Examining the Heterogeneous Impact of Ride-Hailing Services on Public Transit Use

Abstract

Practice or Policy Abstract

Abstract

Over the past 10 years, app-enabled ride-hailing services such as Uber and Lyft have permeated several geographies, fundamentally changing the transit landscape. Ride-hailing services deliver an on-demand, door-to-door transport service that has the potential to interact with other preexisting modes of transport, potentially serving as a complement (e.g., expanding the geographic coverage of a transit mode) or as a replacement. In this study, the authors explore these effects on various modes of public transit across 200 cities in the United States, paying particular attention to the features of a transit mode and the local operating context. The study demonstrates that, on average, Uber has tended to displace city bus services while complementing commuter rail services. Further, the study demonstrates the importance of local context, in that the average effect on a particular transit mode is found to depend on a variety of surrounding factors, including weather patterns, rates of violent crime, gas prices, and the overall quality of the public transit services. This work offers actionable insights for policymakers, public-transit managers, and ride-hailing service operators. Estimates of the annual profit (cost) impacts that ride-hailing services have had on particular cities’ transit services are provided.

Abstract

We examine the impact that ride-hailing services have had on the demand for different modes of public transit in the United States, with a particular focus on understanding heterogeneity in the effects. We assess these effects using a panel data set that combines information on public transit utilization (from the Federal Transit Administration) with information on ride-hailing providers’ staggered arrival into different locations, based on public press releases and newspaper reports. Our analysis indicates that, on average, ride-hailing services have led to significant reductions in the utilization of city bus services while increasing utilization of commuter rail services. These average effects are also subject to a great deal of contextual heterogeneity, depending on the size of the local population, rates of violent crime, weather, gas prices, transit riders’ average trip distance, and the overall quality of public transit options. We demonstrate the robustness of our findings to alternative model specifications. Our findings contribute to the prior literature on technology substitution and complementarity and suggest explanations for contradictory findings that have been reported on ride-hailing’s influence on public transit demand. We also offer useful insights for policymakers, highlighting the nuanced implications of ride-hailing services for different transit operators, depending on the local context.