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Daily activity and travel sequences of students, faculty and staff at a large Canadian university

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  • Mohammad Hesam Hafezi
  • Naznin Sultana Daisy
  • Lei Liu
  • Hugh Millward

Abstract

This paper examines the activity engagement, sequencing and timing of activities for student, faculty and staff commuter groups at the largest university in the Maritime Provinces of Canada. The daily activity patterns of all university community groups are modeled using the classification and regression tree classifier algorithm. The data used for this study are derived from the Environmentally Aware Travel Diary Survey (EnACT) conducted in spring 2016 at Dalhousie University, Nova Scotia. Results show that there are significant differences in activity and travel behavior between university population segments and the general population in the region, and between campus groups. For example, students participate in more recreation activities compared to faculty and staff. They also take more trips to and from campus, and are more flexible in their scheduling of trips. The insights gained from this study will provide helpful information for promoting sustainability across university campuses, and for development of campus-based travel demand management strategies.

Suggested Citation

  • Mohammad Hesam Hafezi & Naznin Sultana Daisy & Lei Liu & Hugh Millward, 2018. "Daily activity and travel sequences of students, faculty and staff at a large Canadian university," Transportation Planning and Technology, Taylor & Francis Journals, vol. 41(5), pages 536-556, July.
    • Handle: RePEc:taf:transp:v:41:y:2018:i:5:p:536-556
    DOI: 10.1080/03081060.2018.1469286
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    Cited by:

    1. Hamad, Khaled & Obaid, Lubna, 2022. "Tour-based travel demand forecasting model for a university campus," Transport Policy, Elsevier, vol. 117(C), pages 118-137.
    2. Hossain, Sanjana & Loa, Patrick & Ong, Felita & Habib, Khandker Nurul, 2022. "The determinants of commute mode usage frequency of post-secondary students in the Greater Toronto and Hamilton Area," Transportation Research Part A: Policy and Practice, Elsevier, vol. 166(C), pages 164-185.
    3. Daisy, Naznin Sultana & Millward, Hugh & Liu, Lei, 2018. "Trip chaining and tour mode choice of non-workers grouped by daily activity patterns," Journal of Transport Geography, Elsevier, vol. 69(C), pages 150-162.

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