Screening Mechanism When Online Users Have Privacy Concerns

31 Pages Posted: 8 May 2019

See all articles by Jagan Jacob

Jagan Jacob

University of Rochester - Simon Business School

Date Written: April 16, 2019


In consumer-to-consumer online platforms that enable selling (e.g., eBay, Taobao) or sharing (e.g., Airbnb, Uber) of goods and services, information asymmetry between providers (e.g., sellers, hosts, drivers) and consumers (e.g., buyers, guests, passengers) pose challenges. Such platforms facilitate transactions between users (providers and consumers), who are often strangers. Stricter screening, background checks, and identity verification requirements may reduce the probability of bad users entering the platform. However, users are reluctant to share personal information on the Internet. We design a matching mechanism to maximize platform profit when users are heterogeneous with some more likely to be good than others, but the platform does not know who. We argue that in some cases, the platform increases its profit by allowing users with a higher probability of being bad to join as well.

Keywords: Game Theory, Information Asymmetry, Mechanism Design, Incentive Compatibility, Online Platforms, Trust, Electronic Commerce, Sharing Economy

JEL Classification: D42, D82, L86, M10, M20, M30

Suggested Citation

Jacob, Jagan, Screening Mechanism When Online Users Have Privacy Concerns (April 16, 2019). Available at SSRN: or

Jagan Jacob (Contact Author)

University of Rochester - Simon Business School ( email )

Rochester, NY 14627
United States

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