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Trip chain complexity: a comparison among latent classes of daily mobility patterns

Author

Listed:
  • Florian Schneider

    (Delft University of Technology)

  • Danique Ton

    (Delft University of Technology)

  • Lara-Britt Zomer

    (Delft University of Technology)

  • Winnie Daamen

    (Delft University of Technology)

  • Dorine Duives

    (Delft University of Technology)

  • Sascha Hoogendoorn-Lanser

    (KIM, Netherlands Institute for Transport Policy Analysis)

  • Serge Hoogendoorn

    (Delft University of Technology)

Abstract

This paper studies the relationship between trip chain complexity and daily travel behaviour of travellers. While trip chain complexity is conventionally investigated between travel modes, our scope is the more aggregated level of a person’s activity-travel pattern. Using data from the Netherlands Mobility Panel, a latent class cluster analysis was performed to group people with similar mode choice behaviour in distinct mobility pattern classes. All trip chains were assigned to both a travel mode and the mobility pattern class of the traveller. Subsequently, differences in trip chain complexity distributions were analysed between travel modes and between mobility pattern classes. Results indicate considerable differences between travel modes, particularly between multimodal and unimodal trip chains, but also between the unimodal travel modes car, bicycle, walking and public transport trip chains. No substantial differences in trip chain complexity were found between mobility pattern classes. Independently of the included travel modes, the distributions of trip chain complexity degrees were similar across mobility pattern classes. This means that personal circumstances such as the number of working hours or household members are not systematically translated into specific mobility patterns.

Suggested Citation

  • Florian Schneider & Danique Ton & Lara-Britt Zomer & Winnie Daamen & Dorine Duives & Sascha Hoogendoorn-Lanser & Serge Hoogendoorn, 2021. "Trip chain complexity: a comparison among latent classes of daily mobility patterns," Transportation, Springer, vol. 48(2), pages 953-975, April.
  • Handle: RePEc:kap:transp:v:48:y:2021:i:2:d:10.1007_s11116-020-10084-1
    DOI: 10.1007/s11116-020-10084-1
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    References listed on IDEAS

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    1. Currie, Graham & Delbosc, Alexa, 2011. "Exploring the trip chaining behaviour of public transport users in Melbourne," Transport Policy, Elsevier, vol. 18(1), pages 204-210, January.
    2. Frank Primerano & Michael Taylor & Ladda Pitaksringkarn & Peter Tisato, 2008. "Defining and understanding trip chaining behaviour," Transportation, Springer, vol. 35(1), pages 55-72, January.
    3. Krygsman, Stephan & Arentze, Theo & Timmermans, Harry, 2007. "Capturing tour mode and activity choice interdependencies: A co-evolutionary logit modelling approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 41(10), pages 913-933, December.
    4. Lawrence Frank & Mark Bradley & Sarah Kavage & James Chapman & T. Lawton, 2008. "Urban form, travel time, and cost relationships with tour complexity and mode choice," Transportation, Springer, vol. 35(1), pages 37-54, January.
    5. Ming Lee & Michael McNally, 2006. "An empirical investigation on the dynamic processes of activity scheduling and trip chaining," Transportation, Springer, vol. 33(6), pages 553-565, November.
    6. Yang, Liya & Shen, Qing & Li, Zhibin, 2016. "Comparing travel mode and trip chain choices between holidays and weekdays," Transportation Research Part A: Policy and Practice, Elsevier, vol. 91(C), pages 273-285.
    7. Li, Zhibin & Wang, Wei & Yang, Chen & Jiang, Guojun, 2013. "Exploring the causal relationship between bicycle choice and trip chain pattern," Transport Policy, Elsevier, vol. 29(C), pages 170-177.
    8. David Hensher & April Reyes, 2000. "Trip chaining as a barrier to the propensity to use public transport," Transportation, Springer, vol. 27(4), pages 341-361, December.
    9. Ye, Xin & Pendyala, Ram M. & Gottardi, Giovanni, 2007. "An exploration of the relationship between mode choice and complexity of trip chaining patterns," Transportation Research Part B: Methodological, Elsevier, vol. 41(1), pages 96-113, January.
    10. de Haas, M.C. & Scheepers, C.E. & Harms, L.W.J. & Kroesen, M., 2018. "Travel pattern transitions: Applying latent transition analysis within the mobility biographies framework," Transportation Research Part A: Policy and Practice, Elsevier, vol. 107(C), pages 140-151.
    Full references (including those not matched with items on IDEAS)

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