Screening Mechanism When Online Users Have Privacy Concerns

Abstract

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 cheeks, 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 maximise 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.