On the Influence of Land Use and Transit Network Attributes on the Generation of, and Relationship between, the Demand for Public Transit and Ride-Hailing Services in Toronto

Document Type

Journal Article

Publication Date


Subject Area

place - north america, place - urban, planning - surveys, ridership - demand, ridership - modelling, land use - impacts


Built environment, Demand, Demographics, Land use, Probits, Public transit, Regression analysis, Ridership, Ridesourcing, Social factors, Travel surveys


In North American cities, the growing use of ride-hailing services, such as Uber and Lyft, has occurred at a time when public transit ridership has either stagnated or declined. Previous studies on the topic have found that the relationship between ride-hailing and public transit services tends to be context-specific in nature. In some cases, ride-hailing has been shown to complement public transit, while, in others, it can be a substitute. This paper takes an integrated approach to modeling the generation of demand for ride-hailing and public transit services, using trip-level ride-hailing data and data from a regional household travel survey. In addition, the relationship between the demand for ride-hailing and transit services is also explored. This paper uses the bivariate ordered probit model and the recursive regression model to study the role that built environment and socio-demographic attributes play in the generation of transit and ride-hailing demand. The model results reveal that there are several built environment attributes, such as transit accessibility and the density of commercial and recreational establishments, that influence the generation of both ride-hailing and transit demand. The results also indicate that the relationship between ride-hailing and transit services tends to be more complementary than substitutive in nature. This does not, however, mean that ride-hailing services are never used as a substitute for public transit in Toronto. The results of this study aim to provide transit agencies with a means of identifying locations where ridership may be threatened by ride-hailing services.


Permission to publish the abstract has been given by SAGE, copyright remains with them.