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Trip chaining and tour mode choice of non-workers grouped by daily activity patterns

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  • Daisy, Naznin Sultana
  • Millward, Hugh
  • Liu, Lei

Abstract

Transportation planners are increasingly looking to reduce drive-alone travel. However, the existence of complex tours could be a major barrier to the shift from drive-alone to public transport. This is particularly problematical for the non-worker segment of the population (most of whom are women and/or older adults). To better understand how socio-demographics, trip attributes, and land use pattern shape tour complexity and mode choices for individuals, this paper introduces a cluster-based approach to model tour complexity, trip chaining, and tour mode choice. Based on daily activity patterns and time-use, five non-worker clusters were identified from the Space-Time Activity Research (STAR) data for Halifax, Canada. Number of tours per day for all clusters was modeled using a Poisson regression model. Trip chaining was then modeled using an Ordered Probit model. Finally, tour mode choice was modeled using a Multinomial Logit (MNL) model. This framework utilizes home-based travel tours, the sequence of trips that begin and end at home, as the basic unit of analysis. Results show that socio-demographic characteristics and tour attributes are strong explanatory factors of travel behavior, consistent with existing literature. Also, urban form characteristics have significant influence on non-workers' travel behaviour and tour complexity. This paper also offers a typology of travel tours to account for different non-work travel purposes. The findings of this study will improve the future evaluation of transportation projects and land-use policymaking.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:jotrge:v:69:y:2018:i:c:p:150-162
    DOI: 10.1016/j.jtrangeo.2018.04.016
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    References listed on IDEAS

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    1. Frank Primerano & Michael Taylor & Ladda Pitaksringkarn & Peter Tisato, 2008. "Defining and understanding trip chaining behaviour," Transportation, Springer, vol. 35(1), pages 55-72, January.
    2. Ho, Chinh Q. & Mulley, Corinne, 2013. "Multiple purposes at single destination: A key to a better understanding of the relationship between tour complexity and mode choice," Transportation Research Part A: Policy and Practice, Elsevier, vol. 49(C), pages 206-219.
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    Cited by:

    1. Franco, Patrizia & Johnston, Ryan & McCormick, Ecaterina, 2020. "Demand responsive transport: Generation of activity patterns from mobile phone network data to support the operation of new mobility services," Transportation Research Part A: Policy and Practice, Elsevier, vol. 131(C), pages 244-266.
    2. Fang, Jia & Yan, Xiang & Bejleri, Ilir & Chen, Changjie, 2022. "Which trip destination matters? Estimating the influence of the built environment on mode choice for home-based complex tours," Journal of Transport Geography, Elsevier, vol. 105(C).
    3. Bautista-Hernández, Dorian Antonio, 2022. "Individual, household, and urban form determinants of trip chaining of non-work travel in México City," Journal of Transport Geography, Elsevier, vol. 98(C).
    4. Reid Ewing & Torrey Lyons & Seyed Hassan Ameli & John Hersey & Justyna Kaniewska, 2024. "Regional Policies, Practices, Tools, and Strategies to Implement Polycentric Development: Comparative Case Studies of Portland, Seattle, and Denver," Land, MDPI, vol. 13(2), pages 1-29, February.
    5. Harsh Shah & Andre L. Carrel & Huyen T. K. Le, 2024. "Impacts of teleworking and online shopping on travel: a tour-based analysis," Transportation, Springer, vol. 51(1), pages 99-127, February.
    6. Yang, Wenyue & Chen, Huiling & Wang, Wulin, 2020. "The path and time efficiency of residents' trips of different purposes with different travel modes: An empirical study in Guangzhou, China," Journal of Transport Geography, Elsevier, vol. 88(C).
    7. Huang, Yuqiao & Gao, Linjie & Ni, Anning & Liu, Xiaoning, 2021. "Analysis of travel mode choice and trip chain pattern relationships based on multi-day GPS data: A case study in Shanghai, China," Journal of Transport Geography, Elsevier, vol. 93(C).
    8. Obregón-Biosca, Saúl A., 2022. "Choice of transport in urban and periurban zones in metropolitan area," Journal of Transport Geography, Elsevier, vol. 100(C).
    9. Wenjing Wang & Yanyan Chen & Haodong Sun & Yusen Chen, 2021. "Multiple Binary Classification Model of Trip Chain Based on the Fusion of Internet Location Data and Transport Data," Sustainability, MDPI, vol. 13(21), pages 1-15, November.

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