge about social activities from its use, while instant messaging is more for relationship maintenance and development. UGT sees a medium as a source of influence within the context of other possible influences. The theory also underscores the role of social and psychological elements in mitigating mechanistic effects and sees mediated communication as being socially and psychologically constrained (Rubin, 2002). Applying the UGT framework to the context of social media use, people may use Facebook to stay in touch with friends, Twitter to follow news and trending topics, Snapchat to instantly share short videos with selected individuals, and Instagram to easily filter and upload visual images (Figure 1). Differences in main features and functions among key SNS platforms examined in this study are presented in Figure 1. [Insert Figure 1 about here] Due to the unique and different design and usability features of SNS platforms, as well as users’ different social psychological motivations to use each platform (Quan-Haase & Young, 2010), it can be hypothesized that individuals who most frequently use Facebook, Twitter, Instagram, or Snapchat to follow brands, would differ significantly on six gratifications derived. H1: SNS users who most frequently use Facebook, Twitter, Instagram, or Snapchat for following brands, will differ significantly on six gratifications of SNS use: (a) passing time, (b) showing affection, (c) following fashion, (d) sharing problems, (e) demonstrating sociability, and (f) improving social knowledge. Figure 2 graphically presents the research model proposed in H1. [Insert Figure 2 about here] 7 2.3. SNS Brand Communities A brand community 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). In online brand communities, members often exhibit shared consciousness, rituals and traditions, and a sense of moral responsibility, with many Internet users assuming memberships in multiple brand communities, and managing their personal and social identities through these memberships (Muniz & Schau, 2007). Similarly, on SNSs, consumers are motivated to join brand communities to fulfill their social and identification needs. SNS brand communities include groups centered around particular brands and products, as well as brand pages which allow SNS users to “like” or “follow” brands and brand updates, as well as comment and share these posts (Chi, 2011; Tsai & Men, 2013). Due to the ability to craft brand messages that can be propagated by SNS users in a viral manner through their social networks on various SNS platforms, brand pages are becoming an increasingly important part of digital advertising and marketing strategies (Qualman, 2013). Brand pages not only allow consumers with common brand interests to engage in communal activities, but also serve as a way for these consumers to define their personal and social identities based on different brands they “like” or “follow” on SNSs. Many brand pages also allow followers to engage in community activities, including participating in contests, creating and sharing UGC such as videos and pictures, and getting promotional offers. Previous research on Internet-based brand communities has found that members establish shared connections and a collective identity through their common interest in particular brands, even in communities with a lack of social interaction among members (Algesheimer, Dholakia, & Herrmann, 2005; Carlson, Suter, & Brown, 2008). Through identifying with others in the 8 brand community and conforming to group norms with regards to their consumption habits, individuals satisfy their own intrinsic utilitarian (e.g., finding information about brands) and hedonic (e.g., experiencing sensory pleasure through brands) consumption goals, while also integrating the brand community as part of their identity on the SNS (Muniz & Schau, 2007). Individuals who identify strongly with brand communities also develop stronger brand trust (Hung, Li, & Tse, 2011), are more easily persuaded by brand messages (Kilambi, Laroche, & Richard, 2013), and are more likely to share brand messages with others (Kim et al., 2014). Additionally, consumers who are more engaged with brand communities are more likely to follow the community rules, participate in brand-related activities, and exhibit higher brand loyalty over a longer period of time (Hollebeek, Glynn, & Brodie, 2014; Kwon et al., 2014). Moreover, when consumers are highly committed to a brand community, they are more likely to purchase the brand’s products (Kilambi et al., 2013; Muniz & Schau, 2007; Scarpi, 2010). Consumers with higher membership intention also visit brand pages more regularly, actively upload UGC, spread eWoM, and stay on as brand “followers” for a longer period of time (Jin & Phua, 2014; Sung, Kim, Kwon, & Moon, 2010). It can be hypothesized, therefore, that individuals who most frequently use Facebook, Twitter, Instagram, or Snapchat to follow brands, and who are members of brand communities on these SNS platforms, would differ significantly on brand community-related outcomes. H2: SNS users who most frequently use Facebook, Twitter, Instagram or Snapchat for following brands, would differ significantly on brand communities with regard to users’: (a) brand identification, (b) brand engagement, (c) brand commitment, and (d) membership intention. Blue diagrams and lines in Figure 3 graphically present the research model proposed in H2. 9 [Insert Figure 3 about here] 2.4. Attention to Social Comparison, SNS Trust, Tie Strength, and Homophily Attention to social comparison refers to a person’s awareness of and sensitivity to the reactions of others with regards to his/her own behavior (Lennox & Wolfe, 1984). Social comparison with others within one’s social groups is a self-enhancement strategy that enables an individual to raise his/her self-esteem through evaluating oneself with significant reference groups. Attention to social comparison plays a significant role in influencing consumer purchases and usage of peer-endorsed brands (Bearden & Rose, 1990; Chan & Prendergast, 2008; Mandel, Petrova, & Cialdini, 2006). On SNSs, due to the ability of users to view brands and products followed and/or liked by others within their social networks, as well as posts and comments uploaded by peer consumers on brand pages, social comparison may have a significant effect on consumers’ perceptions of brand communities (Kim et al., 2014; Sung et al., 2010). Additionally, SNS trust, tie strength, and network homophily, have a strong effect on SNS users’ engagement with brand communities, and propensity to seek, give, and pass along opinions about brands on the sites (Chu & Kim, 2011; Shan & King, 2015). SNS trust refers to users’ willingness to rely on others in whom they have confidence (Moorman, Deshpande, & Zaltman, 1993). Tie strength is the degree to which bonds among SNS members are strong or weak (Mittal, Huppertz, & Khare, 2008). On SNSs, members derive bridging social capital with acquaintances and distant others (Jin & Phua, 2014) and bonding social capital with close friends and family (Phua & Jin, 2012). A study by Ellison, Steinfield and Lampe (2007) found that intensity of Facebook use led to greater bridging social capital, but not bonding social capital. Intensity of SNS use therefore did not necessarily increase trust nor tie strength, since bridging 10 social capital involves loose and weak friendship ties with low levels of trust but greater ability for diffusion of new information (Granovetter, 1973). Homophily refers to the degree of similarity among SNS network connections based on their beliefs, values, social status, and interests (McPherson, Smith-Lovin, & Cook, 2001), with brand messages propagated within homogeneous networks (Liu-Thompkins, 2012). When group members are homogeneous, reference group influence becomes strong since similar users tend to interact frequently and develop strong ties (Brown & Reingen, 1987). Homogeneous users within SNS-based brand communities have more opportunity to exchange brand-related information and are more likely to identify with the group members. When message senders (SNS posters) and receivers (SNS viewers) in brand communities are more homogeneous, the information exchanged and shared is likely to be perceived as more credible and trustworthy. Furthermore, a marketing stimulus that focuses attention on consumers’ identification with a reference group and is relevant to that identification elicit more positive responses (Reed, 2004). Based on these empirical findings and theoretical rationales, it can be hypothesized that attention to social comparison, SNS trust, tie strength, and network homophily would moderate the relationship between consumers’ SNS use and brand community-related outcomes. H3: The relationship between consumers’ brand-related participation in their most frequently used SNS for following brands (Facebook, Twitter, Instagram or Snapchat), and brand community-related outcomes (identification, engagement, commitment, and membership intention) would be moderated by (a) attention to social comparison, (b) SNS trust, (c) SNS tie strength, and (d) SNS homophily. Red diagrams and lines in Figure 3 graphically present the research model proposed in H3. 11 3. Methods 3.1. Participants College students (N = 305) enrolled at a major university in the United States participated in the study for extra credit. A total of 252 (82.6%) were female, while 53 (17.4%) were male. For ethnicity, 229 (75.1%) were White, 28 (9.2%) were African-American, 28 (9.2%) were Asian, 10 (3.3%) were Latino/Hispanic, 5 (1.6%) were Mixed, and 5 (1.6%) were Other. For year in school, 23 (7.5%) were freshmen, 92 (30.2%) were sophomores, 116 (38.0%) were juniors, 71 (23.3%) were seniors, and 3 (1.0%) were graduate students. For annual household income, 90 (29.5%) earned less than $20,000, 12 (3.9%) earned $20,000-$40,000, 40 (13.1%) earned $40,000-$60,000, 42 (13.8%) earned $60,000-$80,000, 36 (11.8%) earned $80,000$100,000, and 85 (27.9%) earned more than $100,000. Mean participant age was 20.3 years old (SD = 1.25). 3.2. Procedure An online questionnaire created using Qualtrics was posted to the college’s research participation pool. At the beginning of the questionnaire, participants were first asked to select only one SNS from a drop-down list (including Facebook, Twitter, Instagram and Snapchat) that they most frequently used for following brands, and to answer all subsequent questions based on their use of this one specific SNS. By doing this, we ensured that the SNS chosen by each participant was the one that they most frequently used for acquiring brand-related information and content, and participating in brand-related communities. 3.3. Measures All measures were drawn from previously used scales that have been empirically validated in published research. Gratifications of SNS use were assessed using six sub-scales 12 modified from Quan-Haase and Young (2010): passing time, affection, fashion, sharing problems, demonstrating sociability, and improving social knowledge, on 7-point Likert scales, ranging from “strongly disagree” to “strongly agree”. Passing time (9 items) included “to kill time” and “to get away from pressures and responsibility” (Cronbach’s = .85). Affection (5 items) included “to thank people” and “to let people know I care about them” (Cronbach’s .87). Fashion (3 items) included “to look stylish” and “to look fashionable” (Cronbach’s = = .83). Sharing problems (3 items) included “to forget about my problems” and “because I need someone to talk to or be with” (Cronbach’s = .79). Demonstrating sociability (3 items) included “to make friends” and “to meet new acquaintances” (Cronbach’s = .81). Improving social knowledge (1 item) included “to know what’s going on with other people”. To measure brand-related participation in the most frequently used SNS for following brands, we included seven items modified from Rosen, Carrier, and Cheever (2013), on 7-point Likert scales ranging from “not at all” to “frequently”. Items included “how often do you read postings by brand pages on the SNS?” and “how often do you browse profiles and photos of brand pages on the SNS?” (Cronbach’s = .84). Brand community identification, engagement, commitment, and membership intention were assessed using items modified from Sung et al. (2010) on 7-point Likert scales ranging from “strongly disagree” to “strongly agree”. Identification (5 items) included “I see myself as part of this brand community” and “I am very attached to this brand community” (Cronbach’s = .89). Engagement (4 items) included “I am motivated to participate because I am able to reach personal goals” and “I am motivated to participate because I can support other members” (Cronbach’s = .90). Commitment (2 items) included “I am proud to belong to this brand community” and “I feel a sense of belonging to this brand community” (Cronbach’s = .79). Membership intention (3 items) included “I intend to 13 stay on as a follower of this brand community” and “I plan to regularly visit this brand community” (Cronbach’s = .80). To measure attention to social comparison, we used 13 items modified from Lennox and Wolfe (1984) on 7-point Likert scales, ranging from “strongly disagree” to “strongly agree”. Items included “I actively avoid wearing clothes that are not in style” and “At parties I usually try to behave in a manner that makes me fit in” (Cronbach’s = .85). Meanwhile, SNS trust, tie Strength and homophily were measured using items modified from Chu and Kim (2011), on 7point Likert scales ranging from “strongly disagree” to “strongly agree”. Trust (3 items) included “I trust my friend connections on this SNS”, and “I have confidence in my friend connections on this SNS” (Cronbach’s = .84). SNS tie strength (3 items) included “I feel very close to my friend connections on this SNS” and “I communicate frequently with my friend connections on this SNS” (Cronbach’s = .83). SNS homophily (3 items) included “My friend connections on this SNS think like me” and “My friend connections on this SNS behave like me” (Cronbach’s = .86). 4. Results 4.1. SNS Use For SNS most frequently used to follow brands, 116 (38.0%) answered Instagram, 93 (30.5%) answered Facebook, 60 (19.7%) answered Twitter, 28 (9.2%) answered Snapchat, 6 (2.0%) answered Tumblr, 1 (.4%) answered Pinterest, and 1 (.4%) answered Google+. For main device to log in to the SNS, 241 (79.0%) used smartphones, 55 (18.0%) used laptops, 5 (1.6%) used desktops, and 4 (1.3%) used tablets. These findings were consistent with a Pew Research Center report on teenagers, SNS and technology use (Lenhart et al. 2015). Mean time as a member of the SNS most frequently used was 52 months (SD = 24.9); mean time per week spent 14 using the SNS was 161 minutes (SD = 90.9); mean number of friends on the SNS was 480 (SD = 219.5); mean number of brands followed on the SNS was 39 (SD = 70.6). For the final data analysis, the eight participants who reported using Tumblr, Pinterest or Google+ most frequently for following brands were excluded, leaving 297 total participants who reported using Facebook, Twitter, Instagram or Snapchat more frequently for following brands. 4.2. Gratifications of Using SNSs A one-way MANOVA was conducted to examine gratifications of using SNSs (passing time, showing affection, following fashion, sharing problems, demonstrating sociability, and improving social knowledge) by SNS platform most frequently used to follow brands (Facebook, Twitter, Instagram or Snapchat). Results revealed a significant multivariate main effect by SNS platform most frequently used to follow brands (Wilks’ λ = .757, F (18, 815) = 4.68, p < .001, partial η2 = .089, observed power = 1.00). Given the significance of the overall test, univariate ANOVA results were examined with the p-value set at < .0125 to control for Type I error. Significant univariate main effects by SNS platform were obtained for “passing time” [F (3, 293) = 5.21, p < .001, partial η2 = .051, observed power = .925]; “showing affection” [F (3, 293) = 5.17, p < .001, partial η2 = .050, observed power = .923]; “following fashion” [F (3, 293) = 11.55, p < .001, partial η2 = .106, observed power = 1.00], “sharing problems” [F (3, 293) = 5.60, p < .001, partial η2 = .054, observed power = .942] “demonstrating sociability” [F (3, 293) = 12.86, p < .001, partial η2 = .116, observed power = 1.00], and “improving social knowledge” [F (3, 293) = 5.98, p < .001, partial η2 = .058, observed power = .956] . Levene’s tests of equality of error variances were insignificant for all dependent measures, hence Scheffe post-hoc tests were used to compare pairwise group means. 15 Scheffe post-hoc tests revealed that for “passing time,” significant differences were observed between Snapchat and Facebook use (p < .01), Instagram and Facebook use (p < .001), and Twitter and Facebook use (p < .01). Mean score for “passing time” was highest on Snapchat (M = 5.46, SD = .92), followed by Instagram (M = 5.39, SD = .82), Twitter (M = 5.38, SD = .91), and Facebook (M = 4.93, SD = 1.09). For “showing affection,” significant differences were observed between Instagram and Twitter use (p < .01), Facebook and Twitter use (p < .01), and Snapchat and Twitter use (p < .01). Mean score for “showing affection” was highest on Instagram (M = 4.13, SD = 1.16), followed by Facebook (M = 4.11, SD =1.25), Snapchat (M = 4.05, SD = 1.33), and Twitter (M = 3.44, SD = .97). For “following fashion,” significant differences were observed between Instagram and Facebook use (p < .001), Instagram and Twitter use (p < .001), and Snapchat and Twitter use (p < .01). Mean score for “following fashion” was highest on Instagram (M = 4.43, SD = 1.42), followed by Snapchat (M = 4.17, SD = 1.62), Facebook (M = 3.58, SD=1.55), and Twitter (M = 3.21, SD = 1.19). For “sharing problems,” significant differences were observed between Snapchat and Twitter use (p < .01), Facebook and Twitter use (p < .01), and Instagram and Twitter use (p < .01). Mean score for “sharing problems” was highest on Snapchat (M = 4.20, SD = 1.66), followed by Facebook (M = 3.96, SD = 1.67), Instagram (M = 3.62, SD = 1.74) and Twitter (M = 2.99, SD = 1.07). For “demonstrating sociability,” significant differences were obtained between Instagram and Twitter (p < .001), Facebook and Twitter use (p < .001), and Snapchat and Twitter use (p < .01). Mean score for “demonstrating sociability” was highest on Instagram (M = 4.72, SD = 1.53), followed by Facebook (M = 4.45, SD = 1.71), Snapchat (M = 4.39, SD = 1.72), and Twitter (M = 3.16, SD = 1.48). For “improving social knowledge,” significant differences were observed between Snapchat and Facebook use (p < .01) and Twitter and Facebook use (p < 16 .01). Mean score for “improving social knowledge” was highest on Snapchat (M = 5.96, SD = 1.20), followed by Twitter (M = 5.85, SD = 1.29), Instagram (M = 5.48, SD = 1.13), and Facebook (M = 5.18, SD = 1.29). [Insert Figure 4 and Figure 5 about here] 4.3. Brand Community Outcomes A one-way MANOVA was conducted to examine brand community outcomes (identification, engagement, commitment, and membership intention) by SNS platform most frequently used for following brands (Facebook, Twitter, Instagram or Snapchat). Results revealed a significant multivariate main effect by SNS platform most frequently used for following brands (Wilks’ = .772, F (12, 768) = 6.56, p < .001, partial η2 = .082, observed power = 1.00). Given the significance of the overall test, univariate ANOVA results were examined with the p-value set at < .0125 to control for Type I error. Significant univariate main effects by SNS platform were obtained for “brand community identification” [F (3, 293) = 22.89, p < .001, partial η2 = .190, observed power = 1.00]; “brand community engagement” [F (3, 293) = 24.13, p < .001, partial η2 = .190, observed power = 1.00]; “brand community commitment” [F (3, 293) = 33.76, p < .001, partial η2 = .257, observed power = 1.00], and “brand community membership intention” [F (3, 293) = 17.50, p < .001, partial η2 = .152, observed power = 1.00]. Levene’s tests of equality of error variances were insignificant, hence Scheffe post-hoc tests were used to compare pairwise group means. Scheffe post-hoc tests revealed that for “brand community identification,” significant differences were obtained between Twitter and Facebook use (p < .001), Twitter and Instagram use (p < .001), Twitter and Snapchat use (p < .001), Instagram and Facebook use (p < .01), and Instagram and Snapchat use (p < .001). Mean score for “brand community identification” was 17 highest on Twitter (M = 5.15, SD = 1.13), followed by Instagram (M = 4.49, SD = 1.13), Facebook (M = 3.90, SD = 1.18), and Snapchat (M = 3.37, SD = .81). For “brand community engagement,” significant differences were observed between Instagram and Facebook use (p < .001), Instagram and Snapchat use (p < .001), Twitter and Facebook use (p < .001), and Twitter and Snapchat use (p < .001). Mean score for “brand community engagement” was highest on Instagram (M = 5.21, SD = 1.22), followed by Twitter (M = 5.02, SD = .86), Facebook (M = 4.19, SD = 1.10), and Snapchat (M = 3.68, SD = 1.23). For “brand community commitment,” significant differences were observed between Instagram and Facebook use (p < .001), Instagram and Snapchat use (p < .001), Twitter and Facebook (p < .001), and Twitter and Snapchat use (p < .001). Mean score for “brand community commitment” was highest on Instagram (M = 5.61, SD = 1.16), followed by Twitter (M = 5.37, SD = .986), Facebook (M = 4.23, SD = 1.49), and Snapchat (M = 3.75, SD = .81). For “brand community membership intention,” significant differences were observed between Twitter and Instagram use (p < .01), Twitter and Facebook use (p < .001), Twitter and Snapchat use (p < .001), Instagram and Facebook use (p < .001), and Instagram and Snapchat use (p < .001). Mean score for “brand community membership intention” was highest on Twitter (M = 5.62, SD = .85), followed by Instagram (M = 5.16, SD = .99), Facebook (M = 4.56, SD = 1.21) and Snapchat (M = 4.28, SD = 1.05). [Insert Figure 6 and Figure 7about here] 4.4. Moderation Effects To test the moderation effects proposed in H3, hierarchical multiple regression analyses were conducted. To avoid potential high multicollinearity, each variable was centered, and interaction terms were created between brand-related participation in the SNS most frequently 18 used for following brands and each potential moderator, and entered into model two of each set of hierarchical regressions. For each potentially significant moderation effect, the PROCESS macro for SPSS (Hayes, 2013), across 1000 bootstrap samples, was run on the centered terms to examine the effect. Attention to social comparison significantly interacted with brand-related participation in most frequently used SNS for following brands to influence brand community identification [ R2 = .016, F (1, 293) = 5.29, p < .05,β = -.123, 95% CI [-.237, -.010], t (293) = -2.14, p < .05], but not engagement [ R2 = .001, F (1, 293) = .380, p = .538], commitment [ R2 = .009, F (1, 293) = 2.93, p = .09], and membership intention [ R2 = .007, F (1, 293) = 2.29, p = .131]. SNS site trust significantly interacted with brand-related participation in most frequently used SNS for following brands to influence brand community identification, [ R2 = .018, F (1, 293) = 5.40, p < .05,β = .126, 95% CI [.012, .239], t (293) = 2.18, p < .05], and membership intention [ R2 = .022, F (1, 293) = 6.88, p < .01,β = .130, 95% CI [.038, .222], t (293) = 2.78, p < .01], but not engagement [ R2 = .001, F (1, 293) = .319, p = .573] and commitment [ R2 = .000, F (1, 293) = .004, p = .949]. Similarly, SNS tie strength significantly interacted with brand-related participation in most frequently used SNS for following brands to influence brand community identification [ R2 = .055, F (1, 293) = 17.65, p < .001,β = .135, 95% CI [.067, .203], t (293) = 3.90, p < .001] and membership intention [ R2 = .043, F (1, 293) = 13.26, p < .001,β = .135, 95% CI [.067, .203], t (293) = 3.91, p < .001], but not engagement [ R2 = .008, F (1, 293) = 2.29, p = .131] and commitment [ R2 = .003, F (1, 293) = .976, p = .324]. Meanwhile, SNS homophily significantly interacted with brand-related participation in most frequently used SNS for following brands to influence brand community commitment, [ R2 = .017, F (1, 293) = 5.10, p < .05,β = -.160, 95% CI [-.274, -.046], t (293) = -2.76, p < .01], but not identification [ R2 = .007, F (1, 293) = 2.00, p = .158], engagement [ R2 = .003, F (1, 19 293) = .921, p = .338], and membership intention [ R2 = .006, F (1, 293) = 1.71, p = .191]. Interaction plots of significant moderator effects are shown in Figure 8. [Insert Figure 8 about here] 5. Discussion 5.1. Key Empirical Findings, Managerial Implications, and Theoretical Contributions The results indicate that individuals who most frequently used Facebook, Twitter, Instagram, or Snapchat to follow brands differ significantly on six gratifications of SNS use: passing time (H1a), showing affection (H1b), following fashion (H1c), sharing problems (H1d), demonstrating sociability (H1e), and improving social knowledge (H1f). Specifically, individuals who used Snapchat most frequently for following brands scored highest on passing time, sharing problems, and improving social knowledge, while individuals who used Instagram most frequently for following brands scored highest on showing affection, following fashion, and demonstrating sociability. Snapchat and Instagram are both photo and video messaging apps gaining in popularity among millennials (Lenhart et al., 2015). On Snapchat, users set a time limit for how long recipients can view their “snaps” before they are deleted while on Instagram, users apply shaded filters to their photos before posting them to their profiles (Lenhart et al., 2015). Individuals who used Snapchat most frequently for following brands score the highest on passing time, followed by those who used Instagram, Twitter and Facebook most frequently, indicating that they found Snapchat most useful for entertainment and relaxation purposes, as well as being fun and a form of escapism from their everyday routines. Individuals who used Snapchat most frequently for following brands also scored the highest on sharing problems, followed by Facebook, Instagram, and Twitter. As such, users found Snapchat to be most helpful when they need someone online to listen to them in order to forget their problems. Additionally, 20 individuals who used Snapchat most frequently to follow brands also felt that the site most fulfilled their need for improving social knowledge, making them feel most involved with what’s going on with other people, followed by those who most frequently used Twitter, Instagram and Facebook. These findings are likely due to the synchronous and personal nature of Snapchat, whereby users send photo or video “snaps” via their mobile devices and are able to receive immediate, personal replies from recipients. Comparatively, on Facebook, Twitter, and Instagram, one’s posts are less personal and more asynchronous, since posts can be seen by a larger number of people over a longer period of time, with friends’ replies to one’s posts also being broadcast publicly. As a result, users of these sites may not be as comfortable sharing problems, and consequently, feel less involved with what’s going on in others’ lives, compared to the more personal, intimate nature of Snapchat. On the other hand, individuals who most frequently used Instagram for following brands score the highest on showing affection, followed by Facebook, Snapchat and Twitter, indicating that Instagram most fulfill users’ needs to thank people, let others know they care, offer help, and show encouragement and concern (Quan-Haase & Young, 2010). Instagram was also rated the highest on following fashion, with members using the site primarily as a style guide, compared to Snapchat, Facebook, and Twitter. Additionally, individuals who used Instagram most frequently for following brands also ranked the highest for demonstrating sociability, or making friends of the opposite sex, meeting new acquaintances, and being least inhibited chatting to strangers, followed by those who most frequently used Facebook, Snapchat, and Twitter. These results may be explained by the fact that Instagram, being a visual image-based SNS primarily for posting pictures with shaded filters, acts as a showcase for one’s style and fashion. At the same time, Instagram users may also be less inhibited, since the visual nature of the SNS allows 21 them to view “like,” and “follow” other members whom they may not know in real life, but interact with on the site through their pictures. Moreover, the uninhibitedness of Instagram users may also lead to their greater showing of affection toward others, through commenting on others’ pictures and using emoticons, compared to the other three SNSs. More importantly and with regard to contributions to empirical findings about and data on social media-related brand outcomes, the results indicate that level of brand-related participation in the SNS most frequently used for following brands (Facebook, Twitter, Instagram or Snapchat) resulted in significantly different levels of brand community identification (H2a), engagement (H2b) commitment (H2c), and membership intention (H2d) from the sites. Specifically, individuals who used Twitter most frequently for following brands reported the highest brand community identification from the site, followed by those who most frequently used Instagram, Facebook, and Snapchat for following brands As such, individuals who use Twitter most frequently for following brands have the strongest attachment to brand communities, sharing brand-related objectives and seeing themselves as part of the larger community (Algesheimer et al., 2005; Carlson et al., 2008; Muniz & Schau, 2007). This may be possible due to Twitter being a micro-blogging site where brands post multiple updates in real time and allow followers to “retweet” these updates, search for brands using hashtags, and spread eWoM using their own 140-character posts which are then re-broadcast to their followers’ feeds (Jin & Phua, 2014). On Twitter, marketers are also best able to imbue brands with human personalities, and therefore build strong identification with consumers (Kwon et al., 2014). Individuals who used Twitter most frequently for following brands also reported the highest brand community membership intention, followed by those who most frequently used Instagram, Facebook and Snapchat for following brands. Individuals who used Twitter most frequently for 22 following brands are hence most likely to regularly visit brand pages they follow, stay on as brand followers, create UGC, and spread eWoM (Chu & Kim, 2011; Jin & Phua, 2014). One of the major functions of Twitter for SNS-based marketing is the ability for followers to retweet brand messages. As Kim et al. (2014) found, Twitter users reported significantly higher membership intention when performing retweeting behavior, consistent with the findings of the current study whereby retweeting is analogous to a form of eWoM. This study also found that individuals who most frequently used Instagram for following brands reported highest brand community engagement, followed by those who most frequently used Twitter, Facebook or Snapchat for following brands. Individuals who most frequently used Instagram for following brands are therefore most likely to participate in brand-related activities, follow community rules, and be loyal to brand they follow over a longer period of time (Hollebeek et al., 2014). Since Instagram is a photo-sharing platform, whereby members post pictures and short videos with different filters applied, brands are able to post their products’ graphic content in a visually pleasing and highly stimulating way (Lenhart et al., 2015). Thus, it is possible that Instagram users would be more engaged with brands they follow on the site, participate in brand-related activities, and have high brand loyalty. Furthermore, individuals who most frequently used Instagram for following brands also exhibited the highest brand community commitment, followed by those who most frequently used Twitter, Facebook, and Snapchat for following brands. When one is committed to a brand community, he/she is more likely to feel a sense of belonging and have higher brand purchase intention (Kilambi et al., 2013; Scarpi, 2010). The results indicate that Instagram users show the greatest belongingness and pride in the brand pages on which they participate. Consequently, this commitment to the brand community can contribute to future intention to purchase the brand’s products (Jin & Phua, 2014; Muniz & 23 Schau, 2007). These empirical findings have tremendous managerial implications for effective management of social media platforms for brand communication. Another major finding of this study is that brand-related participation in the SNS most frequently used for following brands (Facebook, Twitter, Instagram or Snapchat) significantly interacted with several moderators to affect brand community identification, engagement, commitment, and membership intention. Specifically, attention to social comparison (H3a) moderated the relationship between brand-related participation in the SNS most frequently used for following brands and brand community identification. For consumers with low attention to social comparison, greater brand-related participation in the SNS most frequently used for following brands led to higher brand community identification, whereas for those with high attention to social comparison, greater brand-related participation in the SNS most frequently used for following brands led to lower identification. Additionally, SNS trust (H3b) significantly moderated the relationship between brand-related participation in SNS most frequently used for following brands and brand community identification and membership intention. Consumers with higher SNS trust increased their brand communication, identification, and membership intention through increased brand-related participation in the SNS most frequently used for following brands, while those with lower SNS trust decreased their identification and membership intention if they participated more in the SNS most frequently used for following brands. SNS tie strength (H3c) also significantly moderated the relationship between brandrelated participation in the SNS most frequently used for following brands and brand community identification and membership intention. Consumers who perceived stronger ties to their SNS friends increased their identification and membership intention as their brand-related participation in the SNS most frequently used for following brands increased, while those who 24 perceived weaker ties to their SNS friends decreased their identification and membership intention with increased brand-related participation in the SNS most frequently used for following brands. Finally, SNS homophily (H3d) significantly moderated the relationship between brand-related participation in the SNS most frequently used for following brands and brand community commitment. Consumers with more homogeneous networks decreased their brand community commitment when brand-related participation in the SNS most frequently used for following brands increased, while those with more heterogeneous networks increased their brand community commitment when brand-related participation in the SNS most frequently used for following brands increased. These results indicate that many intervening factors affect the relationship between a consumer’s brand-related participation in the SNS most frequently used for following brands and his or her contributions to, and benefits derived from, brand communities followed on the particular SNS (Chu & Kim, 2011; Kim et al., 2014). Overall, this research advances our understanding of SNS users’ various motivations for using different social media platforms to follow brands, thus providing brand manages with deeper insights into the management of SNS platforms building upon the solid understanding of consumers’ motivations and needs in the context of social media marketing. With regard to theoretical contributions, this research not only empirically tests UGT in the novel domain of social media and brand communities but also adds theoretical discussions on user habit and motivations across a variety of social media platforms to existing UGT literature, thus contributing to the development of UGT in computer-mediated brand communications. 5.2. Limitations and Implications There are some limitations to the present study, which offer suggestions and implications for future research. First, we asked participants to self-report their most frequently used SNS for 25 following brands, level of brand-related participation in the SNS most frequently used for following brands, and perceived identification, engagement, commitment, and membership intention, for brand pages they follow on the particular SNS. Although self-reports provide accurate data about media use drawing from UGT (Rubin, 2002), future studies should access actual SNS usage data using social monitoring programs, so as to establish greater generalizability of the results. Second, the six gratifications included (passing time, showing affection, following fashion, sharing problems, demonstrating sociability, and improving social knowledge) were from one prior study (Quan-Haase & Young, 2010). Future studies should further explicate SNS uses and gratifications through factor analysis and structural modeling combining additional scales from other studies. Third, our study sample consisted of undergraduate students, who have been found to be more active on newer SNSs like Snapchat and Instagram (Lenhart et al., 2015), and as such, our results may be skewed towards this particular population of millennials. To increase external validity of this line of research, future studies should recruit participants from a wider age range, so as to obtain results most applicable to the general SNS-using population. Fourth, we did not control for specific brands followed by users on each SNS. It is possible that SNS users who follow hedonic versus utilitarian brands, and brands in different product categories (e.g. fashion, automobiles, travel etc.) may derive different brand community-related outcomes from their participation. Future studies should compare SNS followers of one particular type of brand or product category across different SNS platforms. Fifth, we did not examine other antecedents of purchase intention, such as brand awareness and brand image, nor explore factors affecting SNS members’ following of or using brand communities, which future studies should assess. 26 Our study also offers some practical implications for advertisers and marketers looking to harness different SNS platforms to improve their branding. First, as our results strongly suggest, SNS users derive significantly different gratifications from their frequent use of Facebook, Twitter, Instagram, or Snapchat to follow brands. Those who used Snapchat most frequently for following brands rated the SNS highest for passing time, sharing problems, and improving social knowledge, while those who used Instagram most frequently for following brands rated it highest for showing affection, following fashion, and demonstrating sociability. Advertisers should thus match their brands/products to appropriate SNS platforms based on gratifications derived from each site, so as to effectively reach their intended target audience. Second, those who used Twitter most frequently for following brands had greatest brand community identification and membership intention, while those who used Instagram most frequently for following brands had greatest brand community engagement and commitment. As such, advertisers should upload different content (e.g. pictures, videos, GIFs etc.) at different frequencies to their brand pages on each platform, so as to maximize consumers’ brand-related outcomes. Third, our results also suggest that advertisers should seek to win their brand followers’ trust and also strengthen their ties to the brand community (e.g. through contests, encouraging UGC, and providing incentives, etc.), in order to improve brand outcomes (Jin, 2013). Applying UGT (Katz et al., 1973), this study examined SNS users’ goal-directed consumption behaviors through their use of one of four popular SNS platforms (Facebook, Twitter, Instagram, or Snapchat) for following brands, gratifications gained from each SNS, impact on brand community-related outcomes, and moderators (attention to social comparison, SNS trust, tie strength, and network homophily) influencing this process. Overall, this study contributes to the current research literature on consumers’ brand-related activities on SNSs, 27 offering insights into the utility of different SNSs for brand-related marketing outcomes, through their attendant influences on consumers’ perceptions of brands they follow, from a marketing communication perspective. 28 References Algesheimer, R., Dholakia, U. M., & Herrmann, A. (2005). The social influence of brand community: Evidence from European car clubs. Journal of Marketing, 69, 19-34. doi: http://dx.doi.org/10.1509/jmkg.69.3.19.66363 Bearden, W. O., & Rose, R. L. (1990). Attention to social comparison information: An individual difference factor affecting consumer conformity. Journal of Consumer Research, 16, 461-471. boyd, D. M., & Ellison, N. B. (2007). Social network sites: Definition, history, and scholarship. Journal of Computer-Mediated Communication, 13, 210-230. doi:10.1111/j.10836101.2007.00393.x Brown, J. J., & Reingen, P. (1987). Social ties and word-of-mouth referral behavior. Journal of Consumer Research, 14, 350-362. Carlson, B. D., Suter, T. A., & Brown, T. J. (2008). Social versus psychological brand community: The role of psychological sense of brand community. Journal of Business Research, 61, 284-291. doi:10.1016/j.jbusres.2007.06.022 Chan, K., & Prendergast, G. P. (2008). Social comparison, imitation of celebrity models and materialism among Chinese youth. International Journal of Advertising, 27(5), 799-826. doi:10.2501/S026504870808030X Chatterjee, P. (2011). Drivers of new product recommending and referral behavior on social network sites. International Journal of Advertising, 30, 77-101. doi:10.2501/IJA-30-1077-101 Chi, H. H. (2011). Interactive digital advertising vs. virtual brand community: Exploratory study of user motivation and social media marketing responses in Taiwan. Journal of Interactive Advertising, 12, 44-61. doi:10.1080/15252019.2011.10722190 Christodoulides, G., Jevons, C., & Bonhomme, J. (2012). Memo to marketers: Quantitative evidence for change: How user-generated content really affects brands. Journal of Advertising Research, 52. doi:10.2501/JAR-52-1-053-064 Chu, S. C., & Kim, Y. (2011). Determinants of consumer engagement in electronic word-ofmouth (eWOM) in social networking sites. International journal of Advertising, 30, 4775. doi:10.2501/IJA-30-1-047-075 Colliander, J., & Dahlén, M. (2011). Following the fashionable friend: The power of social media-weighing publicity effectiveness of blogs versus online magazines. Journal of advertising research, 51, 313-320. doi:10.2501/JAR-51-1-313-320 29 Dimmick, J., Chen, Y., & Li, Z. (2004). Competition between the Internet and traditional news media: The gratification-opportunities niche dimension. The Journal of Media Economics, 17, 19-33. doi:10.1207/s15327736me1701_2 Ellison, N. B., Steinfield, C. and Lampe, C. (2007), The benefits of Facebook “friends:” Social capital and college students’ use of online social network sites. Journal of ComputerMediated Communication, 12, 1143–1168. Granovetter, M. S. (1973). The strength of weak ties. American journal of sociology, 78(6), 1360-1380. Gülnar, B., Balcı, ., & Çakır, V. (2010). Motivations of Facebook, You Tube and similar web sites users. Bilig, 54, 161-184. Goh, K.Y., Heng, C.S., & Lin, Z. (2013). Social media brand community and consumer behavior: Quantifying the relative impact of user- and marketer-generated content. Information Systems Research, 24(1), 88–107. Hayes, A. F. (2013). Introduction to mediation, moderation, and conditional process analysis: A regression-based approach. New York, NY: Guilford Press. Hollebeek, L. D., Glynn, M. S., & Brodie, R. J. (2014). Consumer brand engagement in social media: Conceptualization, scale development and validation. Journal of Interactive Marketing, 28, 149-165. doi:10.1016/j.intmar.2013.12.002 Hung, K., Li, S. Y., & Tse, D. K. (2011). Interpersonal trust and platform credibility in a Chinese multibrand online community. Journal of Advertising, 40, 99-112. doi:10.2753/JOA0091-3367400308 Jin, S. A. (2013). The potential of social media for luxury brand management: A structural equation modeling approach. Marketing Intelligence & Planning, 30, 687-699. Jin, S. A. A., & Phua, J. (2014). Following celebrities’ tweets about brands: The impact of twitter-based electronic word-of-mouth on consumers’ source credibility perception, buying intention, and social identification with celebrities. Journal of Advertising, 43, 181-195. doi:10.1080/00913367.2013.827606 Katz, E., Blumer, J. G., & Gurevitch, M. (1974). Utilization of mass communication by the individual. In J. G. Blumler, & E. Katz (Eds.), The uses of mass communications: Current perspectives on gratifications research (pp. 19-34). London, England: SAGE. Kilambi, A., Laroche, M., & Richard, M. O. (2013). Constitutive marketing: Towards understanding brand community formation. International Journal of Advertising, 32, 4564. doi:10.2501/IJA-32-1-045-064 30 Kim, E., Sung, Y., & Kang, H. (2014). Brand followers’ retweeting behavior on Twitter: How brand relationships influence brand electronic word-of-mouth. Computers in Human Behavior, 37, 18-25. doi:10.1016/j.chb.2014.04.020 Ko, H., Cho, C. H., & Roberts, M. S. (2005). Internet uses and gratifications: A structural equation model of interactive advertising. Journal of advertising, 34, 57-70. doi: 10.1080/00913367.2005.10639191 Krishnamurthy, S., & Dou, W. (2008). Note from special issue editors: Advertising with usergenerated content: A framework and research agenda. Journal of Interactive Advertising, 8, 1-4. doi:10.1080/15252019.2008.10722137 Kwon, E. S., Kim, E., Sung, Y., & Yoo, C. Y. (2014). Brand followers: Consumer motivation and attitude towards brand communications on Twitter. International Journal of Advertising, 33, 657-680. doi:10.2501/IJA-33-4-657-680 Laroche, M., Habibi, M. R., Richard, M. O., & Sankaranarayanan, R. (2012). The effects of social media based brand communities on brand community markers, value creation practices, brand trust and brand loyalty. Computers in Human Behavior, 28, 1755-1767. doi:10.1016/j.chb.2012.04.016 LaRose, R., & Eastin, M. S. (2004). A social cognitive theory of Internet uses and gratifications: Toward a new model of media attendance. Journal of Broadcasting & Electronic Media, 48, 358-377. doi:10.1207/s15506878jobem4803_2 Lee, M., & Youn, S. (2009). Electronic word of mouth (eWOM) How eWOM platforms influence consumer product judegment. International Journal of Advertising, 28, 473499. doi:10.2501/S0265048709200709 Lenhart, A., Duggan, M., Perrin, A., Stepler, R., Rainie, L., & Parker, K. (2015). Teens, social media, and technology 2015. Retrieved from http://www.pewinternet.org/files/2015/04/PI_TeensandTech_Update2015_0409151.pdf Lennox, R., & Wolfe, R. (1984). Revision of the self-monitoring scale. Journal of Personality and Social Psychology, 46, 1349-1364. doi: http://dx.doi.org/10.1037/00223514.46.6.1349 Lipsman, A., Mudd, G., Rich, M., & Bruich, S. (2012). The power of “like”: How brands reach (and influence) fans through social-media marketing. Journal of Advertising Research, 52, 40-52. doi:10.2501/JAR-52-1-040-052 Liu-Thompkins, Y. (2012). Seeding viral content: The role of message and network factors. Journal of Advertising Research, 52, 465-478. doi:10.2501/JAR-52-4-465-478 31 Mandel, N., Petrova, P. K., & Cialdini, R. B. (2006). Images of success and the preference for luxury brands. Journal of Consumer Psychology, 16, 57-69. doi:10.1207/s15327663jcp1601_8 McPherson, M., Smith-Lovin, L., & Cook, J. M. (2001). Birds of a feather: Homophily in social networks. Annual Review of Sociology, 27, 415-444. Mittal, V., Huppertz, J. W., & Khare, A. (2008). Customer complaining: the role of tie strength and information control. Journal of Retailing, 84, 195-204. doi:10.1016/j.jretai.2008.01.006 Moorman, C., Deshpande, R., & Zaltman, G. (1993). Factors affecting trust in market research relationships. Journal of Marketing, 81-101. doi:10.2307/1252059 Muniz, Jr, A. M., & O’guinn, T. C. (2001). Brand community. Journal of Consumer Research, 27, 412-432. doi:10.1086/319618 Muniz, Jr, A. M., & Schau, H. J. (2007). Vigilante marketing and consumer-created communications. Journal of Advertising, 36, 35-50. doi:10.2753/JOA0091-3367360303 Muntinga, D. G., Moorman, M., & Smit, E. G. (2011). Introducing COBRAs: Exploring motivations for brand-related social media use. International Journal of Advertising, 30, 13-46. doi:10.2501/IJA-30-1-013-046 Papacharissi, Z., & Mendelson, A. (2010). Toward a new(er) sociability: Uses, gratifications and social capital on Facebook. In S. Papathanassopoulos (Ed.), Media perspectives for the 21st century (pp. 212–230). New York, NY: Routledge. Park, N., Kee, K. F., & Valenzuela, S. (2009). Being immersed in social networking environment: Facebook groups, uses and gratifications, and social outcomes. CyberPsychology & Behavior, 12, 729-733. doi:10.1089/cpb.2009.0003 Phua, J., & Ahn, S. J. (2014). Explicating the ‘like’ on Facebook brand pages: The effect of intensity of Facebook use, number of overall ‘likes’, and number of friends’ ‘likes’ on consumers’ brand outcomes. Journal of Marketing Communications, (ahead-of-print), 116. doi:10.1080/13527266.2014.941000 Phua, J., & Jin, S. A. A. (2011). ‘Finding a home away from home’: The use of social networking sites by Asia-Pacific students in the United States for bridging and bonding social capital. Asian Journal of Communication, 21, 504-519. doi:10.1080/01292986.2011.587015 Qualman, E. (2013). Socialnomics: How social media transforms the way we live and do business. Hoboken, NJ: Wiley. 32 Quan-Haase, A., & Young, A. L. (2010). Uses and gratifications of social media: A comparison of Facebook and instant messaging. Bulletin of Science, Technology & Society, 30, 350361. doi:10.1177/0270467610380009 Reed II, A. (2004). Activating the self-importance of consumer selves: Exploring identity salience effects on judgment. Journal of Consumer Research, 31, 286-295. Rosen, L. D., Carrier, L. M., & Cheever, N. A. (2013). Facebook and texting made me do it: Media-induced task-switching while studying. Computers in Human Behavior, 29, 948958. doi:10.1016/j.chb.2012.12.001 Rubin, A. M. (1986). Uses, gratifications, and media effects research. In J. Bryant, & D. Zillmann (Eds.), Perspectives on media effects (pp. 281–301). Hillsdale, NJ: Lawrence Erlbaum. Rubin, A. M. (2002). The uses and gratifications perspective of media effects. In J. Bryant, & D. Zillmann (Eds.), Media Effects: Advances in Theory and Research (pp. 525–548). Hillsdale, NJ: Lawrence Erlbaum. Scarpi, D. (2010). Does size matter? An examination of small and large web-based brand communities. Journal of Interactive Marketing, 24, 14-21. doi:10.1016/j.intmar.2009.10.002 Shan, Y., & King, K. W. (2015). The effects of interpersonal tie strength and subjective norms on consumers' brand-related eWOM referral intentions. Journal of Interactive Advertising, 15, 16-27. doi:10.1080/15252019.2015.1016636 Statista. (2015). Leading social networks worldwide as of August 2015. Retrieved from http://www.statista.com/statistics/272014/global-social-networks-ranked-by-number-ofusers/ Stelzner, M. A. (2015). 2015 Social Media Marketing Industry Report. Retrieved from http://www.socialmediaexaminer.com/SocialMediaMarketingIndustryReport2015.pdf Sung, Y., Kim, Y., Kwon, O., & Moon, J. (2010). An explorative study of Korean consumer participation in virtual brand communities in social network sites. Journal of Global Marketing, 23, 430-445. doi:10.1080/08911762.2010.521115 Taylor, D. G., Strutton, D., & Thompson, K. (2012). Self-enhancement as a motivation for sharing online advertising. Journal of Interactive Advertising, 12, 13-28. doi:10.1080/15252019.2012.10722193 Tsai, W. H. S., & Men, L. R. (2013). Motivations and antecedents of consumer engagement with brand pages on social networking sites. Journal of Interactive Advertising, 13, 76-87. doi:10.1080/15252019.2013.826549 33 Vanden Bergh, B. G., Lee, M., Quilliam, E. T., & Hove, T. (2011). The multidimensional nature and brand impact of user-generated ad parodies in social media. International Journal of Advertising, 30, 103-131. doi:10.2501/IJA-30-1-103-131 Xie, K. & Lee,Y. J. (2015). Social media and brand purchase: Quantifying the effects of exposures to earned and owned social media activities in a two-stage decision making model. Journal of Management Information Systems, 32(2), 204–238. 34 Figure 1. Differences in Main Features and Func ons Among Key SNS Pla orms Examined in the Study SNS Pla orm Main Features / Func ons Post long-form content (e.g. video, news ar cle, pictures); browse newsfeed of friends’ updates; “like”, comment and share content Post short messages (140 characters or less) containing links to ar cles, photos and videos; microblogging; use of # (hashtags) searchable by topic Post filtered photographs and short videos, add cap ons, use of # (hashtags) searchable by topics; like and comment on photos and short videos posted Post content (photos, videos) to selected individuals; Snaps are deleted a er a specified period of me; add filters and lenses to posted content; “Discover” channels with branded content 35 36 37 Figure 4. Gra fica ons Derived from Most Frequently Used SNS for Following Brands (N=297) (H1) GRATIFICATION SNS PLATFORM WITH HIGHEST SCORES Mean (SD) Passing Time 5.46 (.92) Showing Affec on 4.13 (1.09) Following Fashion 4.43 (1.42) Sharing Problems 4.20 (1,66) Demonstra ng Sociability 4.72 (1.53) Improving Social Knowledge 5.96 (1.20) 38 Figure 5. Study Participants’ (N = 297) Gratifications of using Facebook, Twitter, Instagram and Snapchat 39 Figure 6. Brand Community-Related Outcomes Derived from Most Frequently Used SNS for Following Brands (N=297) (H2) BRAND COMMUNITY-RELATED OUTCOMES SNS PLATFORM WiTH HIGHEST SCORES Brand Community Iden fica on Brand Community Engagement Mean (SD) 5.15 (1.13) ; 5.21 (1.22) Brand Community Commitment 5.61 (1.16) Brand Community Membership Inten on 5.62 (.85) 40 Figure 7. Study Participants’ (N = 297) Brand Community Outcomes from using Facebook, Twitter, Instagram and Snapchat 41 Figure 8. Plots of Significant Moderators of SNS Use and Brand Community Outcomes (N = 297) Top left: Interaction between SNS Use and Social Comparison on Brand Community Identification; top right: Interaction between SNS Use and SNS Trust on Brand Community Identification; middle left: Interaction between SNS Use and SNS Trust on Brand Community Membership Intention; middle right: Interaction between SNS Use and SNS Tie Strength on Brand Community Identification; bottom left: Interaction between SNS Use and SNS Tie Strength on Brand Community Membership Intention; bottom right: Interaction between SNS Use and SNS Homophily on Brand Community Commitment. 42 Highlights 1. 2. 3. 4. 5. Snapchat is used for passing time, sharing problems, and social knowledge. Instagram is used for showing affection, following fashion, and sociability. Twitter users had highest brand community identification and membership intention. Instagram users had highest brand community engagement and commitment. Social comparison, trust, tie strength, and network homophily are moderators. 43