Recent statistics provide solid evidence on the popularity of ride-hailing services as emerging mobility choices. However, there is still a gap between the occasional adoption of such modes and viewing them as a permanent replacement for conventional mobility options. This research analyzes frequent ride-hailing decisions by identifying significant determinants and their impacts on ride-hailing behavior. A principal component analysis was conducted to identify latent patterns of mode dependency. These latent factors were incorporated into a support vector machine model to classify the sample into frequent versus non-frequent ride-hailers. Results showed that transit-dependent travelers reflected the highest affinity towards regular ride-hailing. Those who use their cars solely for daily commutes and non-driving students came next. Highly car-dependent travelers and individuals from large families were less likely to be frequent ride-hailing users. Results from this study provide a clearer picture of the current ride-hailing market and its impact on vehicle ownership patterns.

CICTP