Abstract
Ride-sourcing has the potential to attract demand from more sustainable modes, alter activity patterns, and worsen congestion; however, it can also help increase the mobility and accessibility of those who cannot drive. Understanding how and why these services are used can help inform policies that address the negative externalities of these services while taking advantage of their benefits. This study examines the use of ride-sourcing services, which were introduced just before the COVID-19 pandemic, in the Metro Vancouver Region. Using data from a web-based survey, this study applies latent class cluster analysis to identify profiles of ride-sourcing users based on the purposes for which they use ride-sourcing. To the authors’ knowledge, this is only the second study to identify latent segments of ride-sourcing users and the first to do so based on the purposes of their ride-sourcing trips. Additionally, the decision to use ride-sourcing and the profile to which an individual belongs are jointly modelled using a two-stage multinomial logistic regression model. The results suggest the impacts of ride-sourcing use on other modes and the frequency of ride-sourcing use may differ based on the profile to which the user belongs. Besides, the findings of this study highlight the influence of socio-demographic attributes, the use of other shared mobility services, and attitudinal factors on the utilization of ride-sourcing. This study aims to contribute to the literature by offering further insights into the heterogeneity among ride-sourcing users, which can help inform a more targeted approach to addressing the negative externalities of these services.
Published Version
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call