Understanding Variations in Tipping Behavior in Ridesharing Services
Soo Jeong Hong, Nelson Granados, Kwangjin Lee, and Johannes M. Bauer
International Journal of Electronic Commerce,
Volume 29, Number 3, 2025, pp. 460-495.
Abstract:
Researchers and policymakers currently debate whether providers in sharing economy platforms receive fair compensation, and platform companies are increasingly being regulated to address this problem. This study provides a different angle to the problem, by examining the contribution to compensation by consumers in ridesharing services, leveraging the fact that ridesharing platforms such as Uber and Lyft allow passengers to tip the driver. Using an online experiment with 8,413 participants, we explore how extrinsic attributes of consumers and service providers affect the valuation of the service and the tipping behavior. We find no evidence of systematically biased tipping at an aggregate level, but we do find in-group bias in the form of positive discrimination when White passengers have the same gender as the driver, and Black, Hispanic, and Asian passengers tip drivers more when they share the same race. We also observe out-group bias among White passengers, who tip Hispanic drivers more. We also find that White passengers who use ridesharing services more frequently and for longer durations tend to tip less, whereas Black and Asian passengers who use ridesharing more frequently or for longer durations tend to tip more. Passengers who value justice tend to tip more overall. The findings offer insights for the management of ridesharing platforms by companies and inform pending public policy debates.