an integrated model of influential antecedents of online shopping initial trust: empirical evidence...

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An Integrated Model of Influential Antecedents ofOnline Shopping Initial Trust: Empirical Evidence in aLow-Trust EnvironmentMing Zhou a & Ding Tian aa Marketing Department, Business School , Hubei University, Wuchang District , Wuhan,Hubei Province, P.R. ChinaPublished online: 16 Mar 2010.

To cite this article: Ming Zhou & Ding Tian (2010) An Integrated Model of Influential Antecedents of Online Shopping InitialTrust: Empirical Evidence in a Low-Trust Environment, Journal of International Consumer Marketing, 22:2, 147-167, DOI:10.1080/08961530903476212

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Journal of International Consumer Marketing, 22:147–167, 2010Copyright c© Taylor & Francis Group, LLCISSN: 0896-1530 print / 1528-7068 onlineDOI: 10.1080/08961530903476212

An Integrated Model of Influential Antecedents of OnlineShopping Initial Trust: Empirical Evidence in a Low-Trust

Environment

Ming ZhouDing Tian

ABSTRACT. This article explores the issue of what factors contribute to which dimensions of con-sumers’ initial trust in online vendors in a relatively low-trust environment such as the People’s Republicof China. The article has adopted the trust model proposed by McKnight and Chervany (2002) andexplored the determinant factors of online shopping initial trust through building an integrated model.In our model, a multidimensional approach has been applied. Through hierarchical regression analysis,we find that distinct discrepancies do exist between influential antecedents of consumer initial trust inonline vendors in a low-trust environment like China and those in a high-trust environment. Specif-ically, perceived corporate image, perceived security, and perceived reference power are influentialantecedents of all three dimensions of trusting beliefs (except the effect of perceived security on abilityand the effect of perceived reference power on benevolence), but perceived Web site quality is found toexert no significant influence on trusting beliefs, and it can moderate trusting intentions. Moreover, incontrast to prior studies conducted in high-trust environments, our research finds that trusting intentionsare significantly influenced by consumers’ trust in the firm’s integrity rather than their trust in its abilityor benevolence. Additionally, we find little support for the hypothesis that a consumer’s disposition totrust has a direct or a moderating effect on initial trust in an online vendor.

KEYWORDS. Influential antecedents, online shopping, initial trust, trusting beliefs, trusting intentions,low-trust environment

RESEARCH BACKGROUND

With the increasing cost-effectiveness ofcommunication technologies, online shoppinghas already become one of the most importantareas of electronic commerce. A recent study in-dicated that “online retail sales in the U.S. willreach nearly $230 billion by 2008” (Lin et al.

Ming Zhou is Lecturer in Marketing and Consumer Behavior and Ding Tian is a graduate student inthe Marketing Department of the Business School at Hubei University, Wuchang District, Wuhan, HubeiProvince, P.R. China.

Address correspondence to Ming Zhou, Lecturer in Marketing and Consumer Behavior, Marketing De-partment, Business School at Hubei University, Wuchang District, Wuhan, Hubei Province, 430062 P.R.China. E-mail: [email protected]

2006). In developing countries like China, on-line retail sales have jumped to Y= 59.4 billionin 2007, up from a mere Y= 1.8 billion in 2002(CNNIC 2007). However, the Internet is stillfar from achieving its full potential as an e-marketplace due to consumers’ reluctance toengage in online transactions. While many on-line vendors have enjoyed a rapid increase in

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148 JOURNAL OF INTERNATIONAL CONSUMER MARKETING

the number of clicks on their Web sites, theyhave faced disappointments in converting theseclicks into purchases. An estimated 65% of Inter-net shoppers abandon their shopping carts afteran initial attempt at navigating a retail Web site(Raymond 2001). Despite the fast growth in on-line retail sales in China, up to 2007 only 22.1%netizens have online shopping experiences (CN-NIC 2007).

Because of the physical and temporal distancebetween buyers and sellers, online shoppingcreates uncertainty and increases risk throughthe delay between purchase and delivery andthe information asymmetry between the twoparties. Moreover, online transactions oftenrequire sharing of sensitive personal information(such as mailing address or telephone number),corporate information (such as inventory data),and financial information (such as credit cardnumbers) between the transacting parties (Bhat-tacherjee 2002). Online shoppers feel hesitationand apprehension about passing along their per-sonal information on the Internet (Haas 1998;Minahan 1997; Romani 1998), because they areconcerned that online companies would givetheir personal information to other firms withouttheir knowledge or permission. These concernsare already justified by a string of notoriousincidents that occurred over the last coupleof years involving e-commerce firms Ama-zon.com, DoubleClick, Inc., and Toysmart.com,among others, accused of improperly or perhapsillegally sharing consumer information withthird parties (Hemphill 2002). Internet fraud isanother growing concern. Online shoppers areconcerned about the inability to confirm the le-gitimacy of electronic businesses (Hassan et al.2006). Consumers simply lack enough trustto engage in business relationships involvingfinancial transactions (Hoffman, Novak, andPeralta 1999). According to a 2001 McKinsey& Co. research report, lack of consumer trustis a critical impediment to the success ofe-commerce (Dayal, Landesberg, and Zeisser2001). Many other market surveys and researchreports have also shown that trust is consideredto be one of the main barriers for acceptanceof e-business (Hoffman et al. 1999; Liu et al.2005; Ratnasingam, Gefen, and Pavlou 2005;Van Slykes et al. 2006; Warrington, Abgrab,

and Caldwell 2000). A survey conducted byCNNIC in July 2007 indicated that only 35.1%of Chinese netizens trust the Internet. Thus, itis reasonable to assume that lack of trust is oneof the greatest barriers inhibiting online trans-actions in both mature and emerging markets.

Actually, trust has been playing an impera-tive role in online purchasing. Trust builds con-fidence in customers’ minds, whereby they aremore willing to engage in a purchase relation-ship with an organization they trust (Keen 2000).In the online world, trust acts as an informalcontrol mechanism that reduces friction, limitsopportunistic behaviors, minimizes the need forbureaucratic structures, encourages future trans-actions, and helps build long-term relationships.Therefore, initiating, building, and maintainingtrust between buyers, sellers, and partners arewidely believed to be the key drivers of successfor most online firms (Keen 1997)..It is appar-ent that e-commerce is predicated on trust (Chenand Barnes 2007; Hwang and Kim 2007; Pavlou,Liang, and Xue 2007), and the establishment oftrust in customers’ minds is a crucial step in theprocess of creating sound business relationshipswith them (Thakur and Summey 2007).

Although there are already many studies inthis domain, few studies have distinguishedonline trust of potential customers from thatof repeat customers and pointed out differentfactors contributing to each of them. Previouspurchase experience, for instance, an accreditedimportant factor, can only be a predictor ofonline trust of repeat customers. Moreover, themajority of extant literature treats trust as a one-dimensional concept when studying precursorsof consumer online trust, but such a parsimo-nious approach is likely to obscure specificeffects on different trusting dimensions playedby those precursors and to make it difficult tounderstand the holistic mechanism betweentrust and factors that influence it. Those studiesthat do consider trust as a multidimensionalconcept mainly focus on the conceptualizationof trust, and empirical studies are rather rare.

Last but not least, most relevant researchhas been conducted in mature markets and rel-atively high-trust environments like the U.S.,and few empirical studies have been made intransient economies with relatively low-trust

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Ming Zhou and Ding Tian 149

environments in which factors contributing toconsumers’ online initial trust may differ fromthose in relatively high-trust environments. It isbelieved that national culture influences individ-ual and organizational behavior such that it hasimplications for trust development and efficacy(Doney, Cannon, and Mullen 1998). Also, con-sumers are influenced not only by how muchthey trust a company and its representatives butalso by how much they trust the broader contextin which the market exchange is taking place(Grayson, Johnson, and Chen 2008). However,Chinese have a long tradition of distrust, due tothe hostile social, psychological, and sociolog-ical environment over millennia (Kiong & Kee1998). China has a considerably high Power Dis-tance Index, which indicates a high level of in-equality of power in Chinese society (Hofstede1991). For centuries, in China implementationof laws was subject to personal interpretationby officials, many of whom were corrupt, andbribery was widespread. This bred a deep senseof distrust that still exists (Kiong & Kee 1998).Consequently, Chinese rely on face-to-face con-tact more so than other cultures (Davies et al.1995). Since cultural homogeneity in Chinesesociety is greater than in many Western coun-tries, reputational and ascriptive means of de-veloping trust, rather than some more generalsocial institutional means such as the profes-sional certification of competences and the le-gal system, remain effective over considerabledistances through elaborate and extensive repu-tational networks, as demonstrated by overseasChinese (Limlingan 1986). In Chinese society,relations depend heavily on trust, but ironically,trust is difficult to build beyond circles of kinshipor closely knit social networks (Chow 2008).The foundation of trust formation in a Chinesecontext is built on a Quanzi—a small intimatecircle of friends—and guanxi. It is a culturalgiven in Chinese society that trust has to beearned, and is not easily earned. Thus, comparedwith Western countries such as the U.S., China isa nation with a relatively low-trust environmentin both the online and offline business world.

E-commerce environment in China is alsocharacterized by low-trust because transactionaland institutional trust is found to be the majorimpediments to e-commerce in China (Efendio-

glu and Yip 2004). This, as Efendioglu and Yipexplain, is mainly caused by the counterfeitingand distribution of below-par products, therebyincreasing the lack of transactional trust betweenparties that do not know each other personally.Pang, Yen, and Tarn (2007) argue that the initialonline trust of Chinese Internet users is relativelylow because of their low trust in online vendorsin general. Nevertheless, with up to 215 millionnetizens in China (CNNIC 2007), only 22.1% ofwhom currently have online buying experience,it is a huge potential market for online vendorswho should never miss such an immerse marketopportunity. Their main task is to build onlineinitial trust of potential customers.

The purpose of this article is to investigate ina relatively low-trust environment what factorscontribute to consumers’ initial trust in an on-line vendor and to which dimensions the trustextends, thereby uncovering whether such anonline initial trust formation mechanism is dif-ferent from that in a relatively high-trust envi-ronment. The findings may offer crucial con-tributions to extant literature via proposing acomprehensive research framework based on ex-isting literature and verifying whether findingsand theories established in relatively high-trustenvironments are still applicable in a relativelylow-trust environment like China. Our findingsare expected to provide online vendors intend-ing to seize the untapped business opportunitiesin China with helpful insights into how to con-vert Chinese Web site visitors into online buyers.To fulfill that objective, our research is struc-tured as follows. The article begins with a lit-erature review on online initial trust and factorsimpacting it. This is followed by research mod-eling and hypotheses generation. Then a descrip-tion of the methodology and statistical analysisprecedes a discussion of the results. The studyconcludes with the implications as well as thelimitations.

LITERATURE REVIEW

What is Online Initial Trust?

It is essential to fully understand trust forthe success of e-commerce. But what is on-line trust and what leads to it? As a research

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concept, trust has been examined in many socialscience disciplines, such as sociology, psychol-ogy, organizational behavior, economics, mar-keting, and most recently, e-commerce. In thecontext of e-commerce, many researchers havegiven various definitions from different perspec-tives. Jarvenpaa and colleagues (1999) definetrust as consumers’ willingness to rely on theseller and take action in circumstances wheresuch action makes the consumer vulnerable tothe seller. Lee and Turban (2001) hold that trustis the willingness of a consumer to be vulnerableto the actions of an Internet merchant in an In-ternet shopping transaction, based on the expec-tation that the Internet merchant will behave incertain agreeable ways, irrespective of the abilityof the consumer to monitor or control the Inter-net merchant. Ba and Pavlou (2002) argue thattrust refers to the subjective assessment of oneparty that another party will perform a particulartransaction according to his or her confident ex-pectations, in an environment characterized byuncertainty. In contrast, some researchers deemthat trust is a multidimensional concept (e.g.,E. Kim and Tadisina 2007; McKnight and Cher-vany 2002). McKnight, Choudhury, and Kacmar(2002a, 2002b) define initial trust as trust in anunfamiliar trustee, a relationship in which theactors do not yet have credible, meaningful in-formation about, or affective bonds with, eachother, and initial trust was measured with trust-ing beliefs (one believes that the other party hasone or more characteristics beneficial to oneself)and trusting intentions (one is willing to dependon, or intends to depend on, the other party eventhough one cannot control that party). E. Kimand Tadisina (2007) define trust in an e-businessas (1) trusting beliefs: a customer’s perceptionsthat an e-business has competence and good-will to serve customers, (2) trusting attitudes:a customer’s confidence in and affect for the e-business, and (3) trusting intention: a customer’swillingness to take a risk in the relationship withthe e-business.

Obviously, some researchers define trust asa one-dimensional concept while others holdthat trust is multidimensional. Since trust is avery complicated and comprehensive concept,we believe that a multidimensional view of trustcould best capture the breadth and complexity of

this complex construct. Trust is actually a mat-ter of perception, and many of its dimensionsare cognitive and affective. Based on the priorresearch above, we adopt the trust model pro-posed by McKnight and Chervany (2002) andassume trust is composed of two aspects: trust-ing beliefs (cognitive aspect) and trusting in-tentions (behavioral aspect). The distinction be-tween trusting beliefs and trusting intentions hasbeen recognized by several researchers (Moor-man, Zaltman, and Deshpande 1992; Sirdesh-mukh, Singh, and Sabol 2002). Trusting beliefsrepresent an expectation or sentiment about anexchange partner’s trustworthiness (Moorman,Deshpande, and Zaltman 1993) and can be con-ceptually clustered into three related yet distinctdimensions: ability, benevolence, and integrity(Mayer, Davis, and Schoormann 1995; McK-night et al. 2002a). Ability refers to the trustor’s(consumer) perception of the trustee’s (onlinevendor) competencies and knowledge salient tothe expected behavior (Mayer et al. 1995). Suchperceptions may be based on prior (firsthand orsecondhand) experience or institutional endorse-ments. In e-commerce contexts, according toBhattacherjee’s research (2002), consumer per-ceptions of a firm’s ability are based on two re-lated beliefs: (1) whether the firm is competentenough to perform the intended behavior, and(2) whether the firm has access to the knowledgerequired to perform the behavior appropriately.Perceived lack of these beliefs could thereforeundermine perceptions of the trustee’s ability.Benevolence is the extent to which a trustee isbelieved to intend doing good to the trustor, be-yond its own profit motive (Mayer et al. 1995).A benevolent trustee would help a trustor, evenwhen the trustee is not required to be helpful oris not rewarded for being helpful (Bhattacher-jee 2002). Benevolence introduces faith and al-truism in a relationship, reducing uncertaintyand the inclination to guard against opportunis-tic conduct. Integrity refers to the trustor’s per-ception that the trustee will adhere to a set ofprinciples or rules of exchange acceptable to thetrustor during and after the exchange (Mayeret al. 1995). Perceived integrity can not only in-still a trustor’s confidence in a trustee’s behav-ior but also reduces his/her perceptions of risk.According to Bhattacherjee’s research (2002), in

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e-commerce contexts, rules of integrity refer to:(1) conduct of online transactions, (2) customerservice policies following a transaction, and (3) afirm’s use of private user information. Note thatadherence to any set of rules is not adequate;such rules must be perceived by the trustor asbeing fair and reasonable.

Trusting intentions represent a willingness tomake oneself vulnerable to another party in thepresence of risk (P. H. Kim et al. 2004). Whatdistinguishes trusting intentions from other typesof behavioral intentions is that they involverisk (Moorman et al. 1992). Here in our study,trusting intentions means online purchase inten-tions, representing a willingness to transact withan online vendor under the circumstances of alack of experience with the online vendor. Thereasons we rule out the trusting attitudes dimen-sion (a customer’s confidence in and affect forthe e-business) proposed by E. Kim and Tadisina(2007) are that affect embodied in attitude ispartially captured within the benevolent and in-tegrity dimensions of trust (Bhattacherjee 2002)and that trust inherently entails the assumption ofrisk (a probability of loss) since absence of riskobviates the need for investing in trust-buildinginitiatives; however, confidence eliminates riskby ignoring possible alternatives and is thereforedistinct from trust (Luhmann 1988).

Initial trust is characterized by a lack of expe-rience with or firsthand knowledge of the otherparty. Based on above-mentioned analyses, wedefine a consumer’s online initial trust under thecircumstances of a lack of experience with anonline vendor, the willingness of a consumer tobe vulnerable to the actions of the online vendorin an online shopping transaction, based on theexpectation that the online vendor will behave incertain agreeable ways, irrespective of the abilityof the consumer to monitor or control the onlinevendor.

Factors Impacting Online Initial Trust

In the business-to-consumer (B2C) context,several factors have been identified as predic-tors of trust. These factors can be categorizedinto two groups based on the scope or level:macrolevel factors and microlevel factors (E.Kim and Tadisina 2007). Macrolevel factors

are macroenvironment factors that enable con-sumers to take part in e-commerce activitiesoverall such as social norms, government reg-ulations to secure online transactions, or rele-vant legal systems. Microlevel factors are thosefactors that affect a consumer’s trust in a spe-cific company. Since those macrolevel factorsare relatively uncontrollable for online vendors,we primarily focus our study on microlevel fac-tors, which are more important for establishinga customer’s initial trust in a specific online ven-dor. Though there are several different classi-fications of these factors proposed by differentresearchers, we categorize those factors into fouraspects from consumers’ perspectives: Web sitequality, corporate image, reference power, andsecurity. Some researchers have proposed addi-tional factors that are not explicitly included inour model (e.g., familiarity, belief that the ven-dor has nothing to gain by cheating, service level,customer satisfaction, and frequency). We do notinclude these explicitly in our model becausethey either seem to be vague in meaning or canbe included in the four aspects proposed by us.Familiarity, for instance, is not clear as to whatthe consumer is familiar with. Meanwhile, a con-sumer may also be quite familiar with a notori-ous online vendor but definitely does not trust it.Thus, familiarity is not a salient or sound factor.Customer satisfaction or satisfaction with pasttransactions, however, is a determinant only rea-sonable for repeat customers. Frequency itselfdoes not seem to be a sound predictor of trustas a consumer might contact an online vendorfrequently to complain. Disposition to trust, alsoknown as trust propensity, is treated as a factorthat may have a direct effect on online initial trustand also perform as a moderator in our modelas one’s disposition to trust can greatly affecthis/her perception, which in turn will influencehis/her trust level and online purchase intentions.

RESEARCH MODEL ANDHYPOTHESES

Perceived Web Site Quality

Online consumers normally cannot directlyinteract with an online vendor in any purchase

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transaction; hence the channel (Web site) mayact as a type of agent in the exchange relationship(Wakefield, Stocks, and Wilder 2004). Potentialconsumers have no prior relationship with thecompany, and therefore their initial impressionsshould largely depend on their experience withthe Web site. In e-commerce, the first introduc-tion between a consumer and an online vendoris almost always through the Web site of the on-line vendor. McKnight and colleagues (2002b)find that Web site quality reflects the consumer’sinitial perceptions about the Web site and is astrong predictor of trust in the online vendor.Based on previous studies, we cluster perceivedWeb site quality into four dimensions: user inter-face quality, Web site information, service qual-ity, and navigability. User-interface quality mayfacilitate consumers to form a positive impres-sion of the Web site and therefore perceive thehigh quality of the Web site and that the on-line vendor cares about them. Web site informa-tion is operationalized as information quality andthe presentation of information. Web site infor-mation is very important because a consumer’spurpose for visiting a Web site is to search forinformation. Besides, according to information-processing theory, the most important determi-nant of online trust is how the information ispresented on the Web site. Though service qual-ity was treated by some researchers as a factorparallel to Web site quality, we believe that likethe other dimensions of Web site quality, ser-vice quality like warranties and guarantees aredemonstrated and perceived via Web site. Thus,it is reasonable to consider service quality asone dimension of Web site quality. Good nav-igability can enhance a consumer’s search effi-ciency and perception of convenience, which inturn would be directly related to a consumer’sinitial trust in the Web site and therefore inthe online vendor. Therefore, it is hypothesizedthat:

H1a: The higher Web site quality potentialcustomers perceived, the higher ability be-liefs potential customers would have in anonline vendor.

H1b: The higher Web site quality potentialcustomers perceived, the higher benevo-

lence beliefs potential customers wouldhave in an online vendor.

H1c: The higher Web site quality potentialcustomers perceived, the higher integritybeliefs potential customers would have inan online vendor.

Perceived Corporate Image

Many researchers included company-image-related factors in their models as predictors oftrust (Grazioli and Jarvenpaa 2000; H.-W. Kim,Xu, and Koh 2004; E. Kim and Tadisina 2007;Koufaris and Hampton-Sosa 2004; McKnightet al. 2002b). Consumers’ perceptions of a com-pany’s image or profile are likely to influencetheir trust because it may be the source of trustdevelopment (E. Kim and Tadisina 2007). In thee-commerce context, Jarvenpaa and colleagues(1999, 4) consider size and reputation to bethe predictors of trust and mentioned that theseare closely related to each other and also tolongevity. For example, “larger firms might beexpected to be around longer and hence firmsthat are larger and more reputable might be moretrusted.” These three factors are correlated withone another. But consumers usually have veryfew cues to help them form a perception concern-ing the company’s size, and the Web sites alonecould not provide enough cues to determine thesize of the company (Koufaris and Hampton-Sosa 2004). Consequently, we believe that in theonline world when its reputation and longevityare taken into full account, the influence of anonline vendor’s size on corporate image can beomitted. Brand equity is defined as the valueattributed to a certain brand when the consumeris familiar with that brand and holds somefavorable, strong, and unique brand associationsin memory (Keller 1993). The brand equity ofproducts integrates the characteristics of relia-bility and quality that are associated with retailertrust in prior consumer research (Altman andTaylor 1973; Crosby, Evans, and Cowles 1990).Product brand equity is also an important cue inthe electronic marketplace. Houston and Taylor(1999) find that product quality is an importantdeterminant in purchasing from a Web site. Weclassify these concepts (reputation, longevity,

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product brand equity) into a group, i.e.,corporate image. Therefore, we propose that:

H2a: The better corporate image potentialcustomers perceived, the higher ability be-liefs potential customers would have in anonline vendor.

H2b: The better corporate image potentialcustomers perceived, the higher benevo-lence beliefs potential customers wouldhave in an online vendor.

H2c: The better corporate image potentialcustomers perceived, the higher integritybeliefs potential customers would have inan online vendor.

Perceived Reference Power

The transference process (Stewart 1999) is thejustification of the effect of reference power onconsumers’ trust in e-businesses. Stewart refersto Heider’s cognitive balance theory to establishtransference as a means of building customers’trust in an unknown party through a well-knownparty. He defined transference as “a process bywhich consumers trust in an unknown target isinfluenced by trust in associated targets.” Thus,trust can be transferred from a trusted party toanother unknown party.

Reference power may involve endorsementby previous customers, third-party seals, recom-mendations from friends/relatives, and referralsfrom prestigious media. Endorsement by previ-ous customers can be a great reference power topotential customers. Lim and colleagues (2006)find that satisfied customer endorsement by sim-ilar peers was found to increase consumers’trusting beliefs about the store, which, in turn,positively influenced consumers’ attitudes to-ward the store and their willingness to buy fromthe store, which ultimately led to actual buy-ing behaviors. Third-party seal programs haveemerged as a thriving e-service for building con-sumer trust on the Internet. Coleman (1990) in-dicates that presence of a third party can maketwo involved transaction parties trust each other.In e-commerce, a third party can play a more sig-nificant role, as two involved parties cannot doface to face transactions. Cook and Luo (2003)point out that given the impersonal nature of e-

commerce, third-party seals are well positionedto act as the intermediary between competitiveonline vendors and nervous online consumers.Many consumers rely on the referrals made bythese third-party agencies in choosing onlinevendors, while online vendors, on the other hand,use the endorsement of third-party agencies asa tool to build consumer trust. Third-party sealssuch as TRUSTe and BBB Online are used toproduce trust (Gefen and Straub 2003), whichcould be a strong reference power for potentialcustomers in that customers usually believe Websites with third-party seals are more trustworthy.The same applies to referrals from prestigiousmedia such as famous business magazines ornewspapers and the like, which is actually a kindof publicity or WOM (word of mouth) greatly in-fluencing consumers’ purchase decisions. Hav-ing brand name recognition outside the Web willbring shoppers to a online vendor’s Web site.Recommendation from friends/ relatives is an-other crucial aspect because it is likely that con-sumers’ attitude toward an online vendor andpurchase intentions would be greatly influencedby their friends/relatives’ previous purchase ex-perience and recommendations. Therefore, wepropose that:

H3a: The stronger reference power potentialcustomers perceived, the higher ability be-liefs potential customers would have in anonline vendor.

H3b: The stronger reference power poten-tial customers perceived, the higher benev-olence beliefs potential customers wouldhave in an online vendor.

H3c: The stronger reference power potentialcustomers perceived, the higher integritybeliefs potential customers would have inan online vendor.

Perceived Security

Security is another crucial factor influencingconsumers’ trust in an online vendor. Jamieson(1999) finds trust can be enhanced by security-based mechanisms that provide protective mea-sures for safeguarding individual information.Security of a high level may result in potentialcustomers’ confidence that they can trust that

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their personal information, such as credit cardnumbers, financial data, and demographic dataremains secure. When an online vendor fails toprovide the threshold level security, perceivedrisks might escalate, undermining consumers’online initial trust. Actually, the most importantthing that can slow down the Internet and e-commerce growth surge is loss of confidence ina company’s ability to protect consumers’ pri-vacy and to provide secure data managementsystems (Keen 2000). In short, security fosterse-business activities via establishing consumers’online trust.

We categorize security into three dimensions:privacy statements, protective measures for pay-ment, and opportunism. Privacy statementsindicate that no one other than the individualcustomer and the online vendor has access to thecustomer’s personal information without the in-dividual customer’s knowledge or permission.This is quite important because online con-sumers place a high premium on informationprivacy and will not divulge personal data ifthey are uninformed about how that informa-tion will be used (Houston and Taylor 1999).A study conducted by Hoffman and colleagues(1999) find that 69% of Web users did not pro-vide data to Web sites because the sites providedno information about how their data would beused. Protective measures for payment such asorder-fulfillment software, security encryption,and firewall technologies are another importantdimension, which may remove hesitation andenhance consumers’ confidence to trade online.Opportunism is defined as a deceit-oriented vi-olation of implicit or explicit promises abouta predetermined role of behavior (John 1984).In e-commerce transactions, opportunism mayinvolve such acts as withholding or distortinginformation, disclosing private information, orfailing to fulfill promises or obligations (E. Kimand Tadisina 2007). In 2001, 46% of the generalInternet-using population had concerns over se-curity and privacy of information on the Web(Pastore 2001). Hence, perceptions of oppor-tunism may undermine consumers’ perceptionof security and become a barrier to online shop-ping activities. Overall, protective measures forpayment reflect online vendors’ ability to pro-tect consumers’ personal information, while pri-

vacy statements and opportunism represent on-line vendors’ goodwill and perceptions of onlinevendors’ goodwill to protect information. Over-all, it is hypothesized that:

H4a: The higher security potential customersperceived, the higher ability beliefs poten-tial customers would have in an online ven-dor.

H4b: The higher security potential customersperceived, the higher benevolence beliefspotential customers would have in an on-line vendor.

H4c: The higher security potential customersperceived, the higher integrity beliefs po-tential customers would have in an onlinevendor.

Disposition to Trust

Disposition to trust, also named trust propen-sity, has been found to be another indispensablefactor impacting online trust. It is defined asa general tendency for or inclination towardshowing faith or belief in humanity and adoptinga trusting stance toward others (Gefen 2000;McKnight et al. 2002a). Disposition to trust hasan essential impact on the initial formation oftrust because consumers may vary in their readi-ness to trust others when they have insufficientinformation, especially in an unfamiliar situa-tion (Gefen 2000; Koufaris and Hampton-Sosa2004). Mayer and colleagues (1995) proposethat a trustee’s characteristic-based factor (trustpropensity) had a direct effect on trust and amoderating effect on the relationships betweentrust and its predictors. Gefen (2000) suggeststhat for new relationships such as that betweena consumer and a previously unused online ven-dor, disposition to trust is a strong determinantof online initial trust. Thus, it is hypothesizedthat:

H5a: Disposition to trust is positively relatedwith potential consumers’ initial formationof online trusting beliefs in an online ven-dor.

H5b: Disposition to trust has a moderatingeffect on the relationships between onlineinitial trust and its predictors.

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FIGURE 1. An Integrated Model of Antecedents of Online Initial Trust.

Perceived Web

Site Quality

Perceived

Corporate Image

Perceived

Reference Power

Perceived

Security

Trusting

IntentionsBenevolence

Integrity

Ability

Trusting Beliefs

Online Initial Trust

Disposition to Trust

H1a

H2a

H3a

H4a

H5b

H5a

H6a

H6b

H6c

H1bH1c

H2bH2c

H3bH3c

H4b

H4c

Online Initial Trusting Beliefs andTrusting Intentions

Based on prior research, we adopt the trustmodel proposed by McKnight and Chervany(2002) and assume trust is composed of twoaspects: trusting beliefs (cognitive aspect) andtrusting intentions (behavioral aspect). Trust-ing beliefs represent an expectation or senti-ment about an exchange partner’s trustworthi-ness (Moorman et al. 1993) and can be con-ceptually clustered into three dimensions: abil-ity, benevolence, and integrity (McKnight et al.2002a). Ability reflects a consumer’s confidencethat the firm has the skills necessary to performthe job (Mayer et al. 1995); benevolence re-flects a consumer’s confidence that the firm hasa positive orientation towards its customers be-yond its own profit motive (Mayer et al. 1995);integrity reflects a consumer’s confidence thatthe firm sticks to a set of professional stan-dards or moral principles that guide interactionswith its customers (Schlosser, White, and Lloyd2006).Trusting intentions represent a willing-

ness to make oneself vulnerable to another partyin the presence of risk (P. H. Kim et al. 2004),reflecting a consumer’s willingness to buy froman online vendor. To the extent that consumersare concerned about various risks of purchasingonline such as delivery of inferior products, fail-ure of personal information protection and thelike, online purchase intentions reflect trustingintentions (Schlosser et al. 2006).

Online trust acts as an informal control mech-anism that reduces friction, limits opportunisticbehaviors, minimizes the need for bureaucraticstructures, encourages future transactions, andhelps build long-term relationships (Keen 1997).Many market surveys and research reports haveshown that trust is considered to be one of themain barriers for acceptance of e-business (Hoff-man et al. 1999; Liu et al. 2005; Ratnasingamet al. 2005; Van Slykes et al. 2006; Warring-ton et al. 2000). The establishment of trust incustomers’ minds is an important step in theprocess of creating sound business relationshipswith them (Thakur and Summey 2007). Trustbuilds confidence in customers’ minds; hence

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they are more willing to engage in a purchase re-lationship with an organization they trust (Keen2000). Thus, it is hypothesized that:

H6a: Ability beliefs in an online vendor arepositively associated with a consumer’strusting intentions (online purchase inten-tions).

H6b: Benevolence beliefs in an online vendorare positively associated with a consumer’strusting intentions (online purchase inten-tions).

H6c: Integrity beliefs in an online vendorare positively associated with a consumer’strusting intentions (online purchase inten-tions).

Based on the analysis presented above, a re-search model is presented in Figure 1, proposingan integrated framework of antecedents of onlineinitial trust.

METHODOLOGY

The proposed model was tested by meansof a field study and data collected through awell-established questionnaire. College studentswere used as subjects for this study because on-line shoppers are mainly composed of highlyeducated young people (Hoffman et al. 1999),and young people with university education ac-counted for 47.7% of online consumers in China(CNNIC 2006). In addition, prior empirical workhas shown that online behavior is not signif-icantly different from a sample of the gen-eral population (Gallagher, Parsons, and Foster2001).

Those who had online purchase experiencewere asked to fill out the questionnaire by recall-ing their first online purchase situations. Specif-ically, to ensure the validity and soundness ofrespondents’ replies, our survey targeted thosewho had just made their first online purchaseswithin a month. Used as a comparison group,those who had no online purchase experiencewere also asked to fill out the questionnaire (ex-cluding the scale of online trust in the onlinevendor) to identify the most influential factor oftheir initial trust in an online vendor and to tes-tify whether discrepancies exist in perceptions

TABLE 1. Means and Standard Deviations

Group 1 Group 2

Variables Mean S.D. Mean S.D.

Perceived Web Site Quality 3.91 .56 3.76 .40Perceived Corporate Image 3.63 .60 3.52 .58Perceived Reference Power 3.98 .55 3.89 .53Perceived Security 4.16 .58 3.68 .55Disposition to Trust 2.95 .81 3.04 .80General Trust in Online Purchase 3.05 .78 3.58 .69

Note. Group 1 represents those who have never purchased online,sample size = 98; Group 2 represents those who have just madetheir first online purchases within one month, sample size = 86.

of the importance of factors impacting onlineinitial trust between consumers who have neverpurchased online and those who have just madetheir first online purchases.

A pilot test was conducted beforehand tomodify the questionnaire and therefore to securethe validity of our subsequent analysis. The ini-tial questionnaire, which adopted a 5-point Lik-ert scale (1 = strongly disagree, 5 = stronglyagree) was composed of 48 items (perceivedWeb site quality, 17 items; perceived corporateimage, 8 items; perceived security, 9 items; on-line initial trust, 14 items). Most of these itemswere adapted from the existing literature, and allof them were carefully translated into Chinese.Some necessary changes were made to make thequestions suitable for Chinese reading habits.During the pilot test, 6 inappropriate items weredeleted, and the revised questionnaire was final-ized. The survey was then conducted and lastedfor one week. In this study, 210 questionnaireswere distributed and 184 (87.6%) valid question-naires were collected for analysis. Of the sam-ple, 96 (52.2%) of the respondents were maleand 88 (47.8%) were female; 86 (46.7%) hadmade their first online purchase within a monthwhile 98 (53.3%) had never bought online.

RESULTS

Table 1 presents means and standard devia-tions among the variables. It was found that re-spondents who had never purchased online gen-erally held lower general trust in online purchase

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TABLE 2. Reliability Analysis

Construct Cronbach’s α

Perceived Web Site Quality .777Perceived Corporate Image .814Perceived Security .830Perceived Reference Power .555Disposition to Trust .830Online Initial Trust .881

(3.05) and disposition to trust (2.95) than dothose who had already conducted their first on-line purchase (3.58 and 3.04 respectively). Theresult was consistent with the fact that consumerswho have a higher level of trust in online pur-chasing and/or disposition to trust are more in-clined to engage in online purchasing behavior.Moreover, security (4.16) is perceived to be themost influential predictor of initial trust in anonline vendor for those who have never pur-chased online. This also justifies the reason whythese respondents have never purchased onlinesince great concern over perceived security in-dicates their low level of trust in online pur-chasing and/or disposition to trust. In contrast,reference power (3.89) is perceived to be themost influential predictor of initial trust in anonline vendor for those who have indeed pur-chased online once. The result just indicates thevital importance of WOM in the online businessworld. This to some extent helps explain whyseveral online vendors such as JoYo Amazonand DangDang accounted for the majority of theChinese B2C market (63.3%) in 2008 in thatthey have a good reputation among consumersand thus enjoy much more WOM marketing thanother online vendors. In short, discrepancies doexist in perceptions of the importance of factorsimpacting initial trust between consumers whohave never purchased online and those who in-deed are conducting first online purchases.

Next, further analysis was made based on thedata of those who have already conducted theirfirst online purchase. Reliability analysis wasconducted. The Cronbach alpha coefficient wasused to assess internal reliability of each con-struct. As shown in Table 2, the Cronbach alphacoefficients are generally acceptable, with .881for online initial trust, .830 for both disposition

TABLE 3. Principal Components Analysis

Bartlett’s Testof Sphericity

Construct Subconstruct Item Loading KMO Chi-square Sig.

PWQ UIQ UIQ1 .746 .740 304.734 .000UIQ2 .768

WI WI1 .608WI2 .834WI3 .430WI4 .738WI5 .569

SQ SQ1 .691SQ2 .615SQ3 .604SQ4 .607SQ5 .726

NAV NAV1 .470NAV2 .739NAV3 .728

PCI REP REP1 .919 .724 238.772 .000REP2 .891REP3 .696

LON LON1 .921PBE PBE1 .897

PBE2 .889PSE PS PS1 .828 .816 248.480 .000

PS2 .796PS3 .516

PMP PMP1 .539PMP2 .765PMP3 .851

OPP OPP1 .827OPP2 .840OPP3 .630

TRB ABI ABI1 .797 .848 511.853 .000ABI2 .850ABI3 .567

BEN BEN1 .761BEN2 .708BEN3 .779

INT INT1 .740INT2 .787INT3 .763INT4 .787

TRI TRI1 .778TRI2 .817TRI3 .838

Note. PWQ: Perceived Web site Quality; PCI: Perceived CorporateImage; PSE: Perceived Security; TRB: Trusting Beliefs; TRI: Trust-ing Intentions; UIQ: User Interface Quality; WI: Web site Informa-tion; SQ: Service Quality; NAV: Navigability; REP: Reputation; LON:Longevity; PBE: Product Brand Equity; PS: Privacy Statements;PMP: Protective Measures for Payment; OPP: Opportunism; ABI:Ability; BEN: Benevolence; INT: Integrity; Sample size = 86.

to trust and perceived security, .814 for perceivedcorporate image, and .777 for perceived Web sitequality. The Cronbach alpha coefficient of per-ceived reference power is low (.555), mainly be-cause perceived reference power is composed ofonly four items; this deserves further refinement

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TABLE 4. Hierarchical Regression Analysis

Model 1 Model 2 Model 3 Model 4 Model 5 Model 6IndependentVariable β t β t β t β t β t β t

PWQ −.070 −0.601 −.052 −0.426 .099 0.949 .070 0.670 .019 0.208 .036 0.370PCI .497 5.126∗∗∗ .510 5.238∗∗∗ .163 1.879∗ .181 2.172∗∗ .302 3.905∗∗∗ .305 3.879∗∗∗

PRP .170 1.734∗ .139 1.372 .081 0.926 .088 1.016 .134 1.719∗ .119 1.450PSE .159 1.417 .169 1.509 .513 5.110∗∗∗ .492 5.127∗∗∗ .541 6.047∗∗∗ .538 5.940∗∗∗

DIT .074 0.826 .081 0.871 .110 1.376 .142 1.787∗ .054 0.749 .054 0.723DIT×PWQ .063 0.513 .087 0.823 .139 1.393DIT×PCI −.233 −2.095∗∗ −.030 −0.318 −.019 −0.213DIT×PRP −.059 −0.565 .047 0.526 .028 0.330DIT×PSE .057 0.428 −.319 −2.776∗∗ −.140 −1.291Durbin-Watson 1.809 1.744 2.122 2.257 1.774 1.793R2 .371 .410 .495 .566 .600 .614Adjusted R2 .332 .340 .463 .515 .575 .568F 9.437*** 5.876∗∗∗ 15.659∗∗∗ 11.030∗∗∗ 23.966∗∗∗ 13.414∗∗∗

DependentVariable

ABI BEN INT

Note. ∗p < .1; ∗∗p < .05; ∗∗∗p < .001.

in future research. But in general these scaleshave acceptable reliability.

Regarding content validity, most of the itemsin the questionnaire were based on previous re-search and theories; therefore the content of thequestionnaire is valid. Discriminant validity isthe degree to which measures of different con-cepts are distinct. The discriminant validity ofeach construct is assessed by principal com-ponents analysis (PCA) with Varimax rotation(perceived reference power and disposition totrust are not included as each has only one di-mension). Prior to the implementation of PCA,the value of Kaiser-Meyer-Olkin (KMO) andBartlett’s test of sphericity are tested to exam-ine whether the data are suitable to conduct aPCA. When common factors exist among vari-ables, partial correlations among these variableswill be small and the KMO value will be large.Bartlett’s test of sphericity tests the null hypothe-sis: The correlation matrix is an identity matrix.If this hypothesis cannot be rejected, data willnot be suitable for PCA. As shown in Table 3,the results indicate that for all four constructs theKMO values of these measures are all above .7and Bartlett’s test of sphericity values are all sig-nificant at the level .000. Therefore the data aresuitable for PCA. With varimax rotation, the fi-nal results of the factor analysis with PCA can be

seen in Table 3. Factor loadings for all items areover .5, except for WI3 (.430) and NAV1 (.470),with no cross-construct loadings. According toHair et al. (1998), a reasonable factor cut-offpoint for our sample size is .40. Therefore, thescales show acceptable convergent and discrim-inant validity.

In order to test our proposed model, mul-tiple linear regression analysis was employed.The results of hierarchical regression analysisare shown in Table 4 and Table 5. As shown inTable 4, perceived Web site quality, perceivedcorporate image, perceived security, perceivedreference power, and disposition to trust are en-tered as independent variables to check whetherthey exert a significant effect on different di-mensions of online initial trust (Model 1-6). Inaddition to direct effect, the moderating effect ofdisposition to trust on the relationships betweenonline initial trust and other predictors is alsotested by computing interaction items (Model2, Model 4, and Model 6). To correct for themulticolinearity that arises when testing moder-ated relationships among continuous variables,all independent variables were centered beforegenerating interaction items (Cohen and Cohen1983).

Results indicate that all these six models havegenerally good fit at the .001 significance level

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TABLE 5. Linear Regression for Trusting Intentions

Dependent Variable Independent Variable β t VIF F Durbin-Watson R2 Adjusted R2

TRI ABI −.040 −0.332 1.377 4.129** 1.938 .131 .099BEN .073 0.441 2.568INT .322 1.901∗ 2.712

Note. ∗p < .1; ∗∗p < .05.

(F = 9.437, p < .001; F = 5.876, p < .001;F = 15.659, p < .001; F = 11.030, p < .001;F = 23.966, p < .001; F = 13.414, p < .001).Adjusted R2 of these six models ranges from.332 to .575, meaning 33.2% to 57.5% of vari-ance for the dependent variable can be explainedby its independent variables. In the social sci-ences, low R2s in regression equations are notuncommon, especially for cross-sectional analy-sis, and a seemingly low R2 does not necessarilymean that an OLS regression equation is useless(Wooldridge 2000). Adjusted R2s of these sixmodels are neither very high nor too low; there-fore they are generally acceptable. Meanwhile,to address the problem of multicollinearity, theVariance Inflationary Factor (VIF) is used to testcorrelation among all variables. Multicollinear-ity is problematic for interpreting regressionanalyses when the maximum VIF is greater than10 (Neter, Wasserman, and Kutner 1990). Sincethe VIF values of independent variables in allmodels are less than 3, the data utilized in thisstudy are judged to have no significant multi-collinearity problem. A Durbin-Watson test wasconducted as well. The Durbin-Watson valuesof all the six models in table 4 are around 2,demonstrating weak autocorrelation amongresiduals and good model fit. Besides, the stan-dardized residuals of each model are normallydistributed and show no indications of het-eroscedasticity in the data.

Specifically, Model 1 examines the effects ofperceived Web site quality, perceived corporateimage, perceived security, perceived referencepower, and disposition to trust on ability beliefs.Among the five variables, perceived corporateimage (t = 5.126, p < .001) has the greatestand significant effect on ability beliefs, and itspositive coefficient means that perceived corpo-rate image positively affects a customer’s ability

beliefs in an online vendor. Perceived referencepower (t = 1.743) also has significant positiverelationships with ability beliefs at the signifi-cance level of .1. The other three variables arenot statistically significant.

Model 2 examines the moderating effect ofdisposition to trust on the relationships betweenability beliefs and its predictors. In this model,perceived corporate image (t = 5.238, p < .001)still has the greatest and most significant posi-tive effect on ability beliefs, but perceived refer-ence power is no longer significantly influentialto ability beliefs like the other three variables.Among all the interaction items, only DIT ×PCI (t = –2.095, p < .05) has significantly neg-ative effect on ability beliefs.

Model 3 examines the effects of perceivedWeb site quality, perceived corporate image, per-ceived security, perceived reference power, anddisposition to trust on benevolence beliefs. Per-ceived security (t = 5.110, p < .001) has a sig-nificant and positive effect on benevolence be-liefs. Perceived corporate image (t = 1.879, p <

.1) has a positive effect on benevolence beliefs atthe significance level of .1, while perceived Website quality, perceived reference power, and dis-position to trust have no statistically significanteffect on benevolence beliefs.

Model 4 examines the moderating effect ofdisposition to trust on the relationships betweenbenevolence beliefs and its predictors. Perceivedsecurity (t = 5.127, p < .001) still has a sig-nificant and positive effect on benevolence be-liefs. Perceived corporate image (t = 2.172) hasa positive effect on benevolence beliefs at thesignificance level of .05 as well as disposition totrust (t = 1.787) at the significance level of .1.Among all the interaction items, only DIT×PSE(t = –2.776, p < .05) has significant and nega-tive effect on benevolence beliefs.

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Model 5 examines the effects of perceivedWeb site quality, perceived corporate image, per-ceived security, perceived reference power, anddisposition to trust on integrity beliefs. Both per-ceived corporate image (t = 3.905, p < .001)and perceived security (t = 6.047, p < .001) arefound to have significant and positive influenceon integrity beliefs. Perceived reference power(t = 1.719) has a positive effect on integrity be-liefs at the significance level of .1.

Model 6 examines the moderating effect ofdisposition to trust on the relationships betweenintegrity beliefs and its predictors. Both per-ceived corporate image (t = 3.879, p < .001)and perceived security (t = 5.940, p < .001)are found to have significant and positive in-fluence on integrity beliefs. Perceived referencepower is no longer significantly influential to in-tegrity beliefs even at the significance level of .1.The other variables, including all the interactionterms, are not statistically significant.

As shown in Table 5, we modeled online ini-tial trusting intentions as a function of ability be-liefs, benevolence beliefs, and integrity beliefs.Results indicate that the overall model has a goodfit (F = 4.129, p < .05). R2 is .131 and adjustedR2 is .099. All the VIF values of independentvariables in this model are less than 3; there-fore no significant multicollinearity problemexists. Durbin-Watson values (1.938) demon-strate weak autocorrelation among residuals andgood model fit. Among the three independentvariables, only integrity beliefs (t = 1.901, p <

.1) has significant and positive effect on trustingintentions.

DISCUSSIONS AND CONCLUSION

The primary purpose of this study was to ex-amine the establishment of initial trust by newand potential customers of a Web–based com-pany (an online vendor) in a relatively low-trust environment. This study has identified sev-eral important precursors to online initial trust.Specifically, we found that both perceived cor-porate image and perceived reference power aresignificant (at different significance levels) an-tecedents of ability beliefs, one of the three di-mensions of trusting beliefs. This is because

good reputation and referrals from friends or rel-atives normally result from a firm’s excellent ca-pabilities to meet consumers’ needs. Perceivedcorporate image and perceived reference power,therefore, serve to bolster consumers’ beliefsthat the firm has the expertise and skills nec-essary to cater to their needs. When the moder-ating effect of disposition to trust is considered,both perceived corporate image and the inter-action term between perceived corporate imageand disposition to trust are influential determi-nants, but perceived reference power is not. Es-pecially, the interaction term between perceivedcorporate image and disposition to trust nega-tively affect ability beliefs, implicating the un-dermining effect of disposition to trust on abilitybeliefs. We can therefore conclude that perceivedcorporate image is significantly related to abilitybeliefs.

Meanwhile, benevolence beliefs are signif-icantly affected by perceived corporate imageand especially by perceived security. When themoderating effect of disposition to trust is con-sidered, perceived security as well as perceivedcorporate image still have a significant impact onbenevolence beliefs and at the same time disposi-tion to trust (but only significant at the level of .1)and the interaction term between perceived secu-rity and disposition to trust also exert significantinfluence. Especially, the interaction term be-tween perceived security and disposition to trustnegatively affect benevolence beliefs, implicat-ing the compromising effect of disposition totrust. This may be partly because rampant onlinefraud exists and various tricks have been createdto cheat consumers out of money; consumersmay contrarily hesitate and doubt the benevo-lence of the online vendor when they perceiveunusually high security in an online vendor. Inaddition, perceived corporate image, perceivedreference power (but only significant at the levelof .1), and perceived security are significantlypositive antecedents of integrity beliefs. Whenthe moderating effect of disposition to trust isconsidered, perceived reference power no longersignificantly affects integrity beliefs. Besides, allthe interaction terms are not statistically signif-icant. We can therefore conclude that perceivedsecurity is significantly related to integrity be-liefs.

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Overall, perceived corporate image, perceivedsecurity, and perceived reference power are in-fluential precursors of trusting beliefs, for thesevariables positively influence all three aspects oftrusting beliefs (except the effect of perceivedsecurity on ability and the effect of perceivedreference power on benevolence). This findingis not surprising and is consistent with priorresearch (e.g., Cook and Luo 2003; Jamieson1999; Jarvenpaa et al. 1999; McKnight et al.2002b). The absence of tangible products and apersonal interface with online vendors preventsthe establishment of the traditional bases fortrust. Consumers are generally concerned aboutpassing sensitive personal information to a partythey are quite unfamiliar with, and perceivedgood corporate image and perceived security canhelp solve this problem. This helps explain whyin a cutthroat competitive environment, severalonline vendors like DangDang (34.8%) and JoYoAmazon (28.5%) account for 63.3% of the Chi-nese B2C market in 2008, as they have a goodreputation with consumers and adopt various se-curity measures for payment. The result that per-ceived security exerts no significant impact onability tallies with that of research conductedby Schlosser and colleagues (2006). The reasonis that privacy and security statements, guaran-teed by back-end technologies such as firewalls,security encryption and so forth, communicatesthe online vendor’s goodwill, ethics, and values(i.e., benevolence and integrity) but not its abil-ity. However, the reason why perceived referencepower does not communicate benevolence in anonline vendor is unclear, and further researchneeds to be done.

Surprisingly, in our study perceived Web sitequality exerts no significant influence on anydimensions of trusting beliefs (ability, benev-olence, and integrity beliefs). This finding isat variance with previous research conductedin high-trust environments like the U.S. (e.g.,H.-W. Kim et al. 2004; McKnight et al. 2002b;Schlosser et al. 2006; Wakefield et al. 2004).Several explanations may account for the dis-crepancy. One possible explanation is that a well-designed Web site does not necessarily demon-strate an online vendor’s ability in site design,because an online vendor sometimes resorts tooutsourcing. If site design is outsourced, the Web

site certainly does not reflect the vendor’s on-line abilities. Given that the online vendor it-self established the Web site, it does not followthat abilities in Web site design would be ap-plied to other areas, such as shipping and de-livery, which are indispensable to satisfy con-sumers’ demand. Consequently, consumers withsuch concerns may not associate Web site qual-ity with an online vendor’s ability. Furthermore,online fraud in China is ubiquitous, and varioustricks, including building attractive Web sites,have been created to cheat consumers out ofmoney. Many Internet users have encounteredWeb sites that have a quite high–quality designbut, in fact, are traps. According to the APWG(Anti-Phishing Working Group), the number ofphishing Web sites in China had already rankedsecond in the world in 2005, accounting for 13%of the entire phishing Web sites throughout theglobe. The nature of online shopping as well asonline fraud has intensified consumers’ beliefthat good Web site quality does not necessar-ily denote sound competence, goodwill, or in-tegrity of an online vendor to honor its promises.In a relatively low-trust business context likeChina, a beautifully designed website accom-panied by unclear privacy-protection statementsor very limited structural assurance could be in-terpreted as having no other means to persuadeconsumers to make a purchase. As a result, po-tential consumers doubt the benevolence and in-tegrity of the online vendor, and the formation ofconsumers’ online initial trust is negatively af-fected. An additional possible explanation is thatfactors such as perceived corporate image maysubstantially dilute effects of perceived Web sitequality since when a consumers perceive a verygood image of an online vendor they generallyoverlook the Web site quality no matter whetherit is enjoyable or not, especially when a goodimage is accompanied with a perception of highsecurity.

However, interestingly, we find that perceivedWeb site quality significantly affects trusting in-tentions instead of trusting beliefs. This meansthat despite the fact that Web site quality has lit-tle influence on the formation of trusting beliefsin online vendors, it can indeed enhance con-sumers’ online purchase intentions. Generally,trusting intentions involve risk, which causes

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consumers to consult their trusting beliefs to de-termine whether to perform the trusting behav-ior (Schlosser et al. 2006). However, in Chinamany online vendors have adopted the policy ofC.O.D., i.e., cash on delivery, so as to relieveconsumers’ concern over possible financial loss.This measure of paying money on receipt of thegoods has greatly reduced the perceived risks ofpotential customers. Thus, when the purchasingscenario involves relatively little risk, consumersprobably do not consult their trusting beliefs todetermine whether to perform the trusting be-havior. In other words, perceived Web site qual-ity may directly affect trusting intentions (onlinepurchase intentions). Additionally, this findinghas to some extent proved the theory of boundedrationality and indicates consumers’ impulsivepurchase in the online context. In some circum-stances, Web site quality may be more importantfor online vendors, and we cannot arbitrarily as-sert that Web site quality is of little use thoughit does not directly influence trusting beliefs.

Meanwhile, we find no support for the hy-pothesis that consumers’ disposition to trust hasany significant direct effect on initial trust inan online vendor. This finding is inconsistentwith some prior research (e.g., Gefen 2000; Leeand Turban 2001). However, our paper only fo-cuses on initial trust, and the finding corrobo-rates other previous studies (for instance, Kou-faris and Hampton-Sosa 2004). The reason forthat is the various interpretations of the natureof trust by different studies. Studies that finddisposition to trust to be a significant antecedentto trust do not distinguish trust by repeat cus-tomers from initial trust by prospects. This mayindicate that trust propensity has a different ef-fect on initial trust in an online vendor than ontrust after continuous experience with the vendor(Hampton-Sosa and Koufaris 2005). Accordingto Hampton-Sosa and Koufaris (2005), it is pos-sible that when it comes to online shopping at anew company, consumers suppress their intrin-sic trusting intentions and instead rely more onevidence from the characteristics of the Web siteto form their initial trusting beliefs. In addition,in our studies disposition to trust, in most cases,does not moderate consumer initial trust in on-line shopping. This finding is consistent with theview of trust researchers who consider that the

individual’s trust response is more influenced bysituational factors than by a dispositional ten-dency to trust (Kramer 1999; Wicks, Berman,and Jones 1999). Therefore, it is advisable thatonline vendors, especially new entrants, shouldtry their best to attract all potential customersregardless of their level of disposition to trust.

With regard to trusting intentions (online pur-chase intentions), we find integrity is the onlyvariable among the three dimensions of trustingbeliefs that significantly affects trusting inten-tions (online purchase intentions). Nevertheless,the finding that the perceived integrity of theonline vendor has significant predictive valuein terms of the formation of consumers’ ini-tial trust in online shopping contradicts with thestudy by Schlosser and colleagues (2006), whofind online purchase intentions are influencedby searchers’ trust (consumers who search forproduct information) in the firm’s ability ratherthan their trust in its benevolence and integrity.Institutional factors may be the main causes. Ina relatively low-trust environment, initially con-sumers will consciously or unconsciously payclose attention to an unfamiliar vendor’s ethicsand values (i.e., integrity) to identify whetherthe vendor will do what it promises. Integritybeliefs can not only instill a consumers’ confi-dence in online vendors’ behavior but also re-duces their perceptions of risk. The integrity ofthe vendor (the vendor’s adherence to its moralprinciples or business philosophy) is thereforethe top reason why a consumer is willing to con-clude a transaction, whereas the ability of thevendor to fulfill orders is only secondary in con-sumers’ evaluation process and final buying de-cisions. Moreover, our finding is consistent withthe view of researchers who consider a percep-tion of integrity to be a critical antecedent totrust in a traditional environment (Butler 1991;Lieberman 1981). The finding indicates that itis important for an online firm to identify themost influential trusting beliefs (integrity be-liefs) in order to identify the signal that willmost effectively enhance trusting intentions. Allin all, our findings provide interesting insightsinto the factors that predict consumer initial trustin online shopping in a relatively low-trust envi-ronment. Table 6 summarizes the results of theanalysis.

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TABLE 6. Results of Research Hypotheses

Hypothesis Result

H1a. The higher Web site quality potential customers perceived, the higher ability beliefs potentialcustomers would have in an online vendor.

Not supported

H1b. The higher Web site quality potential customers perceived, the higher benevolence beliefs potentialcustomers would have in an online vendor.

Not supported

H1c. The higher Web site quality potential customers perceived, the higher integrity beliefs potentialcustomers would have in an online vendor.

Not supported

H2a. The better corporate image potential customers perceived, the higher ability beliefs potentialcustomers would have in an online vendor.

Supported

H2b. The better corporate image potential customers perceived, the higher benevolence beliefs potentialcustomers would have in an online vendor.

Supported

H2c. The better corporate image potential customers perceived, the higher integrity beliefs potentialcustomers would have in an online vendor.

Supported

H3a. The stronger reference power potential customers perceived, the higher ability beliefs potentialcustomers would have in an online vendor.

Supported

H3b. The stronger reference power potential customers perceived, the higher benevolence beliefspotential customers would have in an online vendor.

Not supported

H3c. The stronger reference power potential customers perceived, the higher integrity beliefs potentialcustomers would have in an online vendor.

Supported

H4a. The higher security potential customers perceived, the higher ability beliefs potential customerswould have in an online vendor.

Not supported

H4b. The higher security potential customers perceived, the higher benevolence beliefs potentialcustomers would have in an online vendor.

Supported

H4c. The higher security potential customers perceived, the higher integrity beliefs potential customerswould have in an online vendor.

Supported

H5a. Disposition to trust is positively related with potential consumers’ initial formation of trusting beliefsin an online vendor.

Not supported

H5b. Disposition to trust has a moderating effect on the relationships between online initial trust and itspredictors.

Not supported

H6a. Ability beliefs in an online vendor are positively associated with a consumer’s trusting intentions(online purchase intentions).

Not supported

H6b. Benevolence beliefs in an online vendor are positively associated with a consumer’s trustingintentions (online purchase intentions).

Not supported

H6c. Integrity beliefs in an online vendor are positively associated with a consumer’s trusting intentions(online purchase intentions).

Supported

IMPLICATIONS AND LIMITATIONS

This study is the first to explore what factorscontribute to which dimensions of consumers’initial trust in online vendors in a relativelylow-trust environment. In general, our proposedmodel has provided interesting insights into thenature and formation mechanisms of consumers’online initial trust.

First, the research finds that distinct discrep-ancies do exist between influential antecedentsof consumer initial trust in online vendors in alow-trust environment like China and those ina high-trust environment like the U.S. Althoughperceived corporate image, perceived security,and perceived reference power are influential

precursors of trusting beliefs, for these variablespositively influence all three aspects of trustingbeliefs (except the effect of perceived securityon ability and the effect of perceived referencepower on benevolence), perceived Web site qual-ity is found to exert no significant influence onthe formation of initial trust. This suggests thatin order to increase consumers’ trusting beliefsonline, vendors intending to reach the Chinesemarket should try their utmost to build a rep-utable image and display high respect for andconcern about security by adopting advancedtechnologies and stringent rules to protect con-sumers’ privacy rather than investing heavily andsolely on the enhancement of Web site quality.Nevertheless, if established online vendors want

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to or have to encourage consumers’ impulsivepurchases, Web site quality is indeed a desir-able instrument since it directly impacts onlinepurchase intentions.

Moreover, in contrast to prior studies con-ducted in high-trust environments, our researchfinds that trusting intentions (online purchaseintentions) are significantly influenced by con-sumers’ trust in the firm’s integrity rather thantheir trust in its ability or benevolence. Thus, in-tegrity beliefs of consumers should be the toppriority for an online vendor to obtain in thatconsumers’ purchase intentions can hardly beenhanced even when consumers perceived out-standing ability or benevolence of the seller ifthey believe the seller may have ill will andthus may fail to keep its promises or to complywith business ethics. So, it would be reasonablefor online vendors to demonstrate great integrityin order to strengthen consumers’ trusting in-tensions. It is possible for an online vendor toconvey a perception of integrity by providingclearly defined terms and conditions concern-ing transactions and by providing consumerswith guarantees that their rights have been care-fully protected. This finding also provides em-pirical support for the position that trustingbeliefs should be considered separately fromtrusting intentions, for building trusting beliefsdoes not necessarily lead to higher trusting in-tentions. We find trusting beliefs do not al-ways efficiently transform into trusting inten-tions. However, this is not surprising becauseSchlosser and colleagues (2006) have demon-strated that trusting beliefs influence online pur-chase intentions (trusting intentions) only whenrisk is high, or when the behavior requirestrust. But in China, many Web sites have em-ployed the policy of C.O.D., in order to re-lieve consumers’ general concern over financialloss. The method of paying money on receipt ofthe goods greatly reduces the perceived onlinepurchasing risks, hence substantially weaken-ing trusting beliefs’ predictive value on trustingintentions.

In addition, generally we find no support forthe hypothesis that a consumer’s disposition totrust has any significant direct effect on onlineinitial trust, and at the same time we find in-sufficient justification for the moderating effect

of disposition to trust. This finding is consistentwith the view of trust researchers who considerthat the individual’s trust response is more in-fluenced by situational factors than by a dispo-sitional tendency to trust (Kramer 1999; Wickset al. 1999). Therefore, online vendors need notdelve into consumers’ trust propensities. It is ad-visable that online vendors, especially new en-trants, should try their best to attract all potentialcustomers regardless of their level of dispositionto trust. But it is possible that with more expe-rience with an online vendor, trust propensityeventually becomes a significant factor (Kou-faris and Hampton-Sosa 2004). Hence, longitu-dinal research on its effects is needed to explorethat possibility.

Our research does not come without limita-tions. First of all, our study relies on student sam-ples. Several studies in the past have argued ei-ther against using such samples for research pur-poses or that the results should be accepted withcaution (Shuptrine 1975; Soley and Reid 1983).Another limitation is the cross-sectional researchdesign employed. In any model in which causal-ity is suggested, longitudinal studies provide forstronger inferences (Morgan and Hunt 1994).Consequently, longitudinal research needs to beconducted in further studies. Also, factors likeprices, purchasing power, and product varietiesmay affect consumers’ online initial trust. Thus,future research is needed to progress toward afull understanding of such factors that may in-fluence consumer initial trust in online shoppingat a general level.

Our research is just a small step in under-standing online trust and consumer behavior onthe Internet. We hope it will prompt new ques-tions and further studies that will provide moreguidelines and insights for Web-based compa-nies seeking to enhance the trust they instill intheir customers so as to expand their customerbase and thus boost sales.

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RECEIVED: February 23, 2009REVISED: June 24, 2009

ACCEPTED: September 14, 2009

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an integrated model of influential antecedents of online shopping initial trust: empirical evidence...

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