Previous studies on information disclosure have heavily relied on the justice theory to explain how users balance the benefits and privacy risks (e.g., privacy calculus) induced by the information disclosure behavior. However, the specific mechanism of privacy calculus (or the role of justice) and the boundary conditions under which the privacy calculus works have been rarely empirically investigated. To fill this research gap, we propose a moderated mediation model to examine the mediating role of justice and the conditions under which the mediating mechanism applies. Based on a field survey from the users of location-based social networks in China, we find that (1) privacy risks weaken the relationship between perceived benefits and perceived justice but strengthen the relationship between perceived justice and information disclosure intention, (2) privacy risks weaken the direct effect of perceived benefits on intention while strengthen the indirect effect of perceived benefits on intention via perceived justice, and (3) the total effect of perceived benefits on intention is stronger when privacy risks are lower than when they are higher. This paper contributes to the information disclosure literature by highlighting the moderated mediation mechanism of the key factors identified in previous research.
Sun, Yongqiang; Wang, Nan; and Shen, Xiao-Liang, "PERCEIVED BENEFITS, PRIVACY RISKS, AND PERCEIVED JUSTICE IN LOCATION INFORMATION DISCLOSURE: A MODERATED MEDIATION ANALYSIS" (2014). PACIS 2014 Proceedings. 135.