Modeling Ride-Hailing and Carsharing Adoption & Use Patterns: Deciphering the Substitutive and Complementary Impacts of Built Environment, Transit Accessibility, & Active Travel

The rise of shared mobility services, including carsharing and ride-hailing, has transformative impacts on transportation systems. We present a behavioral framework to jointly model individuals’ carsharing and ride-hailing use with a focus on deciphering the substitutive vs. complementary roles of the built environment, transit accessibility, and active travel. Based on a sample of over 3,200 individuals from the 2019 Puget Sound Travel Survey, detailed travel behavior data are spatially integrated with neighborhood-level objectively assessed built environment and transit accessibility data. Joint heterogeneity-based multivariate ordered discrete choice models are specified to simultaneously account for random (unobserved) and systematic (observed) heterogeneity. The use patterns of carsharing and ride-hailing services exhibited positive dependence. Reflecting complementary impacts, neighborhood walkability, urban compactness, pedestrian-oriented urban design, and transit accessibility exhibited positive associations with individuals’ carsharing and ride-hailing use. Active travel behaviors (walking, biking, and transit use) also exhibited synergistic relationships with carsharing and ride-hailing use. While transit accessibility and active travel independently complement shared mobility services, our findings indicate that the interaction between the two could replace ride-hailing services. Results suggest a mix of complementary vs. substitutive impacts, as opposed to the assumption of dichotomized (complementary or substitutive) impacts. Significant random and systematic heterogeneity in the behavioral, environmental, and demographic determinants of shared mobility services was revealed. We discuss the relevance and implications of the new findings considering scenario planning and travel demand modeling needs.