  In light of the increasing interest to transform the fixed-route public
transit (FRT) services into on-demand transit (ODT) services, there exists a
strong need for a comprehensive evaluation of the effects of this shift on the
users. Such an analysis can help the municipalities and service providers to
design and operate more convenient, attractive, and sustainable transit
solutions. To understand the user preferences, we developed three hybrid choice
models: integrated choice and latent variable (ICLV), latent class (LC), and
latent class integrated choice and latent variable (LC-ICLV) models. We used
these models to analyze the public transit user's preferences in Belleville,
Ontario, Canada. Hybrid choice models were estimated using a rich dataset that
combined the actual level of service attributes obtained from Belleville's ODT
service and self-reported usage behaviour obtained from a revealed preference
survey of the ODT users. The latent class models divided the users into two
groups with different travel behaviour and preferences. The results showed that
the captive user's preference for ODT service was significantly affected by the
number of unassigned trips, in-vehicle time, and main travel mode before the
ODT service started. On the other hand, the non-captive user's service
preference was significantly affected by the Time Sensitivity and the Online
Service Satisfaction latent variables, as well as the performance of the ODT
service and trip purpose. This study attaches importance to improving the
reliability and performance of the ODT service and outlines directions for
reducing operational costs by updating the required fleet size and assigning
more vehicles for work-related trips.
