Dennis Zhang, Washington University, St. Louis
Dennis Zhang, Washington University, St. Louis
Discrimination with Incomplete Information in the Sharing Economy: Evidence from Field Experiments on Airbnb
Discrimination with Incomplete Information in the Sharing Economy: Evidence from Field Experiments on Airbnb
12 Oct 201712:30 PM – 2:00 PM
Faculty and doctoral students only
Location:
Baker Library | Bloomberg Center 102
Organizer:
Recent research has found widespread discrimination by
hosts against guests of certain races in online marketplaces. In this paper, we
explore how to reduce such discrimination with online reputation systems. We
conducted two randomized field experiments among 1,256 hosts on Airbnb by
creating fictitious guest accounts and sending accommodation requests to them.
We find that requests from guests with distinctively African American names are
19 percentage points less likely to be accepted than those with distinctively
White names. However, a public review posted on a guest’s page significantly
reduces discrimination: when guest accounts receive a positive review, the
acceptance rates of guest accounts with distinctively White and African
American names are statistically indistinguishable. We further demonstrate that
a non-positive review also significantly reduces discrimination. Our finding is
consistent with statistical discrimination: when lacking perfect information,
hosts infer the quality of a guest by race and make rental decisions based on
the average predicted quality of each racial group; when more information is
provided, hosts infer less from guests’ race about their quality, and discrimination
is reduced. Our results offer direct and clear guidance for sharing-economy
platforms on how to reduce discrimination.