Tuesday, September 17, 2019
Auyon Siddiq, University of California, Los Angeles (UCLA) - Anderson School of Management and Terry Taylor, University of California, Berkeley - Haas School of Business analyze Ride-Hailing Platforms: Competition and Autonomous Vehicles.
ABSTRACT: Problem Definition: Ride-hailing platforms, which compete over drivers and riders, assert that autonomous vehicles (AVs) will transform their operations by reducing variable cost payments to drivers. This paper explores the implications of competition and access to AVs for the management of ride-hailing platforms.
Academic/Practical Relevance: Ride-hailing, which has been transformed by platforms' use of independent driver-workers, has the potential to be transformed again by AVs. Methodology: We employ a game-theoretic model that captures platforms' AV fleet size, price and wage decisions.
Results: A platform's access to supply-side (namely, AV) technology changes prescriptions for its demand-side (namely, pricing) decisions: The intuitive prescription from the setting without AVs, that price increases in the intensity of competition in the labor market, is reversed. The presence of demand-side competition changes prescriptions for a platform's supply-side (namely, AV fleet size) decisions: The intuitive prescription from the setting without demand-side competition, that the AV fleet size increases in the intensity of competition in the labor market, is reversed. We characterize the conditions under which these reversals occur and explain the driving forces behind the reversals. Finally, whether a platform benefits from its rival's access to AV technology depends on a simple comparison between the relative wage sensitivity of labor and the relative price sensitivity of demand.
Managerial Implications: Competition and access to AVs each reverse intuitive prescriptions for the management of ride-hailing platforms.