Understanding social media effects across seller, retailer ......ORIGINAL EMPIRICAL RESEARCH Understanding social media effects across seller, retailer, and consumer interactions Adam

ORIGINAL EMPIRICAL RESEARCH

Understanding social media effects across seller, retailer,and consumer interactions

Adam Rapp & Lauren Skinner Beitelspacher &

Dhruv Grewal & Douglas E. Hughes

Received: 14 May 2012 /Accepted: 3 January 2013 /Published online: 27 January 2013# Academy of Marketing Science 2013

Abstract In this research, the authors propose a contagioneffect of social media use across business suppliers, retailers,and consumers. After developing and validating social mediausage measures at three levels—supplier, retailer, and custom-er—the authors test social media contagion effects and theirultimate impact on multiple performance measures. The con-ceptual framework and empirical results offer new insightsinto the contagion effects of social media usage across thechannel of distribution as well as important social influencemechanisms that enhance these effects. Consistent with thepredictions, social media use positively contributes to brandperformance, retailer performance, and consumer–retailer loy-alty. Also, the effect of supplier social media usage on retailersocial media usage and in turn on customer social media usageis moderated by brand reputation and service ambidexterity.With the ever-increasing growth and adoption of social mediaapplications and similar technologies, this research provides a

framework to promote usage by supply channel partnerswhich ultimately influences performance-related outcomes.

Keywords Social media . Salespeople . Retailer .

Contagion . Buyer–supplier relationships . Relationshipmarketing

Social media is changing the business landscape and redefin-ing how businesses communicate across their channels ofdistribution and with their customers. A recent survey of 399random European and U.S. firms indicated that 88.2% of thefirms had begun to undertake social media initiatives, andnearly half of these firms (42.1%) had fully integrated socialmedia into their business strategies (Insites Consulting 2011).Related research demonstrates that consumers are spending25% of their Internet time on social networking sites, up from15% in 2009 (Nielsen 2010). Consumers use social media tointeract with friends, view photos and videos, and find busi-nesses and brands. More than half of online shoppers interactwith a retailer on social networking sites such as Facebook,LinkedIn, and Twitter, and retailers and brands are capitalizingon this new promotional dimension to strengthen their cus-tomer relationships.

Social media usage is also extending beyond business-to-consumer (B2C) settings and becoming more apparent in thebusiness-to-business (B2B) community. More than 93% ofB2B marketers use one or more forms of social media tointeract with their customers (Holden-Bache 2011), and as of2010, Fortune 100 companies averaged 20 social mediaaccounts each, which they used to interact with customers,corporate partners, end consumers, and other stakeholders. Asfirms look to forge stronger connections with their customers ina competitive marketplace, the use of social media tools candramatically influence firm performance through customer en-gagement and the value created from customer interactions(Trainor 2012). However, roughly half of the 250 organizations

A. Rapp (*)Department of Marketing and Management,University of Alabama, 133 Alston Hall,Tuscaloosa, AL 35487, USAe-mail: [email protected]

L. S. BeitelspacherDepartment of Marketing, Portland State University,631 SW. Harrison St.,Portland, OR 97207, USAe-mail: [email protected]

D. GrewalDepartment of Marketing, Babson University, 213 Malloy Hall,Babson Park, MA 02457, USAe-mail: [email protected]

D. E. HughesDepartment of Marketing, Michigan State University,302 N. Business Complex,East Lansing, MI 48824, USAe-mail: [email protected]

J. of the Acad. Mark. Sci. (2013) 41:547–566DOI 10.1007/s11747-013-0326-9

taking a recent “social readiness assessment” have a jaundicedview of the business value of social media, viewing it as a threatto the effective functioning of the enterprise (Bradley andMcDonald 2012).

One challenge of social media integration is that it can bedifficult to quantify the return from such activity. Althoughmany suppliers use social media as a tool that promotesboundary spanning, suppliers have no measure of whethertheir brand message, delivered via social media, spreadsacross the channel to reach end consumers or of the mes-sage’s ultimate effects on brand as well as partner perfor-mance. Moreover, many companies suffer from ambiguouspolicies, inconsistent messages, and the lack of a definedsocial media strategy.

Despite the widespread and growing interest in socialmedia, empirical research is only in its infancy, particularlyin a B2B context, no doubt contributing to the uncertaintysurrounding the efficacy of its use. Our aim is to investigatethe cascading effect of social media use among suppliers,retail channel members, and consumers and to provide afoundation for additional research in this area. Accordingly,we investigate the outcomes of social media use throughouta distribution channel while examining the adoption ofsocial media as a communication mechanism amongchannel participants.

Considerable research has explored the role of social influ-ence in the diffusion of innovation, in particular that of newtechnology (e.g., Angst et al. 2010; Homburg et al. 2010;Kulviwat et al. 2008). Channels of distribution have long beencharacterized as social systems (Bagozzi 1975) and, as such,subject to imitative behavior among members. Social conta-gion is one theoretical framework that has been used toexplain the diffusion of innovation, imitative response, andtechnology transfer across many contexts, including the con-tinuances of behaviors throughout the supply chain from onedyadic channel partner to the next (McFarland et al. 2008).Therefore, we use the concept of contagion as a theoreticallens to examine the adoption of social media usage throughoutdownstream channel relationships and the resulting impact onbrand and channel member performance. This perspectivemay be particularly beneficial to the supplier in understandinghow its brand message cascades via social media throughoutthe supply chain.

Our research has several goals. First, we build a strongconceptual foundation for future research in the realm ofsocial media by developing and validating social media usagescales across three levels within the supply chain. Second, weinvestigate the effectiveness of social media in enhancingbusiness performance while establishing a better understand-ing of its contagion effects throughout a channel of distribu-tion. Third, we examine what relational factors may enhancethe transference of social media across the channel levels.Finally, we present practical implications for managers and

researchers regarding social media adoption and provide ave-nues for future investigations.

More specifically, our research explores the impact ofsocial media usage by supplier sales representatives on retailstore social media usage, and the effect of retail store usageon consumer social media usage, using contagion theory toexplain the imitative effects of social media across thechannel. Contagion theory suggests that individuals or firmsengage in behaviors because of their interactions with otherindividuals or firms who are engaged in similar behaviors(Burt 1987; Contractor and Eisenberg 1990; Latane 2000).Supply chain contagion in particular refers to interfirmbehaviors in one dyadic relationship that spread to the nextdyadic relationship in the chain (McFarland et al. 2008).Because of the social learning and normative influences ofcontagion, social media use by a supplier may propel theretailer’s social media use and ultimately the consumer’s.

We hypothesize that these contagion effects of socialmedia use across the channel are moderated by customerinteraction frequency, channel entity brand reputation, andservice ambidexterity (i.e., the ability to deliver high qualityservice while proactively seeking ways to improve service).In addition, we examine the performance implications ofsocial media usage from both the supplier and retailer per-spectives. In particular, we assess the extent to which socialmedia usage across the channel favorably influences brandperformance, retailer performance, and consumer–retailerloyalty. Therefore, we suggest that social media use ulti-mately works to the advantage of both supplier and retailer,and that its diffusion is facilitated by the firms’ adeptness inmanaging the service encounter at each level in the distri-bution channel, by the degree of personal interaction be-tween buyer and seller, and by the supplier and retailer’sreputation among its customers.

We organize the paper as follows. First, we present ourconceptual framework and hypotheses, and then we report theresults of two studies. Our initial study is used to developsocial media usage measures—important due to the scarcity ofexisting research on this topic and a contribution to the disci-pline in and of itself. In the second study, we collect andanalyze matched multilevel data from sales employees repre-senting a global brand, retail channel partners of this brand,and consumers who patronize those retailers. This allows us toassess the contagion effects of social media use across thechannel, draw related conclusions, and derive useful implica-tions for researchers and managers.

Conceptual development

With little research having been conducted on the influenceof social media in a business environment, it was necessaryto adopt theory and extant literature from other areas of

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inquiry. The underpinnings of our conceptual frameworkstem from theories of social contagion and concepts fromrelationship marketing. We use these theories and the repre-sentative domains of technology, adoption, and retailer re-search to develop our conceptual framework and build ourpropositions as presented below. We present in Fig. 1 ouroverarching framework of the contagion effects across thechannel and the factors that moderate these effects.

Contagion theory

Contagion theory stems from the medical concept of contagion,with the implication that a behavior, similar to a disease, istransmittable and can grow over time. Gustave LeBon firstintroduced the theory in 1896 to explain the “hypnotic influ-ence” that a crowd has, such that the anonymity of a large groupof people can ignite irrational or emotionally charged behavior.Since then, the use of contagion theory has expanded acrossmultiple disciplines. Social contagion occurs when peoplechange their behavior after an interaction with another personor group, due often to heightened awareness, social learning,and/or the desire to adhere to perceived norms through a processof relating (Latane 2000; Van den Bulte, and Wuyts 2007).

Managerial research indicates that contagion is supportedby communication networks that expose people to the infor-mation, attitudes, behaviors, and beliefs of others in the net-work (Burt 1987; Contractor and Eisenberg 1990). The moreexposure people have to these networks, the more likely theyare to adopt similar characteristics. Frequency, strength, andasymmetry of communication can increase or diminish thesecontagion effects (Erickson 1988). Managerial research alsoextends contagion theory by identifying structural dimensionsof contagious behaviors, such as contagion by cohesion or bystructural equivalence. The former occurs among people in thesame primary group, where the recipient has a strong relation-ship to the source. Contagion by structural equivalence occursbetween competitors, such that “the recipient and source aredefined by the same pattern of relations with friends, clients,and enemies” (Burkhardt and Brass 1990, p. 2). Galaskiewiczand Burt (1991) find evidence of contagion by structuralequivalence in corporate philanthropy when executive man-agers compared themselves to their peer groups and wereinspired to contribute more to philanthropies by competitorsin similar positions.

Marketing researchers also use contagion theory to un-derstand new product adoption, examining interpersonal

Fig. 1 Hypothesized model

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interactions and influences among members of a targetpopulation (Bass 1969; Du and Kamakura 2011; Mahajanet al. 2000). In this context, a primary channel for contagionis word of mouth (WOM). Opinion leaders with dispropor-tionate influences use communication and social networksto accelerate product adoption and expedite contagion(Iyengar et al. 2011). Contagion effects are also essentialin determining how likely a communication message is togo viral and spread through traditional or electronic WOM(Aral and Walker 2011). Even nonverbal conduits of conta-gion may explain customer adoption; in a retail setting,consumer product evaluations are higher when a consumerperceives a product as having been physically touched by anattractive person (Argo et al. 2008).

Supply chain contagion moves the focus beyond theemployee or consumer perspective, to the organizationaland inter-organizational context. This concept refers to the“propagation of inter-firm behaviors from one dyadic rela-tionship to an adjacent dyadic relationship within the supplychain” (McFarland et al. 2008, p. 63). It draws from insti-tution theory, which states that the institutional environmentstrongly influences an organization’s formal structures, suchthat institutional pressures eventually increase homogeneityin the institutional environment. For example, early adoptedinnovations that improve technological efficiencies get le-gitimized by the institutional environment, such that firmsthat ultimately do not adopt these technologies appear irratio-nal, even if the technology does not improve their efficiency(DiMaggio and Powell 1999).

McFarland et al. (2008) suggest that supply chain conta-gion occurs because of three types of imitation pressures (asadapted from Grewal and Dharwadkar 2002): reflexive imita-tion, compliant imitation, and normative imitation. Reflexiveimitation is a firm’s customary response to uncertainty thatinvolves mimicry of successful behaviors. Reflexive imitationcan also occur when organizations perceive similarity becauseshared identities create shared perceptions of environmental orcompetitive realities. Compliant imitation is a firm’s responseto inter-organizational dependence and is positively influ-enced by the cohesion that arises from interdependence inbusiness-to-business relationships. Finally, normative imita-tion is driven by high levels of socialization and interactionamong members of the same competitive, institutional envi-ronment. Normative imitation is characterized by the devel-opment of collective beliefs and acceptance of standardsamong channel members, which leads to the adoption andtransfer of behaviors from one level to the next, i.e., spawningsupply chain contagion.

In our focal supplier–retailer–consumer context, we ex-pect that reflexive and normative imitation in particularcauses increased social media usage by one group to en-courage the adoption of social media usage throughout thesupply chain. To reduce opportunism, organizations actively

seek to form alliances marked by trust and rich informationexchanges (Gulati and Gargiulo 1999) which stem fromopen communication (Palmatier et al. 2007a, b). Over time,these relationships evolve into networks that share informa-tion about competencies and the reliability of potential part-ners (Gulati 1995). More interdependent organizationalpartners also look to their networks for cues on strategicdecisions (Gulati and Gargiulo 1999). Organizations withina network exchange information and communicate frequently,leading to the imitative behavior outlined above.

Reflexive imitation occurs when one organization seeksto mimic the success of a partner organization. Retailersoften look to suppliers for the best ways to showcase andpromote supplier brands, which are vital to their own iden-tity. Suppliers focus their energies on developing identifica-tion strategies to promote the performance of the brandthroughout the channel. Many of these strategies may in-volve social media initiatives. The ultimate goal of thesebrand enhancement strategies is to improve the performanceof the brand, benefitting both the supplier and the retailer(Hughes and Ahearne 2010). Retailers may attempt to mimicthese strategies in the supply chain to increase their ownsuccess. Therefore, we suggest that in the supplier–retailerrelationship, contagion is primarily driven by reflexiveimitation.

As noted earlier, normative imitation is driven by high levelsof socialization and collective beliefs. For consumers, especial-ly, the groups that they belong to are an important source ofpride, self-esteem, fulfillment, and belonging. Consumers whoaremembers of product communities often engage in collectivebehaviors praising their favorite products (McAlexander et al.2002). Also, consumers may view the retailers that they fre-quent and brands that they carry as extensions of their personalidentities, especially for high involvement purchases. Thisresearch suggests that the consumers’ desire to identify with aretailer will perpetuate normative imitation that will enhancethe contagion effects of social media usage from the retailer tothe consumer.

It is important to recognize that social media encouragestwo-way communication. Although initiated by the up-stream channel member, social media is useful in commu-nicating both downstream and upstream. Thus, there is aninstrumental reason behind the contagion effects of socialmedia in that social media usage by upstream channel mem-bers alters or augments the mechanisms of interaction withdownstream participants, thus spawning both reflexive andnormative imitation.

H1a: As the supplier sales representative’s social mediausage increases, the retailer’s social media usageincreases.

H1b: As the retailer’s social media usage increases, con-sumer social media usage increases.


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Moderating influences

Social psychologists examining behavioral contagion and thediffusion of technologies through populations note that socialstructure and the nature of accompanying relationships andinteractions play a critical role in determining the rate ofadoption. For example, in their seminal research on contagion,Polansky et al. (1950) identify relative prestige and commu-nication availability as mechanisms of influence that stimulatecontagion effects across individuals. Similarly, McFarland etal. (2008) demonstrate that frequency of contact and perceivedsimilarity among boundary spanning personnel help spawncontagion effects across supply chains.

Therefore, we investigate three contributors to socialinfluence–customer contact frequency, brand reputation,and service ambidexterity–that we propose will facilitatethe spread of social media across channels. Customer con-tact frequency (i.e., the amount of time channel membersspent with their respective customers) implies high levels ofsocialization and interaction, thus facilitating communica-tion and understanding between channel partners. Brandreputation refers to the extent to which upstream channelmembers are perceived as stable, reputable, and trustworthy.The reputation of both retailer and supplier brands shouldincrease or decrease the relational value and influenceamong channel partners. Service ambidexterity involves afirm’s ability to both explore and exploit service-relatedopportunities within their competitive environment, oftenin response to uncertainty. In an increasingly service-dominant marketing environment, possessing this capabilityshould enable the firm to increase its influence with channelmembers. We suggest that each of these dimensions moder-ates the contagion effect of social media usage across chan-nels, such that the link becomes stronger when eachdimension is higher rather than lower. We discuss eachinfluence in more detail below.

Customer contact frequency Research on network strengthproposes that social networks consist of relationships withvarying tie strength, which Granovetter (1973, p. 1361)contends is driven by a “combination of the amount of time,the emotional intensity, the intimacy (mutual confiding), andthe reciprocal services which characterize a tie.” As sug-gested by previous research (Mittal et al. 2008; Nelson1989), tie strength has been measured using a variety ofvariables, including frequency of social contact. Customercontact frequency is an assessment by the upstream channelmember (i.e., supplier or retailer) about the frequency ofcontact with downstream partners. It stands to reason thatrelationships characterized by high levels of contact arelikely to be strong tie relationships.

Strong ties are influential in the diffusion process in thatthey serve to facilitate information flow and collective actions

across parties. Burt (1987) notes that physical proximity inand of itself may enable social contagion in that the closer thecontact between two parties the more likely one party’s adop-tion will trigger another’s. Imitation of behavior betweenorganizational firms has been shown to increase as the levelof interaction between the buyer and supplier firms increases(McFarland et al. 2008). Coleman (1990) contends that whenpeople have dense and overlapping (i.e., strong) ties, theyenjoy a greater sense of trust within the network. Networkswith strong ties therefore should experience improved infor-mation flow, because trust provides a foundation for sharinginformation and knowledge, as well as taking risks (Amabileet al. 1996). For example, embracing social media and itscommunication flows could expose a retailer or end consumerto privacy risks; when members trust others in the network,this risk is mitigated.

One might argue that contact frequency could actuallydecrease social media usage because abundant communica-tion through traditional mechanisms reduces the need forsocial media as a means of contact. However, based on thefacilitating and influential role of strong ties discussedabove and the imitative behavior that this spawns, we be-lieve that contact frequency will strengthen the relationshipbetween social media usage across channel levels. In sup-port of this assertion, Obstfeld (2005) notes that althoughstrong ties in dense networks inhibit innovation, they alsoeffectively support collective action. Social media usageacross channel levels is a collective action, such that partiesincur some risk, based on the level of information sharingsocial media demands. Strong bonds should help alleviatethis risk while enabling channel participants to share in thecollective benefit of an interactive communication device.Therefore, we hypothesize:

H2a: The frequency of customer interactions moderatesthe relationship between supplier social media usageand retailer social media usage, such that the rela-tionship is significantly stronger when the frequencyof customer interactions is high.

H2b: The frequency of customer interactions moderatesthe relationship between retailer social media usageand consumer social media usage, such that therelationship is significantly stronger when the fre-quency of customer interactions is high.

Brand reputation Brand reputation refers to the perceptions ofdownstream channel partners and final consumers about thebrand, as reflected by brand associations held in memory(Keller 1993). As a particular type of association, brand atti-tudes depend on people’s overall evaluations of the brand(Wilkie 1986), which can be driven by product- or non–prod-uct-related attributes (Rossiter and Percy 1987). Consistentwith the nature of the buyer–seller relationship that we are


examining and the power of social influence, wemeasure brandreputation using relational (non–product-related) elements,such as whether the brand appears trustworthy, reputable, andhonest in the claims it makes. Fournier (1995) finds that brandsoften become active relationship partners for consumers andprovide meanings in a psycho-sociocultural context. Forretailers and consumers, we contend that brand reputation is asought-after resource that can enhance the likelihood of socialmedia usage across channel levels.

Products supported by favorable brand reputationsshould be desired by retailers and consumers. These covetedresources enhance the likelihood of retailer success andprovide consumers a means to shape their self-concept.For example, runners often associate themselves with par-ticular running groups that are associated with a local retailbrand. The link between group and retailer helps forge anidentity for the group and its members, while also mitigatingrisk (Erdem and Swait 1998), because new members can beconfident, knowing that they have the appropriate runningequipment. The brand also provides a mechanism throughwhich consumers can shape (Sprott et al. 2009) and com-municate their self-concept (e.g., Levy 1959). To emerge asa local retailer of choice, the store must carry an assortmentof desirable brands. In many ways, a retailer’s own brand isa function of the supplier brands it offers to its customers.That is, to a large extent the retailer “borrows equity” fromsupplier brands to construct its own identity. Therefore, inthe example above, brand reputation is important not onlyfor consumers in shaping and supporting their self-conceptbut also for the retailer in establishing its identity as adesirable source of related products.

The desire for resources in the network (i.e., productswith favorable brand images) thus necessitates strongerrelationships with channel members that possess thoseresources. Therefore, we posit that the reflexive and norma-tive influences that facilitate the spread of social mediausage across channel levels will be stronger when suppliersand retailers possess favorable reputations.

H3a: Supplier brand reputation (perceived by the retailer)moderates the relationship between supplier socialmedia usage and retailer social media usage, suchthat the relationship is significantly stronger whenbrand reputation is more positive.

H3b: Retailer brand reputation (perceived by the consum-er) moderates the relationship between retailer socialmedia usage and consumer social media usage, suchthat the relationship is significantly stronger whenbrand reputation is more positive.

Service ambidexterity Ambidexterity in an organizationalcontext refers to a firm’s ability to perform conflicting tasks orpursue contrasting goals simultaneously (Yu et al. 2010), often

requiring managers to simultaneously sense changes and seizeopportunities in their competitive environment (O’Reilly andTushman 2011). Ambidexterity implies that firms can explorenew growth opportunities while also exploiting existing com-petencies with equal skill and dexterity (Lubatkin et al. 2006).Whereas exploitation occurs as a response to a firm’s currentenvironmental (day-to-day) conditions using existing resources(Lubatkin et al. 2006), exploration means firms develop newand innovative technologies to meet new market demands andrespond to changing environmental trends (Lubatkin et al.2006; Nonaka 1994). Managing both functions simultaneouslyis difficult, because the components require different types oflearning. With exploration, managers must use a bottom-uplearning approach and abandon old routines in pursuit of newopportunities. For exploitation, they must rely on a top-downlearning process in which current competencies and strengthsbecome a routine part of the infrastructure (Lubatkin et al. 2006;Wooldridge and Floyd 1989,). In addition, both exploration andexploitation require managers to continually scan their internalenvironments for core competencies and their external environ-ments for opportunities and threats.

Previous research on ambidexterity is primarily organiza-tional level, although employees also might engage in ambi-dextrous behaviors when attempting to achieve service andsales goals (Jasmand et al. 2012). We extend the concept ofambidextrous behavior to relationship development in thesupplier–retailer–consumer triad, specifically as it relates toprovision and improvement of service. Suppliers explore op-portunities to strengthen relationships with retailers while alsoexploiting their existing relationships with retailers and con-tinuously scanning the competitive environment for new op-portunities. Retailers in turn exploit strengths in their existingstrategies and relationships with existing customers, whilealso scanning the competitive environment to explore newopportunities. Such skills at both supplier and retailer level arelikely to strengthen ties and facilitate social learning, therebyaiding in the diffusion of ideas and related behaviors acrosschannel members. Specifically, suppliers and retailers thatstrive to identify needs and satisfy customers through explo-ration and exploitation increase the breadth and depth ofrelationships that influence imitative adoption of social mediaas a means of enhancing supplier–retailer and retailer–cus-tomer communication.

H4a: Supplier service ambidexterity moderates the relation-ship between supplier social media usage and retailersocial media usage, such that the relationship is signif-icantly stronger when ambidexterity is more positive.

H4b: Retailer service ambidexterity moderates the rela-tionship between retailer social media usage andconsumer social media usage, such that the relation-ship is significantly stronger when ambidexterity ismore positive.


Relationship marketing: social media usage, loyalty,and performance

As discussed, the number of firms and consumers that areadopting and using social media applications is growing at anexponential rate. With this high rate of use, it is important toexamine whether this adoption is affecting performance-related outcomes such as loyalty and sales at the brand orstore level. According to studies conducted during the 2011holiday shopping season, social media platforms like Twitterand Facebook gave businesses a chance to promote theirproducts, build store and brand loyalty, and fine tune theiroperations (Brin 2011). In keeping with the tenets of relation-ship marketing, particularly interfirm relationship marketingtheory (Palmatier 2007), we argue that the multilevel relation-ships we model are of importance.

Consumer–retailer loyalty results when a retailer can con-sistently deliver superior value that is manifested in the cus-tomer’s purchase behaviors. Zeithaml et al. (1996) classifyloyalty as a consumer’s intent to stay with an organization,and loyalty may encompass attitudinal or emotional elementstoo. Truly loyal customers are those who feel so stronglyabout a company that they virtually exclude competitors fromtheir consideration. Such “true loyalty” is a psychologicaltendency that leads to positive WOM repeat purchases(Shankar et al. 2003), and higher likelihoods of future use.Loyalty is a commitment by the customer to purchase from anorganization and help that organization succeed, mostly driv-en by customer satisfaction. When customers are satisfied,they view the exchange or transaction as equitable and fair(Oliver and Swan 1989). Retailers are able to use social mediato gather customer information and feedback in real time, thusallowing retailers to quickly adapt to changing customer tastesor to respond to potential service failures. This real-timeresponse and problem resolution often yields higher levelsof customer satisfaction (Brin 2011). According to Radian6,a market research firm specializing in retailer social mediausage, social media has created a shift in the consumer mind-set. Customers now expect an overall seamless experience andare more loyal to retailers who use social media to provide thatexperience and adapt to customers. Retailers can enhanceloyalty by increasing satisfaction through higher levels ofaffect the customer feels for the firm, such as by addingexcitement or more interpersonal experience to the servicedelivered (Yim et al. 2008).

When customers use social media to engage with retailers,it should enhance the relationship and create a more tailored,interpersonal relationship. In a highly digitized world, con-sumers attribute interpersonal relationship characteristics tocomputers, through a phenomenon known as social responsetheory. When computers display humanlike characteristics,consumers apply social rules to them, even though they knowthat they are engaging with a machine (Reeves and Nass

1996). When consumers consider the website representativeof the firm, they respond favorably to positive social cuesdisplayed during the exchange (Wang et al. 2007). When aretail website uses more human characteristics, such as lan-guage, voice, and interactivity, the consumer attributes moresocial cues to the website. The more favorable the consumer’ssocial perceptions are, the more favorably the consumer viewsthe exchange, leading to positive patronage and repurchaseintentions (Wang et al. 2007).

In addition, social media allows organizations to commu-nicate on a more personal level. Retailers can engage in one-on-one dialogues with customers, respond immediately tocomplaints, and alert customers to customized offerings.Thus, social media usage again is driven primarily by humaninteraction, with technology as the conduit. The social per-ceptions that consumers attribute to a website should expandsignificantly with social media usage, because of the interper-sonal and highly communicative interaction it provides. Thatis, the more the consumer interacts with a retailer using socialmedia, the more likely the retailer is to create a feeling ofexcitement and generate affection. The consumer also shouldattribute positive social cues to the retailer, leading to in-creased loyalty to the retailer.

H5: As consumer social media usage increases, consumer–retailer loyalty increases.

Retailer social media usage and performance The indirecteffects of supplier and firm relationship development ontobrand and retailer performance, respectively, also are sup-ported by considerable research. Previous studies indicatethat relationship development both directly and indirectlyaffects firm performance through mediating influences,such as enhanced inter-employee coordination, operation-al efficiency, and organizational knowledge development(Nahapiet and Ghoshal 1998). Firms with stronger relation-ships can improve performance through intellectual capitalcreation, interfirm learning, resource exchange, product inno-vation, team effectiveness, knowledge exploitation, and sup-plier relations (Palmatier et al. 2006; Yli-Renko et al. 2001).Thus, building relationships across levels should augmentbrand and retailer performance, measured as brand and totalsales per retail store for the one-year period following the datacollection, through enhanced social media usage amongpartners.

Retailers use social media to engage and interact withtheir customers; suppliers can use social media to createmore interpersonal connections with retailers. Suppliers alsomight use social media to announce events, incentives,promotions, and industry events. Because we anticipate acontagion effect throughout the supply chain, the more asupplier salesperson uses social media, the more the retailerwill use social media (H1a). When the contagion effect


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increases the retailer’s social media usage, it may incorpo-rate more of the supplier’s message into its social mediacommunication. In effect, not only will the salespersonpromote the supplier brand, but the retailer will promotethe supplier brand as well. According to Campalyst (amarket research firm that measures the impact of socialmedia), the top Internet retailers on social media includeAmazon.com, Office Depot, Staples, and Walmart in the top10 performers (2011). These retailers all sell national brand-ed merchandise in addition to their private label merchan-dise. They are deemed to be successful on social mediabecause of their ability to drive traffic to their stores, re-spond quickly to customer requests and concerns, and pro-vide the product assortment that customers want. Often, thesocial media campaigns focus on multiple brands and store-wide events, versus specific brand events. This increase insocial media–driven sales benefits all the brands that thesestores sell as well as the individual national brands.Therefore, retailer social media usage should positivelyinfluence brand performance within the retail outlet, due toincreased exposure.

H6a: As retailer social media usage increases, supplierbrand performance within the retailer increases.

Additionally, social media might spark a dialogue betweenthe retailer and consumers or between consumers. Retailersthen can use social media to improve communication anddevelop interpersonal relationships with consumers. This ac-tive and continuous level of engagement will not only pro-mote brand performance but also improve the retailer’sperformance.

H6b: As retailer social media usage increases, retailer salesperformance increases.

Consumer–retailer loyalty and performance For customersto be truly loyal, they must frequently purchase a productand have a favorable attitude toward it. Reichheld (1996)summarizes the benefits of customer loyalty: increased rev-enue and decreased cost of customer acquisition. As wenoted previously, customer loyalty often is measured bythe customer’s purchase behaviors; greater loyalty meansthe customer’s higher propensity to continue to purchase,which implies a positive impact on firm performance.Customers who are loyal to a retailer buy more, are moreopen to learning about new or add-on products, and tend torecommend a retailer to others. When customers are loyal toa specific retailer, they are more likely to visit the retailerand prefer the retailer over its competitors (Evanschitzkyet al. 2012).

H7: Consumer–retailer loyalty enhances (a) supplier brandsales performance and (b) retailer sales performance.

Study 1: Social media scale development

Construct definition and domain

To develop a parsimonious scale, representative of the fullrange of social media usage behaviors, we followed standardscale development procedures suggested by Nunnally (1978)and Churchill (1979). The first step was to generate a list ofitems that captures the breadth of social media usage. Usingprevious customer-facing technology scales as a model, wedeveloped a list of behaviors that fit the basic criteria used todistinguish social media usage behaviors. To understand thesebehaviors, we first needed to understand what supply chainmembers perceived to constitute social media–related activi-ties.We asked 10 retail store managers and 10 B2B salespeopleto list the social media behaviors or activities they engage in tosupport or promote their business, including specific, job-related activities rather than personal social networking activi-ties outside their work-related activity. Nearly all respondentsindicated their use of multiple accounts, one for personal useand one for business purposes.

We next asked participants to generate lists of socialmedia usage behaviors they engage in. To facilitate theprocess, we asked them to think about how they use socialmedia, the purpose behind their use, its perceived businessadvantages, and so on, with the goal of arriving at a com-prehensive list of behaviors. We compared the lists generat-ed by the managers and salespeople to behaviors previouslystudied, including customer relationship management tech-nologies, sales force automation, WOM activities, and var-ious communications and promotions. We added items toreflect behaviors that we found in the literature that had notbeen listed by the respondents. Finally, we reviewed andincluded activities identified by the popular press. Our finallist contained 31 different activities.

Item generation and refinement

We presented our list of 31 items to a panel of 20 academiccolleagues, experts in the field, and general customers, whosuggested additional items, recommended removal of someitems, and clarified the wording of several items. This testactually reduced the number of items. Much discussion sur-rounded whether to include specific social media applicationsor keep the scale a broad, global measure of social media use.Consensus from the group and the sponsoring organization forStudy 2 recommended removing all specific applicationnames (e.g., Flickr, Oovoo) except for Facebook andTwitter, which were in use by nearly every member of thepanel. The inclusion of these two applications leaves the scalebroad in nature; they can be adapted for future research if theyare not relevant to a specific study. This global measure ofusage includes different levels within the supply chain for


Nicole Lancaster

Nicole Lancaster

generalizability and does not focus solely on downward influ-ences. The group discussion also prompted us to adopt differ-ent wording and items for the scale(s), based on the level in thesupply chain. These differences helped capture the nature ofthe B2B relationship at the supplier level and the B2C rela-tionship at the retailer level. Our item list decreased to 13items for the supplier scale and 13 items for the retailer scale.The retailer scale also represented a customer scale (i.e.,retailers are customers of the supplier) but refined it by re-moving specific business promotion items (e.g., used fortargeting customers) to arrive at our 10-item customer scale.

Scale construction and reliability

Next we administered the 13-item supplier scale to a sampleof 106 B2B salespeople, to generate reliability statistics andtest the initial scale structure. Participants considered spe-cific business relationships and the associated role of socialmedia, to ensure that respondents did not include theirpersonal social media uses in their responses. We also ad-ministered the 13-item scale to a sample of 107 retailer storemanagers and the 10-item scale to 97 consumers for thesame purpose. Participants responded on a seven-pointLikert-type scale with endpoints “never/very often” to indi-cate whether they engaged in the specific social media–related activity.

The items were factor analyzed using a principal compo-nents analysis with Varimax rotation in separate analyses.Each initial solution resulted in a single factor with aneigenvalue greater than 1, and more than 70% of the vari-ance was explained by a single factor for each sample;therefore, the initial item set provides a strong representationof a social media usage scale. The reliability values were α=.97 for the supplier scale, α=.98 for the retailer scale, andα=.96 for the customer scale.

Validity

We proceeded with our scale validation by testing for dis-criminant and nomological validity. Although there is littletheory for a nomological framework, we reason that friend-ship can be a predictor of social media and communicationcan be an outcome. We used multi-item measures for thesetwo constructs from extant literature to create a causalframework and found that both measures offered acceptablereliabilities in the supplier, retailer, and customer subsam-ples (friendship (Grayson 2007): α=.78, .73, and .79; com-munication (Anderson et al. 1987): α=.95, .96, and .96,respectively). For each sample, we used structural equationmodeling to evaluate the overall fit of the social media usagescales in the presence of the other constructs. Fit indices forall models were acceptable. For example, from the supplierconfirmatory factor analyses (CFA), we uncovered χ2=

413.7 (165) (p<.01; χ2/df=2.51) confirmatory fit index(CFI)=.90, incremental fit index (IFI)=.90, and square rootmean residual (SRMR)=.07. The fit from the CFAs for theretailer (χ2=513.1 (165); p<.01; χ2/df=3.11; CFI=.90,IFI= .90, SRMR=.06) and customer (χ2=231.4 (114);p<.01; χ2/df=2.03; CFI=.94, IFI=.94, SRMR=.06) weresimilarly good. To assess discriminant validity, we com-pared the square root of the average variance extracted withthe correlations among constructs. On average, each con-struct related more strongly to its own measures than toothers. The average variance extracted exceeded .50 for allconstructs (Fornell and Larcker 1981).

To test whether the social media scale related empirically tothese factors, we examined the relationships across variables.Social media related significantly and positively to friendshipand communication for all samples. Specifically, friendshippredicted social media usage (supplier β=.403, t=4.292,p<.01; retailer β=.476, t=4.709, p<.01; customer β=.436,t=4.514, p<.01). Similarly, social media predicted communi-cation (supplier β=.229, t=2.310, p<.05; retailer β=.244,t=2.416, p<.05; customer β=.261, t=2.491, p<.01). Withthe results suggesting nomological validity, we proceeded tothe second, multilevel framework.

Study 2: Multilevel framework

Sample

For Study 2, we used a three-level dataset, collectedfrom supplier salespeople, retail store managers, andcustomers as represented in Fig. 2. The focal suppliercompany is a global leader in sporting goods; we thus inves-tigated a typical U.S. retail structure, in which the brandproducer uses B2B salespeople to visit retail outlets andmarket its products. Retailers have direct contact with thecustomer and offer the brand’s product(s) as well as those inthe competitive set. Accordingly, the retailer’s performance isa function of the brand’s sales, as well as sales of all otherproducts in the store.

It is important to note that the retail stores used in thisstudy were privately operated. Although some operatedunder a franchised name, retail managers had completeautonomy on sales, promotional activities, etc. Also, socialmedia usage at both the supplier and retailer level wasoptional and not mandated by the firm or franchise.Therefore, the responsibility of using social media for busi-ness fell solely on the shoulders of those who responded toour survey. Considering that a small portion of our sampleoperated under similar franchise names, we conducted anANOVA analysis to ensure that there were no group effectspresent in sample. Our analyses yielded non-significantresults for social media usage (F=1.352; p<.256), which


suggests that groups do not have differing degrees of sever-ity of leniency when rating usage.

As mentioned, we obtained data from supplier sales-people, retail managers, and consumers. We distributedsurvey questionnaires to all 28 salespeople in one distri-bution channel of the company and received responsesfrom all 28 (100% response rate). To test the cross-levelhypotheses of social media usage and the proposed inter-actions, we partnered with the professional association ofthe specific retail category and contacted 304 U.S.retailers. We received 144 usable responses, for a 47.4%response rate. We then cooperated with the premiere mag-azine related to this retail category to send invitations to10,000 subscribers and request that they complete a briefsurvey, in return for an honorarium. After removingrespondents that did not match with our retailer responses,we received 445 consumer responses (4.45% responserate), which provided multiple responses per store (aver-age 3.09 respondents per retail store, 15.8 respondents persupplier salesperson). Consumer response demographicprofiles on age, gender, education, and income were com-pared to archival profile data held by the professionalassociation and validated by the supplier to ensure arepresentative sample of customers. Consumer sample sta-tistic comparisons (sample vs. population) were: age 45–64 (27.4%/26.6%), female (56.4%/57.0%), college educa-tion (57.9%/60.8%), and annual household income$100,000 or over (37.2%/39.8%). To check for nonre-sponse bias, we compared early and late responders onall constructs.

Measures

The latent measures in this study came from the previouslyconstructed multi-item scales, except for social media usagein the supply chain, as outlined previously. The measures forsocial media demonstrated similar loadings to those in thepretest. Social media usage reliability (supplier (α=.90),retailer (α=.91), and customer (α=.96)) levels were accept-able. All items appear in the Appendix. The means, standarddeviations, and latent construct correlations across levels arepresented in Table 1.

To determine reputation at the supplier level (α=.91;Rwg=.83), we used the five-item brand reputation scaledeveloped by Veloutsou and Moutinho (2009). Reputation atthe retailer (i.e., store) level (α=.97; rwg=.84) used the similarfive-item reputation scale. The specific items were: trustwor-thy, reputable, makes honest claims, has a long lasting nature,and values behind this brand will not change. We then aggre-gated the scores to assess the interaction with social mediausage by the channel partner, after calculating the within-group correlations (rwg). Both scales demonstrated levelsabove the recommended .70 cutoff level.

The service ambidexterity measure consisted of a four-item scale from Lubatkin et al. (2006), as refined by Yu et al.(2010) and Collier and Sherrell (2010), that determined howa firm explored and exploited products and services toachieve greater satisfaction. The specific items were: weincrease the level of service quality delivered to customers,we constantly survey existing customers’ satisfaction, wetalk to accounts to gain new ideas on how to merchandise

Fig. 2 Sources of data collection


products, and we take pleasure in explaining what newproduct lines are available. Both scales were reliable at thesupplier (α=.93) and retailer (α=.75) levels.

For consumer–retailer loyalty, we used the six-item scaledeveloped by Palmatier et al. (2007a, b), targeted toward theretailer and aggregated according to the process we describedpreviously. This scale also was reliable (α=.92; rwg=.80).

Customer interaction at the retailer level was measured asthe average percentage of time the respondent spent withcustomers, parallel to the measure used to assess the amountof interaction between virtual team members (e.g., Rapp etal. 2010). Retail managers were asked what percentage oftheir time, on average, they spent with customers. For thesupplier level, the sponsoring firm provided actual amountof time spent with each account for the year prior to the datacollection which was collected via the firm’s customer rela-tionship management tracking system. Finally, for brandperformance, we measured total sales of the brand in theretail outlet and retailer sales performance was measured asthe total store sales. Both brand and retailer performancemetrics were for the 12 months following the data collectioneffort.

Analytical strategy

Due to the multilevel aspects of our conceptual frame-work, it is important to consider the hierarchical natureof our data structure before undertaking our empiricalanalyses. In this framework we have a dependent vari-able, specifically social media adoption at the retailerlevel, which is nested within specific salespeople.Similarly, with multiple customers reporting their socialmedia usage for each retailer outlet, the customer socialmedia usage variable is nested within retail units. Therefore,

with these hierarchical concerns, it is imperative to select theappropriate method of estimation.

To analyze this multilevel framework, we adopt a multi-level approach referred to as hierarchical linear modeling(HLM) (Raudenbush and Bryk 2002). HLM provides asimultaneous estimation of relationships which are nestedacross levels. Importantly, with customers nested withinretailers and retailers nested within salespeople, HLM ap-propriately takes into consideration the non-independencebetween observations into account. Simply, it is possiblethat the responses from one set of consumers (or retailers)may be more similar than they are from another set ofconsumers (or retailers) and this non-independence willinfluence statistical results if not appropriately modeled(Bliese and Hanges 2004). Recent marketing literature hasadopted a similar HLM approach and procedure (e.g.,Hughes and Ahearne 2010; Lam et al. 2010).

Before estimating the hypothesized paths, we deemed itimportant to determine how much variance resides withinand between units, to serve as a foundation for subsequentanalyses. We first estimated a series of baseline models(intercepts only) that included only the dependent variable(i.e., social media usage as an outcome). Using social mediausage at the retailer level as our dependent measure in theintercept-only model, we determined significant between-group variation (χ2=155.1 (27); p<.001). Specifically, 52%of the variance in social media usage resided within retailers(1 – ICC (1)=σ2/(σ2+τ00)), and 48% resided between sup-plier salespeople. In the second intercept-only model, weincluded social media usage at the consumer level as thedependent measure. Again, we found significant variance inthe customer’s use of social media, stemming from activitiesor behaviors at the retailer level (χ2=336.8 (142); p<.001).The ICC(1) calculation shows that 68% of the variance of

Table 1 Correlations at retailer level

1 2 3 4 5 6 7 8 9 10

1 Retailer social media 1

2 Service ambidexterity 0.297** 1

3 Supplier brand reputation 0.314** −0.048 1

4 Retailer reputationa 0.267*** 0.478** 0.024 1

5 Customer contact −0.024 −0.029 0.187* −0.086 1

6 Customer social mediaa 0.077 −0.168* 0.022 −0.113 0.131 1

7 Consumer–retailer loyaltya 0.078 −0.001 −0.032 0.156 0.006 0.256** 1

8 Supplier brand sales Perf 0.186* −0.053 0.047 0.129 −0.214* 0.155 0.191* 1

9 Retailer sales performance 0.257** 0.105 0.132 0.145 0.059 0.162* 0.228** 0.321** 1

10 Retail store size 0.074 0.095 −0.011 −0.072 0.077 0.049 0.062 −0.024 0.016 1

*Correlation is significant at the 0.05 level (2-tailed)

**Correlation is significant at the 0.01 level (2-tailed)a Aggregated from Customer Level


social media usage stems from the retailer store, and 32% isat the individual level. This preliminary analysis revealedthat retail stores can have a direct influence on the socialmedia behaviors of their consumers.

In support of our first hypotheses, we uncovered a directeffect of social media usage from the supplier to the retailstore (H1a γ=.246, p<.05), as well as the link from theretail store to the customer (H1b γ=.176, p<.05). Forretailers, social media usage in and of itself may influencethe consumers’ use of social media. Many consumers appearto follow retailer stores for promotional and advertising infor-mation. Similarly, results suggest that retail stores are trackingsocial media usage of the supplier salesperson. Although werealize that other approaches or theories could be used tosupport these initial relationships, our preliminary results areconsistent with the contagion influence outlined above.

Regarding the moderating influences of the three individ-ual constructs, our results showed that both reputation (H3aγ=.360, p<.05; H3b γ=.194, p<.05) and ambidexterity(H4a γ=.260, p<.01; H4b γ=.256, p<.05) positively mod-erated the use of social media at the lower level in the supplychain. However, customer interaction did not demonstratethe same significance as a moderator in either relationship(H2a γ=−.001, p<.32; H2b γ=.186, p<.13). To gain abetter understanding of these interactions, we graph theindividual moderating effects in Fig. 3a–d.

As we show in Fig. 3, Panel A, the relationship betweenthe supplier salesperson’s social media use and that of theretailer is enhanced when the brand reputation is high andreduced when the brand reputation is low. In Panel C, therelationship between social media usage of the retailer andthat of the consumer is enhanced when the brand reputationis high. These two findings suggest that as a brand (or aretail store’s) reputation becomes more prominent, the actorsengaging that group will be more likely to use social mediaas the group’s use increases. Interestingly, a weak supplierreputation actually reverses the contagion effect to the ex-tent that the retailer is less likely to adopt social media. Wealso show in Fig. 3, Panel B, the relationship between socialmedia usage of the supplier salesperson and that of theretailer is enhanced when the ambidexterity is high andreduced when ambidexterity is low. Finally, in Panel D, asimilar relationship between social media usage of the re-tailer and that of the consumer as a function of ambidexter-ity is plotted. Speculating on these interactions, it appears toincrease downstream social media adoption as suppliersalespeople and retailers explore more customer-related op-portunities. Again, in the case of supplier–retailer contagion,the effect is reversed when ambidexterity is low.

These figures suggest different phenomena are occurringacross levels, so engaging in relationship development behav-iors appears to represent a valuable undertaking. Having de-termined how suppliers and retailers can influence social

media usage by their customers, we also need to gauge if thisusage can influence performance (Tables 2 and 3).

In the final portion of our analyses, we investigated relatedoutcomes of social media usage. Although not the focus ofthis research, as past research has identified relationshipsbetween our moderating constructs and loyalty and perfor-mance, we deemed it valuable to include them as covariates.We also include store size as a covariate. First, the consumer’suse of social media directly influences his or her loyalty to theretail store (H5 β=.120, p<.01). Second, social media influ-ences both brand (H6a β=.180, p<.05) and store (H6bβ=.172, p<.05) performance. Third, as we expected, moreloyal consumers tended to buy more across the brand (H7aβ=.162, p<.05) and the total retail store offering (H7bβ=.158, p<.05) (Table 4).

Discussion

Recent research (Crittenden et al. 2010) has painted a pictureof a “connected consumer” who uses technology and socialmedia to become intertwined in business processes. As endconsumers rely more and more on social media applications tokeep connected, these applications emerge increasingly asimportant forms of interactivity for B2B firms as well.Customers expect interactions across their personal networksbut also with their business counterparts. This demand for andadoption of social media has not gone unnoticed.

The shift in consumer expectations challenges firmsthroughout the supply chain to develop and deploy newtechnologies that facilitate customer–firm interactions; it alsohas broadened the notion of what it means to manage custom-er relationships. Perhaps more than ever, effectively managingcustomer relationships and technology simultaneously candramatically influence performance for all members of thesupply chain network. To reinforce this point, Wang et al.(2007) have demonstrated, using social response theory, thatconsumers treat computers and technology as social actors,not just as mediums in retail site interactions, which caninfluence their purchase decisions.

Despite the increased usage of and applications for socialmedia technology, marketing research has yet to advance aframework that incorporates both the role of social media andthe affected supply chain relationship or performance implica-tions. Most literature on social media tends to be conceptual oranecdotal in nature, often from the popular press. By develop-ing social media usage scales, we examine the influence of thesocial media usage across the channel, with grounding in thefoundations of contagion theory and relationship marketing.

Accordingly, we make several contributions which we out-line in Table 5. In this paper, we develop and validate compre-hensive measures of social media usage for different actors inthe channel (supplier representatives, retailers, and consumers).


A

B

ModeratorLow Reputation Average Reputation Strong Reputation

ModeratorLow Ambidexterity Average Ambidexterity Strong Ambidexterity

C

DModeratorLow Ambidexterity Average Ambidexterity Strong Ambidexterity

ModeratorLow Reputation Average Reputation Strong Reputation

Fig. 3 aModerating influence of supplier brand reputation on suppliersalesperson social media use on retailer social media use. bModeratinginfluence of service ambidexterity on supplier salesperson social mediause on retailer social media use. c Moderating influence of retailer

reputation on retailer social media use on customer social media use. dModerating influence of service ambidexterity on retailer social mediause on customer social media use

Table 2 Supplier influence on retailer’s social media use hierarchicalresults

Fixed effect Coefficient SE t-ratio

p-value

Supplier influence on retailer’s social media use results

Brand reputation 0.720 0.17 4.06 0.01***

Service ambidexterity 0.166 0.17 0.98 0.34

Supplier social media use 0.246 0.10 2.36 0.03**

Customer interaction 0.028 0.01 2.39 0.02**

Supplier to retailer model interactive effects

Brand reputation 0.545 0.26 2.10 0.05**

Service ambidexterity 0.046 0.14 0.32 0.75

Supplier social media use 0.100 0.13 0.76 0.45

Customer interaction 0.063 0.04 1.78 0.08

Soc_med use×Cust int −0.001 0.01 −0.99 0.32

Soc_med use×Serv ambid 0.260 0.09 2.76 0.01***

Soc_med use×Brand rep 0.360 0.15 2.34 0.03**

Table 3 Retailer influence on consumer’s social media use hierarchi-cal results

Fixed effect Coefficient SE t-ratio p-value

Retailer influence on consumer’s social media use results

Retailer social media use 0.176 0.09 1.96 0.05**

Retailer reputation −0.060 0.09 −0.67 0.51

Service ambidexterity −0.177 0.09 −2.04 0.04**


Retailer to customer model interactive effects

Retailer social media use 0.209 0.09 2.37 0.02**

Retailer reputation 0.112 0.09 1.24 0.22

Service ambidexterity −0.095 0.08 −1.13 0.26


Soc_med×Cust int −0.163 0.11 −1.51 0.13

Soc_med×Retail rep 0.194 0.09 2.13 0.04**

Soc_med×Serv ambid 0.256 0.11 2.41 0.02**


The advancement and empirical validation of these scale meas-ures provides a starting point for further research and investi-gation of the topic. Our approach parallels past technologyresearch by emphasizing the importance of adoption as the firststep in the technology usage process. By refining threeunique scales, we capture the nuances at each level in thesupply chain—specifically, the roles of social media for busi-nesses versus customers. With our broad adoption scale de-sign, we believe these scales should remain relevant over time.Although these scales are self-report measures and may sufferfrom inflation biases, we believe that they build a solid foun-dation for future research. Finally, we advance a model ofsocial media using contagion theory which we discuss below.

Contagion theory

We examine how social media cascades across the distributionchannel. With so many firms beginning to recognize theimplications of technological and social shifts in modernsociety, they have started to investigate how to increase adop-tion at all levels. As actors interact, the use of social mediashould influence the partners’ uses of the technology. We basethis premise onwork byMcFarland et al. (2008), who proposethat firm behaviors and actions are imitated in the supplychain. Our findings provide initial support for the contagioneffect of social media usage across retailers and end-consumers. Thus we go beyond statistical validation of arelationship and tap the underlying nature and importance ofthe effects of social media use across the supply chain.

Although we believe these effects highlight contagion acrosssupply chain levels, it would be valuable for future research toexamine the effects of temporal issues, relational norms, andresource allocation, among other things, on the adoption ofsocial media.

Although not stated explicitly in our arguments, the great-est influence on performance likely occurs when both partiesuse social media. As suggested in recent research, businessesare beginning to use social media to develop and maintaindurable relationships with customers, for WOM marketing(Kozinets et al. 2010), community-based customer support(Greenberg 2010), and innovation co-creation (Sawhney etal. 2005). To achieve these desirable outcomes, firms mustconsider, as we demonstrate, how the use of social mediaupstream in the supply chain will influence those downstream,as well as which other factors might moderate the downstreamadoption and its consequences.

Building from the concepts of contagion and social in-fluence, we predicted and tested the role of three moderatingfactors capable of influencing the transfer of social mediausage behaviors across channel dyads. Consistent with re-search that emphasizes the importance of brand relation-ships (e.g., Aggarwal 2004; Fournier 1998; Park et al.2010), we find that retailers and consumers are apt to mirrorupstream social media usage behaviors only when theybelieve the brand is reputable. Previous research has indi-cated that consumers also differ in how they perceive andrelate to brands (Fournier 1998; Muniz and O’Guinn 2001)and that brand affiliations provide consumers a mechanism

Table 4 Hypothesized relations

Standardized parameterestimates*Significant at p<.05 level**Significant at p<.01 level

β t-ratio p-value

H5 Customer social media usage → Consumer retailer loyalty 0.120** 2.53 0.01

Service ambidexterity → Consumer retailer loyalty −0.069 ns –

Customer interaction → Consumer retailer loyalty −0.018 ns –

Retailer reputation → Consumer retailer loyalty 0.223* 2.41 0.02

Retail store size → Consumer retailer loyalty 0.073 ns –

H6a Retailer social media usage → Supplier brand sales perf 0.180* 1.99 0.05

H7a Consumer retailer loyalty → Supplier brand sales perf 0.162* 1.98 0.05

Service ambidexterity → Supplier brand sales perf −0.166 ns –

Customer interaction → Supplier brand sales perf −0.210* −2.55 0.02

Supplier brand reputation → Supplier brand sales perf 0.024 ns –

Retailer reputation → Supplier brand sales perf 0.116 ns –

Retail store size → Supplier brand sales perf −0.007 ns –

H7b Consumer retailer loyalty → Retailer sales performance 0.158* 1.98 0.05

H6b Retailer social media usage → Retailer sales performance 0.172* 2.06 0.04

Service ambidexterity → Retailer sales performance 0.067 ns –

Customer interaction → Retailer sales performance 0.128 ns –

Reatiler reputation → Retailer sales performance 0.015 ns –

Retail store size → Retailer sales performance −0.014 ns –

Supplier brand performance → Retailer sales performance 0.283** 3.57 0.01


Table 5 Summary of key findings and implications

Key findings Implications

Contagion theory

▪ Exposure to upstream channel member socialmedia usage enhances the likelihood of usage andpotential communication through social media.

▪ Customers tend to imitate suppliers ‘and retailers’social media usage behaviors.

▪ The very act of engaging in social media usageprovides firms a mechanism through which theycan enhance customer relationships.

▪ Social media usage by retailers demonstrates a significantrelationship with social media usage amongst customers.

Social media

▪ Tests for moderation indicate that the social medialinkage across channel levels is affected by the differentbehaviors and characteristics of the supplier or retailer.

▪ In and of itself, social media is not a panacea. If littlerelationship capital is possessed, the likelihood ofcustomer imitation diminishes greatly.

▪ Firms with preexisting strong customer relationshipshave an opportunity to further strengthen these relationships.To the contrary, firms with weaker customer relationshipswill not realize the same benefits.

▪ The social media usage linkage is affected by themultiple components of relationship developmentin different ways.

▪ Firms must understand the varying dimensions of theircustomer relationships and how these dimensions mayaffect social media usage amongst customers.

▪ Brand reputation positively moderates the socialmedia usage linkage across channel levels.

▪ Reputable brands provide retailers a more desirableassortment and simultaneously enhance the retailer’s image.Reputable brands also provide consumers a mechanismthrough which they can enhance their self-image.

▪ Firms possessing reputable brands can leverage the brand(and further develop it) through social media, as customers willbe more receptive and more likely to reciprocate the social mediausage given their desire to be associated with the brand.

Service ambidexterity positively moderates thesocial media usage linkage across channel levels.

▪ Retailers and final consumers are more apt to imitatesocial media usage behaviors when upstream firms areable to simultaneously balance a service and sales focus.

▪ Firms must balance their social media foci between increasing salesand more general relationship-building (through service) to avoidbeing seen as opportunistic in their social media usage behaviors.

Customer contact frequency directly influences socialmedia usage behaviors between suppliers and retailers.

▪ From the supplier perspective, it is important salesmanagers be cognizant of what their individual salespeopleare doing to leverage social media.

▪ Retailers must also be conscious of the other channelsthrough which consumers are being communicated withto ensure an appropriate overall level of communications.

▪ Other forms of involvement should be examined in futurestudies of this sort (e.g., customer involvement in aloyalty program, relationship length, etc.).

Relationship marketing Given the interactive effects and social media usage,social media is best leveraged by firms with strongcustomer relationships. These firms are able to use socialmedia as a reinforcing mechanism through whichrelationships can be made even stronger.

▪ Consumer social media usage enhancesconsumer loyalty.

▪ Retailer social media usage directly affects brandand retailer performance even when controlling for theeffects of enhanced consumer loyalty to the retailer.

▪ Retailer social media usage has a direct effect onretailer performance and supplier brand performance.

▪ Aside from stronger customer relationships, social mediausage affects performance in other ways to be exploredin future research.

▪ Consumer loyalty to the retailer positively affectsretailer and supplier brand performance.

▪ The trickle-down benefits suppliers accrue when leveragingsocial media come from (1) their direct relationshipswith retailers, and the fact that (2) these retailers are, in turn,more apt to leverage social media with their consumers.


to enhance their self-image (Shrauger 1975). Here we showthat consumers are more apt to engage in activities that astrong brand undertakes. In the case of retailers, the effect iseven more pronounced to the extent that a weak supplierreputation results in a reduced tendency for the retailer toimitate supplier social media usage. This suggests thatretailers, conscious of protecting their own identities, tendto distance themselves from suppliers whose reputationsthey rate poorly. Thus, only firms with strong and reputablebrands appear to be able to exploit their social media usageto reinforce and strengthen their downstream relationships.

We also reveal that perceived supplier service ambidexter-ity enhances the likelihood of social media use across variouschannel levels. We define ambidextrous activities in terms ofthe supplier’s ability to simultaneously engage in behaviorsthat both exploit existing services and explore ways throughwhich higher levels of customer satisfaction can be attained.When firms are better able to service and satisfy their cus-tomers, the linkage between social media usage across chan-nel levels grows stronger. Previous research has identifiedimportant firm outcomes associated with service quality per-ceptions and satisfaction (e.g., Fornell et al. 1996), but few, ifany, studies have examined their roles in a social media usagecontext. Our finding that service ambidexterity can inducedesirable behaviors is also consistent with the appraisal–emo-tional response–coping framework offered by Bagozzi(1992), which holds that cognitively oriented appraisals in-fluence customers’ behaviors through their attitudes. Similarto our reputation findings, low service ambidexterity createsconditions that not only suppress contagion effects betweensupplier and retailer but reverse them such that the retailer isless prone to imitate supplier behavior.

Surprisingly, our findings do not support the moderatingeffect of customer interaction on the transfer of social mediausage behaviors across channel levels. In their recent study,Godfrey et al. (2011) find that greater communication acrossmultiple channels can have an adverse effect on existingrelationships, because customers come to view the communi-cation as invasive. The authors therefore identify an “idealpoint” beyond which positive repurchase intentions turn, be-cause feelings of positive reciprocity become negative reac-tance. Although this quadratic effect was not identified in ourresearch via a post hoc analysis, communication levels shouldbe monitored closely across multiple channels, to ensure thatthe firm is communicating at an appropriate level. It could bethat high levels of interpersonal contact to some extent miti-gate the need for alternative or supplementary forms of contactvia social media. Also, as the interaction assessment is repre-sentative of the manager’s interaction with customers and notthe frontline salesperson, it is possible that we are not captur-ing the true form of the relationship.

Our multilevel examination of contagion and social influ-ence effects yielded interesting results from a comprehensive

dataset. However, we collected the supplier data from a singlefirm reflecting an industry whose products likely constitutehigh-involvement purchases for some consumers. Higher in-volvement may increase their propensity to engage withretailers and suppliers via social media. Further researchshould examine social media usage in industries involvingconvenience items or low involvement purchases. Also, al-though a single firm approach limits generalizability, it doespermit us to control for extraneous factors such as productportfolio.

It is also important to consider that there could be areverse causal sequence present within our research or afeedback loop which is occurring. Because social media isbecoming more of a platform for two-way communication,co-creation of value could be occurring where both firms’use is driving customer use and vice-versa. It is also possiblethat increased social media usage promotes loyalty whichdrives additional social media use. Although an instrumentalvariable analysis suggests that this reverse causality is notoccurring, we encourage future researchers to undertakelongitudinal and/or experimental research designs to inves-tigate these questions further.

Relationship marketing

We also have moved beyond the effects of social mediausage on other actors’ usage to examine potential outcomesof such usage by both retailers and consumers. In particular,we uncover the positive effect of consumers’ social mediausage on retailer loyalty. Social media applications enablefirms to provide real-time updates and information on prod-ucts and promotions, which provides advertising for the firmbut also helps maintain top-of-mind awareness of the retaileror firm and can lead to greater loyalty. Through socialmedia, people also can interact with each other and acrossthe supply chain. Such sociability makes social media seemlike an immediate extension of the retail or supplier firm.Accordingly, as perceived sociability and online interactionsincrease, it is logical to suggest that loyalty increases too.

Yet the effect of social media usage at the consumer levelextends even beyond retailer loyalty. We discover a signif-icant effect on brand and store performance. The contagioneffects of social media usage underscore the importance ofusage across levels; our findings also demonstrate the valuein the same level of the supply chain. Retailers that employsocial media appear to be making substantial performancestrides, which is an important result, considering that in2009, almost 65% of marketers stated that their organiza-tions used social media, and the rate was expected to grow(VanBoskirk et al. 2009). With so many firms engaging inthis strategy, it is important to understand its performanceimplications, which provide widespread opportunities forfurther investigations of these relationships.


Managerial implications

The marketing environment is changing so dramatically thattraditional marketing methods are not enough. Collaborativecommunication is critical to the success of interfirm rela-tionships, and communication quality (e.g., accuracy, time-liness, adequacy, credibility) is paramount for goalachievement in a B2B partnership (Mohr et al. 1996). Ascustomers experience increasingly varied communicationchannels, communication is becoming fragmented and lesscredible. Social media offers supplier–retailer partners anopportunity to connect and communicate quickly and effec-tively. It also supports interactions with the brand and in-dustry. This multilevel promotion of the supplier, brand, andcompetitive environment provides a more engaging rela-tionship for suppliers and retailers. The use of social mediais no longer just for consumers; it is as important in the B2Bcontext as it is in the B2C context.

From a supplier perspective, it is important to understandthe impact of social media on developing relationships withcustomers, as well as promoting the supplier brand through-out the supply chain. Suppliers that use social media topromote the brand and communicate with retailers encour-age social media usage at the retailer level, which has apositive impact on retail performance and on brand perfor-mance. Buyer–supplier relationships focused on goal simi-larity and long-term orientation can both benefit fromenhanced performance when the symmetry of social mediausage between channel partners increases.

For the retailer, social media provides simultaneous com-munication with supplier partners and consumers.Therefore, the retailer can provide consumers with moreup-to-date information, the moment it is transmitted fromthe supplier. The more the consumer interacts with theretailer, the more loyal the consumer is to the retailer andthe brand, which in turn yields positive performance resultsfor both the retailer and the brand.

The social influence–based moderating effects also yieldinteresting insights for both suppliers and retailers. Wehighlight the importance of reputation at both the brandand retailer level, because it strongly affects social mediausage throughout the supply chain. The more favorable thebrand reputation, the more likely it is the downstream coun-terpart will engage in a socially mediated conversation.Managers must therefore be mindful of brand equity whensetting ROI projections for a social media campaign.

The triadic data we leverage in this research provide astrong applied illustration of the practical implications ofour model. We contacted the sponsoring organization inorder to develop an indication of the precise dollar magni-tude of the effects observed in the current study. Based onthe information provided, we were able to extrapolate theactual dollar effects of social media adoption. By examining

the amount of variance which is accounted for solely bysocial media usage, we see that nearly 7% of the variance inretail store performance is accounted for and slightly over5% for the brand performance. This translates to roughly$82,000 annually per store and $3,000 annually in brandsales per store. These estimates do not include the indirecteffects or interactive effects of social media or the effects ofretailer loyalty on performance, thus providing us with themost conservative estimate. Based on the population of 304retail stores, social media could have an influence upwardsof $25 million dollars which reflects substantive bottom-lineconsequences.

Our study also highlights the importance of service am-bidexterity in multiple supply chain relationships. To remaincompetitive, firms should capitalize on current resources butconstantly survey the environment for new opportunities.The more ambidextrous firms are, the more they use socialmedia for both exploration and exploitation. The better bothsuppliers and retailers are at cultivating ambidexterity, themore powerful social media becomes as a communicationand promotion tool. Although this research is not exhaustivein examining all of the potential linear and moderatingfactors that could be at play within this framework, webelieve that this research provides a robust starting pointfor future investigation.

Appendix

Service ambidexterity (Yu et al. 2010)

In our branch, we talk to accounts to gain new ideas on howto merchandise products.

In our branch, we increase the level of service quality deliveredto customers.

In our branch, we constantly survey existing customers’satisfaction.

In our branch, we take pleasure in explaining what new productlines are available.

Customer contact -percentage measure

What percentage of your work time do you spend in directcontact with your accounts?

Supplier brand reputation (Veloutsou and Moutinho 2009)

This brand is trustworthy.This brand is reputable.This brand makes honest claims.This brand has a long lasting nature.In the past, today, and in the future, the values behind this

brand will not change.


Consumer-retailer loyalty (Palmatier et al. 2007)

For my next purchase, I will consider this retailer firm as myfirst choice.

I will do more business with this retailer in the next fewyears than I do right now.

All else being equal, I plan to buy from this retailer in thefuture.

I say positive things about this retailer to my coworkers.I would recommend this retailer to someone seeking my

advice.I encourage friends and coworkers to do business with this

retailer.

Social media - customer

My relationship with the brand is enhanced by social media.I use social media to monitor other runners in the community.I use social media to follow sales and promotions.I use social media to monitor events.People use social media to reach me.I use social media to improve my relationship with different

brands.I use social media to keep current on events and trends in the

sport.I use social media to communicate with retailers.I use social media to improve my relationship with retailers.My relationship with my retail store is enhanced by social

media.

Retailer reputation (Veloutsou and Moutinho 2009)

This store is trustworthy.This store is reputable.This store makes honest claims.This store has a long lasting natureIn the past, today, and in the future, the values behind this

store will not change.

Social media - retailer

My relationship with my sales reps is enhanced by socialmedia.

My relationship with my supplier firms is enhanced withsocial media.

I use social media to compare my relationship with my salesreps to other relationships they have with customers.

I use social media to monitor event performance and visibility.I use Twitter to communicate with current customers.I use social media to monitor competitors.I use Twitter to target new customers.I use Facebook to target new customers.I use Facebook to communicate with current customers.

I use social media to keep current on events and trends in myindustry.

I engage in social media co-op promotions with suppliers.Our customers use social media to see our current specials

and promotions.I work with suppliers who support social media promotions.

Social media - supplier

My relationship with my accounts is enhanced by socialmedia.

I enhance my customer relationships through social media.I provide my customers information regarding specials and

new products using social media.I use social media to provide my customers information on

events and trends in the sport.I use social media to monitor event performance and visibility.I am friends with many of my accounts on my personal

social media accounts.I use social media to monitor competitors.I engage in social media co-op promotions with suppliers.I work with buyers who support social media promotions.Our customers use social media to see our current specials

and promotions.I compare my relationship with my accounts to other rela-

tionships they have with other accounts online.I use social media to keep current on events and trends in the

sport.I am very conscientious about what is posted on my social

media accounts.

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