Yale SOM Research Investigating Bias in the Gig Economy Honored at INFORMS Conference
Doctoral student Fei Teng and Professors Tristan Botelho and K. Sudhir won the Best Diversity, Equity, Inclusion, and Justice Paper Award.
A Yale SOM study examining the spread of racial bias through gig-economy ratings systems won the Best Diversity, Equity, Inclusion, and Justice (DEIJ) Paper Award this month at the annual meeting of INFORMS, the Institute for Operations Research and the Management Sciences, in Phoenix.
Fei Teng, a doctoral student in quantitative marketing; Tristan Botelho, associate professor of organizational behavior; and K. Sudhir, the James L. Frank ’32 Professor of Private Enterprise and Management and professor of marketing, were honored for “Can Customer Ratings be Discrimination Amplifiers? Evidence from a Gig Economy Platform.” In the study, they found that even a small number of biased customers can create systemic disadvantages for people of color on gig-economy platforms like Uber and TaskRabbit, because their biased ratings affect the behavior of customers who otherwise would not discriminate.
The award was presented on October 16 at a meeting of INFORMS’ Service Science Section.