Information Sharing on Social Networking Websites: Antecedents and Consequences of Trust

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1 Information Sharing on Social Networking Websites: Antecedents and Consequences of Trust Completed Research Paper Mohammad Salehan Seyed Mohammadreza Mousavizadeh Kashipaz College of Business College of Business University of North Texas University of North Texas Chenyan Xu School of Business Richard Stockton College of New Jersey ABSTRACT Social networking websites (SNS) facilitate communication and information sharing between people. Media have reported significant concerns of SNS users regarding their privacy. SNS have tried to address these privacy concerns by introducing controlling features. This study investigates the issue of trust in SNS, its predictors, and its consequences. We suggest that three categories of factors should be considered for the study of social networking websites: (1) website characteristics, (2) environmental factors, and (3) personal factors. We find that trust in the website is a significant predictor of SNS information sharing. We also find that personal factors, such as privacy concerns and trust propensity and social presence, a website characteristic, are significant predictors of trust in SNS. The findings show similarities and differences between the context of e-commerce and SNS. We provide implications for research and practice as well as direction for future research. Keywords Social networking website (SNS), information sharing, trust, privacy, social presence. INTRODUCTION Social networking websites (SNS) are among the most recent forms of communication over the internet. The most popular SNS, FaceBook, has attracted over a billion users (Fowler 2012) since its introduction in February Facebook is currently the most visited website worldwide (Alexa 2012). More than half of Facebook users utilize mobile devices to connect (Socialbakers.com 2012a). Currently, Facebook penetration is 54.01% in US (Socialbakers.com 2012b) which is five percent more than the last year (Raice 2012). This huge and growing number of users and web traffic reveals the potential of such websites to change the face of the world. Information sharing is an important motivation for people to join virtual communities (Ridings and Gefen 2004). Social networking websites empower their users to share different kinds of information such as ideas, pictures, and videos with just a few clicks. Meanwhile, research and media are constantly reporting SNS users concerns about their privacy and security (Barnes 2006; Dwyer, Hiltz and Passerini 2007). Such privacy concerns have even led to some rules and regulations to protect the privacy of SNS users. Recently the governor of California signed a bill that prevents employers and colleges from access to social media accounts (HuffingtonPost 2012). Despite significant privacy concerns, SNS users continue to disclose private information online. Understanding individuals attitude toward privacy and exploring the factors that motivate them to share their information online has been suggested as a major direction of research in the area of social networking websites (Dwyer et al. 2007). Trust in the website has been found to be an important determinant of online information disclosure (Andrews, Preece and Turoff 2001; Ridings, Gefen and Arinze 2002). Although trust in SNS has been found as an important predictor of information sharing on social networking websites (Salehan and Kim 2012), antecedents of trust in social networking websites are not fully understood yet. This study sheds light on the information sharing behavior of SNS users by Proceedings of the Nineteenth Americas Conference on Information Systems, Chicago, Illinois, August 15-17,

2 investigating the effect of trust in SNS on information disclosure of SNS users as well as the antecedents of trust in social networking websites. This study has three objectives: (1) to propose a research model explaining which factors affect trust in SNS and how trust in SNS is related to information disclosure, (2) to empirically test the proposed model using data collected from SNS users, and (3) to give academia and practitioners deep insight about SNS information disclosure and its implications. The remaining parts of this paper are organized as follows. First, we present the background of the study. Next, we propose our research model and hypotheses. Later we discuss our methodology and results. Then we discuss the implications of our study and finally, we present our concluding remarks. LITERATURE REVIEW The Internet promotes new connections and provides new alternatives for users. The Internet not only provides a platform for people to connect to each other, but also provides an environment for them to share their interests and relational goals (Ellison, Steinfield and Lampe 2007). In this cyber world, social networking websites attract millions of people around the world by satisfying different needs (Ellison 2007). Ellison (2007, p. 211) defines social networking website as web-based services that allow individuals to (1) construct a public or semi-public profile within a bounded system, (2) articulate a list of other users with whom they share a connection, and (3) view and traverse their list of connections and those made by others within the system. People join groups, in general, for reasons such as feelings of belonging and affiliation, making long term relationships, information sharing and helping one another (Ridings and Gefen 2004). Similarly, Riding and Gefen (2004) find that people mainly join virtual communities in order to seek information, social support, friendship, and recreation. Therefore, access to information and information sharing is an important motivation for people to join SNS. Although information sharing is an important motivation behind joining social networks, its antecedents have not received much attention from scholars. However, sharing behavior has received more attention in organizational settings. Sharing behavior in organizations is mainly in the form of knowledge sharing. The motivations for sharing within personal networks as opposed to organizational networks may be different. For example, while in non-organizational social networks such as Facebook informational uses are more related to civic and political actions than to recreational uses (Park, Kee and Valenzuela 2009), career advancement and gaining support for ideas and projects are two main reasons that encourage employees to share knowledge on organizational social networks (DiMicco, Millen, Geyer, Dugan, Brownholtz and Muller 2008). Although motivations behind information and knowledge sharing may be different, these two have similarities. For example, subjective norm and attitude toward knowledge sharing are two important predictors of sharing behavior in both organizational and non-organizational social networks (Bock, Zmud, Kim and Lee 2005; Chow and Chan 2008; Salehan and Kim 2012). Different classifications of online information and knowledge sharing have been proposed by past studies. According to Salehan and Kim (2012), SNS information sharing behavior has two dimensions: The first dimension is sharing regularity which is related to the frequency of the information sharing behavior. The second dimension is sharing density which is related to the level of online private information revelation. Chiu and Hsu (2006) found two dimensions of knowledge sharing to be quality and quantity of the knowledge shared. Quantity of knowledge means the volume of the shared knowledge and quality of knowledge refers to the content of the shared knowledge. The study shows that while interaction ties, reciprocity, and identification foster knowledge sharing quantity, the three constructs do not have a significant effect on sharing quality. The study also shows that shared language and vision positively affect quality of the shared knowledge. Knowledge sharing is motivated by different factors. A study on organizational knowledge sharing shows that intention to share knowledge is determined by attitude toward knowledge sharing, subjective norm, and organizational climate (Bock et al. 2005). The study shows that attitude toward knowledge sharing is affected by anticipated reciprocal relationships and subjective norm is affected by sense of self-worth and organizational climate. Another study on organizational social networks shows that main motivation for knowledge sharing is moral obligation and community interest rather than a narrow self-interest (Ardichvili, Page and Wentling 2003). Social factors such as ethical culture, sense of belonging to the SNS and social ties with other users are important determinants of information contribution in SNS (Chai and Kim 2011). Outcome expectation and social capital influence are also important motivations for knowledge sharing in communities (Chiu et al. 2006). Trust is an important determinant of successful online interaction (Coppola, Hiltz and Rotter 2004). Trust has been studied in different contexts such as sociology, economics, marketing, and social psychology (Doney and Cannon 1997). Trust is defined as the willingness of a party to be vulnerable to the actions of another party based on the expectation that the other Proceedings of the Nineteenth Americas Conference on Information Systems, Chicago, Illinois, August 15-17,

3 will perform a particular action important to the trustor, irrespective of the ability to monitor or control the other party (Mayer, Davis and Schoorman 1995, p.712). Trust as a cognitive component consists of several beliefs (Anderson and Narus 1990; Doney and Cannon 1997). Different types of trust can be found in the literature (Panteli and Sockalingam 2005). The first type is dispositional trust which is mainly motivated by faith in humanity (McKnight, Cummings and Chervany 1998). A second type of trust is conditional trust. This kind of trust can be found in initial period of a relationship when there is no cue for distrust (Panteli and Sockalingam 2005). While a number of factors such as technical, psychological, and sociological factors affect trust, the role of ethical factors on trust is very significant (Argandoña 1999). Trust issues are a critical challenge for web-based systems (Berners-Lee, Hall and Hendler 2006; Pavlou 2003; Rubin and DE Geer 1998). Trust in website has been extensively studied in the context of ecommerce as an important predictor of online shopping (Corbitt, Thanasankit and Yi 2003; Gefen 2000; Gefen, Karahanna and Straub 2003b; Kim 2008; Pavlou 2003; Suh and Han 2003). Trust is also a key factor in promoting individuals to participate and share knowledge and information in virtual communities (Andrews et al. 2001; Dwyer et al. 2007; Ridings et al. 2002; Salehan and Kim 2012). Research findings show that social and mutual trust among members in organizations are critical factors in promoting knowledge sharing (Chow and Chan 2008). Trust in website is an important predictor of online behavior. Trust in website significantly affects SNS users attitude toward information sharing (Salehan and Kim 2012). According to Flavián, Guinalíu and Gurrea (2006) trust consists of three perceptions of the user regarding honesty, benevolence, and competence of the target of trust. According to Kim (2008), trust in an e-vendor is determined by transference-based trust and self-perception-based trust. Self-perception-based trust is mainly based on cognitive reasoning (McAllister 1995) and is formed through direct experience or direct interactions with a partner (Kim 2008). In contrast, transference-based trust is transferred from a trusted proof source such as friends, family, or organizations (Doney and Cannon 1997). Different factors such as perceived security control (Ray, Ow and Kim 2011) and social interaction ties (Tsai and Ghoshal 1998) affect trust in website. According to Flavián et al. (2006) website usability and user satisfaction positively affect trust in website. Another study proposes that two groups of factors affect trust. Website user trust which consists of benefit attraction, user s tendency to trust, and shared value positively affects trusting beliefs. Institutional trust that consists of monitoring and privacy policies of the organization positively affects trust (Wu and Tsang 2008). RESEARCH MODEL AND HYPOTHESES Kim, Song, Braynov and Rao (2005) find four components of e-commerce markets to be technology, consumer, third party, and seller. They believe that these four entities form trust in B-to-C e-commerce. From these four entities, two are present in the context of SNS: technology (i.e. the website) and customer (i.e. the user). The other two (seller and third party) are not very significant SNS entities because social networking does not entail any buying and selling and consequently there is no seller and no need for a third party to guarantee the transaction. On the other hand, social networking involves interaction with other people. The environment consisting of significant others, other users, and norms of behavior is an important SNS entity which is not present in the context of e-commerce. Consequently, we propose that three different categories of factors should be considered in the context of SNS: website characteristics, environmental factors, and personal factors (i.e. user characteristics). Based on this categorization, we propose a research model to study trust in SNS. Our research model is depicted in figure one. Website Characteristics According to Delone and McLean s (2003) IS success model, quality which has three dimensions of information quality, system quality, and service quality is an important predictor of IS adoption. There are three approaches to evaluating the quality of a website: machine evaluation, expert judges, and customer s evaluation (Loiacono, Watson and Goodhue 2002). Among these three, customer is the ultimate judge (Loiacono et al. 2002). Perceived quality of an e-commerce website is a significant predictor of trust in website (Everard and Galletta 2006). The same thing can be valid in the context of SNS. There are two reasons for this argument. First, when an SNS cares about quality, this will induce its users that the website cares about different needs of them such as the need for privacy and security. Second, higher perceived website quality is associated with less concerns about bugs, security breaches, and vulnerabilities.. Therefore it will positively affect users trusting beliefs. Thus we hypothesize that: H1: Website quality positively affects trust in website. Social presence is defined as the degree of salience of the other person in the interaction and the consequent salience of interpersonal relationships (Short, Williams and Christie 1976,P. 65). Social presence is an important predictor of online Proceedings of the Nineteenth Americas Conference on Information Systems, Chicago, Illinois, August 15-17,

4 trust by implying direct or indirect human contact which affects predictability, ability, and benevolence of the target website (Gefen and Straub 2004). Social presence is also a positive factor in selecting communication channel when the task is uncertain and ambiguous (Straub and Karahanna 1998). A possible reason for this preference is that the presence of human factor can moderate the uncertainty associated with interacting with machines. In other words, social presence can increase the trust of users by decreasing the uncertainty associated with operating computers which requires special skills. Hence, we hypothesize that: H2: Social presence positively affects trust in website. Environmental Characteristics Figure 1-Research Model According to Venkatesh, Morris, Davis and Davis (2003, p. 451) social influence is defined as the degree to which an individual perceives that important others believe he or she should use the new system. They believe that social influence is an important missing from technology acceptance model (TAM) (Davis, Bagozzi and Warshaw 1989). This construct play an important role in understanding how users make decision about adoption and use of new technologies (Venkatesh and Morris 2000). Social influence can positively affect user s trust in SNS. The reason is that individuals tend to trust in people that are close to them such as family and friends. Accordingly, individuals will have the feelings that their important others don t want to expose them to risks. As a result, when important others expect the person to use the SNS, the person is more likely to trust the website. This leads to the following hypothesis: H3: Social influence positively affects trust in website. Personal Factors Privacy concerns have a significant negative relationship with trusting beliefs (Kim 2008; Malhotra, Kim and Agarwal 2004; Van Dyke, Midha and Nemati 2007). It has also been found out that privacy concerns affect intention to disclose private information (Bansal, Zahedi and Gefen 2010) as a result of a risk benefit analysis (Dinev and Hart 2006). On the other side, higher levels of privacy concerns can make people be more worried about potential outlets of private information because such outlets can hurt their privacy. Social networking websites can be a potential outlet of private information because they collect and maintain large volumes of private information from their users. So it seems normal that people with higher privacy concerns be more cautious in dealing with such websites and have less trust in them. So we propose that: Proceedings of the Nineteenth Americas Conference on Information Systems, Chicago, Illinois, August 15-17,

5 H4: Privacy concern negatively affects trust in website. Trust propensity refers to the propensity to be willing to depend on others (McKnight et al. 1998). Such propensity is formed through a lasting socialization process that leads to a tendency to, or not to, have faith in other people and to trust them (McKnight et al. 1998; Rotter 1971). Trust propensity is especially important when people engage in a new relationship but it s importance diminishes as the relationship matures because a more mature relationship means that people have had appropriate opportunities to assess whether they should trust the other one or not (McKnight et al. 1998). Trust propensity is a significant predictor of trust in website in the context of e-commerce. Although the effect is stronger for new customers, it is still significant for repeat customers (Gefen, Karahanna and Straub 2003a). Considering the importance of trust propensity on people s trust on other people and entities, we can expect this construct to have a significant effect on trust in social networking website both for new users and experienced users. This leads to the following hypothesis: H5: Trust propensity positively affects trust in website. Trust in website positively affects attitude of SNS users toward online information sharing which in turn positively affects frequency of sharing information and the amount of private information revelation (Salehan and Kim 2012). In addition to affecting information sharing of SNS users through changing their attitudes, trust in website can have a direct effect on SNS information sharing. When people perceive a social networking website as trustworthy and dependable, they will have fewer concerns regarding their information being misused or observed by unintended audience because they will have more confidence that their SNS will maintain their privacy and security as promised. So they can reveal more private information with peace of mind that their information will be safe in their social networking website without their privacy and security getting violated. Hence we hypothesize that: H6: Trust in website positively affects information sharing. METHODOLOGY Measurement All scales were adapted from prior studies with small modifications. Survey items are listed in appendix 1. The scale for website quality was adapted from Everard & Galletta (2006). The scale for social presence was drawn from Gefen and Straub (2003). Privacy concern scale was adapted from Xu, Dinev, Smith and Hart (2011). The scale for trust propensity was adapted from Gefen et al. (2003a). Social influence scale was drawn from Venkatesh et al. (2003). Trust in website was adapted from Pan and Zinkhan (2006). The information sharing scale was adapted from Salehan and Kim (2012) with some additional items. All items were measured using a five-point Likert scale with anchors being strongly disagree and strongly agree. A list of five popular social networking websites was provided and respondents were asked to indicate the SNS that they used most. There was also an other option with a box to specify their most popular SNS if it wasn t in the list. Data Collection Data were collected from students in a large university in south west US. A total of 184 responses were collected from students. Students received extra credit for participating in the survey. After removing incomplete answers, we ended up with a sample of 180 respondents indicating a usable sample rate of 97.8%. Our sample consists of %56.5 males and %43.5 females. Measurement Model We used partial least squares (PLS) to validate our mode. Using the Smart-PLS software, we first examined our data to assess reliability and validity before testing the structural model. All items loaded significantly on their corresponding constructs as suggested by Gefen and Straub (2005). Most items had a high loading on their corresponding constructs (above.80) and none were less than.60, which is higher than the cutoff point of.40 suggested by Hulland (1999). The pattern of loadings and cross-loadings supported internal consistency and discriminant validity. Table 1 shows PLS loadings and cross loadings for all items. The composite reliabilities of all of the items were above the threshold of.70 (Hulland 1999). The average variance extracted (AVE) for all of the constructs was above.50 (Barnes 2006). Table 2 shows reliability, correlations, and AVEs. Structural Model We ran our model in PLS to test the proposed model. The results show support for four of the six hypotheses. Figure 2 shows the results of data analysis. The results show that social presence, privacy concerns, and trust propensity significantly affect Proceedings of the Nineteenth Americas Conference on Information Systems, Chicago, Illinois, August 15-17,

6 trust in social networking website accounting for %33 of its variance. Among the antecedents of trust, privacy concern has the strongest impact with a path coefficient of and social presence comes second with a path coefficient of Accordingly, trust in website significantly affects information sharing on social networking websites accounting for %11.6 of its variance. The path coefficient for this relationship is.340 showing the important impact of trust in website on information sharing. Mean Std. Deviation Privacy Quality Information Sharing Social Influence Social Presence Disposition to Trust Trust in Website PC PC PC PC PC QUAL QUAL QUAL QUAL ISH ISH ISH SI SI SI SP SP SP SP SP DT DT DT DT DT TW TW TW TW Table 1-PLS Loadings and Cross-Loadings Proceedings of the Nineteenth Americas Conference on Information Systems, Chicago, Illinois, August 15-17,

7 AVE Composite Reliability Cronbach s Alpha Information Sharing Privacy Quality Social Influence Social Presence Trust in Website Disposition to Trust Information Sharing Privacy Quality Social Influence Social Presence Trust in Website Disposition to Trust Table 2-Reliability, Correlations, and AVEs DISCUSSION Figure 2-Model Analysis Results Social networking websites provide a platform for different people to connect to each other and share information. Building on recent studies demonstrating the factors affecting the motivation of users to use and share information on social networking websites, this study investigates the effect of website characteristics, environmental factors, and personal factors on SNS information sharing. This section first discusses the key findings of the study, and then reports the limitations of this study, followed by the implications for both research and practice. Discussion of Key Findings The study investigates the effect of five factors on trust in SNS and the consequent effect of trust in SNS on information sharing behavior. In this study, the antecedents of trust in website are categorized in three groups: website characteristics, Proceedings of the Nineteenth Americas Conference on Information Systems, Chicago, Illinois, August 15-17,

8 environmental factors, and personal factors. Website characteristics include website quality and social presence of which social presence was a significant predictor of trust in website. The insignificant effect of quality on trust in website contradicts the findings of previous studies (e.g., Everard and Galletta 2006) in the area of e-commerce regarding the effect of perceived website quality on trusting intentions. One possible explanation for this insignificant effect is that website quality, based on our scale, measures general quality of the website. General quality is the general perception about different dimensions of quality such as user-friendliness, design quality, and other factors many of which are not related to concerns of users such as security and trust issues. Therefore, website quality may not predict trust in website. On the other hand, the findings confirm the previous findings regarding the importance of social presence on online trust especially in the context of e-commerce (Gefen and Straub 2004). Results also show that the effect of the single environmental factor in this study, social influence, was not significant on trust in website. This is in line with the findings of other studies (Cheung, Chiu and Lee 2011; Salehan and Kim 2012) regarding the insignificant effect of the expectation of reference groups on sharing behavior of SNS users. One possible explanation is that SNS users may believe that their important others do not consider their concerns regarding the use of SNS. Another explanation is that users may believe that their concerns are different from that of their significant others. At the same time, we see that social presence positively affects trust in SNS. This suggests that trust in SNS is mainly driven by the presence of others and observable activities of them rather than just their expectations. Finally, the findings display the strong effect of personal factors on trust in SNS. Privacy concerns and trust propensity significantly affect SNS user s trust in social networking websites. The significant effect of trust propensity on trust in website is in line with the findings in the context of e-commerce (Gefen et al. 2003a) suggesting that SNS and e-commerce context have similarities. The significant and strong effect of privacy concerns on trust in SNS confirms the reported concerns about privacy of online social networking and suggests that such concerns still exist and should receive strong attention. In summary, the findings suggest that a user s trust in social networking website is mostly derived from personal factors as well as the interaction of the user with other users. Privacy concerns and trust propensity are the human factors rooted in personality and experience of the user. Social presence is the other important factor resulted from interaction of the user with other users. The findings also suggest that although the SNS context is similar to e-commerce context in many ways, there are certain differences between these two contexts. Limitations Like any other studies, this study has limitations. First, student sample was used for this study. Although some researchers argue that student data are artificial and lack external validity (Gordon, Slade and Schmitt 1986), some other researchers have argued that student data can be useful and have a great contribution. We believe that student data is a good sample for the study of social networking websites because it reflects a very high proportion of SNS users which are college students. Future research with non-student sample can provide better understanding regarding SNS trusting beliefs. Second, our sample lacks cultural diversity. Since different cultural types can affect trust in different ways (Kim 2008), our results may lack generalizability to other cultures. Future research can look at other cultures or use a more diversified sample to check for the effect of culture on trust in SNS. Finally, in this study we measured the effect of general website quality on trust in SNS which was not significant. One possible reason behind this insignificant effect is that we just measured general quality. Research shows that quality has several dimensions. For example, Delone and McLean (2003) suggest that quality three dimensions: information quality, system quality, and service quality. Future research can investigate the effect of different dimensions of website quality on trust in SNS to give better insights into the way quality affects trust. Implications This study has implications for both theory and practice. This study contributes to research in four ways. First, the study provides a classification of potential factors affecting online trust in three categories. This classification can be used by researchers to develop models for studying online behavior of users in other areas like web 2.0. Second, the study signifies the importance of personal factors and website characteristics on trust in SNS and shows that environmental factors are less important than these two. This is an important direction for future research to focus on personal and website-related antecedents of online trust to make better predictive models. Third, the study shows the significant effect of trust in website on SNS information sharing. This signifies the importance of trusting beliefs on online social activity. This finding also complements previous findings regarding the effect of trust in SNS on attitudes toward online information sharing (Salehan Proceedings of the Nineteenth Americas Conference on Information Systems, Chicago, Illinois, August 15-17,

9 and Kim 2012). Future research can look for other ways that trust can affect SNS adoption and information disclosure. Finally, the study shows that although there are a lot of similarities between trust in SNS and e-commerce, these two have certain differences. Future research can look at other differences between these two by examining other significant antecedents of e-commerce adoption and behavior in the SNS context. In terms of practical contribution, this study has three implications. First, the study stresses the importance of privacy concerns on SNS information revelation. Such privacy concerns have been a topic of discussion since the introduction of social networking websites. This study shows that despite the recent initiatives in social networking websites like the privacy settings introduced by Facebook, such concerns still have a significant impact on user behavior. Social networking websites still need to put more effort on this issue to increase their users trust. Second, the study shows trust in website is a significant predictor of SNS information revelation. Social networking websites need to increase their customer s trust to increase the level of information revelation which will lead to more user activity and higher traffic for these websites. Finally, the paper showed the significant effect of social presence on trust in website. This finding implies that higher sense of human interaction leads to higher level of trust in users. One possible explanation is that when a user observes that other users are active and revealing a lot of information, they will be persuaded that such websites are relatively harmless and trustable. Social networking websites need to design their pages in a way that induces higher levels of social presence to users which can lead to higher user trust and consequently higher information disclosure. The new Facebook sidebar is a good example of website features inducing high levels of social presence. CONCLUSION This study examines the effect of website characteristics (website quality and social presence), environmental factors (social influence), and personal factors (trust propensity and privacy concerns) on trust in the context of SNS. The study also evaluates the effect of trust in SNS on users Information sharing. The findings show that trust in SNS, which is affected by social presence, trust propensity, and privacy concerns, positively affects information sharing. We find that although trust in SNS and trust in e-commerce website have similarities, they also have differences. We also find that others can affect one s trust in SNS by their active presence rather than just their expectations. REFERENCES 1. Alexa "Facebook.com Site Info (available online 2. Anderson, J. C., and Narus, J. A "A model of distributor firm and manufacturer firm working partnerships," the Journal of Marketing (54:1), pp Andrews, D., Preece, J., and Turoff, M "A conceptual framework for demographic groups resistant to online community interaction," System Sciences, Proceedings of the 34th Annual Hawaii International Conference on, IEEE2001, p. 10 pp. 4. Ardichvili, A., Page, V., and Wentling, T "Motivation and barriers to participation in virtual knowledgesharing communities of practice," Journal of knowledge management (7:1), pp Argandoña, A "Sharing out in alliances: Trust and ethics," Journal of Business Ethics (21:2), pp Bansal, G., Zahedi, F., and Gefen, D "The impact of personal dispositions on information sensitivity, privacy concern and trust in disclosing health information online," Decision Support Systems (49:2), pp Barnes, S. B "A privacy paradox: Social networking in the United States," First Monday (11:9), pp Berners-Lee, T., Hall, W., and Hendler, J. A "A framework for web science," Now Pub. 9. Bock, G. W., Zmud, R. W., Kim, Y. G., and Lee, J. N "Behavioral intention formation in knowledge sharing: Examining the roles of extrinsic motivators, social-psychological forces, and organizational climate," Mis Quarterly (29:1), pp Chai, S., and Kim, M "A socio-technical approach to knowledge contribution behavior: An empirical investigation of social networking sites users," International Journal of Information Management (32:2). 11. Cheung, C. M. K., Chiu, P. Y., and Lee, M. K. O "Online social networks: Why do students use facebook?," Computers in Human Behavior (27:4), pp Chiu, C. M., Hsu, M. H., and Wang, E. T. G "Understanding knowledge sharing in virtual communities: An integration of social capital and social cognitive theories," Decision Support Systems (42:3), pp Chow, W. S., and Chan, L. S "Social network, social trust and shared goals in organizational knowledge sharing," Information & Management (45:7), pp Coppola, N. W., Hiltz, S. R., and Rotter, N. G "Building trust in virtual teams," Professional Communication, IEEE Transactions on (47:2), pp Proceedings of the Nineteenth Americas Conference on Information Systems, Chicago, Illinois, August 15-17,

10 15. Corbitt, B. J., Thanasankit, T., and Yi, H "Trust and e-commerce: a study of consumer perceptions," Electronic commerce research and applications (2:3), pp Davis, F. D., Bagozzi, R. P., and Warshaw, P. R "User acceptance of computer technology: a comparison of two theoretical models," Management science (35:8), pp Delone, W. H., and McLean, E. R "Information systems success revisited," System Sciences, HICSS. Proceedings of the 35th Annual Hawaii International Conference on, IEEE2003, pp DiMicco, J., Millen, D. R., Geyer, W., Dugan, C., Brownholtz, B., and Muller, M "Motivations for social networking at work," Proceedings of the 2008 ACM conference on Computer supported cooperative work, ACM2008, pp Dinev, T., and Hart, P "An extended privacy calculus model for e-commerce transactions," Information Systems Research (17:1), pp Doney, P. M., and Cannon, J. P "An examination of the nature of trust in buyer-seller relationships," the Journal of Marketing (61:2), pp Dwyer, C., Hiltz, S. R., and Passerini, K "Trust and privacy concern within social networking sites: A comparison of Facebook and MySpace," Proceedings of AMCIS2007, pp Ellison, N. B "Social network sites: Definition, history, and scholarship," Journal of ComputerMediated Communication (13:1), pp Ellison, N. B., Steinfield, C., and Lampe, C "The benefits of Facebook friends: Social capital and college students use of online social network sites," Journal of Computer Mediated Communication (12:4), pp Everard, A., and Galletta, D. F "How presentation flaws affect perceived site quality, trust, and intention to purchase from an online store," Journal of Management Information Systems (22:3), pp Flavián, C., Guinalíu, M., and Gurrea, R "The role played by perceived usability, satisfaction and consumer trust on website loyalty," Information & Management (43:1), pp Fowler, G. A "Facebook: One Billion and Counting," The Wall Street Journal (available online Gefen, D "E-commerce: the role of familiarity and trust," Omega (28:6), pp Gefen, D., Karahanna, E., and Straub, D. W. 2003a. "Inexperience and experience with online stores: The importance of TAM and trust," Engineering Management, IEEE Transactions on (50:3), pp Gefen, D., Karahanna, E., and Straub, D. W. 2003b. "Trust and TAM in online shopping: An integrated model," Mis Quarterly (27:1), pp Gefen, D., and Straub, D "A practical guide to factorial validity using PLS-Graph: Tutorial and annotated example," Communications of the Association for Information Systems (16), p Gefen, D., and Straub, D. W "Managing user trust in B2C e-services," E-service Journal (2:2), pp Gefen, D., and Straub, D. W "Consumer trust in B2C e-commerce and the importance of social presence: experiments in e-products and e-services," Omega (32:6), pp Gordon, M. E., Slade, L. A., and Schmitt, N "The 'science of the sophomore' revisited: From conjecture to empiricism," Academy of management review (11:1), pp HuffingtonPost "Social Network Privacy Bill Signed By California Governor Jerry Brown," Huffington Post (available online Hulland, J "Use of partial least squares (PLS) in strategic management research: a review of four recent studies," Strategic management journal (20:2), pp Kim, D. J "Self-perception-based versus transference-based trust determinants in computer-mediated transactions: A cross-cultural comparison study," Journal of Management Information Systems (24:4), pp Kim, D. J., Song, Y. I., Braynov, S. B., and Rao, H. R "A multidimensional trust formation model in B-to-C e-commerce: a conceptual framework and content analyses of academia/practitioner perspectives," Decision Support Systems (40:2), pp Loiacono, E. T., Watson, R. T., and Goodhue, D. L "WebQual: A measure of website quality," Marketing theory and applications (13:3), pp Malhotra, N. K., Kim, S. S., and Agarwal, J "Internet users' information privacy concerns (IUIPC): The construct, the scale, and a causal model," Information Systems Research (15:4), pp Mayer, R. C., Davis, J. H., and Schoorman, F. D "An integrative model of organizational trust," Academy of management review (20:3), pp McAllister, D. J "Affect-and cognition-based trust as foundations for interpersonal cooperation in organizations," Academy of management Journal (38:1), pp McKnight, D. H., Cummings, L. L., and Chervany, N. L "Initial trust formation in new organizational relationships," Academy of management review (23:3), pp Proceedings of the Nineteenth Americas Conference on Information Systems, Chicago, Illinois, August 15-17,

11 43. Pan, Y., and Zinkhan, G. M "Exploring the impact of online privacy disclosures on consumer trust," Journal of Retailing (82:4), pp Panteli, N., and Sockalingam, S "Trust and conflict within virtual inter-organizational alliances: a framework for facilitating knowledge sharing," Decision Support Systems (39:4), pp Park, N., Kee, K. F., and Valenzuela, S "Being immersed in social networking environment: Facebook groups, uses and gratifications, and social outcomes," CyberPsychology & Behavior (12:6), pp Pavlou, P. A "Consumer acceptance of electronic commerce: Integrating trust and risk with the technology acceptance model," International journal of electronic commerce (7:3), pp Raice, S "Days of Wild User Growth Appear Over at Facebook," The Wall Street Journal (available online Ray, S., Ow, T., and Kim, S. S "Security Assurance: How Online Service Providers Can Influence Security Control Perceptions and Gain Trust," Decision Sciences (42:2), pp Ridings, C. M., and Gefen, D "Virtual community attraction: Why people hang out online," Journal of Computer Mediated Communication (10:1). 50. Ridings, C. M., Gefen, D., and Arinze, B "Some antecedents and effects of trust in virtual communities," The Journal of Strategic Information Systems (11:3), pp Rotter, J. B "Generalized expectancies for interpersonal trust," American Psychologist; American Psychologist (26:5), p Rubin, A. D., and DE Geer, J "A survey of Web security," Computer (31:9), pp Salehan, M., and Kim, D. J "The Effect of Attitude, Social Trust and Trust in Social Networking Sites on Two Dimensions of Sharing Behavior," 18th Americas Conference on Information Systems, Seattle, WA, Short, J., Williams, E., and Christie, B "The social psychology of telecommunications," Wiley: London. 55. Socialbakers.com 2012a. "Facebook Hits 488 Million Mobile Users ", available online Socialbakers.com 2012b. "Facebook Statistics by Country," available online Straub, D., and Karahanna, E "Knowledge worker communications and recipient availability: Toward a task closure explanation of media choice," Organization Science (9:2), pp Suh, B., and Han, I "The impact of customer trust and perception of security control on the acceptance of electronic commerce," International journal of electronic commerce (7), pp Tsai, W., and Ghoshal, S "Social capital and value creation: The role of intrafirm networks," Academy of management Journal (41:4), pp Van Dyke, T. P., Midha, V., and Nemati, H "The Effect of Consumer Privacy Empowerment on Trust and Privacy Concerns in E-Commerce," Electronic Markets (17:1), pp Venkatesh, V., and Morris, M. G "Why don't men ever stop to ask for directions? Gender, social influence, and their role in technology acceptance and usage behavior," Management Information Systems Quarterly (24:1), pp Venkatesh, V., Morris, M. G., Davis, G. B., and Davis, F. D "User acceptance of information technology: Toward a unified view," Mis Quarterly (27:3), pp Wu, J. J., and Tsang, A. S. L "Factors affecting members' trust belief and behaviour intention in virtual communities," Behaviour & Information Technology (27:2), pp Xu, H., Dinev, T., Smith, J., and Hart, P "Information Privacy Concerns: Linking Individual Perceptions with Institutional Privacy Assurances," Journal of the Association for Information Systems (12:1), pp Proceedings of the Nineteenth Americas Conference on Information Systems, Chicago, Illinois, August 15-17,

12 Appendix 1 Survey Items Constructs Item Question Privacy Concern Website Quality Information Sharing Social Influence Social Presence Disposition to trust Trust in website PC1 PC2 PC3 PC4 PC5 Qual1 Qual2 Qual3 Qual4 ISH1 ISH2 ISH3 ISH4 ISH5 ISH6 SI1 SI2 SI3 SP1 SP2 SP3 SP4 SP5 DT1 DT2 DT3 DT4 DT5 TW1 TW2 TW3 TW4 TW5 I am concerned that the information I submit to this website could be misused. I am concerned that others can find private information about me from this website. I am concerned about providing personal information to this website, because of what others might do with it. I am concerned about providing personal information to this website, because it could be used in a way I did not foresee. I am concerned that the information I submit to this website may be viewed by an unintended audience My SNS is of high quality. The quality of my SNS is extremely high. My SNS is of very good quality. My SNS appears to be of very poor quality I have my personal information (such as real name, current town, sexual orientation, education, employment, and so on) on my SNS I have my contact information (such as , cell phone number, address and so on) on my SNS I have shared my personal pictures on my SNS I have shared my personal videos on my SNS I have shared my ideas, opinions and recommendations through my SNS I have sought help on my SNS People who influence my behavior think I should use the SNS. People who are important to me think I should use the SNS. People whose opinions I value encourage me to use the SNS. There is a sense of human contact in my SNS. There is a sense of personalness in my SNS. There is a sense of sociability in my SNS. There is a sense of human warmth in my SNS. There is a sense of human sensitivity in my SNS. I generally trust other people. I tend to count on other people. I generally have faith in humanity. I feel that people are generally reliable. I generally trust other people unless they give me reason not to. My SNS is a trustworthy social network. I can count on my SNS to protect my privacy. I can count on my SNS to protect my personal information from unauthorized use. My SNS can be relied on to keep its promises. I am concerned that the information I submit to this website may be viewed by an unintended audience. Proceedings of the Nineteenth Americas Conference on Information Systems, Chicago, Illinois, August 15-17,