The effect of web communities onconsumers’ initial trust in B2C

e-commerce websitesMalaika Brengman

Department of Business, Vrije Universiteit Brussel, Brussels, Belgium, and

Farhod P. KarimovDepartment of Business, Westminster International University in Tashkent,

Tashkent, Uzbekistan

Abstract

Purpose – The purpose of this paper is to test the effectiveness of the mere integration of socialnetwork applications to provide a signal concerning the “trustworthiness” of an unfamiliar e-vendor inorder to enhance subsequent purchase intentions.

Design/methodology/approach – To investigate the impact of web communities on consumers’initial trust beliefs (i.e. ability, benevolence and integrity), a 2 £ 3 between-subjects full factorial onlineexperiment was carried out, using a fictitious web site for a gift gadgets selling company, manipulatingit for inclusion or exclusion of a “social networking site”, and for inclusion or exclusion of “a corporateblog (text only blog, photo and text blog, or no blog)”. Data were obtained from 226 online shoppers.

Findings – Although the authors could not reveal any effects of the integration of social networkapplications on “ability” beliefs, it was possible to demonstrate their capacity to “signal” “benevolence”and “integrity”, which in turn have a significant impact on purchase intentions. Unfamiliar e-retailersmay foster perceptions of “integrity” by utilizing text-blogs into their web sites, but they should avoidembedding facial photos of shop representatives in the blog. If e-retailers want to make use of“a corporate blog with facial photo”, it is recommended to combine it with the integration of a socialnetworking site such as Facebook in order to boost perceptions of “benevolence”.

Research limitations/implications – The simple integration of “social network applications” canaffect “initial trust beliefs” towards unfamiliar e-tailers and subsequent “purchase intentions”, but itappears essential to utilize just the right cue combination in order to obtain the desired effect.The effectiveness of integrating a social network application may vary according to the type and mayaffect different trust beliefs (benevolence, integrity).

Originality/value – An important issue in e-commerce remains how trust is developed betweenconsumers and e-retailers. This paper investigates the use of different web communities and theinfluence of their integration in the commercial web site on consumers’ initial trust beliefs in the onlineenvironment. The findings will help business managers to understand how social media should beused to lead to optimal results.

Keywords Electronic commerce, Consumer behaviour, Trust, Social media, Internet, Initial online trust,Social networks, Corporate blog, B2C e-commerce

Paper type Research paper

1. IntroductionThe internet is an inherently risky environment due to the absence of personalcontact, the impossibility of physical product evaluation, and the lack of solid

The current issue and full text archive of this journal is available at

www.emeraldinsight.com/2040-8269.htm

The authors would like to thank Kelly Dehaen, Master student at the Vrije Universiteit Brusselwho devoted her Master thesis to this subject, for her help in the data collection.

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Management Research ReviewVol. 35 No. 9, 2012

pp. 791-817q Emerald Group Publishing Limited

2040-8269DOI 10.1108/01409171211256569

transaction protections. The absence of physical contact while shopping online makesthe issue of trust more imperative on the web than in the real world. As a result, themajority of thriving e-retailers try to increase consumer trust by utilizing differentkinds of social media applications, such as Facebook, YouTube, Twitter, and corporateblogs, which support two-way interactions between online shoppers, thus enhancingthe feeling of social presence (Karimov and Brengman, 2011). The effective use of socialmedia marketing tools to generate traffic and to boost sales volume has become the topagenda for e-retailers (Kaplan and Haenlein, 2010). Hence, many e-retailers seek newways in which they can make profitable use of social media marketing applications.

Nevertheless, several issues remain unexplored. Despite the fact that a large numberof e-retailers try to integrate social networking sites (SNSs) in their e-stores,experiment-based studies investigating the effectiveness of social media cues in ane-commerce setting remain limited. More and more e-retailers are involved in creatingcorporate blogs in order to generate traffic and to ease consumers’ online shopping.Dell Inc., for example, hires bloggers to create blogs on their web sites so that the onlinecompany can address any issue raised by consumers (Spaulding, 2010). However,studies investigating the effectiveness of such social network applications are in shortsupply. In this paper, we aim to fill this gap by studying online consumers’ affective andcognitive responses with respect to online social media cues. Specifically, the integrationof web communities such as SNSs and corporate blogs into e-tail web sites is proposed toinfluence cognitive and affective aspects of online trust towards unfamiliar e-commercevendors. Our findings demonstrate that, while the integration of such social networkapplications can be effective in enhancing different aspects of initial online trust, theiruse requires a gestalt approach in order to be effective.

This paper is structured as follows. First, we introduce the concept of initialonline trust, which is of primordial importance for unfamiliar e-retailers. Subsequently,we provide a theoretical foundation, based on cue signaling theories, elucidating theimpact of the integration in the web site of social network applications on initial trustformation and subsequent purchase intentions. This will lead us to our research modeland hypotheses. Next, we describe the research methodology and data collectionprocedure. Consecutively, analyses and results are presented, followed by a discussionand conclusions. Finally, we do acknowledge some limitations and provide somesuggestions for further research.

2. Initial online trustTrust is important in an e-commerce context because it mitigates perceptions ofuncertainty, decreases perceived risk and positively affects purchase intentions(Chang and Chen, 2008; Pavlou and Gefen, 2004; Pavlou and Fygenson, 2006). In ane-commerce setting, certain cues such as company reputation information (Jin et al.,2008) or an offline parent brand (Horppu et al., 2008) may help consumers to base theirtrust in an online retailer. However, such information may not be available to consumerswhen they deal with “unfamiliar” e-vendors. In this context, the concept of “initial trust”becomes of paramount importance. It forms during the very first interaction with anunfamiliar e-retailer, based on initial impressions of its web site characteristics (Wu et al.,2010). In this paper we focus on initial trust and define it as “trust in an unfamiliartrustee, a relationship in which the actors do not yet have credible, meaningfulinformation about, or affective bonds with, each other” (McKnight et al., 2002, p. 335).

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Initial trust is composed of beliefs dealing with the “ability” (i.e. competence, expertness,and dynamism), “benevolence” (i.e. goodwill, responsiveness), and “integrity”(i.e. honesty, credibility, morality, reliability) of the unfamiliar trustee (Gefen andStraub, 2004; McKnight et al., 1998). Underneath, we provide a more in-depth elucidationof these trust dimensions.

According to the e-commerce trust literature, “ability” represents the competitivepower of the seller in a specific field. An online consumer’s perception of a firm’s “ability”is based on two related beliefs regarding the e-retailer’s competence (expertise or skills)to perform the intended behavior and its access to the necessary knowledge to performthe behavior appropriately (Bhattacherjee, 2002). More specifically, “ability” is theconsumer’s belief about the competence, skills, and knowledge of the e-retailer to providegood quality products and services (Gefen, 2002). The beliefs about the ability of anonline retailer may increase consumer’s intentions to purchase from the web site(Gefen and Straub, 2004; Schlosser et al., 2006). Online retailers may “signal” their abilityto consumers by publishing metrics on their web sites such as number of customers,items sold, and other transactional information (Bhattacherjee, 2002).

“Benevolence” denotes that the seller will not behave opportunistically and will treatthe buyer benevolently. It is defined as “the buyer’s belief that a seller has beneficialmotives, is genuinely concerned about the buyer’s interests, and will act in a goodwillmanner beyond short-term profit expectations” (Pavlou and Dimoka, 2006, p. 395). Thiskind of belief is especially important for online shopping because in such interactions thedegree of consumer vulnerability is higher as it is possible that an online vendor may notfulfill the expected side of the contract (Gefen, 2002; Schlosser et al., 2006). In order toboost perceptions of benevolence, online retailers may use different features in their website such as online recommendation agents, seller-provided task-facilitating interactiveinformational tools (i.e. filter systems and buying guides), or set strong privacy policiesto “signal” their benevolent intentions (Gupta et al., 2009; Lauer and Deng, 2007; Wangand Benbasat, 2007).

“Integrity” implies that the seller will adhere to a set of rules of exchange and willtreat the buyer honestly during and after the exchange. It is defined as “the buyer’sbelief that a seller is competent and reliable and will fulfill the transaction’s contractualrequirements” (Pavlou and Dimoka, 2006, p. 395). The integrity belief involves honesty,fairness, credibility, consistency, predictability, reliability, and dependability(Bhattacherjee, 2002). The specific conditions of integrity are context-dependent andmany aspects of it, such as obeying to the rules and fulfilling promises are obviouslyimportant in an e-commerce context (Gefen, 2002). Several scholars empirically confirmthat e-retailers may boost consumers’ integrity perceptions by providing strongprivacy policies, and online recommendation agents with tradeoff explanations ontheir web sites (Lauer and Deng, 2007; Wang and Benbasat, 2007).

These three trust beliefs tap into both the “cognitive” and the “affective” dimensionsof trust (Bhattacherjee, 2002; Gefen, 2002). Several authors have designated “ability” and“integrity” to “cognitive trust” and “benevolence” to “affective trust” (Dabholkar et al.,2009; Komiak and Benbasat, 2006; McAllister, 1995; Pavlou and Dimoka, 2006).“Cognitive” or “cognition-based trust” is defined as a consumer’s rational expectationthat an online vendor will have the necessary attributes to be relied upon (Komiak andBenbasat, 2004). The concept of cognitive trust is derived from the theoreticalperspective to view trust as a trustor’s rational choice that is motivated by the conscious

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calculation of advantages (Komiak and Benbasat, 2006). “Cognition-based trust” evolvesfrom a pattern of careful rational thinking, while “affect-based trust” (also called“emotional trust”) develops from one’s instincts, intuition, or feelings concerningwhether an individual, group or organization is trustworthy (Morrow et al., 2004). Thus,“cognitive trust” reflects the customer’s confidence that an e-retailer is honest, accurate,and dependable, and keeps promises, whereas “affective trust” is the conviction thatthe e-retailer has genuine concern for the customer’s welfare, and is caring andsupportive (Dabholkar et al., 2009, p. 149).

The reason for this conceptualization of trust is that both cognitive processes andaffective influences may play a role in the formation of trust (Hui, 2011; Morrow et al.,2004). Collectively, they provide the basis for trust-related decision making regarding avendor and many of the other trust dimensions proposed in the literature can bereconciled within these two encompassing trust dimensions (Bhattacherjee, 2002;Fuller et al., 2007). Although distinguishing between affective and cognitive trust isoften done in explaining the concept of trust, findings from neuroscience indicate that aclear difference between them can hardly be maintained (Riegelsberger et al., 2005).Thus, cognitive trust and affective trust can exist at the same time for the sameperson(s) towards the same object (Corritore et al., 2003). In this paper, we considerboth cognitive and affective trust dimensions.

3. Theoretical background and research modelTo investigate the impact of the integration of social network applications in a virtual storeon initial trust formation, we propose a model based on the stimulus-organism-response(S-O-R) paradigm shown in Figure 1. The S-O-R paradigm suggests that certainatmospheric elements of the web site (S) may influence an individual’s affective andcognitive states (O) that mediate his/her approach (avoidance) responses (R) during onlineshopping (Eroglu et al., 2001, 2003). In the context of online retailing, the stimulus (S) isdefined as “the total sum of all the cues that are visible and audible to the online shopper”(Eroglu et al., 2001, p. 179).

3.1 Cue signaling theories“Cue signaling theories” such as the “cue utilization theory” (Olson and Jacoby, 1972)and the “cue consistency theory” (Maheswaran and Chaiken, 1991) may provide auseful framework to understand how these web site atmospheric cues can be used

Figure 1.Research framework Covariate: Trust propensity

OrganismStimulus

Web Communities

Social Network SiteFACEBOOK

CorporateBLOG

Trust Beliefs

Cognitive trustAbility

Integrity

Affective trustBenevolence

Response

Approach/Avoidance

Purchase intention

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to stimulate consumers’ affective and cognitive trust perceptions towards unfamiliarvendors. Prior research has used these theories to examine the impact of extrinsic cueson consumers’ perceptions of product quality (Miyazaki et al., 2005), the trustworthinessof web seals (Hu et al., 2010), and the effect of online social media cues on initial trust(Aldiri et al., 2008). In this paper, we intend to investigate whether integrating socialmedia cues into the e-tail site may provide a signal regarding the trustworthiness of anonline vendor, which, in turn, may affect consumers’ purchase intentions. Therefore, weuse these theories as a foundation to develop our hypotheses.

The “cue utilization theory” suggests that a product sends out a series of intrinsic andextrinsic cues signaling its quality to consumers (Olson and Jacoby, 1972). “Intrinsiccues” are product-related attributes, such as ingredients, that cannot be manipulatedwithout also altering the physical properties of the product. Conversely, “extrinsic cues”are product-related attributes which are not part of the physical product, such as price,brand name, and packaging (Richardson et al., 1994). On the internet, the absence ofphysical proximity prevents consumers to check the intrinsic attributes of products withtheir senses. As a result, they rely more on extrinsic cues to assess the trustworthiness ofthe online vendor (Hu et al., 2010). These extrinsic cues may encompass brand image,customer reviews, third party endorsements, embedded social presence, and so on(Karimov et al., 2011). In our study, the presence of web communities will serve asextrinsic cues signaling the trustworthiness of an online vendor. We will have a closerlook at the “diagnosticity” (i.e. the capacity to signal e-vendor trustworthiness) of twodifferent kinds of social network applications.

The “cue consistency theory” proposes furthermore that multiple sources ofinformation that corroborate one another are more useful than if they offer incongruentmessages (Maheswaran and Chaiken, 1991). That is, extrinsic cues are significantlymore predictive of quality when they are consistent as opposed to when they presentinconsistent information (Miyazaki et al., 2005). An online vendor can utilize multipleweb site atmospheric cues such as colors, graphics, layout, navigation aids, animation,music and sounds, entertainment, pictures, and site awards to increase the hedonic orexperiential value of shopping, to provide information about its quality, and to influenceonline shoppers’ responses (Eroglu et al., 2003). In our study, we apply the “cueconsistency theory” to provide some insight into how multiple social media cues worktogether in generating consumers’ online initial trust.

3.2 Signaling and building trustworthinessTrust is typically “built” gradually through ongoing social interactions (Luhmann,1979). The lack of social contact with store employees is still one of the main factorsholding back consumers to purchase online (Lowry et al., 2010). However, this does notmean that social presence cannot be achieved in online interactions. In a web interface,social interactions go beyond normal relationships in which a medium facilitates asense of understanding, connection, involvement, and interaction among participantsin stimulating online shoppers’ internal affective and cognitive states (Kumar andBenbasat, 2002). Transmitting a sense of social presence by either direct or indirectpersonal, sociable, and sensitive human contact via the web interface can triggerconsumers’ trust beliefs which in turn positively influence their purchase intentions(Gefen and Straub, 2003; Gefen and Straub, 2004).

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The e-commerce literature suggests that higher levels of social presence can beachieved by embedding social cues such as human images (Cyr et al., 2009), videostreams (Aljukhadar et al., 2010), avatars (Qiu and Benbasat, 2009), and text-to-speechvoice technologies (Qiu and Benbasat, 2005) into the e-tail interface “signaling” thetrustworthiness of an online vendor. Many e-retailers are involved in integrating socialmedia applications that support synchronous and asynchronous communication such asblogging, podcasting, and instant messaging into their e-tail interfaces (Badawy, 2009).These kinds of new media tools enable individuals to have interpersonal interactions witheach other as an online alternative to “face-to-face” social interactions (Papacharissi, 2009).Consequently, the perception of a high degree of social presence during the virtualinteraction contributes to the formation of trust (Gefen and Straub, 2004).

3.3 Trust propensityOf course there are many factors affecting consumers’ trust. One of the importantfactors that particularly have a significant influence in forming new relationships is aperson’s general tendency to trust or distrust others. This tendency is referred to astrust propensity (also called trust disposition). Trust propensity is a psychological traitthat is formed from early childhood and develops throughout the life period dependingon an individual’s socio-cultural background, developmental experiences, and his orher personality traits (Mayer et al., 1995). Trust propensity is defined as “the extent towhich a person displays a tendency to be willing to depend on others across a broadspectrum of situations and persons” (McKnight et al., 2002, p. 339). Internet retailerscannot influence an individual’s trust propensity by applying specific trust buildingstrategies (Corritore et al., 2003; Leimeister et al., 2005). In an e-commerce setting, thefindings regarding the effect of trust propensity on online trust are contradictory.While some studies confirm the positive influence of trust propensity on consumers’initial trust in a web retailer (Chen and Barnes, 2007), others find that it is not animportant predictor of online trust (Lowry et al., 2008). Since trust propensity has beenargued to be an antecedent of trust in new relationships (Gefen and Straub, 2004), wefeel trust propensity needs to be included in an empirical model at least as a controlvariable. Therefore, we include trust propensity as a covariate and expect that itgenerates a direct effect on consumers’ trust beliefs regarding an unfamiliar e-retailer.

3.4 The mediating role of the online vendor’s perceived trustworthinessPrior e-commerce researchers have found that both cognitive and affective appraisals ofthe web environment have a strong influence on consumers’ purchase decisions(Dabholkar et al., 2009; Lee and Kozar, 2009). The commitment-trust theory of relationshipmarketing suggests that trust is a key mediating variable between its determining factorsand behavioral outcomes (Morgan and Hunt, 1994). Increased trust leads to a favorableattitude towards online shopping as well as positively affects consumers’ purchaseintentions (Lim et al., 2006; Pavlou and Fygenson, 2006). Past research suggests thatonline trust beliefs are important mediators between web site atmospheric cues andconsumers’ purchase intentions (Benedicktus et al., 2010; Schlosser et al., 2006).

4. Research objectives and hypothesesThe objective of this study is to investigate whether the mere integration of webcommunities, such as an SNS and/or a corporate blog in the e-tail interface can

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affect consumers’ initial trust towards an unfamiliar e-vendor and subsequent purchaseintentions. As new and unknown e-retailers will have a hard time conveying theirtrustworthiness to potential online shoppers, we wonder whether integrating socialnetwork applications in their web sites can “signal” their trustworthiness during a firstinteraction with the web site. While building trust in a relationship obviously takes time,conveying “initial trust” during a first encounter is of paramount importance for lessfamiliar e-retailers. In this study we make the distinction between SNSs and corporateblogs as we believe that these two social network applications may influence consumers’initial trust differently, because user generated reviews on SNSs can be perceived asmore objective as compared to corporate blog posts and may thus provide a more“diagnostic” (or stronger) signal of trustworthiness. Moreover, we are interested to seewhether the use of multiple social media cues interact with each other in engenderingperceptions of trustworthiness. In the following sections the social network applicationsfocused upon in this study are defined and our hypotheses concerning their effects oninitial online trust and subsequent purchase intentions are generated.

4.1 Social network applicationsA “SNS” is defined as a:

[. . .] web-based service that allows individuals (1) to construct a public or semi-public profilewithin a bounded system (2) to compile a list of other users with whom they share aconnection, and (3) to view and traverse their list of connections and those made by otherswithin the system (Boyd and Ellison, 2008, p. 211).

Diverse types of online social networks exist. These online networks can be used forversatile reasons such as information sharing, video sharing, photo sharing, chatting,tagging, dating, gaming, and blogging (Hoadley et al., 2010). The best examples ofpopular SNSs are Facebook, MySpace, Twitter and YouTube that allow user contentcreation, such as personal profiles, interests and contact information, photos, videos,and other messages posted by friends (Rosen et al., 2011). People participate in virtualsocial networks because of their personal, social and hedonic benefits (Lievens andMahr, 2010). Maintaining existing relationships, keeping in touch with people, learningfriends’ updates, showing personal information, finding people with similar interests,finding dates, and meeting new people are rated as the most useful features of SNSs(Hoadley et al., 2010).

A “blog” is another popular type of social networking application that can come in amultitude of different variations. A “blog” can be defined as a virtual communitywhere an organization or an individual publishes and manages content in aninteractive format to attain its goals (Lee et al., 2006). The blogosphere may containtext-based blog entries and profiles, pictures and multimedia resources (Li and Chen,2009). Visitors use such virtual communities to maintain and expand their network ofrelationships, and to satisfy their needs for personal fulfillment, social exchange, andentertainment (Lievens and Mahr, 2010). Nowadays, about one third of top onlineretailers attempt to address these needs by maintaining “corporate blogs” in order tocommunicate with their customers and to provide support to ease their shoppingdecisions (Karimov and Brengman, 2011). Dell Inc., for example, has been successful inshifting part of its product support to online communities by creating support blogs toanswer questions and solve issues (Spaulding, 2010).

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4.2 Signaling trustworthiness by integrating social network applicationsSince it is impossible to examine the intrinsic attributes of products in avirtual environment, online consumers may seek unbiased supportive information inpurchasing more technically complicated or less familiar (niche) products. In thisrespect, online product reviews have become a major information source for consumersregarding product quality (Hu et al., 2008). SNSs, for example, promote the vision of ahuman-centric web, where the network of people and their interests are the primarysource of information (Pallis et al., 2011). Information shared within SNSs is likely tohave a high credibility, since it is expected to lack a commercial nature. These kinds ofseemingly unbiased opinions or recommendations, shared between online shoppers,can ease their shopping decisions. Guo et al. (2011) investigated Taobao, a Chineseconsumer marketplace, which is the world’s largest e-commerce web site. Their findingsdemonstrate that communication between buyers is a fundamental driver of purchasingactivity from the commercial site. Hsiao et al. (2010) also empirically confirm that socialnetwork related factors such as the expertise of a recommender in the social networkmay increase consumer trust in an e-retailer.

The blog platform also facilitates a very high level of interpersonal interactionthat allows users to express their opinions, to make friends, and to exchange information(Schau and Gilly, 2003). It enables users to share feelings, emotions, experiences, and placetrust in others by creating mutual bonds within their social circles (Nambisan and Baron,2007). Although communication takes place in virtual worlds by chance, due to similarityin emotions and experiences in life, users feel harmony in terms of opinions and actions,which strengthens communication and creates positive perceptions of experiential value,which in turn positively impact their perceptions and attitudes (Keng and Ting, 2009).Since blogs provide the possibility of interaction with others by adding reflectionsand comments, the integration of blogs into an e-commerce interface can be considered asan effective mechanism that fosters a high level of social presence in the virtual world.

In the virtue of this discussion, we can conclude that the presence of socialnetwork applications in a web interface may allow users to experience others as beingpsychologically present in the virtual environment. Hence, according to the “cue utilizationtheory”, we can presume that integrating social cues that promote social presence in ane-commerce interface may enhance consumers’ initial online trust. Specifically, we proposethat the integration of web communities such as SNSs and corporate blogs into the e-tailinterface can provide a “signal” regarding the trustworthiness of unfamiliar e-commercevendors. Based on the “cue consistency theory”, we also presume that integrating multipleextrinsic social cues, such as “an SNS” along with “a corporate blog”, will have a cumulativeeffect on consumer’s initial trust beliefs. Thus, we put forward the following hypotheses:

H1. The integration of an SNS in an e-commerce interface will increase consumer’sinitial trust beliefs (a. ability; b. benevolence; c. integrity) towards anunfamiliar e-retailer.

H2. The integration of a corporate blog in an e-commerce interface will increaseconsumer’s initial trust beliefs (a. ability; b. benevolence; c. integrity) towardsan unfamiliar e-retailer.

H3. The integration of an SNS along with a corporate blog will have a cumulativeeffect on consumer’s initial trust beliefs (a. ability; b. benevolence; c. integrity)towards an unfamiliar e-retailer.

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H4. Trust beliefs (a. ability; b. benevolence; c. integrity) mediate the relationshipbetween social media applications and consumers’ purchase intentions froman unfamiliar e-tail web site.

5. Methodology5.1 Experimental designAn experiment-based online survey was conducted to validate the proposed researchmodel and to test our hypotheses concerning the impact of web communities onconsumers’ initial trust beliefs (i.e. ability, benevolence, and integrity), and theirsubsequent purchase intentions. For the experimental treatments we set up a 2 £ 3between-subjects full-factorial design, manipulating for:

. inclusion or exclusion of a “SNS” (i.e. Facebook); and

. inclusion or exclusion of “a corporate blog” (“text blog, photo and text blog, or noblog”).

For the experiment we used a “fictitious”, and thus by definition “unfamiliar”, web sitefor a gift gadgets selling company called WebGiftDirect, in order to avoid any potentialbias from previous branding or web-experiences. We outsourced the web site design to aprofessional web-designer in order to create a real functioning e-commerce web site witha professional “look and feel” to simulate a real online shopping experience. Hence, wehave developed six different versions of the web site. One version of the web site did nothave any web community application and the participants who viewed this version arereferred to as the control group. The other five versions served as treatment conditionsand all contained different levels of the above mentioned “web community” applicationsdisplayed prominently on the web sites. To simulate the presence of “an SNS”, weincluded “a Facebook Like Box” in the web site which was linked to our experimentalweb site’s Facebook page. To incorporate “a corporate blog” we have created severalblogs on behalf of a company representative.

5.2 Data collection and subjectsWhat the data collection is concerned, we have sent e-mail invitations to approximately16,000 students from different universities and graduate schools in Belgium, throughthe use of different internal fora, which allow reaching students of different facultiesand years as well as by means of Facebook contacts. Using students as the subject poolfor this internet study was deemed appropriate as they have advanced computer skills,have more internet experience, are heavy internet users, are particularly active in SNSs,and have more positive attitudes towards online shopping than most other populationsegments (Seock and Bailey, 2008; Sorce et al., 2005; Grabner-Krauter and Kaluscha,2003). This resulted in 306 completed records; of which 80 incomplete cases had to beeliminated because a large proportion of the questions remained unanswered, leavinga final dataset of 226 usable records. 50 percent of our respondents belonged to theage group 15-21 and 50 percent were older. The majority of our respondents werefemale (67.3 percent). The demographical distribution of our final sample is provided inTable I. We performed Pearson x 2 tests which confirmed an equal distribution ofrespondents over the experimental conditions what age, gender and educational levelis concerned.

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Six

site

sF

aceb

ook

Cor

por

ate

blo

gT

otal

x2

No

Fac

eboo

kF

aceb

ook

x2

No

blo

gT

ext

blo

gP

hot

ob

log

x2

n(%

)(S

ig.)

n(%

)n

(%)

(Sig

.)n

(%)

n(%

)n

(%)

(Sig

.)

Age

15-2

111

3(5

0.0)

4.33

560

(51.

3)53

(48.

6)0.

159

31(4

2.5)

38(5

0.0)

44(5

7.1)

3.22

922

þ11

3(5

0.0)

(0.502)

57(4

8.7)

56(5

1.4)

(0.790)

42(5

7.5)

38(5

0.0)

33(4

2.9)

(0.199)

Gender

Mal

e74

(32.

7)7.

677

39(3

3.3)

35(3

2.1)

0.03

830

(41.

1)23

(30.

3)21

(27.

3)3.

571

Fem

ale

152

(67.

3)(0.175)

78(6

6.7)

74(6

7.9)

(0.888)

43(5

8.9)

53(6

9.7)

56(7

2.7)

(0.168)

Education

,H

igh

sch

ool

60(2

6.5)

31(2

6.5)

29(2

6.6)

15(2

0.5)

27(3

5.5)

18(2

3.4)

Un

der

gra

du

ate

92(4

0.7)

7.71

952

(44.

4)40

(36.

7)1.

837

34(4

6.6)

26(3

4.2)

32(4

1.6)

5.27

8G

rad

uat

e.

74(3

2.7)

(0.656)

34(2

9.1)

40(3

6.7)

(0.399)

24(3

2.9)

23(3

0.3)

27(3

5.1)

(0.260)

Tot

al22

6(1

00)

117

(51.

8)10

9(4

8.2)

73(3

2.3)

76(3

3.6)

77(3

4.1)

Notes:

Pea

rson

x2:

com

pu

ted

for

2£

2ta

ble

s;p-

val

ues

are

rep

orte

din

par

enth

eses

Table I.Sample demographics

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5.3 Task and procedureSubjects were given the task of purchasing a birthday gift for a friend(see “experimental task”). There are two reasons for choosing to sell gift gadgets inour experimental web sites. First, while gift gadgets are socially and emotionallyloaded products, the monetary risk involved in such products is rather low. Second,using different unbranded gadgets ensured to avoid any possible brand relatedconfounding effects. The purpose of using unbranded products was to eliminate theeffect of brand equity on initial trust formation (Lowry et al., 2008). Therefore, wecarefully selected different types of gift gadgets both relevant for men and women andensured the products shown on the web site did not possess any brand relatedinformation.

The experiment was conducted entirely online and subjects could complete the studyfrom any computer with an internet connection, thus increasing the online shopping taskrealism. The online questionnaire was created through the use of a free online service“http://thesistools.com/”. The e-mail invitation contained a link to the survey and byclicking on this link subjects were automatically randomly assigned to one of the sixversions of the survey. The shopping task was presented at the beginning of thequestionnaire. Subsequently, subjects had to click on a link to the designated web site,which they had to browse first before continuing with the questionnaire. Subjects couldexplore the designated version of WebGiftDirect.com for as long as they wanted,imagining themselves in a buying situation in which they were interested in purchasinga gift for a friend. After examining the web site contents, subjects could easily beredirected to the survey by clicking on the link provided within the experimental sites.

Experimental task:

Welcome to WebGiftDirect! WebGiftDirect is a new online gift store, offering a wide range ofgifts. Please thoroughly explore the web site in order to become familiar with its contents andchoose the gift that you are most likely to buy for your best friend’s upcoming birthday party.Imagine that you don’t have enough time to go to the offline-store and that WebGiftDirect isthe first site you visit online in order to choose an appropriate gift. After finishing shopping,please click on the “Proceed to Survey” button to complete the questionnaire.

5.4 MeasuresAll measurement items pertained to seven-point Likert-type scales, and were adoptedfrom recent relevant literature, where they have repeatedly been shown to exhibitstrong content validity (Appendix Table AI). The questionnaire measured trust beliefs“ability”, “benevolence”, and “integrity” by means of items taken from Schlosser et al.(2006) (based on Gefen, 2002; McKnight et al., 2002). An exploratory factor analysiswas performed on these trust beliefs, revealing the three underlying dimensions:ability, integrity, and benevolence (Table II).

The Cronbach’s alphas for each sub-construct were larger than the required 0.70 cutoff point: “ability beliefs” (four items; a ¼ 0.879), “benevolence beliefs” (five items;a ¼ 0.880), “integrity beliefs” (five items; a ¼ 0.893), demonstrating their internalvalidity (Nunnally and Bernstein, 1994). The derived factor scores were subsequentlyused to perform further analyses. The items to measure “purchase intention”(five items; a ¼ 0.950) were derived from Loiacono et al. (2007) and “trust propensity”was measured by means of eight items (a ¼ 0.907), which have been adapted fromAljukhadar et al. (2010) (based on McKnight et al., 2002). Minor wording changes

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were made to the measurement instruments in order to adjust them to the online giftshopping task. Since the targeted respondents were Dutch speaking Belgians, thequestionnaire was composed in Dutch. Scales have been (back) translated by amultilingual professor who has a degree in Germanic languages.

5.5 Manipulation checksFor manipulation checks, we followed O’Keefe (2003) to determinewhether the participants were aware of the experimental manipulations in thedifferent conditions of the experiment. Four manipulation check items were included inthe questionnaire for this purpose (Appendix Table AI). For the SNS treatmentcondition, almost all respondents recalled having seen a “Facebook Like Box”(98.2 percent), but interestingly, 23.1 percent of the respondents in the non-treatmentcondition also recalled having seen an SNS. For the “blogging” treatment conditions,a majority of the respondents recalled having seen a “blog” (80.4 percent), but also8.2 percent of the respondents in the non-treatment condition recalled having seen a“blog”. It is possible that some of the respondents did not actually make a distinctionbetween both kinds of social networking applications. Still, whether or not respondentsdid make this distinction or whether they paid actual attention to the social networkingapplications is not really an issue, as the signaling process we aim to examine may workunconsciously (O’Keefe, 2003).

Rotated component matrixa

ComponentCode Construct items 1 2 3

IntegrityTBI2 I do not doubt the honesty of WebGiftDirect 0.858 0.190 0.228TBI5 I can count on WebGiftDirect to be sincere 0.797 0.267 0.256TBI1 Promises made by WebGiftDirect are likely to be reliable 0.743 0.308 0.379TBI4 I expect that the advice given by WebGiftDirect is their best

judgment0.599 0.444 0.147

TBI3 I expect that WebGiftDirect will keep the promises they make 0.552 0.494 0.302Benevolence

TBB2 I expect that WebGiftDirect has good intentions towards me 0.241 0.804 0.286TBB4 I expect that WebGiftDirect puts customers’ interests before their

own0.248 0.755 0.023

TBB1 I expect that WebGiftDirect is ready and willing to assist andsupport me

0.152 0.701 0.379

TBB3 I expect that WebGiftDirect’s intentions are benevolent 0.488 0.652 0.313TBB5 I expect that WebGiftDirect is well meaning 0.526 0.632 0.241

AbilityTBA2 I believe that WebGiftDirect understands the market they work in 0.212 0.126 0.860TBA3 I believe that WebGiftDirect knows about gifts 0.183 0.233 0.821TBA4 I believe that WebGiftDirect knows how to provide excellent service 0.240 0.389 0.711TBA1 I believe that WebGiftDirect is competent 0.450 0.150 0.706

Cronbach’s alpha 0.893 0.880 0.879Eigenvalue percentage of variance 25.589 24.417 22.683

Notes: aRotation converged in six iterations; “extraction method”: principal component analysis;“rotation method”: varimax with Kaiser normalization

Table II.Factor analysis

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6. Analyses and resultsThe data were analyzed using multivariate analysis of covariance (MANCOVA) inorder to identify to what extent the integration of “web communities” (i.e. an SNS and acorporate blog) can impact consumers’ “initial trust” (i.e., ability, benevolence, andintegrity) towards an unfamiliar e-tail web site. First, we checked the data forviolations of statistical assumptions in order to be able to perform a MANCOVAanalysis. Box’s test assessing the assumption of equality of covariance matrices isnon-significant ( p . 0.05), hence, the covariance matrices are roughly equal and theassumption of homogeneity is met. Levene’s statistics also indicate that for each of theresiduals, there are equal group variances, which lends support to the assumption ofequal covariance matrices across the different experimental groups.

Because consumers’ “trust propensity” appeared to have, as expected, a significantpositive impact on “trust beliefs”, it was included as a covariate in the analysis. Butfirst it was verified and confirmed that all the preconditions to do so were met. Alsothe respondents’ “age” appeared to have a significant impact on “trust beliefs”, morespecifically what “ability” beliefs are concerned. Therefore, we also controlled for ageby including it as a covariate in the analysis. Table III displays the results ofthe MANCOVA analysis.

Our multivariate test shows that no overall interaction effect can be revealed. Whilethere seems to be no significant main effect of the presence of the SNS “Facebook” onoverall “trust beliefs” (l ¼ 0.995, F (df ¼ 3) ¼ 0.346, p ¼ 0.792), according to Wilk’slambda, there does appear to be a significant main effect of the presence of a “corporateblog” on overall “trust beliefs” (l ¼ 0.928, F(df ¼ 6) ¼ 2.728, p ¼ 0.013).

Since we are interested, however, in the effects of the social networking applicationson the individual trust beliefs, we will further discuss the results of the univariateANCOVA tests. Our results show that there are no main effects of the presence of an“SNS” on any of the individual trust beliefs either, and thus H1 should be rejectedentirely. We do note however a significant interaction effect of the integration of an“SNS” and a “corporate blog” what perceived “benevolence” is concerned(F(df ¼ 2) ¼ 3.791, p ¼ 0.024) and will have a closer look at that later on. Regardingthe integration of a “blog” we cannot reveal any main effect on perceived “ability”, thuswe should reject H2a, but we do notice some significant main effects on perceived“benevolence” (F(df ¼ 2) ¼ 4.690, p ¼ 0.010) and “integrity” (F(df ¼ 2) ¼ 3.721,p ¼ 0.026), inclining us to accept H2b and H2c. However, it seems necessary to havea closer look at our findings first, as shown in Figures 2 and 3.

Figure 2 clearly reveals that the integration of a “corporate blog” in an e-retailer website appears to enhance “integrity” beliefs only in case it involves a “text blog withoutphoto”. Integrating a blog with picture even seems to have a detrimental effect onperceived integrity, but a post hoc Bonferroni test indicates that this difference is notsignificant. In fact the only significant difference emerges when comparing the perceivedintegrity evoked by both blog conditions (“perceived integrity” ¼ 0.222text only blog

versus 20.183text and photo blog, post hoc Bonferroni: p ¼ 0.024).In Figure 3 we clearly notice the positive impact on perceived “benevolence” of the

presence of a blog, which appears to be most pronounced when a “photo and text” blogis integrated in the web site. Pairwise comparisons prove this latter effect to be highlysignificant (“perceived benevolence” ¼ 0.263text and photo blog versus 20.201no blog,post hoc Bonferroni: p ¼ 0.010).

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Ind

epen

den

tv

aria

ble

sC

ovar

iate

sM

ain

effe

cts

Inte

ract

ion

effe

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rust

pro

pen

sity

Ag

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log

SN

SB

log£

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tv

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sS

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log

Ph

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No

Yes

Sig

.S

ig.

Ab

ilit

y(0.025)

(0.001)

0.07

22

0.04

22

0.02

9(0.743)

0.01

62

0.01

4(0.819)

(0.973)

Ben

evol

ence

(0.002)

(0.167)

20.

201

20.

078

0.26

3(0.010)

20.

030

0.01

9(0.700)

(0.024)

Inte

gri

ty(0.000)

(0.654)

20.

048

0.22

22

0.18

3(0.026)

0.05

52

0.06

0(0.351)

(0.569)

Wil

k’s

lam

bd

a(0.000)

(0.003)

(0.013)

(0.792)

(0.170)

Notes:

Sam

ple

(n¼

226)

;M

AN

CO

VA

:2£

3b

etw

een

-su

bje

cts

full

-fac

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are

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par

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Table III.The effect of integratingweb communities on trustbeliefs

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Still, a closer look at Figure 4 sheds some more light on the significant interaction of bothsocial network applications on “benevolence” beliefs (F(df ¼ 2) ¼ 3.791, p ¼ 0.024). Thepositive effect of the integration of a “photo and text blog” only seems true in case an“SNS” is also integrated in the web site. In that case “benevolence” perceptions evenreach 0.533SNSþphoto blog, which is quite high when compared to the control conditionwithout any social network application (20.092). When no SNS is present we cannot

Figure 2.The main effect of the

presence of a corporateblog on “integrity” beliefs

0.30000

0.20000

0.10000

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–0.20000

No Blog Blog (text only) Blog (with photo)

CORPORATE BLOG

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Figure 3.The main effect of the

presence of a corporateblog on “benevolence”

beliefs

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reveal any impact of the integration of a blog whatsoever. On the other hand, integratingan SNS only seems to increase “benevolence” beliefs when a blog is also presentincorporating a picture of a sales representative. This provides some partial support forH3b, regarding the combined effect of social network applications in signaling“trustworthiness” what “benevolence” is concerned. No such support could be revealedfor H3a or H3c, concerning “ability” and “integrity” beliefs.

Finally, we investigated the mediating role of “initial trust beliefs” evoked byintegrating social networking applications (i.e. SNS and blog) on shoppers’ “purchaseintentions” (H4). Following the guidelines offered by Zhao et al. (2010) and Hayes andPreacher (2011) we conducted a bootstrapping analysis (with 5,000 bootstrappingsamples and a 95 percent confidence level) to test the mediation effects and to revealthe indirect as well as the direct effects of integrating social networking applications onshopping intentions. We enter the different initial trust beliefs “ability”, “benevolence”,and “integrity” as possible mediators into the model (using Hayes and Preacher’sMEDIATE syntax for SPSS), while examining the main individual effects, as well asthe combined effect of the social media applications of interest in this study(i.e. Facebook and a corporate blog). In order to control for any confounding effectsof age and trust propensity, these variables were again added to the analysis ascovariates. A comprehensive overview of our findings is displayed in Table IV.

According to our mediation analysis we can discern some direct effects (path: c0)of integrating social network applications on “purchase intentions” (R2

adj ¼ 0.096;F(df ¼ 7, 218) ¼ 4.42, p ¼ 0.0001: we identify a significant positive effect of integrating

Figure 4.Interaction effect of SNSand corporate blog on“benevolence” beliefs

0.60000

0.40000

0.20000

0.00000

–0.20000

–0.40000

No Blog Blog (text only) Blog (with photo))

CORPORATE BLOG

SNS

Est

imat

ed M

arg

inal

Mea

ns

No SNSYes SNS

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806

Pat

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Covariates

Tru

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ty0.

3174

(0.000)

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(0.001)

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79n

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4577

(0.000)

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evol

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0.24

80(0.000)

Inte

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3120

(0.000)

Indirecteffectsthrough

Trustbeliefs

(M)on

purchase

intention

(Y)

Pat

h:a£b

Ability

Benevolence

Integrity

Eff

ect

CI l

ow

CI u

pE

ffec

tC

I low

CI u

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mediation

Independentvariables

(X)

SN

S2

0.02

892

0.26

240.

1989

20.

0545

20.

1678

0.05

392

0.07

072

0.21

480.

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Non

med

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892

0.26

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0.09

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med

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0.17

760.

2094

20.

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20.

1189

0.08

982

0.16

602

0.3314

20.0287

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20.

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0.20

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0.26

910.

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160.

2988

Ind

irec

t-on

ly

Notes:

Nu

mb

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sam

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sed

for

ind

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inte

rval

s:5,

000;

boo

tstr

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den

cein

terv

als:

95p

erce

nt;p-

val

ues

are

rep

orte

din

par

enth

eses

Table IV.Direct and indirect effects

on purchase intention

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the combination: “photo blog £ SNS” (b ¼ 0.6124, p ¼ 0.048), but also a marginallysignificant negative effect of integrating a “photo blog only” (b ¼ 20.4047, p ¼ 0.061)

Subsequently, we verified whether any effects of social network applications aremediated by “initial trust beliefs”. When including the trust beliefs “ability”,“benevolence”, and “integrity” into the equation, we cannot discern any direct maineffects of the presence of social network applications (path: c) anymore. We do, however,demonstrate strong effects of “initial trust beliefs” on “purchase intentions” (path: b) –(R2

adj ¼ 0.391; F(df ¼ 10, 215) ¼ 15.44, p , 0.001):, i.e. “ability” (b ¼ 0.458, p , 0.001),“benevolence” (b ¼ 0.248, p , 0.001), and “integrity” (b ¼ 0.312, p , 0.001).

While we cannot reveal any indirect effects through “ability” beliefs (path: a £ b),we do notice some indirect effects through “benevolence” and “integrity” beliefs. Thebootstrap mediation test clearly makes the case (at a ¼ 0.05) that the trust belief“benevolence” mediates the combined effect of “photo blog £ SNS” on “purchaseintentions” (path: a £ b: indirect effect ¼ 0.1774; CIlow ¼ 0.024 and CIup ¼ 0.383). Sincethe direct combined effect of “photo blog £ SNS” (path: c) becomes not statisticallysignificant anymore, this infers a clear “indirect-only” mediation effect (Zhao et al.,2010), also referred to by Baron and Kenny (1986) as “full mediation” effect. Similarly,we find that the trust belief “integrity” mediates the effect of the integration of a “photoblog” on “purchase intentions” (path: a £ b: indirect effect ¼ 20.1660; CIlow ¼ 20.331and CIup ¼ 20.029). Since the direct effect of the “photo blog” (path: c) also becomesnot statistically significant anymore, this point to another clear “indirect-only” or “full”mediation effect. Therefore, the mediation hypothesis (H4) can be supported what“benevolence” (H4b) and “integrity” (H4c) are concerned, but should be rejected what“ability” (H4a) is concerned.

7. DiscussionIn this study we tested the effectiveness of the mere integration of social networkapplications to provide a signal concerning the “trustworthiness” of an unfamiliare-vendor in order to enhance subsequent purchase intentions. While the simple integrationof Facebook could not enhance the perceived “ability”, “benevolence” or “integrity” of theonline merchant, the combination of Facebook with a corporate blog featuring the pictureof a sales representative did appear to have a positive effect on “benevolence” beliefs,which were in turn proven to play an important mediating role explaining the indirectimpact of such a combination of social network applications on ultimate purchaseintentions. On the other hand, an unfamiliar e-commerce web site featuring only acorporate blog with picture, not combined with an SNS, appeared to have a negativeimpact on “integrity” beliefs, which in turn negatively affect “purchase intentions”. Thus,the simple integration of “social network applications” can affect “initial trust beliefs”towards unfamiliar e-tailers and subsequent “purchase intentions”, but it appearsessential to utilize just the right cue combination in order to obtain the desired effect.

While the MANCOVA analysis demonstrated that integrating a “text blog” in thecommercial web site could enhance perceived “integrity”, adding “a facial photo of ashop representative” in the blog significantly decreased perceived “integrity”.To understand this, one should keep in mind that perceived “integrity” refers toperceived “honesty, fairness, credibility, and reliability” and involves “cognition-basedtrust” that evolves from a pattern of careful rational thinking, which is motivated by aconscious calculation of advantages (Komiak and Benbasat, 2006; Mayer et al., 1995).

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Thus, online shoppers need unbiased and objective product information to make theirrational judgments and product choices (Wang and Benbasat, 2007). The presence of afacial photo of a shop representative in the corporate blog might be elevatingconsumers’ negative perceptions about the “objectivity” of the blog post, because shopassistants are usually perceived as a source of biased suggestions and guidancebecause they are as a rule under the pressure to achieve their sales quota. While themajority of the respondents (90.9 percent), who remembered having seen the “facialphoto” in the blog, evaluated this image as trustworthy, the information presented inthe blog was judged less trustworthy when it featured a “facial photo” of the shoprepresentative next to it. In fact, 44.8 percent of the respondents within the “textblogging” condition who actually paid attention to the blog, reported to find itsinformation content trustworthy, as compared to only 33.3 percent of the respondentswithin the “photo blogging” condition. Prior research also found that onlineshoppers seem more likely to trust cartoon-like characters than human-like charactersduring online transactions, because human-like characters can even be seen as“surveillance” representing a threat to privacy (Luo et al., 2006). Objectivity is amongthe main concerns that consumers have when using online informative guidance(Komiak et al., 2005). Hence, the higher level of social presence evoked by embedding afacial photo of a shop representative may raise suspicions, causing a detrimentaleffect on perceived “integrity” and subsequent “purchase intentions”. Therefore, whenutilizing “a corporate blog” to enhance “purchase intentions”, it is vital to convey astrong sense of justice, honesty, and objectivity to the web community.

Our next interesting finding involves the combined effect of integrating an “SNS”and a “blog” in fostering consumers’ “benevolence” perceptions towards unfamiliare-retailers and subsequent “purchase intentions”. Although we did not find any directeffect of integrating “Facebook” on trust beliefs, combining “a blog with photo” withthe SNS “Facebook” did significantly strengthen the effects of both social mediaapplications in enhancing consumers’ benevolence beliefs. Since perceptions of“benevolence” are based on immediate affective reactions to attractiveness, the humanimages manipulated in the web interface could have inspired emotional responses,which may have resulted in favorable attitudes towards the web site (Cyr et al., 2009).

8. Conclusions, limitations and suggestions for further researchAlthough we could not reveal any effects of the integration of social network applicationson “ability” beliefs, we were able to demonstrate their capacity to “signal” “benevolence”and “integrity”. Moreover, all trust beliefs were shown to have a significant positiveimpact on consumers’ purchase intentions, once again confirming the vital importanceof trust in e-commerce success. More specifically, e-retailers may foster perceptions of“integrity” by integrating “text blogs” into their web sites. However, they need to avoidembedding facial photos of shop representatives in such blogs. Our findings show thatincorporating a facial photo of a shop representative in a “corporate blog” may actuallydiminish the trustworthiness of the blog. We argue that this could be due to a decrease inperceived “objectivity” of the information provided in the blog. Moreover, this studydemonstrates that such doubts regarding the “integrity” of the e-vendor can negativelyaffect purchase intentions. On the other hand, the combination of a “photo blog” with“Facebook” in the web site can enhance “benevolence” beliefs towards an unfamiliare-retailer, which in turn positively affects purchase intentions.

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There are a few limitations to this study that should be addressed in future research.One important limitation to this study concerns the “external validity” of the findings.Unfortunately, as a direct consequence of the main concern for internal validity,experiments are generally rather weak in generalizability. Therefore, extensions of thisstudy to other e-commerce contexts and integrating other (combinations of) socialnetwork applications are called for to determine the generalizability of our findings.Moreover, this was a controlled study. Subjects were given a fictitious task and wereasked to browse a fictitious web site that strictly manipulated design features in order tocontrol for potential biases from extraneous factors such as company or product brandinformation. Future research could enhance the realism of the task by integrating a realfinancial risk, for example, by offering the chance to win the selected products or byoffering real money to spend in the fictitious e-store. The study could even be extended toan actual real world field experiment, where different versions of an actual e-store exist.Regarding the social network applications, we investigated the impact of their merepresence and did not allow for actual interaction on the social network, whichpresumably would evoke an even stronger effect on trust and remains to be investigated.Also we exclusively provided positive content, instead of positive versus negative usercomments. It would be interesting to see how reinforcing or contradictory information isassimilated applying the cue consistency theory as a theoretical framework. Our studyfocused on students, more particular on Dutch speaking Belgian students. It still needsto be determined whether the obtained results hold in other populations (i.e. other agegroups, other cultures, etc.). Another area for future research may be to determine theextent to which the findings presented in this paper can be expanded to othere-commerce settings (c2c, b2b or m-commerce). As our results provide strong support forthe significant positive impact of “trust propensity” on trust beliefs, it is recommended tomeasure and control for this personal characteristic when investigating (other) web siterelated trust determinants.

References

Aldiri, K., Hobbs, D. and Qahwaji, R. (2008), “The human face of e-business: engenderingconsumer initial trust through the use of images of sales personnel on e-commerceweb sites”, International Journal of E-Business Research, Vol. 4 No. 4, pp. 58-78.

Aljukhadar, M., Senecal, S. and Ouellette, D. (2010), “Can the media richness of a privacydisclosure enhance outcome? A multifaceted view of trust in rich media environments”,International Journal of Electronic Commerce, Vol. 14 No. 4, pp. 103-26.

Badawy, A.M. (2009), “Technology management simply defined: a tweet plus two characters”,Journal of Engineering & Technology Management, Vol. 26 No. 4, pp. 219-24.

Baron, R.M. and Kenny, D.A. (1986), “The moderating-mediator variable distinction in socialpsychological research: conceptual, strategic, and statistical considerations”, Journal ofPersonality and Social Psychology, Vol. 51 No. 6, pp. 1173-82.

Benedicktus, R.L., Brady, M.K., Darke, P.R. and Voorhees, C.M. (2010), “Conveyingtrustworthiness to online consumers: reactions to consensus, physical store presence,brand familiarity, and generalized suspicion”, Journal of Retailing, Vol. 86 No. 4, pp. 322-35.

Bhattacherjee, A. (2002), “Individual trust in online firms: scale development and initial test”,Journal of Management Accounting Research, Vol. 19 No. 1, pp. 211-41.

Boyd, D.M. and Ellison, N.B. (2008), “Social network sites: definition, history, and scholarship”,Journal of Computer-Mediated Communication, Vol. 13 No. 1, pp. 210-30.

MRR35,9

810

Chang, H.H. and Chen, S.W. (2008), “The impact of online store environment cues on purchaseintention: trust and perceived risk as a mediator”, Online Information Review, Vol. 32 No. 6,pp. 818-41.

Chen, Y.H. and Barnes, S. (2007), “Initial trust and online buyer behavior”, IndustrialManagement & Data Systems, Vol. 107 No. 1, pp. 21-36.

Corritore, C.L., Kracher, B. and Wiedenbeck, S. (2003), “On-line trust: concepts, evolving themes,a model”, International Journal Human-Computer Studies, Vol. 58 No. 6, pp. 737-58.

Cyr, D., Head, M., Larios, H. and Pan, B. (2009), “Exploring human images in website design:a multi-method approach”, MIS Quarterly, Vol. 33 No. 3, pp. 539-66.

Dabholkar, P.A., van Dolen, W.M. and de Ruyter, K. (2009), “A dual-sequence framework for B2Crelationship formation: moderating effects of employee communication style in onlinegroup chat”, Psychology & Marketing, Vol. 26 No. 2, pp. 145-74.

Eroglu, S.A., Machleit, K.A. and Davis, L.M. (2001), “Atmospheric qualities of online retailing:a conceptual model and implications”, Journal of Business Research, Vol. 54 No. 2,pp. 177-84.

Eroglu, S.A., Machleit, K.A. and Davis, L.M. (2003), “Empirical testing of a model of online storeatmospherics and shopper responses”, Psychology & Marketing, Vol. 20 No. 2, pp. 139-50.

Fuller, M.A., Serva, M.A. and Benamati, J. (2007), “Seeing is believing: the transitory influence ofreputation information on e-commerce trust and decision making”, Decision Sciences,Vol. 38 No. 4, pp. 675-99.

Gefen, D. (2002), “Reflections on the dimensions of trust and trustworthiness among onlineconsumers”, The DATA BASE for Advances in Information Systems, Vol. 33 No. 3,pp. 38-53.

Gefen, D. and Straub, D.W. (2003), “Managing user trust in B2C e-services”, e-Service Journal,Vol. 2 No. 2, pp. 7-24.

Gefen, D. and Straub, D.W. (2004), “Consumer trust in B2C e-commerce and the importance ofsocial presence: experiments in e-products and e-services”, Omega: The InternationalJournal of Management Science, Vol. 32 No. 6, pp. 407-24.

Grabner-Krauter, S. and Kaluscha, E. (2003), “Empirical research in online trust: a review andcritical assessment”, International Journal of Human-Computer Studies, Vol. 58 No. 6,pp. 783-812.

Guo, S., Wang, M. and Leskovec, J. (2011), “The role of social networks in online shopping:information passing, price of trust, and consumer choice”, Proceedings of EC 2011:12th ACM Conference on Electronic Commerce, San Jose, CA, USA, June 5-9.

Gupta, P., Yadav, M.S. and Varadarajan, R. (2009), “How task-facilitative interactive tools fosterbuyers’ trust in online retailers: a process view of trust development in the electronicmarketplace”, Journal of Retailing, Vol. 85 No. 2, pp. 159-76.

Hayes, A.F. and Preacher, K.J. (2011), “Indirect and direct effects of a multicategorical causalagent in statistical mediation analysis”, working paper, available at: www.afhayes.com/public/hp2011.pdf (accessed September 18).

Hoadley, C.M., Xu, H., Lee, J.J. and Rosson, M.B. (2010), “Privacy as information access andillusory control: the case of the Facebook News Feed privacy outcry”, Electronic CommerceResearch and Applications, Vol. 9 No. 1, pp. 50-60.

Horppu, M., Kuivalainen, O., Tarkiainen, A. and Ellonen, H.K. (2008), “Online satisfaction, trustand loyalty, and the impact of the offline parent brand”, Journal of Product & BrandManagement, Vol. 17 No. 6, pp. 403-13.

B2Ce-commerce

websites

811

Hsiao, K.-L., Lin, J.C.-C., Wang, X.-Y., Lu, H.-P. and Yu, H. (2010), “Antecedents and consequencesof trust in online product recommendations: an empirical study in social shopping”, OnlineInformation Review, Vol. 34 No. 6, pp. 935-53.

Hu, N., Liu, L. and Zhang, J. (2008), “Do online reviews affect sales? The role of reviewercharacteristics and temporal effects”, Information Technology Management, Vol. 9 No. 3,pp. 201-14.

Hu, X., Wu, G., Wu, Y. and Zhang, H. (2010), “The effects of web assurance seals on consumers’initial trust in an online vendor: a functional perspective”, Decision Support Systems,Vol. 48 No. 2, pp. 407-18.

Hui, C. (2011), “The impact mechanism of consumer-generated comments of shopping sites onconsumer trust”, Journal of Computers, Vol. 6 No. 1, pp. 43-50.

Jin, B., Park, J.Y. and Kim, J. (2008), “Cross-cultural examination of the relationships among firmreputation, e-satisfaction, e-trust, and e-loyalty”, International Marketing Review, Vol. 25No. 3, pp. 324-37.

Kaplan, A.M. and Haenlein, M. (2010), “Users of the world, unite! The challenges andopportunities of social media”, Business Horizons, Vol. 53 No. 1, pp. 59-68.

Karimov, F.P. and Brengman, M. (2011), “Adoption of social media by online retailers:assessment of current practices and future directions”, International Journal ofE-Entrepreneurship and Innovation, Vol. 2 No. 1, pp. 26-45.

Karimov, F.P., Brengman, M. and Van Hove, L. (2011), “The effect of website design dimensionson initial trust: a synthesis of the empirical literature”, Journal of Electronic CommerceResearch, Vol. 12 No. 4, pp. 272-301.

Keng, C.-J. and Ting, H.-Y. (2009), “The acceptance of blogs: using a customer experiential valueperspective”, Internet Research, Vol. 19 No. 5, pp. 479-95.

Komiak, S.X. and Benbasat, I. (2004), “Understanding customer trust in agent-mediatedelectronic commerce, web-mediated electronic commerce, and traditional commerce”,Information Technology and Management, Vol. 5 No. 1, pp. 181-207.

Komiak, S.X. and Benbasat, I. (2006), “The effects of personalization and familiarity on trust andadoption of recommendation agents”, MIS Quarterly, Vol. 30 No. 4, pp. 941-60.

Komiak, S.X., Wang, W. and Benbasat, I. (2005), “Trust building in virtual salespersons versus inhuman salespersons: similarities and differences”, e-Service Journal, Vol. 3 No. 3, pp. 49-63.

Kumar, N. and Benbasat, I. (2002), “Para-social presence and communication capabilities of aweb site: a theoretical perspective”, e-Service Journal, Vol. 1 No. 3, pp. 5-20.

Lauer, T.W. and Deng, X. (2007), “Building online trust through privacy practices”, InternationalJournal of Information Security, Vol. 6 No. 5, pp. 323-31.

Lee, S., Hwang, T. and Lee, H.-H. (2006), “Corporate blogging strategies of the Fortune500 companies”, Management Decision, Vol. 44 No. 3, pp. 316-34.

Lee, Y. and Kozar, K.A. (2009), “Designing usable online stores: a landscape preferenceperspective”, Information & Management, Vol. 46 No. 1, pp. 31-41.

Leimeister, J.M., Ebner, W. and Krcmar, H. (2005), “Design, implementation, and evaluation oftrust-supporting components in virtual communities for patients”, Journal of ManagementInformation Systems, Vol. 21 No. 4, pp. 101-35.

Li, Y.-M. and Chen, C.-W. (2009), “A synthetical approach for blog recommendations mechanism:trust, social relations, and semantic analysis”, Expert Systems with Applications, Vol. 36No. 3, pp. 6536-47.

MRR35,9

812

Lievens, A. and Mahr, D. (2010), “Social virtual communities: members’ benefits and their impacton word-of-mouth”, Proceedings of the European Marketing Academy Conference,Copenhagen, Denmark, June 1-4.

Lim, K.H., Sia, C.L., Lee, M.K.O. and Benbasat, I. (2006), “Do I trust you online, and if so, will Ibuy? An empirical study of two trust-building strategies”, Journal of ManagementInformation Systems, Vol. 23 No. 2, pp. 233-66.

Loiacono, E.T., Watson, R. and Goodhue, D. (2007), “WebQual: an instrument for consumerevaluation of web sites”, International Journal of Electronic Commerce, Vol. 11 No. 3,pp. 51-87.

Lowry, P.B., Zhang, D., Zhou, L. and Fu, X. (2010), “Effects of culture, social presence, and groupcomposition on trust in technology-supported decision-making groups”, InformationSystems Journal, Vol. 20 No. 4, pp. 297-315.

Lowry, P.B., Vance, A., Moody, G., Beckman, B. and Read, A. (2008), “Explaining and predictingthe impact of branding alliances and web site quality on initial consumer trust ofe-commerce web sites”, Journal of Management Information Systems, Vol. 24 No. 4,pp. 199-224.

Luhmann, N. (1979), Trust and Power, Wiley, London.

Luo, J.T., McGoldrick, P., Beatty, S. and Keeling, K.A. (2006), “On-screen characters: their designand influence on consumer trust”, Journal of Services Marketing, Vol. 20 No. 2, pp. 112-24.

McAllister, D.J. (1995), “Affect- and cognition-based trust as foundations for interpersonalcooperation in organizations”, Academy of Management Journal, Vol. 38 No. 1, pp. 24-59.

McKnight, D.H., Choudhury, V. and Kacmar, C. (2002), “Developing and validating trustmeasures for e-commerce: an integrative typology”, Information Systems Research, Vol. 13No. 3, pp. 334-59.

McKnight, D.H., Cummings, L.L. and Chervany, N.L. (1998), “Initial trust formation in neworganizational relationships”, Academy of Management Review, Vol. 23 No. 3, pp. 473-90.

Maheswaran, D. and Chaiken, S. (1991), “Promoting systematic processing in low-motivationsettings: effect of incongruent information on processing and judgment”, Journal ofPersonality and Social Psychology, Vol. 61 No. 1, pp. 13-25.

Mayer, R.C., Davis, J.H. and Schoorman, F.D. (1995), “An integrative model of organizationaltrust”, Academy of Management Review, Vol. 20 No. 3, pp. 709-34.

Miyazaki, A.D., Grewal, D. and Goodstein, R.C. (2005), “The effect of multiple extrinsic cues onquality perceptions: a matter of consistency”, Journal of Consumer Research, Vol. 32 No. 1,pp. 146-53.

Morgan, R.M. and Hunt, S.D. (1994), “The commitment-trust theory of relationship marketing”,Journal of Marketing, Vol. 58 No. 3, pp. 20-38.

Morrow, J.L. Jr, Hansen, M.H. and Pearson, A.W. (2004), “The cognitive and affective antecedentsof general trust within cooperative organizations”, Journal of Managerial Issues, Vol. 16No. 1, pp. 48-64.

Nambisan, S. and Baron, R.A. (2007), “Interactions in virtual customer environments:implications for product support and customer relationship management”, Journal ofInteractive Marketing, Vol. 21 No. 2, pp. 43-62.

Nunnally, J.C. and Bernstein, I.H. (1994), Psychometric Theory, 3rd ed., McGraw-Hill,New York, NY.

O’Keefe, D. (2003), “Message properties, mediating states, and manipulation checks: claims,evidences, and data analysis in experimental persuasive message effects research”,Communication Theory, Vol. 13 No. 3, pp. 251-74.

B2Ce-commerce

websites

813

Olson, J.C. and Jacoby, J. (1972), “Cue utilization in the quality perception process”,in Venkatesan, M. (Ed.), Proceedings of 3rd Annual Conference, Association forConsumer Research, Chicago, IL, pp. 167-79.

Pallis, G., Zeinalipour-Yazti, D. and Dikaiakos, M.D. (2011), “Online social networks: status andtrends”, in Vakali, A. and Jain, L.C. (Eds), New Directions in Web Data Management 1,Studies in Computational Intelligence, Vol. 331, Springer, Berlin, pp. 213-34.

Papacharissi, Z. (2009), “The virtual geographies of social networks: a comparative analysis ofFacebook, LinkedIn and ASmallWorld”, New Media and Society, Vol. 11 Nos 1/2,pp. 199-220.

Pavlou, P.A. and Dimoka, A. (2006), “The nature and role of feedback text comments in onlinemarketplaces: implications for trust building, price premiums, and seller differentiation”,Information Systems Research, Vol. 17 No. 4, pp. 392-414.

Pavlou, P.A. and Fygenson, M. (2006), “Understanding and prediction electronic commerceadoption: an extension of the theory of planned behavior”, MIS Quarterly, Vol. 30 No. 1,pp. 115-43.

Pavlou, P.A. and Gefen, D. (2004), “Building effective online marketplaces with institution-basedtrust”, Information Systems Research, Vol. 15 No. 1, pp. 37-59.

Qiu, L. and Benbasat, I. (2005), “Online consumer trust and live help interfaces: the effects oftext-to-speech voice and three-dimensional avatars”, International Journal ofHuman-Computer Interaction, Vol. 19 No. 1, pp. 75-94.

Qiu, L. and Benbasat, I. (2009), “Evaluating anthropomorphic product recommendation agents:a social relationship perspective to designing information systems”, Journal ofManagement Information Systems, Vol. 25 No. 4, pp. 145-82.

Richardson, P.S., Dick, A.S. and Jain, A.K. (1994), “Extrinsic and intrinsic cue effects onperceptions of vendor brand quality”, Journal of Marketing, Vol. 58 No. 4, pp. 28-36.

Riegelsberger, J., Sasse, M.A. and McCarthy, J.D. (2005), “The mechanics of trust: a frameworkfor research and design”, International Journal of Human-Computer Studies, Vol. 62 No. 3,pp. 381-422.

Rosen, D., Barnett, G.A. and Kim, J.H. (2011), “Social networks and online environments: whenscience and practice co-evolve”, Social Network Analysis andMining, Vol. 1 No. 1, pp. 27-42.

Schau, H.J. and Gilly, M.C. (2003), “We are what we post? Self-presentation in personal webspace”, Journal of Consumer Research, Vol. 30 No. 3, pp. 385-404.

Schlosser, A.E., White, T.B. and Lloyd, S.M. (2006), “Converting web site visitors into buyers:how web site investment increases consumer trusting beliefs and online purchaseintentions”, Journal of Marketing, Vol. 70 No. 2, pp. 133-48.

Seock, Y.-K. and Bailey, R.L. (2008), “The influence of college students’ shopping orientations andgender differences on online information searches and purchase behaviours”, InternationalJournal of Consumer Studies, Vol. 32 No. 2, pp. 113-21.

Sorce, P., Perotti, V. and Widrick, S. (2005), “Attitude and age differences in online buying”,International Journal of Retail & Distribution Management, Vol. 33 No. 2, pp. 122-32.

Spaulding, T.J. (2010), “How can virtual communities create value for business?”, ElectronicCommerce Research and Applications, Vol. 9 No. 1, pp. 38-49.

Wang, W. and Benbasat, I. (2007), “Recommendation agents for electronic commerce: effects ofexplanation facilities on trusting beliefs”, Journal of Management Information Systems,Vol. 23 No. 4, pp. 217-46.

MRR35,9

814

Wu, G., Hu, X. and Wu, Y. (2010), “Effects of perceived interactivity, perceived web assuranceand disposition to trust on initial online trust”, Journal of Computer-MediatedCommunication, Vol. 16 No. 1, pp. 1-26.

Zhao, H., Lynch, J.G. and Chen, Q. (2010), “Reconsidering Baron and Kenny: myths and truthsabout mediation analysis”, Journal of Consumer Research, Vol. 37 No. 2, pp. 197-206.

About the authorsMalaika Brengman (PhD in Applied Economics, University of Ghent) (UG), is AssociateProfessor at the Vrije Universiteit Brussel (VUB), where she teaches Marketing, StrategicMarketing Management, Consumer Behaviour and Market Research. She started her academiccareer as Assistant Professor at Hasselt University, where she has also been lecturing inMarketing Communications, e-Business, Services Management and Customer RelationshipManagement. She has also been guest lecturing at other academic institutions such asSolvay Business School at the Universite Libre de Bruxelles and the International School ofManagement at the Leti-Lovanian University in St Petersburg, Russia. Guided by her stronginterests in retailing, marketing communications and consumer behaviour, her scientific researchgenerally focuses on the impact of store atmospherics and consumers’ shopping motivations andbehaviour, specifically also with regard to alternative distribution channels such as e-commerceand shopping in virtual worlds. She also studies marketing communications’ effectiveness,especially with regard to new media. She has published her work in well-established journals,such as the Journal of Electronic Commerce Research, the Journal of Business Research, theJournal of Marketing Communications, the Journal of Retailing and Consumer Services, theJournal of Brand Management, the Journal of Product & Brand Management, and Advances inConsumer Research. She has presented her findings at numerous international conferences.

Farhod P. Karimov (PhD in Applied Economics, Vrije Universiteit Brussel) is a subject arealeader for marketing at Westminster International University in Tashkent (WIUT), where he alsoteaches Marketing, Strategic Marketing Management, Consumer Behaviour, Market Researchand Creating and Delivering Customer Value. As a guest lecturer he has also been teachingPrinciples of Marketing, Consumer Behavior, and Pricing Strategies in Marketing for a couple ofyears at the International Business School in Tashkent. His current scientific research is focusedon understanding the impacts of website atmospherics on online consumers’ shoppingbehaviour, effectiveness of social media applications, security issues in e-commerce and onlinepayment systems. The aim of the research is to capture the lessons of successful models fore-businesses serving promising online segment. He is actively involved in studying the role ofsocial media in e-commerce and specifically how it influences the acceptance of online shopping.In addition to his interest in internet marketing, he also studies entrepreneurial marketing,neuromarketing and ICT research in transition economies. Farhod P. Karimov is thecorresponding author and can be contacted at: Farhod.Karimov@gmail.com

(The Appendix follows overleaf.)

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