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Research Note —Privacy Concerns and Privacy-Protective Behavior in Synchronous Online Social Interactions

Author

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  • Zhenhui (Jack) Jiang

    (Department of Information Systems, School of Computing, National University of Singapore, Singapore 117418; and National University of Singapore (Suzhou) Research Institute, Suzhou, People's Republic of China 215123)

  • Cheng Suang Heng

    (Department of Information Systems, School of Computing, National University of Singapore, Singapore 117418)

  • Ben C. F. Choi

    (Australian School of Business, The University of New South Wales, Sydney, NSW 2052, Australia)

Abstract

Privacy is of prime importance to many individuals when they attempt to develop online social relationships. Nonetheless, it has been observed that individuals' behavior is at times inconsistent with their privacy concerns, e.g., they disclose substantial private information in synchronous online social interactions, even though they are aware of the risks involved. Drawing on the hyperpersonal framework and the privacy calculus perspective, this paper elucidates the interesting roles of privacy concerns and social rewards in synchronous online social interactions by examining the causes and the behavioral strategies that individuals utilize to protect their privacy. An empirical study involving 251 respondents was conducted in online chat rooms. Our results indicate that individuals utilize both self-disclosure and misrepresentation to protect their privacy and that social rewards help explain why individuals may not behave in accordance with their privacy concerns. In addition, we find that perceived anonymity of others and perceived intrusiveness affect both privacy concerns and social rewards. Our findings also suggest that higher perceived anonymity of self decreases individuals' privacy concerns, and higher perceived media richness increases social rewards. Generally, this study contributes to the information systems literature by integrating the hyperpersonal framework and the privacy calculus perspective to identify antecedents of privacy trade-off and predict individuals' behavior in synchronous online social interactions.

Suggested Citation

  • Zhenhui (Jack) Jiang & Cheng Suang Heng & Ben C. F. Choi, 2013. "Research Note —Privacy Concerns and Privacy-Protective Behavior in Synchronous Online Social Interactions," Information Systems Research, INFORMS, vol. 24(3), pages 579-595, September.
    • Handle: RePEc:inm:orisre:v:24:y:2013:i:3:p:579-595
    DOI: 10.1287/isre.1120.0441
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    14. Tawfiq Alashoor & Mark Keil & H. Jeff Smith & Allen R. McConnell, 2023. "Too Tired and in Too Good of a Mood to Worry About Privacy: Explaining the Privacy Paradox Through the Lens of Effort Level in Information Processing," Information Systems Research, INFORMS, vol. 34(4), pages 1415-1436, December.
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    16. Beke, Frank T. & Eggers, Felix & Verhoef, Peter C. & Wieringa, Jaap E., 2022. "Consumers’ privacy calculus: The PRICAL index development and validation," International Journal of Research in Marketing, Elsevier, vol. 39(1), pages 20-41.
    17. Girish N. Punj, 2019. "Understanding individuals’ intentions to limit online personal information disclosures to protect their privacy: implications for organizations and public policy," Information Technology and Management, Springer, vol. 20(3), pages 139-151, September.
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    19. Crystal Reeck & Xue Guo & Angelika Dimoka & Paul A. Pavlou, 2024. "Uncovering the Neural Processes of Privacy: A Neurally Informed Behavioral Intervention to Protect Information Privacy," Information Systems Research, INFORMS, vol. 35(2), pages 727-746, June.
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    21. Chen Liang & Jing Peng & Yili Hong & Bin Gu, 2023. "The Hidden Costs and Benefits of Monitoring in the Gig Economy," Information Systems Research, INFORMS, vol. 34(1), pages 297-318, March.

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