Events

Dr. Dandan Qiao
Assistant professor
Department of Information Systems and Analytics
National University of Singapore

Ride-hailing services have generated remarkable impacts on various aspects of society, but little is known about their influences on hate crimes. We make use of the staggered time points that Uber enters United States counties to create a difference-in-differences model. Our estimations show that Uber-like sharing gigs can significantly reduce hate crimes by around 5.7%. Various robustness checks are conducted to provide evidence supporting our findings. To uncover the underlying mechanics, we introduce the contact theory from psychology into the ride sharing context. Uber services connect members from different groups (e.g., races) into each ride, which offers a natural chance for intergroup interactions. As a consequence, better mutual understanding between groups is built up and prejudice against outgroup individuals is lessened, which leads to the decline of hate crimes. We further verify this contact-based mechanism from different angles, including providing direct evidence through the results of an online survey. This study has important theoretical and practical implications, through advancing our understanding of the effects of ride-sharing and guiding policy makers to combat hate crimes.