An Economic Analysis of Peer-Disclosure in Online Social Communities

Zike Cao, KL Hui, H Xu

Research output: Contribution to journalArticleAcademicpeer-review

13 Citations (Scopus)
117 Downloads (Pure)

Abstract

We study a novel privacy concern, viz. peer disclosure of sensitive personal information in online social communities. We model peer disclosure as imposing a negative externality on other people. Our model encompasses the benefits from posting information, positive externalities such as recognition and entertainment benefits due to others' sharing of information, and heterogeneous privacy preferences. We find that regulation of peer disclosure is necessary. We consider two candidate regulations -- nudging and quota. Nudging reduces user participation and privacy harm and sometimes improve social welfare. By contrast, imposing a quota often improves user participation, privacy protection and social welfare. Adding a nudge on top of a quota does not bring additional benefits. We show that any regulation that uniformly controls the disclosure of sensitive and nonsensitive information will not serve the triple objectives of reducing privacy harm, increasing social welfare, and increasing information contribution. We derive a necessary condition for solutions that can fulfill these three objectives. We also compare the incentives of the platform owner and social planner and draw related managerial and policy implications.
Original languageEnglish
Pages (from-to)546-566
Number of pages21
JournalInformation Systems Research
Volume29
Issue number3
DOIs
Publication statusPublished - 20 Jul 2018

Research programs

  • RSM LIS

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