Impact of ride-hailing services on travel behavior

dissertationRide-hailing services are getting more popular each year, and their markets are growing. Much has been speculated, but not much has been tested, regarding their impacts on the transportation system. This dissertation consists of three papers that share the foundational literature and core concepts of built environment, on-demand ride services, and travel behavior research. In the first study, I examine the relationship between ride-sourcing services and vehicle ownership of households, by using the most up-to-date (2017) national household travel survey (NHTS) data. To better capture the effect of ride-sourcing services on vehicle ownership, I controlled for the effect of socioeconomic characteristics of households and built environment variables, the so- called D variables, i.e., density, diversity, design, and distance to transit. The results suggest that there is a negative correlation between using ride-sourcing services and vehicle ownership. Vehicle ownership is also negatively associated with the number of years Uber has operated in a county. In the second study, through unique access to Uber trip data in 24 diverse U.S. regions, I provide a robust data-driven understanding of how ride-sourcing demand is affected by the built environment, after controlling for socioeconomic factors. Results suggest that Uber demand is positively correlated with total population and employment, activity density, land use mix or entropy, and transit stop density of a census block group. In contrast, Uber demand is negatively correlated with intersection density and iv destination accessibility (both by auto and transit) variables. In the third paper, also using the NHTS data, I investigate how built environment characteristics impact the choice of ride-sourcing services over other modes of transportation. The results suggest that the impact of built environment on modes of travel varies by trip purposes, while most of the directions remain the same. Overall, an increase in D variables is associated with an increase in the choice of ride-sourcing services as well as sustainable modes of transportation. Findings of this dissertation have important implications for policy, planning, and travel demand modeling, where decision-makers seek solutions to shape the built environment in order to reduce automobile dependence and promote walking, biking, and transit use