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Modelling the choice and timing of acquiring a driver’s license: Revelations from a hazard model applied to the University students in Toronto

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  • Nurul Habib, Khandker

Abstract

The declining rate of acquiring drivers’ licenses by young adults in developed countries has elicited concern among transportation researchers because of the potential consequences for future urban transportation systems. The study uses a dataset collected through a large-scale survey of the students of all four universities in Toronto. The specific aim of the study is to improve understanding of factors affecting the choice of acquiring driver’s license by university students in Toronto. Unlike similar studies, it employs econometric approach for the disaggregate analysis using a unique dataset of social-economic, personal, transportation system and land use related variables. Results reveal that the living conditions of university students in the form of living with parents/family show the highest influence in delaying in acquiring drivers’ licenses. However, the empirical model also identifies that better transit accessibility plays the second most critical role in delaying the choice of acquiring a driver’s license. Public transit pass ownership is proven to be an important mobility tool that discourages the acquiring of drivers’ licenses by the students. Students living in densely populated neighborhoods are more likely to delay or do not acquire a driver’s license. Students who delay acquiring their driver’s license may remain transit-users during their time as students and may also continue to have similar public transit use in future.

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  • Nurul Habib, Khandker, 2018. "Modelling the choice and timing of acquiring a driver’s license: Revelations from a hazard model applied to the University students in Toronto," Transportation Research Part A: Policy and Practice, Elsevier, vol. 118(C), pages 374-386.
    • Handle: RePEc:eee:transa:v:118:y:2018:i:c:p:374-386
    DOI: 10.1016/j.tra.2018.09.012
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    8. Aghaabbasi, Mahdi & Shekari, Zohreh Asadi & Shah, Muhammad Zaly & Olakunle, Oloruntobi & Armaghani, Danial Jahed & Moeinaddini, Mehdi, 2020. "Predicting the use frequency of ride-sourcing by off-campus university students through random forest and Bayesian network techniques," Transportation Research Part A: Policy and Practice, Elsevier, vol. 136(C), pages 262-281.
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