Love at First Sight: The Interplay Between Privacy Dispositions and Privacy Calculus in Online Social Connectivity Management

• Published in: Journal of the Association for Information Systems Vol. 19; no. 3; pp. 124 - 151
• Main Authors: Choi, Ben, Wu, Yi, Yu, Jie, Land, Leslie
• Format: Journal Article
• Language: English
• Published: Atlanta Association for Information Systems 01.01.2018
• Subjects: Behavior; Calculus; Capital gains; Chat rooms; Communication; Connectivity; Friendship; Identity theft; Information systems; Location based services; Personal information; Privacy; Social capital; Social networks; Social research; Theory; Websites
• ISSN: 1536-9323; 1536-9323
• DOI: 10.17705/1jais.00487

Privacy has become the key concern of many users when they are confronted with friend requests on online social networking websites. Nonetheless, users' responses to friend requests seem at times inconsistent with their concerns about potential privacy implications. They accept friend requests and expose their personal profiles to largely unfamiliar others even though they are aware of the risks involved. Drawing on impression formation theory and the privacy calculus perspective, this paper elucidates the intriguing roles of privacy risks and expected social capital gains in social connectivity management by examining the key types of social information that users consider and their behavioral responses to online friend requests. We conducted a scenariobased experiment with 141 subjects. Our results indicate that individuals utilize two key types of social information; namely, network mutuality and profile diagnosticity in evaluating privacy risks and expected social capital gains. In addition, we find that privacy risks and expected social capital gains powerfully predict the likelihood of no-action and the likelihood of accepting friend requests on online social networking websites. In sum, this study contributes to the information systems literature by integrating impression formation theory and the privacy calculus perspective to identify the key types of social information that influence privacy tradeoff and predict individuals' behavioral responses toward establishing new online social connections.