TY - JOUR
AU - Wu, Yuhong
AB - Abstract We developed an interdisciplinary model to examine how online consumers' perceived interactivity, perceived Web assurance and disposition to trust affect their initial online trust. Perceived interactivity is theorized as an interpersonal-based antecedent, disposition to trust as a personality-based antecedent, and perceived Web assurance as an institution-based antecedent to initial online trust. Results indicate that both consumers' perceived interactivity and perceived Web assurance positively influence their initial online trust. Therefore, it is of importance that e-vendors make efforts to enhance online consumers' perceived interactivity of their Web sites as well as addressing consumers' major trust concerns by adopting third-party Web assurance seals. In order to stay competitive in the e-markets, small and lesser-known e-vendors have undertaken many strategies to build online consumer trust. However, the issue remains open on how to effectively and efficiently induce a sufficient level of initial online trust so that successful transactions can be fulfilled. Previous research has identified many important factors affecting consumers' initial online trust, such as consumers' perception of a Web site's usefulness, security, privacy, reputation, quality, and e-vendors' willingness to customize (Chen & Barnes, 2007; Koufaris & Hampton-Sosa, 2004; McKnight, Choudhury, & Kacmar, 2004). Surprisingly, consumers' perceived interactivity of a Web site has not been listed as one of the main concerns, though it is widely regarded as a unique characteristic that distinguishes the Internet from other channels of communication and commerce (Stewart & Pavlou, 2002; Yadav & Varadarajan, 2005). A few studies have examined the impact of interactivity on online trust (e.g., Chen, Griffith, & Shen, 2005; Lee, 2005; Merrilees, 2003), but none has focused on the potential impact of consumers' perceived interactivity on consumers' initial online trust. Meanwhile, although the impact of consumers' perceived Web assurance and disposition to trust on their initial trust are identified as important factors, they have not been thoroughly explored. Our research intends to shed light on these issues. Specifically, inspired by McKnight and Chervany's (2001) integrative model of trust, we propose the following antecedents to consumers' initial online trust: perceived interactivity as an interpersonal-based antecedent, disposition to trust as a personality-based antecedent, and perceived Web assurance as an institution-based antecedent. We believe our research contributes to the literature in three significant ways. First, we have proposed and empirically tested a conceptual model of initial online trust, which is interdisciplinary across information systems, marketing, and communication fields. Second, we have enriched McKnight and Chervany's trust model (2001) by concretizing perceived interactivity as an interpersonal-based trust antecedent, perceived Web assurance as an institution-based trust antecedent, and disposition to trust as a personality-based antecedent. Third, we have found empirical evidence to support the positive effects of perceived interactivity and perceived Web assurance on consumers' initial online trust. The remainder of our paper is organized as follows. First, we propose a conceptual model of initial online trust and develop research hypotheses. Second, we state our research methodology and present our research findings. Finally, we summarize our contributions to the literature, discuss the managerial implications of our research, and suggest future research directions. A Conceptual Model of Initial Online Trust Initial Online Trust In online trust studies, researchers generally adopt a definition of trust from the offline context. Consistent with this practice, we use Doney and Cannon's (1997) definition of trust: “the perceived credibility and benevolence of a target of trust” (p. 36). Its first dimension of credibility concentrates on information provided by a trustee in words or written statements that can be relied on by a trusting party, and its second dimension of benevolence focuses on the degree to which the trustee keeps the trusting party's interests in mind and is motivated to seek joint gains. By “initial” we mean “when two parties first meet or interact” (McKnight, Cummings, & Chervany, 1998, p. 473). Therefore, we define initial online trust in this research as the extent to which a person perceives the credibility and benevolence of the other party with which he or she first interacts in an online environment. Clearly, this definition of initial online trust indicates that the differences between general online trust and initial online trust are subtle yet significant. General online trust usually develops over time beyond the first interaction between a consumer and an e-vendor. For example, consumers' general online trust in Amazon.com tends to be built over a sustained period of time through their own experiences of using Amazon.com or indirect experiences of learning about Amazon.com in the media or via word-of-mouth communication. In contrast, consumers' initial online trust forms during the very first interaction with an e-vendor without prior knowledge or experience. For instance, when a consumer wants to purchase appliance parts from a small and unknown e-vendor like appliancepartspros.com for the first time, he or she develops a certain level of initial online trust in the e-vendor. Previous research on initial online trust (e.g., Chen & Barnes, 2007; Koufaris & Hampton-Sosa, 2004; Lowry et al., 2008; McKnight, Choudhury, & Kacmar, 2002) argues that consumers' initial online trust plays an important role. Koufaris and Hamptson-Sosa (2004) assert that Web-based companies must demonstrate their trustworthiness and credibility to their new customers, who may lack credible and meaningful information about these companies via repeated interactions over time. We believe that small and lesser-known e-vendors will benefit from enhancing online consumers' trust during their first interaction. The way an online consumer perceives his or her first interaction with a small and lesser-known e-vendor determines whether an immediate transaction might follow. One author's recent purchase from applicancepartspros.com illustrates this point. After searching for tips on how to fix his gas dryer's no-heat problem, he found that the dryer needed a new solenoid valve. More online search led him to appliancepartspro.com, which was completely unknown to him, but offered the needed parts at a reasonable price. As he clicked through this vendor's Web site, he found that the site was simple and easy to navigate, and the responses were fast and relevant. Then, a 3-minute live chat with an online agent completed the order. Clearly, his satisfied first interaction with applicancepartspro.com not only resulted in a successful transaction for the e-vendor, but also influenced his future interactions with this site. Now, we are ready to discuss a conceptual model of initial online trust as shown in Figure 1. Although many of the paths in the proposed model have been empirically tested in previous research, we include them for two purposes. One is to develop and test a relatively complete model of initial online trust by adopting key constructs from several research streams across different disciplines (i.e., attitude research, e-commerce research, and interactivity research). The other is to replicate and confirm some of the previous findings. Inspired by McKnight and Chervany's (2001) integrative model of trust, our model identifies three key antecedents: (1) interpersonal-based perceived interactivity; (2) institution-based perceived Web assurance; and (3) personality-based disposition to trust. Based on conceptual models from Jarvenpaa, Tractinsky, and Vitale (2000) and Karson and Fisher (2005a, b), we derive the consequences of initial online trust as attitude toward an e-vendor, attitude toward an e-vendor's Web site, perceived risk, and purchase intention. Figure 1 Open in new tabDownload slide A Proposed Conceptual Model of Initial Online Trust Figure 1 Open in new tabDownload slide A Proposed Conceptual Model of Initial Online Trust Antecedents Perceived Interactivity as an Interpersonal-based Trust Antecedent. Previous studies have found that consumers' perceived interactivity influences their online trust (Chen, Griffith, & Shen, 2005; Lee, 2005; Merrilees, 2003; Wu & Chang, 2005). However, as stated earlier, no prior research has focused on the relationship between perceived interactivity and initial online trust. The key difference between initial online trust and general online trust is that the former forms during the very first interaction in a very short period of time, while the latter develops over time. As such, consumers' initial online trust in an unfamiliar e-vendor (e.g., a new visitor to appliancepartspros.com) tends to be formed very quickly, based on initial impressions of an e-vendor's Web site in the time span of a few clicks. This will limit the opportunities (time) for the e-vendor to elaborate. As a result, consumers' initial online trust is ephemeral and fragile. In contrast, consumers' general online trust tends to be formed over a longer period of time based on more substantial knowledge gained through direct or indirect experiences with the e-vendor. Consequently, consumers' general online trust in an e-vendor is more enduring. Although initial trust is temporary and fragile, research shows that it can be paradoxically high among new employees' encounters (McKnight, Cummings, & Chervany, 1998). This paradox of high initial trust presents opportunities for lesser-known e-vendors because it is possible to establish a sufficiently high level of initial online trust among their first-time visitors so that transactions can be fulfilled. The key is how to optimize the first-time interactions. Thus, it becomes important to pay special attention to study the relationship between perceived interactivity and initial online trust. Researchers find that perceived interactivity plays an important role in shaping online consumers behavior, including their attitude toward a Web site (Jee & Lee, 2000; McMillan & Hwang, 2002; Wu, 1999, 2005), their memory and preference (Chung & Zhao, 2004), and their evaluation on the Web site's effectiveness (Song & Zinkhan, 2008). The interactivity research stream has evolved to two major substreams. One focuses on perceptions of interactivity by users (McMillan & Hwang, 2002; Song & Zinkhan, 2008; Wu, 1999), whereas the other views interactivity as an objective characteristic of a medium or a system (Liu & Shrum, 2002). In this research, we adopt Wu's (2006) conceptualization of interactivity. Wu (2006) defines perceived interactivity of Web sites as “a psychological state experienced by a site-visitor during his or her interaction with a Web site” (p. 91). According to Wu (2006), perceived interactivity manifests in three dimensions: (1) perceived control; (2) perceived responsiveness; and (3) perceived personalization of the site. We adopt this conceptualization for two reasons. First, the implicit interpersonal nature of the perceived interactivity conceptualization fits well with McKnight and Chervany's (2001) interpersonal-based source of trust. Second, when online visitors arrive at a lesser-known e-vendor for the first time, their initial interaction with the e-vendor's Web site plays a critical role in shaping their perceptions of trust in the Web site. Such an initial visitor-site interaction is most likely to be captured by a consumer's perception of interactivity in an online environment, rather than by the objective features or characteristics of interactivity. Thus, perceived interactivity could influence the degree to which online visitors perceive the trustworthiness of a Web site in the following ways. First, the perceived control dimension of perceived interactivity affects the development of trusting beliefs by changing online shoppers' confidence in navigating an e-vendor's Web site. The navigation of an unknown e-vendor's Web site often presents an overload of information to its first-time visitors, who are often very uncertain of where they are or where they have been on the Web site. Langer (1975) claims that when people face an uncertain situation, they will make an initial effort (e.g., seeking out clues to confirm a tentative belief) to assure themselves that they have personal control over the situation. Though these perceptions of control are illusions, they actually can make people become overconfident of their judgments and lead to a high level of trust in an initial encounter between two parties. Similarly, we argue that the same process could occur when online visitors encounter a lesser-known e-vendor's Web site for the first time. Their initial series of clicks on the e-vendor's Web site will frame their perceptions of control over the Web site. While navigating through the cognitive landscape of the Web site, the more comfortable they feel, the higher their level of perceived control, and the more confident they feel about their judgments. Conversely, if they feel lost and frustrated in the navigation process, their perceived level of control is likely to be low, which would negatively impact their confidence in judgments. In fact, the way by which a person's perceived control influences his or her confidence is very similar to how self-efficacy impacts attitude and behavior (Koufaris & Hampton-Sosa, 2002; Wu, 2006). Recent research finds that consumers' online transaction self-efficacy affects their trust building toward an e-vendor (e.g., Kim, Kim, & Hwang, 2009), suggesting that perceived control might also influence the development of trusting beliefs. In this paper, such a process is named self-assessment mechanism. Second, the perceived responsiveness dimension of perceived interactivity influences the development of trusting beliefs through some “token control efforts.”McKnight, Cummings, and Chervany (1998) state that two persons on a first meeting tend to use “token control efforts” because “she or he does not know from experience whether or not the other has the attributes needed to be considered trustworthy” (p. 481). A small effort such as making the other person smile at the first meeting would be an example of “token control efforts” (McKnight, Cummings, & Chervany, 1998). Similarly, when online shoppers visit an e-vendor's Web site for the first time, they conduct an immediate other-assessment by testing how fast the other party (i.e., the Web site) responds to their initial set of actions, such as moving one's mouse over a hyperlinked text or icon, clicking on a play button on a video link, or initiating an online chat if available. The faster and more seamless they perceive the Web site's responses to be, the more confident they perceive they can deal with the Web site successfully. Previous studies find that members' perceptions of others' responsiveness in a virtual community positively affect trust in others' ability, benevolence, and integrity (Ridings, Gefen, & Arinze, 2002). Analogously, we propose that online shoppers' perceived responsiveness of the e-vendor's Web site will also impact their trust in the e-vendor. This perceived responsiveness serves as a feedback mechanism to determine online shoppers' confidence in the judgment of their trusting beliefs toward the Web site. Such a feedback mechanism is named other-assessment. Third, the perceived personalization of perceived interactivity influences the development of trusting beliefs in a way that represents a joint-assessment mechanism in which the results of self-assessment and other-assessment are further evaluated to see if the initial self-other interaction relationship can be elevated to be personally relevant in satisfying one's needs. Just as an offline shopper wishes to have a conversation with a warm, knowledgeable, and sociable sales associate in a brick-and-mortar store, an online shopper also longs to be treated as a unique individual with distinctive needs (Suprenant & Solomon, 1987; Wu, 2006). Consumers are still nostalgic about the intimate feeling of shopping in a small town grocery store, where the owner knows them on a first-name basis and the trust between the customers and the store owner is usually high. Undoubtedly, if an e-vendor can simulate that kind of personalized visitor-site interactions, it can induce a high level of initial online trust to facilitate a successful transaction. Previous research shows that personalization affects trust. Komiak and Benbasat (2006) find that perceived personalization significantly increases customers' intention to adopt recommendation agents by increasing cognitive trust and emotional trust. Ball, Coelho, and Vilares (2006) also indicate that personalization increases benevolence trust, which in turn increases bank customers' loyalty. In this research, perceived personalization, one of the three dimensions of perceived interactivity of a Web site, is likely to influence online shoppers' initial trust of an e-vendor. Based on the aforementioned consideration, we propose that: H1a: Consumers' perceived interactivity will positively influence their initial online trust in an e-vendor. Consistent with previous research's findings with regard to the relationship between perceived interactivity, attitude toward brand, attitude toward advertisement, and attitude toward a Web site (McMillan & Hwang, 2002; Wu, 1999, 2005), we hypothesize the following: H1b: Consumers' perceived interactivity will positively influence their attitude toward an e-vendor. H1c: Consumers' perceived interactivity will positively influence their attitude toward an e-vendor's Web site. Perceived Web Assurance as an Institution-Based Trust Antecedent. According to McKnight and Chervany (2001), consumers' beliefs about a Web site's structural assurance play an important role in institution-based trust. Structural assurance means that such contextual conditions as promises, contracts, regulations, and guarantees are in place to be conducive to success. As the online environment presents additional uncertainties and risks compared to the offline environment, consumers should respond well to such structural assurances. The literature suggests three major concerns from online shoppers: (1) privacy; (2) security; and (3) reliability or transaction integrity. In this research, we define perceived Web assurance as online consumers' perceptions of an e-vendor's efforts in addressing privacy, security, and transaction integrity concerns. Lesser-known e-vendors have used various strategies to signal their trustworthiness and to ease online shoppers' concerns over online shopping (e.g. Wang, Beatty, & Foxx, 2002). Displaying third-party Web assurance seal or Trustmark as a structural assurance (e.g. Aiken & Boush, 2006) is one of such strategies. Strategies aiming at promoting online consumers' perceived Web assurance generally involve “impersonal structures” (e.g. third-party assurance seals), which reflects the notion of institution-based trust (McKnight and Chervany, 2001). Previous studies demonstrate that the structural assurance of a Web site contributes positively to consumers' initial online trust toward the site (Gefen, Karahanna, & Straub 2003; McKnight, Choudhury, & Kacmar 2004). Based on the preceding analyses, we propose that: H2a: Consumers' perceived Web assurance will positively influence their initial online trust in an e-vendor. When online visitors perceive that a Web site makes serious efforts in addressing the privacy, security, and integrity issues of online transaction by using such cues as third-party Web assurance seals, their perceived uncertainty and risk associated with online shopping (Kim & Benbasat, 2003) are likely to be reduced. Therefore, with a higher level of perceived Web assurance, consumers would feel less anxious and become more confident in their interactions with the Web site. Consequently, they will perceive more positive interactions with the Web site and form more favorable attitudes toward the Web site. To put them formally, we propose that: H2b: Consumers' perceived Web assurance will negatively influence their perceived risk. H2c: Consumers' perceived Web assurance will positively influence their perceived interactivity. H2d: Consumers' perceived Web assurance will positively influence their attitude toward an e-vendor's Web site. Disposition to Trust as a Personality-Based Trust Antecedent. Disposition to trust is a personality construct that reflects the extent to which a person demonstrates “a consistent tendency to be willing to depend on others across a broad spectrum of situations and persons” (McKnight, Cummings, & Chervany, 1998, p. 477). Such a tendency is not based on direct experience with or knowledge of a specific trusted party (e.g., an unknown e-vendor), but reflects one's faith in humanity and tendency to trust others in general based on his or her lifelong experience and socialization (Gefen, 2000). Because initial online trust presupposes a new relationship, we can infer that disposition to trust would have a significant effect on consumers' initial online trust. Thus, we propose that: H3a: Consumers' disposition to trust will positively influence their initial online trust in an e-vendor. Disposition to trust has two subconstructs: (1) Faith in humanity, meaning the extent to which one believes that nonspecific others are trustworthy and (2) trusting stance, meaning one's intentional willingness to depend on others (McKnight, Cummings, & Chervany, 1998). In other words, if someone has a high disposition to trust, he or she is more likely to believe in the goodness of human beings and is more willing to lend credit of trust for an initial interaction. People of high disposition to trust are more credulous or naÏve (Gefen, 2000), and they are more likely to trust e-vendors who make efforts, such as displaying third-party Web assurance seals, to address consumers' perceptions of privacy, security, and integrity issues. Consequently, people of high disposition to trust are more inclined to frame initial interactions with an unfamiliar Web site in a more positive manner until the trustee's behavior proves to be untrustworthy. H3b: Consumers' disposition to trust will positively influence their perceived Web assurance. Because people of high disposition to trust are more credulous, they tend to perceive less risk associated with an unfamiliar situation than their counterparts (Ridings, Gefen, & Arinze, 2002). This appears to be commonsensical, but the empirical findings are mixed. For example, McKnight, Kacmar, and Choudhury (2004) find empirical support that disposition to trust influences risk perceptions, whereas Kim, Kim, and Hwang (2009) find that no significant relationship exists between disposition to trust and perceived risk. Thus, it is of value to test this relationship in our study. Consequently, we hypothesize the following: H3c: Consumers' disposition to trust will be negatively related to their perceived risk. Consequences Our conceptual model of initial online trust specifies three direct consequences of initial online trust—perceived risk, attitude toward an e-vendor, and attitude toward an e-vendor's Web site. We derive these consequences based on two conceptual models from the current literature in two academic fields: (1) Jarvenppa, Tractinsky, and Vitale's (2000) consumer trust model and (2) Karson and Fisher's (2005a, b) extended dual mediation model. Jarvenppa, Tractinsky, and Vitale (2000) find that consumers' online trust in a store is positively related to their attitude toward the online store but negatively related to their perceived risk. In addition, consumers' attitude toward an e-vendor has a positive impact on their willingness to buy, but their perceived risk has a negative impact on their willingness to buy. Also, consumers' perceived risk is inversely related to their attitude toward an online store. Consistent with their research findings, we hypothesize the following: H4a: Consumers' initial online trust will negatively influence their perceived risk. H4b: Consumers' initial online trust will positively influence their attitude toward an e-vendor. H4c: Consumers' perceived risk will negatively influence their attitude toward an e-vendor. H4d: Consumers' perceived risk will negatively influence their purchase intention. H4e: Consumers' attitude toward an e-vendor will positively influence their purchase intention. In Jarvenppa, Tractinsky, and Vitale's (2000) model, attitude toward the Web site is not considered. However, recent research (e.g., Karson and Fisher, 2005a, b) highlights the importance of consumers' attitude toward the Web site. Karson and Fisher (2005a, b) find that consumers' attitude toward the Web site has a stronger impact on their purchase intention than consumers' attitude toward the brand. The reason is that consumers' attitude toward a Web site also contains nonproduct claims (e.g., site security and site responsiveness) that are relevant to respondents in their purchase intention evaluations. Karson and Fisher (2005a, b) also show that cognitive responses to the Web site are different from those to the brand because of the existence of nonproduct related claims. As initial online trust reflects the extent to which online consumers perceive the credibility and benevolence of an e-vendor, this trusting belief is likely to impact cognitive responses to the Web site. Based on these considerations, we hypothesize the following: H5a: Consumers' attitude toward an e-vendor's Web site will positively influence their attitude toward an e-vendor. H5b: Consumers' attitude toward an e-vendor's Web site will positively influence their purchase intention. H5c: Consumers' initial online trust will positively influence their attitude toward an e-vendor's Web site. Method Stimuli We designed an e-vendor's Web site selling text books, laptops, perfume, and clothing accessories to simulate college students' online shopping (see Appendix A for a screen shot of the Web site's homepage). It had six tabs on the navigation bar: home, company, products, customer service, return policy, and contact. All Web pages contained the credit card symbol signs of American Express, Visa, and MasterCard. These symbols were included to convey Web site credibility as they represented institutional cues to online shoppers. Eight versions of the same Web site were created with variations on the presence or absence of third-party Web assurance seals to address the three major concerns of online shopping—privacy protection, transaction security, and transaction integrity. Specifically, one version of the Web site had no third-party Web assurance seal displayed at all, one version had all three seals displayed, three versions had one of the three seals displayed respectively, and the remaining three versions had a combination of two of the three seals displayed. We used these seals, which we named as CyberTrust, to measure the perceived Web assurance; they were displayed prominently on the navigation bar. The detailed descriptions for the three seals (CyberTrust Privacy, CyberTrust Security, and CyberTrust Integrity) are shown in Appendix B. We used 32 business majors in a southern university in the United States to pretest eight versions of the Web site in order to detect any possible problems with site navigation and content. Sample Profile Two hundred fifty-two students from four university campuses in the United States participated in the study. Forty-two percent of them were female. Eighty-six percent of them were less than 25 years old and 11%t of them were between 25 and 30. The remaining 3% were above 30 years of age. Approximately 83% of the participants had prior online shopping experience. On average, in the last 6 months, this convenience sample shopped online about six times and spent approximately 200 U.S. dollars. They considered themselves to be highly skillful in surfing the Internet with a mean score of 5.8 on a 7-point scale (with 1 being the least skillful and 7 being the most skillful). Data Collection Data was collected in a laboratory setting at four university campuses. After the participants were seated comfortably in front of a computer screen, we told them that an e-vendor with college students as its target audience needed to test-run its online store. We instructed the participants to browse the Web site for 10 minutes by following a predetermined path. Such a process ensured that all participants had carefully read through the Web contents including the description of CyberTrust seal. The seal was shown in a pop-up window (see the sample content in Appendix B). After the 10-minute guided browsing, we told the participants to freely explore the Web site for 5 more minutes. We then distributed questionnaires for them to fill out. We obtained 252 responses in 10 sessions. Measures We used Gefen's (2000) scale to measure disposition to trust (α = .83). Each of the three variables (i.e., privacy protection, transaction security, and transaction integrity) was measured by three items and a composite score was formed by averaging the item scores to measure perceived Web assurance (α = .93). We adopted Wu's (2006) scale to measure perceived interactivity, and Doney and Cannon's scale (1997) to measure initial online trust (α = .83). We used Jarvenpaa, Tractinsky, and Vitale's (2000) scales to measure attitude an e-vendor (α = .92), perceived risk (α = .87), and purchase intention (α = .90). We adopted Chen and Wells' (1999) scale to measure attitude toward an e-vendor's Web site (α = .85). All items were on a 7-point Likert-type scale. The scales used in our research are listed in Appendix C. Results We followed Anderson and Gerbing's (1988) recommendations in analyzing data by adopting a two-stage process—(1) the measurement model assessment, and (2) the structural model assessment. Measurement Model Assessment It is important to distinguish between formative and reflective constructs when assessing factorial validity (Diamantopoulos & Winklhofer, 2001; Lowry et al., 2008), because it is not meaningful to use traditional methods to establish reliability and validity for formative constructs (Lowry et al., 2008; Petter, Straub, & Rai, 2007). In our study, perceived interactivity is a formative construct (Wu, 2006), so it is excluded from the following confirmatory factor analyses. Also, Jarvis, Mackenzie, and Podsakoff (2003) suggest that initial trust, perceived risk, and perceived Web assurance are all formative constructs, so these three are also excluded from confirmatory factor analyses. We conducted a series of confirmatory factor analyses for the four reflective variables in the proposed research model, including initial online trust, attitude toward an e-vendor, attitude toward an e-vendor's Web site, perceived risk, perceived Web assurance, and disposition to trust. We calculated the composite reliability (CR) and average variance extracted (AVE) for each construct using the formulas proposed by Hair et al. (1998). Table 1 shows that the four reflective constructs demonstrate adequate reliability, as their composite reliability scores are higher than .70 (Hair et al., 1998). Meanwhile, these constructs have shown convergent validity, as each construct's AVE exceeds the 0.5 benchmark for convergent validity (Fornell & Larcker, 1981). Furthermore, two of the four constructs have demonstrated discriminant validity, because the square root of the average variance extracted for each construct in bold values (Table 2) is greater than the correlation between the construct and other constructs in corresponding rows and columns (Fornell & Larcker, 1981). The two constructs that fall short of discriminant validity tests are attitude toward an e-vendor's site and attitude toward an e-vendor. Given that the relationship between these two constructs is similar to that between attitude toward the brand and attitude toward the advertisement, a high correlation of .83 is not surprising. It is also below the .85 correlation coefficient threshold suggested by Kline (1998). Table 1 Reliability of the Reflective Constructs in the Model Constructs . No. of items . Cronbach's alpha . Composite reliability . Average variance extracted . Disposition to trust 4 .83 .83 .55 Attitude toward an e-vendor's Web site 6 .85 .86 .52 Attitude toward an e-vendor 6 .92 .92 .65 Purchase intention 4 .90 .91 .73 Constructs . No. of items . Cronbach's alpha . Composite reliability . Average variance extracted . Disposition to trust 4 .83 .83 .55 Attitude toward an e-vendor's Web site 6 .85 .86 .52 Attitude toward an e-vendor 6 .92 .92 .65 Purchase intention 4 .90 .91 .73 Open in new tab Table 1 Reliability of the Reflective Constructs in the Model Constructs . No. of items . Cronbach's alpha . Composite reliability . Average variance extracted . Disposition to trust 4 .83 .83 .55 Attitude toward an e-vendor's Web site 6 .85 .86 .52 Attitude toward an e-vendor 6 .92 .92 .65 Purchase intention 4 .90 .91 .73 Constructs . No. of items . Cronbach's alpha . Composite reliability . Average variance extracted . Disposition to trust 4 .83 .83 .55 Attitude toward an e-vendor's Web site 6 .85 .86 .52 Attitude toward an e-vendor 6 .92 .92 .65 Purchase intention 4 .90 .91 .73 Open in new tab Table 2 Discriminant Validity . 1 . 2 . 3 . 4 . 1. Disposition to trust .74 2. Attitude toward an e-vendor's Web site .16 .72 3. Attitude toward an e-vendor .16 .83 .81 4. Purchase intention .17 .72 .71 .85 . 1 . 2 . 3 . 4 . 1. Disposition to trust .74 2. Attitude toward an e-vendor's Web site .16 .72 3. Attitude toward an e-vendor .16 .83 .81 4. Purchase intention .17 .72 .71 .85 Note: Diagonal elements in bold are the square root of average variance extracted (AVE) between the constructs and their indicators. Off-diagonal elements are correlations between constructs. Open in new tab Table 2 Discriminant Validity . 1 . 2 . 3 . 4 . 1. Disposition to trust .74 2. Attitude toward an e-vendor's Web site .16 .72 3. Attitude toward an e-vendor .16 .83 .81 4. Purchase intention .17 .72 .71 .85 . 1 . 2 . 3 . 4 . 1. Disposition to trust .74 2. Attitude toward an e-vendor's Web site .16 .72 3. Attitude toward an e-vendor .16 .83 .81 4. Purchase intention .17 .72 .71 .85 Note: Diagonal elements in bold are the square root of average variance extracted (AVE) between the constructs and their indicators. Off-diagonal elements are correlations between constructs. Open in new tab Structural Model Assessment We conducted structural equation modeling using AMOS 16.0. Structural equation modeling was considered suitable for analyzing experimental data (Baron & Kenny, 1986; MacKenzie, 2001). Table 3 summarizes the path estimates and goodness-of-fit indexes. According to the recommended cut-off values (Byrne, 2001; Hair et al., 2006), our model fits the data reasonably well: Chi-square = 595.5, df = 216, p < .001; RFI (Relative Fit Index) = .92; TLI (Tucker Lewis Index) = .90; CFI (Comparative Fit Index) = .92; and RMSEA = .08. Table 3 Model Fit and Tests of Proposed Relationships Structural Path . Hypothesis . Standardized Coefficients . Perceived interactivity → initial online trust H1a .18*** (.053) Perceived interactivity → attitude toward an e-vendor H1b −.03 (.070) Perceived interactivity → attitude toward an e-vendor's Web site H1c .45*** (.076) Perceived Web assurance → initial online trust H2a .66*** (.043) Perceived Web assurance → perceived risk H2b −.43*** Perceived Web assurance → perceived interactivity H2c .59*** (.058) Perceived Web assurance → attitude toward an e-vendor's Web site H2d .30*** (.078) Disposition to trust → initial online trust H3a .05 (.058) Disposition to trust → perceived Web assurance H3b .09 (.058) Disposition to trust → perceived risk H3c −.04 (.039) Initial online trust → perceived risk H4a −.43*** (.076) Initial online trust → attitude toward an e-vendor H4b .10 (.067) Perceived risk → attitude toward an e-vendor H4c −.36*** (.044) Perceived risk → purchase intention H4d −.24 (.138) Attitude toward e-vendor → purchase intention H4e .84* (.423 Attitude toward e-vendor's Web site → attitude toward an e-vendor H5a .80*** (.100) Attitude toward e-vendor's Web site → purchase intention H5b .05 (.341) Initial online trust → attitude toward an e-vendor's Web site H5c .25*** (.078) Model fit indexes: Chi-square = 595.5 df = 216, p < .001; RFI = .92 TLI = .90 CFI = .92 RMSEA = .08 Structural Path . Hypothesis . Standardized Coefficients . Perceived interactivity → initial online trust H1a .18*** (.053) Perceived interactivity → attitude toward an e-vendor H1b −.03 (.070) Perceived interactivity → attitude toward an e-vendor's Web site H1c .45*** (.076) Perceived Web assurance → initial online trust H2a .66*** (.043) Perceived Web assurance → perceived risk H2b −.43*** Perceived Web assurance → perceived interactivity H2c .59*** (.058) Perceived Web assurance → attitude toward an e-vendor's Web site H2d .30*** (.078) Disposition to trust → initial online trust H3a .05 (.058) Disposition to trust → perceived Web assurance H3b .09 (.058) Disposition to trust → perceived risk H3c −.04 (.039) Initial online trust → perceived risk H4a −.43*** (.076) Initial online trust → attitude toward an e-vendor H4b .10 (.067) Perceived risk → attitude toward an e-vendor H4c −.36*** (.044) Perceived risk → purchase intention H4d −.24 (.138) Attitude toward e-vendor → purchase intention H4e .84* (.423 Attitude toward e-vendor's Web site → attitude toward an e-vendor H5a .80*** (.100) Attitude toward e-vendor's Web site → purchase intention H5b .05 (.341) Initial online trust → attitude toward an e-vendor's Web site H5c .25*** (.078) Model fit indexes: Chi-square = 595.5 df = 216, p < .001; RFI = .92 TLI = .90 CFI = .92 RMSEA = .08 Note: Standard errors are in parentheses. *p < .05. **p < .01 ***p < .001 Open in new tab Table 3 Model Fit and Tests of Proposed Relationships Structural Path . Hypothesis . Standardized Coefficients . Perceived interactivity → initial online trust H1a .18*** (.053) Perceived interactivity → attitude toward an e-vendor H1b −.03 (.070) Perceived interactivity → attitude toward an e-vendor's Web site H1c .45*** (.076) Perceived Web assurance → initial online trust H2a .66*** (.043) Perceived Web assurance → perceived risk H2b −.43*** Perceived Web assurance → perceived interactivity H2c .59*** (.058) Perceived Web assurance → attitude toward an e-vendor's Web site H2d .30*** (.078) Disposition to trust → initial online trust H3a .05 (.058) Disposition to trust → perceived Web assurance H3b .09 (.058) Disposition to trust → perceived risk H3c −.04 (.039) Initial online trust → perceived risk H4a −.43*** (.076) Initial online trust → attitude toward an e-vendor H4b .10 (.067) Perceived risk → attitude toward an e-vendor H4c −.36*** (.044) Perceived risk → purchase intention H4d −.24 (.138) Attitude toward e-vendor → purchase intention H4e .84* (.423 Attitude toward e-vendor's Web site → attitude toward an e-vendor H5a .80*** (.100) Attitude toward e-vendor's Web site → purchase intention H5b .05 (.341) Initial online trust → attitude toward an e-vendor's Web site H5c .25*** (.078) Model fit indexes: Chi-square = 595.5 df = 216, p < .001; RFI = .92 TLI = .90 CFI = .92 RMSEA = .08 Structural Path . Hypothesis . Standardized Coefficients . Perceived interactivity → initial online trust H1a .18*** (.053) Perceived interactivity → attitude toward an e-vendor H1b −.03 (.070) Perceived interactivity → attitude toward an e-vendor's Web site H1c .45*** (.076) Perceived Web assurance → initial online trust H2a .66*** (.043) Perceived Web assurance → perceived risk H2b −.43*** Perceived Web assurance → perceived interactivity H2c .59*** (.058) Perceived Web assurance → attitude toward an e-vendor's Web site H2d .30*** (.078) Disposition to trust → initial online trust H3a .05 (.058) Disposition to trust → perceived Web assurance H3b .09 (.058) Disposition to trust → perceived risk H3c −.04 (.039) Initial online trust → perceived risk H4a −.43*** (.076) Initial online trust → attitude toward an e-vendor H4b .10 (.067) Perceived risk → attitude toward an e-vendor H4c −.36*** (.044) Perceived risk → purchase intention H4d −.24 (.138) Attitude toward e-vendor → purchase intention H4e .84* (.423 Attitude toward e-vendor's Web site → attitude toward an e-vendor H5a .80*** (.100) Attitude toward e-vendor's Web site → purchase intention H5b .05 (.341) Initial online trust → attitude toward an e-vendor's Web site H5c .25*** (.078) Model fit indexes: Chi-square = 595.5 df = 216, p < .001; RFI = .92 TLI = .90 CFI = .92 RMSEA = .08 Note: Standard errors are in parentheses. *p < .05. **p < .01 ***p < .001 Open in new tab We followed Jarvis, Mackenzie, and Podsakoff's (2003) recommendation by entering both formative and reflective constructs as latent variables, but the model was not identified. Therefore, we entered formative constructs as composite scores and reflective ones as latent variables. The model was identified and the fit index was deemed reasonable. All path relations were examined and they were theoretically sound. It should be noted that we treated perceived interactivity as a single factor variable. Although we have explained how perceived interactivity might influence trust development in three different ways in accordance with the three dimensions of perceived interactivity, it is our intent and focus to treat perceived interactivity as an interpersonal-based trust antecedent as theorized in McKnight and Chervany's (2001) integrative model of online trust. Figure 2 and Table 3 summarize the results of our research. As shown in Table 3, perceived interactivity has a significant positive impact on consumers' initial online trust and attitude toward an e-vendor's Web site but not attitude toward an e-vendor. Thus, H1a and H1c are supported, but H1b is not. The significant effects of perceived interactivity on consumers' attitude toward an e-vendor's Web site reaffirm the important role of perceived interactivity in attitude formation as revealed in previous research (e.g., Sicilia, Ruiz, & Munuera, 2005). Figure 2 Open in new tabDownload slide A Tested Conceptual Model of Initial Online Trust
Note: Dashed lines indicate nonsignificant paths at p = .05; all solid line paths are significant at p < .01. Figure 2 Open in new tabDownload slide A Tested Conceptual Model of Initial Online Trust
Note: Dashed lines indicate nonsignificant paths at p = .05; all solid line paths are significant at p < .01. More importantly, the effect of perceived interactivity on consumers' initial online trust demonstrates that the perceptions of initial consumer-site interactions are vital to initial online trust formation. A posthoc SEM analysis is conducted to see how each dimension of perceived interactivity might affect initial online trust. It reveals that all three dimensions have a significant effect on initial online trust (path estimates: perceived control to initial online trust (λ = .30, p < .001); perceived responsiveness to initial online trust (λ = .20, p < .001); perceived personalization to initial online trust (λ = .40, p < .001)). The fit indices indicate that the model fits the data reasonably well (χ2 = 144.82, df = 52, p = .000; CFI = .91; IFI = .94; TLI = .91; CFI = .937; and RMSEA = .08). Table 3 also shows that consumers' perceived Web assurance has a significant positive effect on their initial online trust, perceived interactivity, and attitude toward an e-vendor's Web site, yet it has a significant negative effect on perceived risk. Thus, H2a, H2b, H2c, and H2d are supported. These results demonstrate that an e-vendor's efforts in using institutional cues to signal trustworthiness are well rewarded. The institutional cues, such as third-party Web assurance seals, could help enhance online consumers' initial trust in a lesser-known e-vendor, boost their confidence in their interactions with the e-vendor's Web site, shift their attitude in a more positive way toward the Web site, and alleviate their perceived risks associated with shopping from the e-vendor's Web site. We predicted that consumers' disposition to trust would positively impact their initial online trust (H3a). However, Table 3 shows that the proposed positive relationship between disposition to trust and initial online trust is not empirically confirmed. Thus, H3a is not supported. We also predicted that consumers' disposition to trust would have a positive effect on their perceived Web assurance. However, the results fail to support such an effect. Hence, H3b is not supported. The nonsignificant effects of disposition to trust on perceived Web assurance and initial online trust are not totally surprising given that the literature contains mixed findings. The Pearson correlation between initial online trust and disposition to trust is .14 (p < .05; two-tailed). Thus, we concur with other researchers' explanations that the other more important trust antecedent factors—perceived Web assurance and perceived interactivity—have displaced much of dispositional trust's effect on initial online trust. Similar explanations have been offered by other researchers (e.g., Lowry et al., 2008; McKnight, Choudhury, & Kacmar 2004)). We anticipated that disposition to trust would negatively impact perceived risk (H3c), but the result indicates that it does not influence perceived risk. This finding is consistent with that in Kim, Kim and Hwang's study (2009). Kim, Kim and Hwang (2009) hint that online transaction self-efficacy might displace much of the effect of disposition to trust on perceived risk. A posthoc correlation analysis confirms this notion, as the Pearson correlation between disposition to trust and perceived risk is −.15 (p < .05; two-tailed). Thus, we believe that in the presence of stronger cues like perceived Web assurance, disposition to trust becomes less important in influencing consumers' perceived risk. We predicted that consumers' initial online trust would negatively influence their perceived risk (H4a) and positively influence their attitude toward an e-vendor (H4b) while consumers' perceived risk would negatively influence their attitude toward an e-vendor (H4c) and purchase intention (H4d). Meanwhile, consumers' attitude toward an e-vendor would positively influence their purchase intention (H4e). The results show that consumers' initial online trust indeed has a negative impact on their perceived risk, which negatively influences their attitude toward an e-vendor and purchase intention. However, consumers' initial online trust shows no direct significant impact on consumers' attitude toward an e-vendor. Their attitude toward an e-vendor reveals a positively influence on purchase intention. Thus, H4a, H4c, H4d, and H4e are supported, but H4b is not supported. We anticipated that consumers' attitude toward an e-vendor's Web site would positively influence their attitude toward an e-vendor (H5a) and their purchase intention (H5b). Further, we proposed that consumers' initial online trust would positively influence their attitude toward an e-vendor's Web site (H5c). The results indicate that H5a and H5c are supported, but H5b is not supported. A closer examination of the results reveals that although consumers' initial online trust does not have a direct effect on their attitude toward an e-vendor, it has an indirect effect on it via the mediation of attitude toward an e-vendor's Web site and perceived risk. Meanwhile, the effect of consumers' perceived risk on their purchase intention is mediated through attitude toward an e-vendor, although a direct relationship is not confirmed in this study. These findings confirm the important role of consumers' attitude toward an e-vendor's Web site in their purchase intention, and validate the contribution of our integrated trust model. Discussions, Managerial Implications, and Future Research Our research examines the role of consumers' perceived interactivity of the Web site, their perceived Web assurance from the Web site, and their disposition to trust in the formation of their initial online trust within a conceptual model of initial online trust. We find empirical evidence to support our notion of incorporating perceived interactivity as an interpersonal-based trust antecedent: perceived interactivity has a positive impact on consumers' initial online trust in a lesser-known e-vendor. We also find that perceived Web assurance is a robust institution-based antecedent to consumers' initial online trust, though we do not find the same effect for disposition to trust as a personality-based antecedent to consumers' initial online trust. Linking perceived interactivity and trust is not a new concept, yet our proposition to treat perceived interactivity as an interpersonal-based trust antecedent is original, and our empirical evidence supports this proposition. In McKnight and Chervany's (2001) integrative model of online trust, the interpersonal-based trust refers to trusting beliefs and intentions that reflect the idea that “interactions between people and cognitive-emotional reactions to such interactions determine behavior” (p. 42). This suggests that interpersonal trust is formed based upon interactions, and our proposition has definitely made it explicit, specific, and measurable. This linkage between consumers' perceived interactivity and their initial online trust enriches McKnight and Chervany's integrative model of online trust, which may help bring together the research streams of the interactivity and online trust. Our empirical findings have several important theoretical implications. First, we have demonstrated how the perceptions of consumer-Web site interactions, also known as consumers' perceived interactivity, shape their initial online trust. Online shoppers perceive their interactions with an e-vendor's Web site in three different ways that affect trusting belief development. Perceived control represents the self-assessment mechanism; perceived responsiveness reflects the other-assessment, or feedback-assessment, mechanism. Both mechanisms ultimately influence consumers' confidence in a judgment. Perceived personalization represents a joint-assessment of the interaction relationship between the two parties (i.e., self and other) in terms of meeting one's needs in a personally relevant way. Second, our finding that consumers' perceived Web assurance has a positive impact on their initial online trust validates Yang et al.'s (2005) finding that displaying a Web assurance seal on an e-vendor's Web site has an indirect effect on consumers' trust via the perception of such a seal. That is, it is not the displaying of a Web assurance seal itself but the perception of it that matters in trust formation. If an e-vendor's visitors pay no attention to a Web assurance seal or if they fail to understand its purpose, the seal may not achieve its intended effect even if it is displayed prominently on an e-vendor's Web site. This might help explain why some studies fail to find a direct effect of a third-party Web assurance seal on consumers' online trust. For example, Metzger (2006) finds that the display of a privacy assurance seal has no significant impact on consumers' trust. It is possible that consumers' perceived privacy assurance might mediate the effect of the displaying of a privacy assurance on consumers' trust. It appears that consumers' awareness and knowledge about the purpose and significance of a Web assurance are essential to achieving its intended purpose of enhancing consumers' initial online trust. Thus, all seal providers should make serious efforts to promote their seals to online consumers. Third, our conceptual model of initial online trust is interdisciplinary. We define initial online trust by drawing it from the marketing and management literatures. We also draw from information systems, advertising, and marketing literatures in specifying the antecedents and consequences of consumers' initial online trust. Such an approach proves to be valuable in our research. For example, we extend Jarvenpaa, Tractinsky, and Vitale's (2000) online shopping model by including the construct of consumers' attitude toward an e-vendor's Web site (Chen & Wells, 1999; Karson & Fisher, 2005a, b). Our results reveal that consumers' attitude toward a Web site mediates the effect of initial online trust on their attitude toward the e-vendor, confirming the results by Karson and Fisher (2005a, b) that attitude toward the brand and attitude toward the brand's Web site are distinctive enough to be specified as separate constructs. We believe our study provides three practical implications for e-vendors. First, because consumers' perceived Web assurance enhances their initial online trust, reduces their perceived risk, increases their perceived interactivity and attitude toward an e-vendor's Web site, online marketers ought to invest resources in addressing online consumers' three majors concerns—privacy protection, transaction security, and transaction integrity. Using third-party Web assurance seals could be one of the strategies. Second, because consumers' perceived interactivity plays a critical role in shaping their initial online trust and influencing their attitude toward an e-vendor's Web site, it is of vital importance for e-vendors to pay close attention to online shoppers' perceived interactivity of its Web site. As perceived interactivity affects trust development in three ways via each of its three dimensions—perceived control, perceived responsiveness, and perceived personalization, online marketers can improve its Web site effectiveness by focusing on these three aspects. The following discussions suggest some tactics. Online marketers need to enhance online visitors' sense of perceived control during their navigation of the cognitive landscape of a Web site. Like driving on an unfamiliar roadway, online visitors should be provided with clear and simple signs as to where they have been, where they are, and where they are heading. Simple design could be the best choice. For example, google.com has a surprisingly simple interface. Web site designers can also boost visitors' perceived control by breaking down large chunks of content into small yet relevant pieces of information presented in a straightforward manner; visitors thus feel that they are in control over the pace or rhythm of their interaction with the information being presented. Online marketers also need to augment visitors' perceived responsiveness by simulating the immediacy of a “face-to-face” conversation. While visitors click through the Web site, they anticipate fast and immediate responses to each and every mouse click or key stroke. Thus, Web sites should avoid using big-size audio/images/video files as well as files that require downloading additional applications (e.g., Flash player). Something as simple as building a text color change function would delight visitors because they perceive a response when their mouse moves over the text. Clearly, compared with all other design elements, online discussion groups, chat rooms, and live agents would be some of the most effective ways to enhance perceived responsiveness. In a computer-mediated communication environment that often tends to be impersonal, visitors desire to be treated as a human being or a guest. As the level of message personalization increases, the perceptions of interactivity and Web site effectiveness are enhanced (Song & Zinkhan, 2008). Therefore, it is imperative to have an in-depth understanding of an e-vendor's key target audience so as to build empathy and sensitivity through its language, design, ambience, and product or service offerings on the Web site. Finally, this study has demonstrated the mediating role of both attitude toward an e-vendor and attitude toward an e-vendor's Web site with regard to the effects of both initial online trust and perceived risk on purchase intention. This means that traditional attitude toward advertisement and attitude toward brand research streams remain highly relevant to our understanding of online consumer behavior as long as we take into consideration the unique characteristics of online environment. Our research has limitations. First, since we conducted a laboratory study, students may not feel it the same as a real online shopping experience, though we made substantial efforts to simulate their real shopping experience by designing a professional-looking Web site and including products relevant to college student participants. Second, because we used a convenient student sample, any broad generalization of our results needs to be taken with caution. Third, while our guided browsing allowed the participants to fully explore every part of the Web site including any third-party Web assurance seal descriptions if presented, we might have restricted their sense of freedom during the first 10 minutes of browsing, which may have lowered their perceived level of interactivity of the Web site. We believe the following issues are worth pursuing in future research. A similar field experiment can be conducted to address the limitation of low external validity in a lab experiment like ours. If the same results can be found in a field experiment, then our findings will be more generalizable. Also, we did not find a significant effect of consumers' disposition to trust on their initial online trust or their perceived Web assurance in this research. We speculate that this might also be due to the homogeneity of our convenient student sample. Therefore, a broadly based sample consisting of different age groups can be used in a future research to validate this explanation. Finally, future research could concentrate on the underlying processes through which perceived interactivity influences initial online trust, and a longitudinal study could be conducted to track whether effects of perceived interactivity on initial online trust would endure. References Aiken , K. D. , & Boush , D. M. ( 2006 ). Trustmarks, objective-source ratings, and implied investments in advertising: Investigating online trust and the context-specific nature of Internet signals . Journal of the Academy of Marketing Science , 34 ( 3 ), 308 – 323. Google Scholar Crossref Search ADS WorldCat Anderson , J. C. & Gerbing , D. W. ( 1988 ). Structural equation modeling in practice: A review and recommended two-step approach . Psychological Bulletin , 103 ( 3 ), 411 – 423. Google Scholar Crossref Search ADS WorldCat Ball , D. , Coelho , P. S., & Vilares , M. J. ( 2006 ). Service personalization and loyalty. Journal of Service Marketing, 20 ( 6 ), 391 – 403. Baron , R. M. , & Kenny , D. A. ( 1986 ). The moderator mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations . Journal of Personality and Social Psychology , 51 ( 6 ), 1173 – 1182. Google Scholar Crossref Search ADS PubMed WorldCat Byrne , B. M. ( 2001 ). Structural equation modeling with AMOS: Basic concepts, applications, and programming . Mahwah, NJ: Lawrence Erlbaum Associates . Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC Chen , Y.H. , & Barnes , S. ( 2007 ). Initial trust and online buyer behavior . Industrial Management & Data Systems , 107 ( 1 ), 21 – 36. Google Scholar Crossref Search ADS WorldCat Chen , Q. , & Wells , W. D. ( 1999 ). Attitude toward the site . Journal of Advertising Research , 39 ( 5 ), 27 – 37. Google Scholar OpenURL Placeholder Text WorldCat Chen , Q. , Griffith , D. A., & Shen , F. ( 2005 ). The effects of interactivity on cross-channel communication effectiveness . Journal of Interactive Advertising , 5 ( 2 ). Retrieved August 8, 2008 , from http://www.jiad.org/vol5/no2/chen/index.htm. Google Scholar OpenURL Placeholder Text WorldCat Chung , X. & Zhao , X. ( 2004 ). Effects of perceived interactivity on Web site preference and memory: The role of personal motivation . Journal of Computer-Mediated Communication , 10 ( 1 ). Retrieved January 16, 2009 >, from http://jcmc.indiana.edu/vol10/issue1/chung.html. Google Scholar OpenURL Placeholder Text WorldCat Diamantopoulos , A. , & Winklhofer , H. M. ( 2001 ). Index construction with formative indicators: An alternative to scale development . Journal of Marketing Research , 38 ( 2 ), 269 – 277. Google Scholar Crossref Search ADS WorldCat Doney , P. M. , & Cannon , J. P. ( 1997 ). An examination of the nature of trust in buyer–seller relationships . Journal of Marketing , 61 ( 2 ), 35 – 51. Google Scholar Crossref Search ADS WorldCat Gefen , D. ( 2000 ). E-commerce: The role of familiarity and trust . Omega , 28 ( 6 ), 725 – 737. Google Scholar Crossref Search ADS WorldCat Gefen , D. , Karahanna , E., & Straub , D. W. ( 2003 ). Trust and TAM in online shopping: An integrated model . MIS Quarterly , 27 ( 1 ), 51 – 90. Google Scholar Crossref Search ADS WorldCat Fornell , C. , & Larcker , D. ( 1981 ). Evaluating structural equation models with unobservable variable and measurement error . Journal of Marketing Research , 18 ( 1 ), 39 – 50. Google Scholar Crossref Search ADS WorldCat Hair , J. F. , Anderson , R. E., Tatham , R. L., & Black , W. C. ( 1998 ). Multivariate data analysis . (4th ed). Upper Saddle River, NJ: Prentice Hall . Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC Hair , J. F. , Black , W. C., Babin , B. J., Anderson , R. E., & Tatham , R. L. ( 2006 ). Multivariate data analysis (6th ed.). Upper Saddle River, NJ: Prentice Hall . Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC Jarvenpaa , S. L. , Tractinsky , J., & Vitale , M. ( 2000 ). Consumer trust in an Internet store . Information Technology and Management , 1 ( 1–2 ), 45 – 71. Google Scholar Crossref Search ADS WorldCat Jarvis , C. B. , Mackenzie , S. B., & Podsakoff , P. M. ( 2003 ). A critical review of construct indicators and measurement model misspecification in marketing and consumer research . Journal of Consumer Research , 30 ( 3 ), 199 – 218. Google Scholar Crossref Search ADS WorldCat Jee , J. & Lee , W-N ( 2002 ). Antecedents and consequences of perceived interactivity: An exploratory study . Journal of Interactive Advertising , 3 ( 1 ). Retrieved December 1, 2008, from http://www.jiad.org/article28 Google Scholar OpenURL Placeholder Text WorldCat Karson , E. J. , & Fisher , R. J. ( 2005a ). Predicting intentions to return to the Web site: Extending the dual mediation hypothesis . Journal of Interactive Marketing , 19 ( 3 ), 2 – 14. Google Scholar Crossref Search ADS WorldCat Karson , E. J. , & Fisher , R. J. ( 2005b ). Reexamining and extending the dual mediation hypothesis in an online advertising context . Psychology and Marketing , 22 ( 4 ), 333 – 351 . Google Scholar Crossref Search ADS WorldCat Kim , Y. H. , Kim . D. J., & Hwang , Y. ( 2009 ). Exploring online transaction self-efficacy in trust building in B2C e-commerce . Journal of Organizational and End User Computing , 21 ( 1 ), 37 – 59. Google Scholar Crossref Search ADS WorldCat Kim , D. , & Benbasat , I. ( 2003 ). Trust-related arguments in Internet stores: A framework for evaluation . Journal of Electronic Commerce Research , 4 ( 2 ), 49 – 63. Google Scholar OpenURL Placeholder Text WorldCat Kline , R. B. ( 1998 ). Principles and practice of structural equation modeling . New York: Guilford Press . Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC Komiak , S. Y. X. , & Benbasat , I. ( 2006 ). The effects of personalization and familiarity on trust and adoption of recommendation agents . MIS Quarterly , 30 ( 4 ), 941 – 960. Google Scholar Crossref Search ADS WorldCat Koufaris , M. , & Hampton-Sosa , W. ( 2002 ). Customer trust online: Examining the role of experience with the Web site. Working paper. Retrieved on April 22 , 2009, from http://cisnet.baruch.cuny.edu/papers/cis200205.pdf Koufaris , M. , & Hampton-Sosa , W. ( 2004 ). The development of initial trust in an online company by new customers . Information and Management , 41 ( 3 ), 377 – 397. Google Scholar Crossref Search ADS WorldCat Langer , E. J. ( 1975 ). The illusion of control . Journal of personality and social psychology , 32 ( 2 ), 311 – 328. Google Scholar Crossref Search ADS WorldCat Lee , T. ( 2005 ). The impact of perceptions of interactivity on customer trust and transaction intentions in mobile commerce . Journal of Electronic Commerce Research , 6 ( 3 ), 165 – 180. Google Scholar OpenURL Placeholder Text WorldCat Liu , Y. , & Shrum , L. J. ( 2002 ). What is interactivity and is it always such a good thing? Implications of definition, person, and situation for the influence of interactivity on advertising effectiveness . Journal of Advertising , 31 ( 4 ), 53 – 64. Google Scholar Crossref Search ADS WorldCat Lowry , P. B. , Vance , A., Moody , G., Beckman , B., & Read ., A. ( 2008 ). Explaining and predicting the impact of branding alliances and Web site quality on initial consumer trust of e-commerce Web site . Journal of Management Information Systems , 24 ( 4 ), 199 – 224. Google Scholar Crossref Search ADS WorldCat MacKenzie , S. B. ( 2001 ). Opportunities for improving consumer research through latent variable structural equation modeling . Journal of Consumer Research , 28 ( 2 ), 159 – 166. Google Scholar Crossref Search ADS WorldCat McKnight , D. H. , & Chervany , N. L. ( 2001 ). What trust means in e-commerce customer relationships: An interdisciplinary conceptual typology . International Journal of Electronic Commerce , 6 ( 2 ), 35 – 59. Google Scholar Crossref Search ADS WorldCat McKnight , D. H. , Choudhury , V., & Kacmar , C. ( 2002 ). The impact of initial consumer trust on intentions to transact with a Web site: A trust building model . Journal of Strategic Information Systems , 11 , 297 – 323. Google Scholar Crossref Search ADS WorldCat McKnight , D. H. , Choudhury , V., & Kacmar , C. ( 2004 ). Shifting factors and the ineffectiveness of third party assurance seals: A two-stage model of initial trust in a Web business . Electronic Markets , 14 ( 3 ), 252 – 265. Google Scholar Crossref Search ADS WorldCat McKnight , D. H. , Cummings , L. L., & Chervany , N. L. ( 1998 ). Initial trust formation in new organization relationships . Academy of Management Review , 23 ( 3 ), 473 – 490. Google Scholar OpenURL Placeholder Text WorldCat McKnight , D. H. , Kacmar , C., & Choudhury , V. ( 2004 ). Dispositional trust and distrust distinctions in predicting high- and low-risk Internet expert advice site perceptions , E-service journal , 3 ( 2 ), 35 – 58. Google Scholar Crossref Search ADS WorldCat McMillan , S. , Hwang , J. S. ( 2002 ). Measures of perceived interactivity: An exploration of the role of direction of communication, user control, and time in shaping perceptions of interactivity . Journal of Advertising , 31 ( 3 ), 29 – 42. Google Scholar Crossref Search ADS WorldCat Merrilees , B. ( 2003 ). E-trust: The influence of perceived interactivity on e-tailing users . Marketing Intelligence and Planning , 21 ( 2 ), 123 – 128. Google Scholar Crossref Search ADS WorldCat Metzger , M. J. ( 2006 ). Effects of site, vendor, and consumer characteristics on Web site trust and disclosure . Communication Research , 33 ( 3 ), 155 – 179. Google Scholar Crossref Search ADS WorldCat Petter , S. , Straub , D. W., & Rai , A. ( 2007 ). Specifying formative constructs in information systems research . MIS Quarterly , 19 ( 2 ), 173 – 187. Google Scholar OpenURL Placeholder Text WorldCat Ridings , C. M. , Gefen , D., & Arinze , B. ( 2002 ). Some antecedents and effects of trust in virtual communities . Journal of Strategic Information Systems , 11 ( 3-4 ), 271 – 295 . Google Scholar Crossref Search ADS WorldCat Sicilia , M. , Salvador R., & Jose L. M. ( 2005 ), Effects of interactivity in a Web site: The moderating effect of need for cognition . Journal of Advertising , 34 ( 3 ), 31 – 44. Google Scholar Crossref Search ADS WorldCat Song , J. H. , & Zinkhan , G. M. ( 2008 ). Determinants of perceived Web site interactivity . Journal of Marketing , 72 ( 2 ), 99 – 113. Google Scholar Crossref Search ADS WorldCat Stewart , D. W. , & Pavlou , P. A. ( 2002 ). From consumer response to active consumer: Measuring the effectiveness of interactive media . Journal of the Academy of Marketing Science , 30 ( 4 ), 376 – 396. Google Scholar Crossref Search ADS WorldCat Suprenant , C. F. , & Solomon , M. R. ( 1987 ). Predictability and personalization in the service encounter . Journal of Marketing , 51 ( 1 ), 86 – 96. Google Scholar Crossref Search ADS WorldCat Wang , S. , Beatty , S. E., & Foxx , W. ( 2004 ). Signaling the trustworthiness of small online retailers . Journal of Interactive Marketing , 18 ( 1 ), 53 – 69. Google Scholar Crossref Search ADS WorldCat Wu , G. ( 1999 ). Perceived interactivity and attitude toward Web sites . In M. Roberts (Ed.), Proceedings of the 1999 Conference of the American Academy of Advertising (pp. 254 – 262 ). Gainesville, FL: University of Florida . Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC Wu , G. ( 2005 ). How interactive advertising works: The mediating role of perceived interactivity in the effect of actual interactivity on attitude toward the Web site . Journal of Interactive Advertising , 5(2). Retrieved October 1, 2008, from http://www.jiad.org/vol5/no2/wu/ Wu , G. ( 2006 ). Conceptualizing and measuring the perceived interactivity of Web sites . Journal of Current Issues and Research in Advertising , 28 ( 1 ), 87 – 104. Google Scholar Crossref Search ADS WorldCat Wu , J. J. , & Chang Y. S. ( 2005 ). Towards understanding members' interactivity, trust, and flow in online travel community . Industrial Management + Data Systems , 105 ( 7 ), 937 – 954. Google Scholar Crossref Search ADS WorldCat Yadav , M. S. , & Varadarajan , R. ( 2005 ). Interactivity in the electronic marketplace: An exposition of the concept of implications for research . Journal of the Academy of the Marketing Science , 33 ( 4 ), 585 – 603. Google Scholar Crossref Search ADS WorldCat Yang , S. C. , Hung , W. C., Sung , K., & Farn , C. K. ( 2005 ). Investigating initial trust toward e-tailers from the elaboration likelihood model perspective . Psychology & Marketing , 23 ( 5 ), 429 – 445. Google Scholar Crossref Search ADS WorldCat About the Authors Guohua Wu (Ph.D., The University of Texas at Austin) is an Assistant Professor of Communications at California State University, Fullerton. His research interests focus on the role of interactivity in online consumer's attitude and trust formation. His articles have appeared in International Journal of Advertising, Journal of Consumer Marketing, Journal of Interactive Advertising, Journal of Current Issues and Research in Advertising, and Journal of Computer-mediated Communication. Address: Department of Communications, California State University, Fullerton, 2600 Nutwood Avenue, Fullerton, CA 92834. Email: mwu@fullerton.edu Xiaorui Hu (Ph.D., The University of Texas at Austin) is an Associate Professor of Decision Sciences and Information Technology Management at the John Cook School of Business, Saint Louis University. Her research focuses on trust related issues in electronic commerce, business-to-business markets, culture impact on international business, and ethical issues in Internet age. She has published in Information Systems Research, Decision Support Systems, IEEE Computer, Journal of Organizational Computing and Electronic Commerce, Journal of Interactive Marketing, Journal of Global Information Technology Management, and other academic journals. Address: John Cook School of Business, Saint Louis University, Saint Louis, MO 63108. Email: hux2@slu.edu Yuhong Wu (Ph.D., The University of Texas at Austin) was an Assistant Professor of Marketing at Christos M. Cotsakos College of Business, William Paterson University. Her research interests lie in the areas of Internet marketing and e-commerce, strategies in network market, and new product development and management. She has published in Journal of Marketing. Email: yuhong_ut@yahoo.com The authors would like to thank the two anonymous reviewers for their helpful comments. Appendices Appendix A The Screenshot of the Simulated Web Site With CyberTrust Seal Appendix B Descriptions of Seals Upon clicking on a Web assurance seal icon (if present) on the Web site, a pop-up window will display the content of the seal. The following two paragraphs are the same for the CyberTrust Privacy, CyberTrust Security, and CyberTrust Integrity seals: You have arrived here from a CyberTrust certified site. The applicable CyberTrust Seal of Assurance symbolizes that this site has been examined by a CyberTrust professional. In order for an entity to be able to display the CyberTrust Seal of Assurance, it must meet one or more of the CyberTrust principles. The CyberTrust Seal of Assurance ensures that any Web site displaying it has met one or more standards established by CyberTrust. The CyberTrust Seal of Assurance combines high standards for e-commerce activities with the requirement for a CyberTrust verification/audit. Together they build trust and confidence among consumers and businesses conducting business over the Internet. The entity has earned the right to display the Seal of Assurance with respect to the CyberTrust principle of: But the rest of the content differs depending on which seal is being clicked. Transaction Integrity: The entity agrees to abide by the Code of Online Business Practices, make commitment to high levels of ethical business practices and customer satisfaction, and cooperate with any CyberTrust request for modification of a Web site to bring it into accordance with the Code. The entity agrees to dispute resolution, at the consumer's request, for unresolved disputes involving consumer products or services. The entity agrees to respond promptly to all consumer complaints and to have a satisfactory complaint handling record with CyberTrust. CyberTrust requires an entity to meet high standards of disclosure of business practices. Privacy: Our standards demand that the entity disclose and comply with its on-line privacy practices. As a result, personally identifiable information obtained as a result of electronic commerce is protected and handled as promised. The entity never rents, sells, or gives your personal information, including name, address, telephone number, e-mail address and, when necessary, credit card information and customer number, to any other organization for marketing purposes. Security: The CyberTrust security principle requires an entity to meet high standards for the security of data transmitted over the Internet and stored on an e-commerce system. The independent verification/audit provides assurance that there are effective security policies that the entity discloses its key security practices for electronic commerce, and that controls exist to ensure that these policies are followed. By committing to an independent verification/audit, the entity clearly demonstrates its commitment to data protection. Appendix C Scales Used in the Study Initial Online Trust This vendor appears to be one who would keep promises and commitments. I believe in the information that this vendor provides me. I trust that this vendor keeps my best interests in mind. The vendor is trustworthy. Attitude toward an e-vendor Using this vendor is a foolish Idea. *R. Using this vendor is a good idea. Using this vendor would be pleasant. I like the idea of using the Internet to shop from this vendor. Using Internet to shop from this vendor is a good idea. I like the idea of using this vendor. Attitude toward an e-vendor's web site This Web site makes it easy for me to build a relationship with this company. I would like to visit this Web site again in the future. I'm satisfied with the service provided by this company. I feel comfortable in surfing this Web site. I feel surfing this Web site is a good way for me to spend my time. Compared with other Web sites, I would rate this one as (one of the worst… one the best). Purchase Intention My intention would be to purchase from this vendor. (Very low … Very high). The likelihood that I would purchase from this vendor is (Very low … Very high). The probability that I would consider buying from this vendor is (Very low … Very high). My willingness to buy from this vendor is (Very low … Very high). Perceived risk There is too much uncertainty associated with shopping from this vendor. Purchasing from this vendor is risky. I feel safe completing commercial transactions with this vendor. *R. Perceived Web Assurance This online store lacks commitment to protect my privacy. *R. This online store makes effort to protect my private information. It appears that this online store can be entrusted with my personal information. This online store lacks commitment to ensure the security of data transaction. *R. This online store makes effort to ensure the secure data transaction. It appears that this online store can ensure my data security. This online store lacks commitment to be complying with high levels of transaction integrity. *R. This online store provides assurances for complete and accurate business transactions. This online store makes effort to abide by the integrity of business practices. Disposition to Trust I tend to count upon other people. I generally have faith in humanity. I generally trust other people unless they give me reasons not to. I generally trust other people. Perceived Interactivity I was in control of my navigation through this Web site. I had some control over the content of this Web site that I wanted to see. I was in control over the pace of my visit to this Web site. I could communicate with the company directly for further questions about the company or its products if I wanted to. The Web site had the ability to respond to my specific questions quickly and efficiently. I could communicate in real time with other customers who shared my interest in this Web site. I felt I just had a personal conversation with a sociable, knowledgeable and warm representative from the company. The Web site was like talking back to me while I clicked through the Web site. I perceived the Web site to be sensitive to my needs for product information. *R means the item is reversely scored. All items except otherwise noted are on a 7-point Likert-type scale, with 1 being “strongly disagree” and 7 being “strongly agree.” © 2010 International Communication Association
TI - Effects of Perceived Interactivity, Perceived Web Assurance and Disposition to Trust on Initial Online Trust
JF - Journal of Computer-Mediated Communication
DO - 10.1111/j.1083-6101.2010.01528.x
DA - 2010-10-01
UR - https://www.deepdyve.com/lp/oxford-university-press/effects-of-perceived-interactivity-perceived-web-assurance-and-tYdqTEbd9S
SP - 1
EP - 26
VL - 16
IS - 1
DP - DeepDyve
ER -