2012International Journal of Electronic CommerceRequires access

Disclosure Intention of Location-Related Information in Location-Based Social Network Services

Ling Zhao, Yaobin Lu, Sumeet Gupta

Open publisher page 243 citations

Abstract

Although location-based social network (LBSN) services have developed rapidly in recent years, the reasons why people disclose location-related information under this environment have not been adequately investigated. This study builds a privacy calculus model to investigate the factors that influence LBSN users' intention to disclose location-related information in China. In addition, this study applies justice theory to investigate the role of privacy intervention approaches used by LBSN Web sites in enhancing users' perception of justice, including incentives provision, interaction promotion, privacy control, and privacy policy. Model testing using structural equation modeling reveals that perceived cost (users' privacy concerns) and perceived benefits (personalization and connectedness) influence intention to disclose location-related information. Meanwhile, providing incentives and promoting interaction enhance, respectively, personalization and connectedness. Privacy control and privacy policies both help in reducing privacy concerns. We also find that individuals' awareness of Internet privacy legislation negatively influences privacy concerns, whereas previous privacy invasions do not. Finally, we find that personal innovativeness significantly influences intention to disclose location-related information. This study not only extends the privacy research on social networking sites under mobile environments but also provides practical implications for service providers and policy makers to develop better LBSNs.

About this research paper

What this paper is about

Although location-based social network (LBSN) services have developed rapidly in recent years, the reasons why people disclose location-related information under this environment have not been adequately investigated. This study builds a privacy calculus model to investigate the factors that influence LBSN users' intention to disclose location-related information in China. In addition, this study applies justice theory to investigate the role of privacy intervention approaches used by LBSN Web sites in enhancing users' perception of justice, including incentives provision, interaction promotion, privacy control, and privacy policy. Model testing using structural equation modeling reveals that perceived cost (users' privacy concerns) and perceived benefits (personalization and connectedness) influence intention to disclose location-related information. Meanwhile, providing incentives and promoting interaction enhance, respectively, personalization and connectedness. Privacy control and privacy policies both help in reducing privacy concerns. We also find that individuals' awareness of Internet privacy legislation negatively influences privacy concerns, whereas previous privacy invasions do not. Finally, we find that personal innovativeness significantly influences intention to disclose location-related information. This study not only extends the privacy research on social networking sites under mobile environments but also provides practical implications for service providers and policy makers to develop better LBSNs.

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OpenAlex reports 243 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

Although location-based social network (LBSN) services have developed rapidly in recent years, the reasons why people disclose location-related information under this environment have not been adequately investigated. This study builds a privacy calculus model to investigate the factors that influence LBSN users' intention to disclose location-related information in China. In addition, this study applies justice theory to investigate the role of privacy intervention approaches used by LBSN Web sites in enhancing users' perception of justice, including incentives provision, interaction promotion, privacy control, and privacy policy. Model testing using structural equation modeling reveals that perceived cost (users' privacy concerns) and perceived benefits (personalization and connectedness) influence intention to disclose location-related information. Meanwhile, providing incentives and promoting interaction enhance, respectively, personalization and connectedness. Privacy control and privacy policies both help in reducing privacy concerns. We also find that individuals' awareness of Internet privacy legislation negatively influences privacy concerns, whereas previous privacy invasions do not. Finally, we find that personal innovativeness significantly influences intention to disclose location-related information. This study not only extends the privacy research on social networking sites under mobile environments but also provides practical implications for service providers and policy makers to develop better LBSNs.

Key concepts: Internet privacy, Structural equation modeling, Business, Social connectedness, Personalization, Information privacy, Incentive, Privacy policy

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