antecedents and consequences of customer engagement in online brand communities

Original Article

Antecedents and consequences ofcustomer engagement in onlinebrand communitiesReceived (in revised form): 19th May 2014

Tommy K.H. Chanis a PhD student in the Department of Finance and Decision Sciences at Hong Kong Baptist University. His research interests includehedonic information systems and social media. His research articles have been published in leading information systems conferenceproceedings.

Xiabing Zhengis currently a PhD candidate at the School of Management, University of Science and Technology of China. She is also a PhDcandidate in the joint program between City University of Hong Kong and University of Science and Technology of China (USTC-CityU Joint Advanced Research Center). Her research interests include information systems, supply chain management andelectronic commerce.

Christy M.K. Cheungis Associate Professor of Information Systems and e-Business Management in the Department of Finance and Decision Sciences atHong Kong Baptist University. She received her PhD from City University of Hong Kong. Her research interests include social media,e-marketing, IT adoption and usage, and the dark side of using IS/IT. Her research articles have been published in MIS Quarterly,Decision Support Systems, Information &Management, the Journal of the American Society for Information Science and Technology,and the Journal of Information Technology.

Matthew K.O. Leeis Chair Professor of Information Systems and E-Commerce at the College of Business, City University of Hong Kong. Professor Leehas research and professional interest in IT-based innovation adoption and diffusion (focusing on systems implementationmanagement issues), knowledge management, social computing, electronic commerce, and legal informatics. Professor Lee’swork has appeared in leading journals such as the Journal of MIS, Communications of the ACM, the Journal of International BusinessStudies and MIS Quarterly. Professor Lee also serves on the editorial board of several research journals in the IS field.

Zach W.Y. Leeis a PhD candidate in the Department of Finance and Decision Sciences at Hong Kong Baptist University. His research interestsinclude the dark side of IS/IT use, hedonic IS and social media. His research articles have been published in the Journal of theAmerican Society for Information Science and Technology and the International Journal of Business and Information, and leadinginformation systems conference proceedings. Zach was PhD Fellow of the 2013 PACIS Doctoral Consortium.

Correspondence: Tommy K.H. Chan, Department of Finance and Decision Sciences, School of Business, Hong Kong BaptistUniversity, 34 Renfrew Road, Kowloon Tong, Kowloon, Hong Kong, China.E-mail: [email protected]

ABSTRACT Today, organizations require additional efforts to develop new streams ofrevenue as competition is intense and new customers are hard to secure at a mature stage.The advent of social networking sites serves as an alternative tactic for organizations to formonline brand communities, engage customers and hence foster brand loyalty. This articlepresents a research model of antecedents and consequences of customer engagement inonline brand communities on social networking sites. Specifically, we examined how systemsupport, community value, freedom of expression, and rewards and recognition encouragecustomer engagement, as well as how customer engagement influences repurchaseintention and word-of-mouth intention. We tested the research model with a sample of 276

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online brand community members. Empirical data supported our hypotheses, and revealedthat customer engagement mediates relationships between community characteristics andbrand loyalty. The current study validated the propositions from prior conceptual frame-works, and shed light for practitioners and scholars.Journal of Marketing Analytics (2014) 2, 81–97. doi:10.1057/jma.2014.9

Keywords: customer engagement; social networking sites; online brandcommunities; community characteristics; social media

INTRODUCTIONToday, most industries are already maturedand saturated. Seeking novel strategies tosurvive is imperative to business, ascompetition is intense and new customers arehard to secure. A wide range of promotionprograms, such as price discounts, coupons andmemberships schemes, have been introducedand implemented to stimulate spending andretain potential customers. All these marketingefforts are moving toward the enhancement ofcustomer loyalty, as customer loyalty has longbeen suggested as the salient prerequisite offavorable customer behaviors (for example,repurchasing, positive word-of-mouth,cross-selling) (Verhoef et al, 2002; Huret al, 2010; Stokburger-Sauer, 2010). Yet,the aforementioned loyalty programs areessential but not a sufficient condition tosimultaneously increase multifaceted customerloyalty (Gustafsson et al, 2005). Developingand sustaining customer loyalty in a holisticsense demands a series of customizedmarketing strategies adapted to different loyaltytypes (Hur et al, 2011).

Recently, the explosive innovation anddiffusion of broadband services and socialnetworking sites has cultivated fertile groundfor new forms of marketing strategies toflourish (Han and Windsor, 2011; Yang,2012). Online brand communities on socialnetworking sites are emerging as a keymodality, facilitating interaction with andamong consumers. Organizations have begunto realize the beauty of online brandcommunities on social networking sites as atool for consumer-brand relationship building

and loyalty nourishment (Bagozzi andDholakia, 2002; Dholakia et al, 2004).Contributing to the ability to transcendgeographic boundaries and facilitespontaneous interactions, online brandcommunities on social networking sites havecaptured the attention of organizations(McWilliam, 2000). Solely in the context ofFacebook, there were already 15 millionpages established by businesses, companiesand organizations in 2013 (Koetsier, 2013),where customers are encouraged to exchangetheir experience and share their enthusiasmwithin the community. Survey data alsorevealed that engagement was one of theleading goals of social media marketing, citedby 67 per cent of respondents, a significantincrease of 17 per cent compared with 2012.Similarly, customer engagement was also theprimary metric when it came to evaluatingthe performance of social media marketing(Pivotcon, 2013). Instead of gaining a warmreception from social users for the officialposts, organizations have recognized theimportance of engaging customers, forexample keeping them constantly posting,‘liking’ and sharing social content in theonline brand community. By stimulatingcustomer engagement activities on thesesocial networking sites, companies canleverage from enhancing brand loyalty(Brodie et al, 2013), increasing sales(Doohwang et al, 2011) and generatingpositive word-of-mouth communication(Libai et al, 2010), and can retain competitivenessin today’s cluttered and often hostile marketingenvironment (Algesheimer et al, 2005).

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Apart from the rising concerns fromorganizations, investigation of this emergingphenomenon is also gaining momentum inacademia, initiated by the fact that this kind ofengagement promotes firms’ competitivenessby building and strengthening long-termrelationships with customers (Stokburger-Sauer, 2010). In IS academia, the urge toexplore the concept of customer engagementin the context of online brand communitieshas become more pressing (Nambisan andBaron, 2007). Kim et al (2011) investigatedthe motivations of using social networkingsites. Chu and Kim (2011) explored thefactors determining engagement in electronicword-of-mouth on social networks. Wu andSukoco (2010) studied the moderating effectof trust in knowledge sharing in online brandcommunities. Past literature has studied socialnetworking sites, brand community andcustomer engagement separately; however,the conjunction of the above phenomenawarrants additional analyses, as well asconceptualization and theories (Zaglia, 2013).

Although IS researchers have begun tostudy the issue from different perspectives, aninvestigation from the view of IT artifacts, thecore of IS discipline, is generally missed in theagenda. Benbasat and Zmud (2003)commented that IT artifacts, as the core ofIT-based systems, have been under-investigated within the discipline. Researchfocusing on customer engagement on socialnetworking sites is still in its infancy, withvery few theoretical grounds established toguide the empirical investigation(Jahn and Kunz, 2012). In addition, there is alack of understanding of how communitycharacteristics contribute to customerengagement as well as brand loyalty. A deeperinvestigation is warranted.

Thus, the main objective of this study is toexplore customer engagement in onlinebrand communities on social networkingsites. In particular, we focus on howcommunity characteristics influence customerengagement in online brand communities andhow customer engagement in turn impacts

customer behavior. We aim to answer thefollowing research questions:

1. What are the factors driving customerengagement in online brand communities onsocial networking sites? Particularly, whichcommunity characteristics affect customerengagement and how?

2. How does customer engagement in online brandcommunities on social networking sites affectbrand loyalty?

This study expects to advance the existingliterature on customer engagement in onlinebrand communities, and to shed light forfurther research on customer engagement inthe context of social networking sites. Inaddition, we aim to inform practitioners onhow community characteristics affectcustomer engagement in the online brandcommunity, and hence revitalize non-performing communities.

The paper is organized as follows. In thefollowing section, we provide a review of priorliterature. We then address a research modeland develop the hypotheses. Subsequently,we describe a survey study of users of onlinebrand communities on Facebook toempirically test our research model. Finally, wepresent the results of our empirical study andconclude the paper by discussing boththeoretical and practical implications.

LITERATURE REVIEW

The concept of engagementThe concept of ‘engagement’ has been widelyexplored by scholars from differentdisciplines, including management, marketingand information system management. Forexample, marketing scholars view customerengagement as ‘the level of a customer’sphysical, cognitive and emotional presence intheir relationship with a service organization’(Patterson et al, 2006). In the IS field, userengagement is defined as ‘a subset of flow anda more passive state representing the extent ofpleasure and involvement in an activity’

Customer engagement in brand communities

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(Webster and Ahuja, 2006). Table 1summarizes past studies on the concept ofengagement. Yet research on engagement hasbeen historically plagued by its inconsistencyin the definitions and operationalizations.Although there have been several calls formore research on engagement in recent years(Scott and Walczak, 2009; O’Brien, 2010;Rich et al, 2010; van Doorn et al, 2010;Cheung et al, 2011; Christian et al, 2011),academia still lacks a coherent and mutualunderstanding of the concept.

Customer engagementConsumer engagement, as a sub conceptunder the umbrella term ‘engagement’, hasbeen broadly investigated in the marketingliterature. Suffering from the lack of mutualagreement on the definition of engagement,the interpretation of customer engagement isstill mired in vagueness and controversy. Tofacilitate future discussion and knowledgeaccumulation, the Marketing ScienceInstitute has emphasized the need for furtherexploration of this important and emergingconcept in its 2010–2012 research priorities.

In response to this call, Bowden (2009)conceptualized customer engagement as a‘psychological process’ comprising cognitiveand emotional aspects. Similarly, Hollebeek(2011) defined customer brand engagement as‘the level of a customer’s motivational, brand-related and context dependent state of mindcharacterized by specific levels of cognitive,emotional and behavioral activity in brandinteractions’. In contrast, Vivek et al (2012)focused on the behavioral aspects of customerengagement and defined the concept as ‘theintensity of an individual’s participation andconnection with the organization’s offeringsand activities initiated by either the customeror the organization’. Consistent with thisperspective on customer engagementemphasizing the notion of interactivity andcustomer experience, Mollen and Wilson(2010) explored online brand engagementconsidering the dimensions of sustained

cognitive processing, perceived instrumentalvalue and experiential value.

In summary, customer engagement is seenas a retention and acquisition strategy forestablishing and maintaining competitiveadvantages, as well as predicting futurebusiness (Sedley, 2008). There are three mainperspectives from which researchers havedefined and studied the concept of ‘customerengagement’ in prior literature: psychologicalprocess, behavioral manifestation andmotivational psychological state (Cheunget al, 2011).

� Bowden (2009) conceptualized apsychological process to define customerengagement that leads to consumer loyaltyto the service brand.

� van Doorn et al (2010) defined customerengagement as ‘the behavioralmanifestation from a customer toward abrand or a firm which goes beyondpurchase behavior’ (p. 254).

� Patterson et al (2006) defined customerengagement as a psychological state that ischaracterized by a degree of vigor,dedication, absorption and interaction.

Online brand communityAn online brand community is defined as acommunity formed in cyberspace on the basisof attachment to commercial brands (Sunget al, 2010). For an organization, the functionof an online brand community is threefold.First, it serves as an additional channel for theorganization to communicate and receivefeedback from customers on products andservices. Second, it establishes a link betweencurrent and potential customers, and developsand maintains long-term relationships withcustomers who are attached to the brand.Finally, it facilitates the development ofcustomers’ brand loyalty and commitment(Sung et al, 2010).

Despite organizations having recognizedthe benefits of online brand communities asan effective and successful tool to achieve

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their strategic goals, the proliferation ofonline brand communities and their impactshas not gone unnoticed by scholars (Adjeiet al, 2010; Lee et al, 2011; Royo-Vela andCasamassima, 2011; Wang et al, 2011b).Scholars have attempted to study onlinebrand communities from differentperspectives. Zhou et al (2012) investigatedthe intermediate mechanism of brandcommunities with brand relationships,revealing that consumer brand attachmentfully mediates the relationship betweenbrand community commitment and brandcommitment, and partially mediates therelationship between brand identificationand brand commitment from a sample ofonline communities in China. Wirtz et al(2013) synthesized prior studies and provideda conceptual framework of online brandcommunity engagement from bothconsumer and organization perspectives.Three antecedents, namely, brand-related,social and functional drives, are proposed.Customer outcomes, organizationaloutcomes, brand outcomes and brand equityare identified as the consequences of onlinebrand community engagement. Althoughthere is no coherent conclusion on theantecedents and outcomes of onlinebrand community, it is evident that thebenefits for organizations are far-reaching(Sedley, 2008).

Customer engagement on socialnetworking sitesThe increasing popularity of online socialplatforms, such as Facebook, MySpace,Netlog and LinkedIn, has furtherencouraged the development of onlinecommunities within these sites, and ledresearchers to explore the role of customerengagement on social networking sites.Hennig-Thurau et al (2010) proposed atheoretical framework of social media’simpact on relationships with customers.Sung et al (2010) conducted an exploratorystudy on a sample of virtual brand

community members on a Korean-basedsocial networking site and identified sixpredominant social and psychologicalmotives, namely, interpersonal utility, brandloyalty, entertainment seeking, informationseeking, incentive seeking and convenienceseeking. Laroche et al (2012) revealed thatbrand communities on social media promoteshared consciousness, obligation to society,shared rituals and traditions, trust, andcustomer loyalty. Brodie et al (2013)adopted a netnographic methodology toexplore the nature and scope of consumerengagement in an online brand communityenvironment, suggesting that engagedconsumers exhibit enhanced consumerloyalty, satisfaction, empowerment,connection, emotional bonding, trust andcommitment.

RESEARCH MODEL ANDHYPOTHESES DEVELOPMENTIn this study, customer engagement isdefined as the level of a person’s cognitive,emotional and behavioral presence in brandinteractions with an online community(Patterson et al, 2006). Engagement is morethan an attitude. It reflects the degree towhich an individual or a member is attentiveto and absorbed in the performance of theirroles in a community. Figure 1 depicts theresearch model of customer engagement inonline brand communities on socialnetworking sites.

The research model has its theoreticalfoundation in reciprocal action theory andsocial identity theory (Dutton and Dukerich,1991; Lee et al, 2011). The interactionsbetween organizations and customers within abrand community on a social networking siteare viewed as an exchange. If communitymembers perceive that their community isproviding useful information and a valuableservice, and seeking to build a strongrelationship with them, they will reciprocateby showing positive attitudes and behaviors



Table 1: Summary of selected research on the concept of engagement

Study and definitions Antecedents Consequences

Employee engagement (job and organization engagement)Saks (2006)Consists of cognitive, emotional and behavioral components thatare associated with individual role performance

Job characteristics;Rewards and recognition;Perceived organizational andsupervisor support;Distributive and proceduraljustice

Job satisfaction;Organizational commitment;Organizational citizenship behavior;Intention to quit

Work engagementChristian et al (2011)A relatively enduring state of mind referring to the simultaneousinvestment of personal energies in the experience or performanceof work

Job characteristics;Leadership;Dispositional characteristic

Task performance;Contextual performance

Job engagementMaslach et al (2001)Characterized by energy, involvement and efficacy, the directopposite of the three burnout dimensions of exhaustion, cynicismand inefficacy

Workload;Control;Rewards and recognition;Community and social support;Perceived fairness;Value

Intention to withdrawal;Performance;Job satisfaction;Commitment;

User engagementWebster and Ahuja (2006)A subset of flow and a more passive state representing the extentof pleasure and involvement in an activity

Perceived disorientation User performance;Future intention to use

O’Brien and Toms (2010), O’Brien and Toms (2008)A quality of user experience that comprises: focused attention,perceived usability, endurability, novelty, aesthetics and feltinvolvement

Hedonic motivations;Utilitarian motivations

—

Customer engagementO’Brien and Toms (2010), O’Brien and Toms (2008)A psychological process that leads to the formation of loyalty

— —

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van Doorn et al (2010)The behavioral manifestation from a customer toward a brand or afirm which goes beyond purchase behavior (p. 2).

— —

Patterson et al (2006)A psychological state that is characterized by a degree of vigor,dedication, absorption and interaction, drew on a variety of parentdisciplines including social psychology and organizationalbehavior

— Customer loyalty

Brand engagementMollen and Wilson (2010)The cognitive and affective commitment to an active relationshipwith the brand as personified by the website or other computer-mediated entities designed to communicate brand value

Telepresence Optimal consumer attitudes and behaviors

Brand engagement in self-concept (BESC)Sprott et al (2009)An individual difference representing consumers’ propensity toinclude important brands as part of how they view themselves.This conceptualization builds on self-schemas to investigate therole of brands in the self-concept

— —

Brand community engagementAlgesheimer et al (2005)Positive influences of identifying with the brand communitythrough the consumer’s intrinsic motivation to interact/cooperatewith community members

Brand community identification Membership continuance intentions;Community recommendation intentions;Community participation intentions

Customer brand engagementHollebeek (2011)The level of an individual customer’s motivational, brand-relatedand context-dependent state of mind characterized by specificlevels of cognitive, emotional and behavioral activity in directbrand interactions (p. 7)

Involvement Trust;CommitmentCustomer satisfaction

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toward the community. Eventually, customersdevelop a strong emotional obligation and thusare more willing to be engaged (cognitively,emotionally and physically) in the brandcommunity to reciprocate the firm’s activerelationship-building efforts and friendliness(De Wulf et al, 2001; Bakker et al, 2008).In the current study, we expect that thefour key community characteristics (that is,system support, community value, freedomof expression, rewards and recognition)will promote customer engagement inonline brand communities ( Jang et al,2008; Kim et al, 2008).

As suggested in social identity theory(Dutton and Dukerich, 1991), committedand involved members will devotethemselves to the actions that support theorganization (Kim et al, 2008). The socialidentity of a member is derived from theknowledge of his membership within acommunity as ‘belonging to it’ andembraced into his self-concept, in terms ofcognitive, affective and evaluativecomponents (Dholakia et al, 2004;Doohwang et al, 2011). In this study, it isexpected that the formation of customerengagement will in turn influence customerloyalty toward the brand.

Antecedents of customerengagement in online brandcommunities

System support and customerengagement

System support refers to the quality of means,capability and opportunity that facilitate thecommunication and interaction betweenmembers in an online brand community( Jang et al, 2008; Kim et al, 2008). Theinfrastructure of online brand communitiesextends the direction of communicationsbetween customers (Kim et al, 2008).Specifically, members can easily share news orinformation about their favorite brands andinteract with others any time and anywherethrough online brand communities onsocial networking sites. When membersperceive that the communities areproviding useful information and a valuableservice, they will reciprocate by showingpositive attitudes (De Wulf et al, 2001; Bakkeret al, 2008).

In addition, Barnes and Vidgen (2012)found that intranet quality (composed ofusability, design and information quality)plays a key role in determining the adoption

Figure 1: Research model.

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and use of a system in an organization.Khayun et al (2012) reported that systemquality is positively related to the useintention of a website. Similarly, whenfeatures in online brand communities are ableto provide effective mechanisms forsupporting members’ communication andinteraction, they will ultimately encouragecustomer engagement within the sites. Thus,we hypothesize:

Hypothesis 1: Perceived system supportis positively related to customerengagement in online brandcommunities on social networkingsites.

Community value and customerengagementCommunity value refers to the extent towhich a member believes that the benefitshe seeks are consistent with what an onlinecommunity provides (Kim et al, 2008).Muniz and O’Guinn (2001) suggested thatbrand communities are formed anddeveloped based on common interestamong members, as well as their sharedfeeling of belonging, responsibility andobligation to the community. Koyuncu et al(2006) found that a high value fit would leadto a high level of engagement, while Wanget al (2011a) also showed that the alignmentof individual needs and organizationalinterests is one of the drivers of usingworkplace e-learning application. Similarly,the match between the potential members’needs and the online brand communityofferings will generate strong feelingsamong customers and thus encourage themto engage in the community. Thus, wehypothesize:

Hypothesis 2: Perceived communityvalue is positively related to customerengagement in online brandcommunities on social networkingsites.

Freedom of expression and customerengagementFreedom of expression refers to the degree ofinformation exchange among communitymembers and between community membersand the host community. It also refers to theextent to which the community facilitatesmembers in expressing diverse opinions ( Janget al, 2008). One of the roles of an onlinebrand community is to provide a social spacefor customers to exchange information andshare their opinions and experience(McWilliam, 2000), where customers withsimilar interests can freely express theiropinions and exchange information withother members of the community.Autonomous interaction has long beensuggested as one of the prime reasons forcustomers to engage in a brand community(Rheingold, 1993). Maslach et al (2001)further showed that feelings of choice are animportant determinant of high engagement.Conversely, if too much control of thecontent and expression is perceived, the levelof participation and interaction among thecustomers in a community might bediminished. Therefore, if the community canprovide an environment where members canfreely express their opinions, members willhave a more favorable attitude toward thebrand community and thus increase the levelof engagement. Thus, we hypothesize:

Hypothesis 3: Perceived freedom of speechis positively related to customerengagement in online brandcommunities on social networking sites.

Rewards and recognition andcustomer engagementRewards and recognition refers to monetaryreward, psychological reward or recognitionfor active participation in a brand community( Jang et al, 2008; Kim et al, 2008). Priorstudies found that the level of engagementdepends on how members perceive thereward and recognition provided (Kahn,



1990). Reciprocally, when participantsperceive rewards and recognition from theonline brand community they participated in,they will feel obliged to devote themselveswith higher levels of engagement. Thus, wehypothesize:

Hypothesis 4: Perceived reward andrecognition is positively related tocustomer engagement in online brandcommunities on social networking sites.

Consequences of customerengagement in online brandcommunities

Customer engagement, repurchaseintention and word-of-mouthintentionBuilding upon social identity theory, engagedcustomers are expected to devote themselvesto the actions that support the organization(Kim et al, 2008). Prior studies haverepeatedly demonstrated that engagement isassociated with a number of positiveoutcomes, such as organizational citizenshipbehavior and organizational commitment(Saks, 2006; Macey and Schneider, 2008);customer loyalty (Patterson et al, 2006); andmembership continuance intentions,community recommendation intentions andcommunity participation intentions(Algesheimer et al, 2005). For example, Tsaiand Huang (2007) drew on marketing andconsumer behavior literature to formulate aconceptual framework, empirically tested thehypotheses using data obtained from a largeonline retailing store in Taiwan, and revealedthat community building is positively relatedto repurchase intention. Accordingly, webelieve that engagement in online brandcommunities will lead to positive behaviors ofmembers, such as word-of-mouth behaviors,repurchase behavior and active participationbehaviors (Hennig-Thurau et al, 2010; Hoyeret al, 2010; Mollen and Wilson, 2010). Inparticular, we expect that a highly engaged

community member will be more willing torepurchase products of the brand, andtospread positive word of mouth about thebrand. Thus, we hypothesize:

Hypothesis 5: Customer engagement inonline brand communities on socialnetworking sites is positively related torepurchase intention.

Hypothesis 6: Customer engagement inonline brand communities on socialnetworking sites is positively related toword-of-mouth intention.

RESEARCH METHODOLOGYWe tested the research model with a sampleof online brand communities’ members onFacebook. To date, Facebook has recorded atotal number of 15 million fan pages withactive participation (Koetsier, 2013). Forexample, Coca-Cola (Coke) has 71 millionsof fans on its fan page and the page is stillgaining fans (Socialbakers, 2013). Withrespect to the popularity of Facebook, webelieve that it is a representable andappropriate sample for the current study.

MeasuresThe constructs of interest in this studyincluded system support, community value,freedom of expression, rewards andrecognition, customer engagement in onlinebrand communities, repurchase intention andword-of-mouth intention. We usedestablished measures from prior literature withminor modifications to fit the context (Saks,2006; Kim et al, 2008). For example, systemsupport is measured by ‘Facebook Pageprovides an effective bulletin board whereparticipants communicate’; community valueis measured by ‘Facebook Page provides aclear purpose of the community’; freedom ofexpression is measured by ‘Facebook Pageproactively embraces negative discussions oropinions about the brand from members’;

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rewards and recognition is measured by‘Facebook Page provides proper rewards toactive members for their efforts’; customerengagement is measured by ‘Being a memberof this organization is very captivating’;repurchase intention is measured by ‘Howlikely is it that would you buy products fromthe brand again?; and word-of-mouthintention is measured by ‘I would like tointroduce the brand to others’. All constructsmentioned above were measured using multi-item perceptual scales on a 7-point Likertscale, anchored from strongly disagree (1) tostrongly agree (7).

Data collection and sampleWe randomly distributed a self-administeredquestionnaire to Facebook users at a localuniversity. The use of self-reported measuresis believed to be vital and qualified in thecurrent study, as all the constructs in theresearch model evaluate cognition, emotionand intention, rather than the actual behavior(Zhou et al, 2012). To encourageparticipation, participants were entitled toenter a lucky draw with supermarketvouchers as an incentive. A total of 276 usefulquestionnaires were collected in the study. Allthe respondents are members of an onlinebrand community in Facebook.

Common method biasAt the initial stage of survey design, weemployed multiple measurement scale types(Likert and open-ended numerical questions)and utilized negatively worded items tomitigate the risk of common method bias.However, as with all self-reported data, thepotential threat of common method variancemight still exist (Podsakoff et al, 2003). In thelight of this, we performed four additionalstatistical analyses to assess the potential risk inthe data. These are Harman’s single-factortest, correlation matrix check (recommendedby Pavlou et al, 2007), PLS approach testing(Podsakoff et al, 2003), and partial correlation

approach testing (Liang et al, 2007). Overall,the combination of results from the abovetests points to the conclusion that thecommon method bias is unlikely to be aserious concern for this study.

DATA ANALYSIS

Measurement modelWe used the Smart Partial Least Squares 2.0(PLS) approach to perform statistical analysisin the current study. The PLS structuremodeling test technique is capable of handlinga small sample and complex predictive modeltesting with no restriction of normaldistribution (Wold, 1989; Barclay et al, 1995;Chin, 1998), and is widely used in IS academia.Following the two-step analytical procedure,the factorial validity of the measurementinstruments was first evaluated, and then thestructural model was examined with anempirical sample of 276 Facebook users.

To achieve sufficient convergent validity,constructs with composite reliability (CR) of0.70 or above and an average varianceextracted (AVE) of higher than 0.50 arerequired (Fornell and Larcker, 1981). Inaddition, all item loadings should be greaterthan 0.70 (Chin, 1998). Table 2 summarizesthe item loading, composite reliability,average variance extracted, mean and standarddeviation of the measures of all the constructsin our research model. All measures in theresearch model fulfilled the recommendedlevels, with the composite reliability valuesranging from 0.85 to 0.97 and the averagevariance extracted values ranging from 0.68 to0.95. The item loadings were all higher thanthe 0.70 benchmark.

Discriminant validity can be demonstratedwhen the square root of average varianceextracted for each construct is greater than thecorrelations between the constructs and allother constructs (Hair et al, 1998). As shown inTable 3, the square root of the AVE of eachconstruct is located on the diagonal of the tableand is in bold. In this study, robust evidence of



discriminant validity was found with empiricaldata.

Structure modelWe assessed the model through the structureequation modeling (SEM) technique withPLS by the bootstrap re-sampling procedure.Figure 2 presents the results with explanatorypowers (R2), estimated path coefficients (allsignificant paths are indicated by asterisks) and

associated t-values of each path in the researchmodel for this study.

As shown in Figure 2, all path coefficientswere statistically supported as hypothesized.The analysis with PLS revealed that theexogenous variables explain 20 per cent of thevariance in online brand communityengagement, 22 per cent of the variance inrepurchase intention and 20 per cent variancein word-of-mouth intention. All antecedentvariables of customer engagement in online

Table 2: Psychometric properties of measures

Constructs Item Loading Mean STDEV

System support (SS)CR=0.90; AVE=0.68

SS1 0.74 4.95 1.22SS2 0.85 4.74 1.18SS3 0.85 4.81 1.22SS4 0.86 4.69 1.31

Community value (CV)CR=0. 92; AVE= 0.80

CV1 0.90 4.73 1.29CV2 0.90 4.71 1.22CV3 0.88 4.77 1.30

Freedom of expression (FE)CR=0.89; AVE=0.79

FE1 0.88 4.19 1.10FE2 0.90 4.14 1.08

Rewards and recognition (RR)CR=0.92; AVE=0.80

RR1 0.86 4.10 1.38RR2 0.91 4.28 1.29RR3 0.91 4.31 1.23

Customer engagement in online brand communities (CE)CR=0.95; AVE=0.75

CE1 0.83 3.85 1.32CE2 0.83 3.97 1.37CE3 0.88 4.04 1.35CE4 0.85 3.57 1.41CE5 0.91 3.65 1.30CE6 0.88 3.83 1.36

Repurchase intention (RI)CR=0.85; AVE=0.74

PI1 0.81 4.49 1.28PI3 0.91 4.05 1.25

Word of mouth (WOM)CR=0.97; AVE=0.95

WOM1 0.98 4.48 1.28WOM2 0.97 4.48 1.26

Note: CR=Composite Reliability; AVE=Average Variance Extracted.

Table 3: Correlation matrix and psychometric properties of key constructs

SS FE RR CV CE RI WOM

System support (SS) 0.83Freedom of expression (FE) 0.30 0.89Rewards and recognition (RR) 0.46 0.44 0.89Community value(CV) 0.50 0.26 0.41 0.89Customer engagement in online brand communities (CE) 0.29 0.34 0.36 0.30 0.86Repurchase intention (RI) 0.17 0.31 0.33 0.30 0.46 0.86Word of mouth (WOM) 0.14 0.19 0.13 0.29 0.44 0.60 0.97

Note: Diagonal elements are square roots of the average variance extracted.

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brand communities were found to bestatistically significant. Freedom of expressionand rewards and recognition exhibitedstronger impacts on customer engagement inonline brand communities, with pathcoefficients at 0.21 and 0.19, respectively.The impacts of system support andcommunity value on customer engagementin online brand communities were relativelyweaker, with path coefficients at 0.10 and0.13, respectively. Furthermore, the twoconsequences, repurchase intention andword-of-mouth intention, were statisticallysignificant, with path coefficients at 0.46 and0.44, respectively.

DISCUSSIONThis study is one of the first to thoroughlyexamine the role of community characteristicsin understanding customer engagement inonline brand communities on socialnetworking sites. Specifically, we introducedfour community characteristics (that is, systemsupport, community value, freedom ofexpression, and rewards and recognition) thatderived from prior literature as antecedents ofcustomer engagement and investigated how

they encourage customer engagement inonline brand communities, and eventuallylead to brand loyalty. A theoretical model wastested with a sample of 276 Facebook brandcommunity members, and the research modelexplained 20 per cent of variance in customerengagement in online brand communities onsocial networking sites. The antecedents andconsequences of customer engagement werefound to be statistically significant in thecurrent investigation (Verhoef et al, 2002;Hennig-Thurau et al, 2010; van Doorn et al,2010; Brodie et al, 2013).

Theoretical implicationsOur study is believed to shed light forthe research communities with severalissues. First, the current study validatedpropositions discussed in prior conceptualframeworks. Specifically, this study wentbeyond conceptualization and appliedreciprocity action theory and social identitytheory to explore the phenomenon,providing evidence for the associationbetween the antecedents and consequences ofcustomer engagement. Repurchase intention(22 per cent in variance) and world-of mouth

Figure 2: PLS results of research model.



intention (20 per cent in variance) are positiveoutcomes of customer engagement.

Second, an additional promising avenue ofresearch may consist of further exploring therole of community characteristics of onlinebrand communities. Past literature hasattempted to explore the concept of customerengagement from the perspective ofindividual intrinsic or extrinsic motivations;our study suggests that communitycharacteristics could play an important role inengaging customers and contribute to thesuccess of an online brand community onsocial networking sites. The differences insettings across social networking sitescould induce variations in predictingcustomer engagement in online brandcommunities.

In sum, the current study paves the wayand direction for addressing the emergingconcerns in customer engagement in ISacademia.

Managerial implicationsWhen traditional marketing strategies are notsufficient in the current competitiveenvironment, engaging customers in onlinebrand communities on social networking sitesis deemed to be a panacea for organizations tosurvive. Nevertheless, only setting up a brandfan page and stimulating visits are insufficientto enhance the customer-brand relationship(Turel and Serenko, 2012). The success of anonline brand community hinges on the levelof customer engagement. Engaged customersshow their enthusiasm for the brand throughtheir engagement in the brand communitieson social networking sites (Cheung et al,2011), and eventually promote repurchaseintention and positive word-of-mouth(Kumar et al, 2010). Here, we offer someguidelines for practitioners (for example, sitedevelopers and online brand communitymanagers) on the design and management ofthe online brand communities on socialnetworking sites.

Enhances system supportSite developers should develop multiplechannels for customers to share and retrieveknowledge. For example, developers couldprovide search functions within the onlinebrand community, and introduce tags fordifferent topics of posts. As a result, it wouldbe easier for members to retrieve relevantinformation. In addition, site developersshould enhance the communication channelsfor community members to exchange ideas;instead of text responses, developers mightconsider image or voice responses as newfunctions for members to interact.

Promotes community valueOnline brand community managers shouldclearly deliver the community values to themembers. When customers join thecommunity, they are generally seekingadvice on the products or services offeredby the organization. Managers shouldpay attention to the needs of these membersand offer support to them. A customerservice team could be set up, aimed atresolving the issues raised by the members.In addition, managers should alsoencourage active responses among existingmembers. Consequently, when membersare provided with personalized solutionsfor their concerns, they are morelikely to be engaged within thecommunity.

Facilitates freedom of expressionOnline brand community managers shouldencourage members to share their experienceand be open to criticism. Handling negativecomments could be challenging to managersbut it offers opportunities for the organizationto understand their weaknesses and discoverareas for improvement. Managers should beaware of prohibiting or filtering customers’comments as this practice could even worsenthe situation.

Chan et al


Offers rewards and recognitionSite developers could develop a rewardsystem to facilitate the recognition of activelyparticipating community members. Forexample, the system could grade thecommunity members based on theirengagement levels (for example, time online,questions responded to, number of newmembers invited) in the online brandcommunity so that managers could rewardthe members accordingly.

In short, a resourceful and comfortableonline brand community fosters engagementbetween customers and helps to promotepositive brand loyalty.

LimitationsLike all empirical studies, the current studyhas some limitations. First, the empiricalresearch is subjected to inherentmethodological limitations. This study hasbeen restricted to cross-sectional empiricalresearch. Future research could build up alongitudinal database to observe the dynamicsof customers’ attitudes and behaviors withinonline brand communities on socialnetworking sites. Second, the selection ofrespondents is bound to Facebook. Futureresearch may further validate the currentresult on other social networking sites, andmodify the research model with the specificsystem characteristics that are embedded inthe online brand community. Finally, themodel in the current study only explained 20per cent of variance of customer engagementin online brand communities on socialnetworking sites, suggesting that there may beother factors aside from IT artifacts that arepredictive in understanding the phenomenon.

CONCLUSIONThe current study shows the complex natureof customer engagement in online brandcommunities on social networking sites.A research model examining the antecedentsand consequences of customer engagement in

online brand communities on socialnetworking sites was empirically tested andvalidated. It is expected that the current studywill provide insights for practitioners to betterutilize and manage online brandcommunities, as well as shed light forresearchers to further investigate thephenomenon.

ACKNOWLEDGEMENTSReprinted with permission, from IEEEJanuary 2014, 47th Hawaii InternationalConference on System Sciences, ‘CustomerLoyalty to C2C Online Shopping Platforms:An Exploration of the Role of CustomerEngagement,’ by C.M.K. Cheung, X. Zhengand M.K.O. Lee. The authors acknowledgewith gratitude the generous support of theHong Kong Baptist University for the FacultyResearch Grant (FRG) FRG2/12-13/015without which the timely production of thecurrent publication would not have beenfeasible.

REFERENCESAdjei, M.T., Noble, S.M. and Noble, C.H. (2010) The

influence of C2C communications in online brandcommunities on customer purchase behavior. Academy ofMarketing Science. Journal 38(5): 634–653.

Algesheimer, R., Dholakia, U.M. and Herrmann, A. (2005)The social influence of brand community: Evidence fromEuropean car clubs. Journal of Marketing 69(3): 19–34.

Bagozzi, R.P. and Dholakia, U.M. (2002) Intentional socialaction in virtual communities. Journal of Interactive Marketing16(2): 2–21.

Bakker, A.B., Schaufeli, W.B., Leiter, M.P. and Taris, T.W.(2008) Work engagement: An emerging concept inoccupational health psychology.Work & Stress 22(3): 187–200.

Barclay, D., Higgins, C. and Thompson, R. (1995) The partialleast squares (PLS) approach to casual modeling: Personalcomputer adoption and use as an illustration. Technology2(2): 285–309.

Barnes, S.J. and Vidgen, R. (2012) User acceptance andcorporate intranet quality: An evaluation with iQual.Information & Management 49(3–4): 164–170.

Benbasat, I. and Zmud, R.W. (2003) The identity crisis withinthe IS discipline: Defining and communicating thediscipline’s core properties. MIS Quarterly 27(2): 183–194.

Bowden, J.L.H. (2009) The process of customer engagement:A conceptual framework. Journal of Marketing Theory& Practice 17(1): 63–74.



Brodie, R.J., Ilic, A., Juric, B. and Hollebeek, L. (2013)Consumer engagement in a virtual brand community:An exploratory analysis. Journal of Business Research 66(1):105–114.

Cheung, C.M.K., Lee, M.K.O. and Jin, X.L. (2011) Customerengagement in an online social platform: A conceptualmodel and scale development. International Conference onInformation Systems 2011, Shanghai, China.

Chin, W.W. (1998) The Partial Least Squares Approach toStructural Equation Modeling Modern Methods for BusinessResearch, Mahwah, NJ: Lawrence Erlbaum Associates.

Christian, M.S., Garza, A.S. and Slaughter, J.E. (2011) Workengagement: A quantitative review and test of its relationswith task and contextual performance. Personnel Psychology64(1): 89–136.

Chu, S.-C. and Kim, Y. (2011) Determinants of consumerengagement in electronic word-of-mouth (eWOM) insocial networking sites. International Journal of Advertising30(1): 47–75.

De Wulf, K., Odekerken-Schröder, G. and Iacobucci, D.(2001) Investments in consumer relationships: A cross-country and cross-industry exploration. Journal of Marketing65(4): 33–50.

Dholakia, U.M., Bagozzi, R.P. and Pearo, L.K. (2004) A socialinfluence model of consumer participation in network- andsmall-group-based virtual communities. International Journalof Research in Marketing 21(3): 241–263.

Doohwang, L., Soo, K.H. and Kyu, K.J. (2011) The impact ofonline brand community type on consumer’s communityengagement behaviors: Consumer-created vs. marketer-created online brand community in online social-networking web sites. CyberPsychology, Behavior & SocialNetworking 14(1–2): 59–63.

Dutton, J.E. and Dukerich, J.M. (1991) Keeping an eye on themirror: Image and identity in organizational adaptation.Academy of Management Journal 34(3): 517–554.

Fornell, C. and Larcker, D.F. (1981) Evaluating structuralequation models with unobservable variables andmeasurement error. Journal of Marketing Research 18(1):39–50.

Gustafsson, A., Johnson, M.D. and Roos, I. (2005) The effectsof customer satisfaction, relationship commitmentdimensions, and triggers on customer retention. Journal ofMarketing 69(4): 210–218.

Hair, J.F., Black, W.C., Babin, B.J., Anderson, R.E. andTatham, R.L. (1998) Multivariate Data Analysis, UpperSaddle River, NJ: Prentice-Hall.

Han, B. and Windsor, J. (2011) User’s willingness to pay onsocial network sites. Journal of Computer Information Systems51(4): 31–40.

Hennig-Thurau, T. et al. (2010) The impact of new media oncustomer relationships. Journal of Service Research 13(3):311–330.

Hollebeek, L.D. (2011) Demystifying customer brandengagement: Exploring the loyalty nexus. Journal ofmarketing management 27(7–8): 785–807.

Hoyer, W.D., Chandy, R., Dorotic, M., Krafft, M. and Singh,S.S. (2010) Consumer cocreation in new productdevelopment. Journal of Service Research 13(3): 283–296.

Hur, W.-M., Ahn, K.-H. and Kim, M. (2011) Building brandloyalty through managing brand community commitment.Management Decision 49(7): 1194–1213.

Hur, W.-M., Park, J. and Kim, M. (2010) The role ofcommitment on the customer benefits-loyalty relationshipin mobile service industry. Service Industries Journal 30(14):2293–2309.

Jahn, B. and Kunz, W. (2012) How to transform consumersinto fans of your brand. Journal of Service Management 23(3):344–361.

Jang, H., Olfman, L., Ko, I., Koh, J. and Kim, K. (2008) Theinfluence of on-line brand community characteristics oncommunity commitment and brand loyalty. InternationalJournal of Electronic Commerce 12(3): 57–80.

Kahn, W.A. (1990) Psychological conditions of personalengagement and disengagement at work. Academy ofManagement Journal 33(4): 692–724.

Khayun, V., Ractham, P. and Firpo, D. (2012) Assessinge-excise sucess with Delone and Mclean’s model. Journal ofComputer Information Systems 52(3): 31–40.

Kim, J.W., Choi, J., Qualls, W. and Han, K. (2008) It takes amarketplace community to raise brand commitment: Therole of online communities. Journal of Marketing Management24(3–4): 409–431.

Kim, J.Y., Shim, J.P. and Ahn, K.M. (2011) Socialnetworking service: Motivation, pleasure, and behavioralintention to use. Journal of Computer Information Systems51(4): 92–101.

Koetsier, J. (2013) Facebook: 15 million businesses, companies,and organizations now have a Facebook page [Online].http://venturebeat.com/2013/03/05/facebook-15-million-businesses-companies-and-organizations-now-have-a-facebook-page/, accessed 15 May 2013.

Koyuncu, M., Burke, R.J. and Fiksenbaum, L. (2006) Workengagement among women managers and professionals in aTurkish bank. Equality, Diversity and Inclusion: AnInternational Journal 25(4): 299–310.

Kumar, V., Aksoy, L., Donkers, B., Venkatesan, R., Wiesel, T.and Tillmanns, S. (2010) Undervalued or overvaluedcustomers: Capturing total customer engagement value.Journal of Service Research 13(3): 297–310.

Laroche, M., Habibi, M.R., Richard, M.-O. andSankaranarayanan, R. (2012) The effects of social mediabased brand communities on brand community markers,value creation practices, brand trust and brand loyalty.Computers in Human Behavior 28(5): 1755–1767.

Lee, H.J., Lee, D.-H., Taylor, C.R. and Lee, J.-H. (2011) Doonline brand communities help build and maintainrelationships with consumers? A network theory approach.Journal of Brand Management 19(3): 213–227.

Liang, H., Nilesh, S., Hu, Q. and Xue, Y. (2007) Assimilationof enterprise systems: The effect of institutional pressuresand the mediating role of top management. MIS Quarterly31(1): 59–87.

Libai, B. et al. (2010) Customer-to-customer interactions:Broadening the scope of word of mouth research. Journal ofService Research 13(3): 267–282.

Macey, W.H. and Schneider, B. (2008) The meaning ofemployee engagement. Industrial and OrganizationalPsychology 1(1): 3–30.

Maslach, C., Schaufeli, W.B. and Leiter, M.P. (2001) Jobburnout. Annual Review of Psychology 52(1): 397.

McWilliam, G. (2000) Building stronger brands throughonline communities. Sloan Management Review 41(3):43–54.

Chan et al


http://venturebeat.com/2013/03/05/facebook-15-million-businesses-companies-and-organizations-now-have-a-facebook-page/



Mollen, A. and Wilson, H. (2010) Engagement, telepresenceand interactivity in online consumer experience:Reconciling scholastic and managerial perspectives. Journalof Business Research 63(9–10): 919–925.

Muniz, A.M. and O’Guinn, T.C. (2001) Brand community.Journal of Consumer Research 27(4): 412–432.

Nambisan, S. and Baron, R.A. (2007) Interactions in virtualcustomer environments: Implications for product supportand customer relationship management. Journal of InteractiveMarketing 21(2): 42–62.

O’Brien, H.L. and Toms, E.G. (2008) What is userengagement? A conceptual framework for defining userengagement with technology. Journal of the American Societyfor Information Science & Technology 59(6): 938–955.

O’Brien, H.L. and Toms, E.G. (2010) The development andevaluation of a survey to measure user engagement. Journalof the American Society for Information Science and Technology61(1): 50–69.

O’Brien, H.L. (2010) The influence of hedonic andutilitarian motivations on user engagement: The case ofonline shopping experiences. Interacting with Computers22(5): 344–352.

Patterson, P., Yu, T. and Ruyter, K.D. (2006) Understandingcustomer engagement in services. Australian and NewZealand Marketing Academy 2006 Conference: AdvancingTheory, Maintaining Relevance, 2006, Australia, Brisbane.

Pavlou, P.A., Huigang, L. and Yajiong, X. (2007)Understanding and mitigating uncertainty in onlineexchange relationships: A principal-agent perspective. MISQuarterly 31(1): 105–136.

Pivotcon (2013) The state of social marketing 2012–2013[Online]. New York: Pivotcon. http://www.pivotcon.com/research_reports/SOS2013.pdf, accessed 2 February2014.

Podsakoff, P.M., Mackenzie, S.B., Lee, J.Y. and Podsakoff, N.P.(2003) Common method biases in behavioral research: Acritical review of the literature and recommended remedies.Journal of Applied Psychology 88(5): 879–903.

Rheingold, H. (1993) The Virtual Community: Homesteading onthe Electronic Frontier, New York: Harper Collins.

Rich, B.L., Lepine, J.A. and Crawford, E.R. (2010) Jobengagement: Antecedents and effects on job performance.Academy of Management Journal 53(3): 617–635.

Royo-Vela, M. and Casamassima, P. (2011) The influence ofbelonging to virtual brand communities on consumers’affective commitment, satisfaction and word-of-mouthadvertising: The ZARA case. Online Information Review35(4): 517–542.

Saks, A.M. (2006) Antecedents and consequences of employeeengagement. Journal of Managerial Psychology 21(7): 600–619.

Scott, J.E. and Walczak, S. (2009) Cognitive engagement witha multimedia ERP training tool: Assessing computer self-efficacy and technology acceptance. Information &Management 46(4): 221–232.

Sedley, R. (2008) Six theses on digital customer engagement ina troubled economy [Online]. http://www.richard-sedley.net/2008/02/six-theses-on-digital-customer-engagement-in-a-troubled-economy/, accessed 31 May 2013.

Socialbakers (2013) Coca-Cola facebook page statistics[Online]. http://www.socialbakers.com/facebook-pages/40796308305-coca-cola, accessed 18 August 2013.

Sprott, D., Czellar, S. and Spangenberg, E. (2009) Theimportance of a general measure of brand engagement onmarket behavior: Development and validation of a scale.Journal of Marketing Research 46(1): 92–104.

Stokburger-Sauer, N. (2010) Brand community: Drivers andoutcomes. Psychology and Marketing 27(4): 347–368.

Sung, Y.J., Kim, Y.J., Kwon, O.Y. and Moon, J.H. (2010) Anexplorative study of Korean consumer participation invirtual brand communities in social network sites. Journal ofGlobal Marketing 23(5): 430–445.

Tsai, H.-T. and Huang, H.-C. (2007) Determinants ofe-repurchase intentions: An integrative model ofquadruple retention drivers. Information & Management44(3): 231–239.

Turel, O. and Serenko, A. (2012) The benefits and dangers ofenjoyment with social networking websites. EuropeanJournal of Information Systems 21(5): 512–528.

van Doorn, J. et al. (2010) Customer engagement behavior:Theoretical foundations and research directions. Journal ofService Research 13(3): 253–266.

Verhoef, P.C., Franses, P.H. and Hoekstra, J.C. (2002) Theeffect of relational constructs on customer referrals andnumber of services purchased from a multiservice provider:Does age of relationship matter? Journal of the Academy ofMarketing Science 30(3): 202–216.

Vivek, S.D., Beatty, S.E. and Morgan, R.M. (2012) Customerengagement: Exploring customer relationships beyondpurchase. Journal of Marketing Theory and Practice 20(2):127–145.

Wang, M., Vogel, D. and Ran, W. (2011a) Creating aperformance-oriented e-learning environment: A designscience approach. Information & Management 48(7): 260–269.

Wang, Y.J., Butt, O.J. and Wei, J. (2011b) My identity is mymembership: A longitudinal explanation of online brandcommunity members’ behavioral characteristics. Journal ofBrand Management 19(1): 45–56.

Webster, J. and Ahuja, J.S. (2006) Enhancing the design of webnavigation systems: The influence of user disorientation onengagement and performance. MIS Quarterly 30: 661–678.

Wirtz, J. et al. (2013) Managing brands and customerengagement in online brand communities. Journal of ServiceManagement 24(3): 223–244.

Wold, H. (1989) Introduction to the Second Generation ofMultivariate Analysis Theoretical Empiricism, New York:Paragon House.

Wu, W.-Y. and Sukoco, B.M. (2010) Why should i share?examining consumers’ motives and trust on knowledgesharing. Journal of Computer Information Systems 50(4): 11–19.

Yang, T. (2012) The decision behavior of Facebook users.Journal of Computer Information Systems 52(3): 50–59.

Zaglia, M.E. (2013) Brand communities embedded in socialnetworks. Journal of Business Research 66(2): 216–223.

Zhou, Z., Zhang, Q., Su, C. and Zhou, N. (2012) How dobrand communities generate brand relationships? Intermediatemechanisms. Journal of Business Research 65(7): 890–895.



http://www.pivotcon.com/research_reports/SOS2013.pdf

http://www.pivotcon.com/research_reports/SOS2013.pdf

http://www.richard-sedley.net/2008/02/six-theses-on-digital-customer-engagement-in-a-troubled-economy/



http://www.socialbakers.com/facebook-pages/40796308305-coca-cola

http://www.socialbakers.com/facebook-pages/40796308305-coca-cola

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