Dennis Zhang, Assistant Professor of Operations and Manufacturing Management at Olin co-authors an article on HBR, “A Better Way to Fight Discrimination in the Sharing Economy” about their research on potential bias on sites like Airbnb.
“We know discrimination exists in the sharing economy,” said Zhang. “We wanted to find out how do we prevent it, and how do we mitigate it?”
In a working paper, Zhang and his co-authors, Ruomen Cui, assistant professor at the Kelly School of Business at Indiana University, and Jun Li, assistant professor at University of Michigan’s Stephen M. Ross School of Business, conducted two randomized field experiments among more than 1,200 Airbnb hosts in Boston, Chicago and Seattle. The researchers used fictitious guest accounts and sent accommodation requests to the hosts using those accounts.
They found requests from guests with African American names — based on name frequency data published by the U.S. Census Bureau— were 19 percent less likely to be accepted than those with Caucasian names.
However, when the researchers posted a single host review for each fictitious user, the tables turned: Acceptance rates for both sets of guests evened out. Zhang says this fact shows strong evidence of concept called statistical discrimination with Airbnb.
The researchers conclude that more information about guests, as opposed to less, is important to eliminate potential bias in sharing economy platforms such as Airbnb.