Determinants of travel mode choices of post-secondary students in a large metropolitan area: The case of the city of Toronto
place - north america, place - universities, planning - surveys, ridership - behaviour, ridership - commuting, ridership - demand, ridership - mode choice
mode choice, Toronto, travel diary
The paper presents an investigation on the mode choice behaviour of post-secondary students commuting to school in the city of Toronto. It uses a large-scale dataset collected through a web-based travel diary survey among all students of four universities (seven campuses) in Toronto. Multinomial logit (MNL), nested logit (NL) and cross-nested logit (CNL) models are used for investigating home to school trips mode choices. In terms of goodness-of-fit, the CNL outperforms the MNL and NL model. Furthermore, the proposed CNL model shows fundamental improvements over the MNL and NL models by capturing non-proportional substitution patterns. Empirical models reveal that the mode choice behaviour of female students who travel to downtown campuses differ significantly from female students who travel to suburban campuses. Female students who travel towards downtown are more transit and active mode oriented than those who travel towards outside of downtown. This study also shows mobility tool ownerships (i.e., transit pass, car and bike ownership) and age groups have distinctive influences on student's mode choice behaviour. Using the CNL model as a tool for policy scenario analysis, it is found that public transit users are highly sensitive to changes in travel time. In the context of policy implementation, if bike and ride mode is encouraged during peak hour commuting, there is likely a large amount of latent demand for this mode.
Permission to publish the abstract has been given by Elsevier, copyright remains with them.
Hasnine, M.S., Lin, T., Weiss, A., & Habib, K.N. (2018). Determinants of travel mode choices of post-secondary students in a large metropolitan area: The case of the city of Toronto. Journal of Transport Geography, Vol. 70, pp. 161-171.