IDEAS home Printed from https://ideas.repec.org/a/kap/transp/v48y2021i2d10.1007_s11116-020-10084-1.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11116-020-10084-1
    File Function: Abstract
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1007/s11116-020-10084-1?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    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)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Rafiq, Rezwana & McNally, Michael G., 2021. "Heterogeneity in Activity-travel Patterns of Public Transit Users: An Application of Latent Class Analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 152(C), pages 1-18.
    2. Cui, Shuang & Tian, Lijun & Xu, Yan & Wang, Yacan, 2024. "Measuring acceptance of tradable credit scheme and its effect on behavioral intention through theory of planned behavior," Transport Policy, Elsevier, vol. 150(C), pages 174-188.
    3. Timmer, Sebastian & Merfeld, Katrin & Henkel, Sven, 2023. "Exploring motivations for multimodal commuting: A hierarchical means-end chain analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 176(C).
    4. Biao Yin & Fabien Leurent, 2023. "What are the multimodal patterns of individual mobility at the day level in the Paris region? A two-stage data-driven approach based on the 2018 Household Travel Survey," Transportation, Springer, vol. 50(4), pages 1497-1526, August.
    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. Zidan Mao & Fangyu Liu & Ying Zhao, 2023. "Happy city for everyone: Generational differences in rural migrant workers’ leisure in urban China," Urban Studies, Urban Studies Journal Limited, vol. 60(16), pages 3252-3271, December.
    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. Chun-Chen Chou & Kento Yoh & Shotaro Hirokawa & Kenji Doi, 2023. "Co-evolution of Smart Small Vehicles and Human Spatial Experiences: Case Study on Battery-Sharing Electric Two-Wheelers Experiment," Sustainability, MDPI, vol. 15(20), pages 1-27, October.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. João De Abreu e Silva, 2018. "The Effects of Land-Use Patterns on Home-Based Tour Complexity and Total Distances Traveled: A Path Analysis," Sustainability, MDPI, vol. 10(3), pages 1-16, March.
    2. Joachim Scheiner & Christian Holz-Rau, 2017. "Women’s complex daily lives: a gendered look at trip chaining and activity pattern entropy in Germany," Transportation, Springer, vol. 44(1), pages 117-138, January.
    3. Liya Yang & Lingqian Hu & Zhenbo Wang, 2019. "The built environment and trip chaining behaviour revisited: The joint effects of the modifiable areal unit problem and tour purpose," Urban Studies, Urban Studies Journal Limited, vol. 56(4), pages 795-817, March.
    4. 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).
    5. 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.
    6. Rafiq, Rezwana & McNally, Michael G., 2020. "An empirical analysis and policy implications of work tours utilizing public transit," Transportation Research Part A: Policy and Practice, Elsevier, vol. 142(C), pages 237-259.
    7. Wan, Li & Tang, Junqing & Wang, Lihua & Schooling, Jennifer, 2021. "Understanding non-commuting travel demand of car commuters – Insights from ANPR trip chain data in Cambridge," Transport Policy, Elsevier, vol. 106(C), pages 76-87.
    8. 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.
    9. Michael Duncan, 2016. "How much can trip chaining reduce VMT? A simplified method," Transportation, Springer, vol. 43(4), pages 643-659, July.
    10. Sottile, Eleonora & Tuveri, Giovanni & Piras, Francesco & Meloni, Italo, 2022. "Modelling commuting tours versus non-commuting tours for university students. A panel data analysis from different contexts," Transport Policy, Elsevier, vol. 118(C), pages 56-67.
    11. 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).
    12. Wang, Rui, 2015. "The stops made by commuters: evidence from the 2009 US National Household Travel Survey," Journal of Transport Geography, Elsevier, vol. 47(C), pages 109-118.
    13. Veronique Acker & Frank Witlox, 2011. "Commuting trips within tours: how is commuting related to land use?," Transportation, Springer, vol. 38(3), pages 465-486, May.
    14. Rafiq, Rezwana & McNally, Michael G., 2022. "A structural analysis of the work tour behavior of transit commuters," Transportation Research Part A: Policy and Practice, Elsevier, vol. 160(C), pages 61-79.
    15. 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).
    16. 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.
    17. Zidan Mao & Dick Ettema & Martin Dijst, 2018. "Analysis of travel time and mode choice shift for non-work stops in commuting: case study of Beijing, China," Transportation, Springer, vol. 45(3), pages 751-766, May.
    18. 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.
    19. François Sprumont & Ariane Scheffer & Geoffrey Caruso & Eric Cornelis & Francesco Viti, 2022. "Quantifying the Relation between Activity Pattern Complexity and Car Use Using a Partial Least Square Structural Equation Model," Sustainability, MDPI, vol. 14(19), pages 1-16, September.
    20. Günter Wallner & Simone Kriglstein & Edward Chung & Syeed Anta Kashfi, 2018. "Visualisation of trip chaining behaviour and mode choice using household travel survey data," Public Transport, Springer, vol. 10(3), pages 427-453, December.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:kap:transp:v:48:y:2021:i:2:d:10.1007_s11116-020-10084-1. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.