IDEAS home Printed from https://ideas.repec.org/a/eee/transa/v201y2025ics0965856425003106.html

Cycling route choice preferences: A taste heterogeneity and exogenous segmentation analysis based on age, gender, Geller typology, and e-bike use

Author

Listed:
  • Lilasathapornkit, Tanapon
  • Bhowmick, Debjit
  • Beck, Ben
  • Wu, Hao
  • Pettit, Christopher
  • Nice, Kerry
  • Seneviratne, Sachith
  • Gupta, Mohit
  • Vu, Hai L.
  • Nelson, Trisalyn
  • Saberi, Meead

Abstract

A range of factors influences cyclists’ route choices, yet infrastructure design often fails to account for the diverse preferences and needs of different groups. This study examines cycling route choice preferences using revealed preference GPS data from Melbourne, Australia. Path Size Logit (PSL) and Mixed Path Size Logit models are estimated to capture path correlation due to overlapping routes and taste heterogeneity in route choice preferences among cyclist groups, segmented by age, gender, e-bike use, and Geller typology. Using a hybrid generalized Breadth-First Search on Link Elimination (BFS-LE) approach, the study enhances the quality and diversity of the generated choice set. Results indicate significant taste heterogeneity in route choices, with distinct preferences across cyclist segments. Risk-averse cyclists, particularly women and the “interested but concerned” group, showed a strong preference for protected bike lanes and off-road paths. In contrast, more confident cyclists, such as “enthused and confident,” exhibited greater flexibility and were less sensitive to infrastructure types, slopes, and turns. Traditional bike riders were found to be more sensitive to infrastructure variability compared to e-bike users. Findings also revealed that cyclists, on average, perceived a 1 % increase in the proportion of a route on an off-road bike path as equivalent to a reduction of 80 m in trip length, though this effect varied across individuals. Similarly, a 1 % increase in the proportion of a route on a protected bike lane was, on average, equivalent to a reduction of 61 m, while each additional turn was perceived, on average, as adding 121 m, highlighting the variability in how route complexity influences cyclists’ choices. Overall, the study offers valuable insights for urban planners and policymakers, emphasizing the need for inclusive cycling infrastructure that accommodates the diverse preferences of different cyclist groups to encourage broader participation.

Suggested Citation

  • Lilasathapornkit, Tanapon & Bhowmick, Debjit & Beck, Ben & Wu, Hao & Pettit, Christopher & Nice, Kerry & Seneviratne, Sachith & Gupta, Mohit & Vu, Hai L. & Nelson, Trisalyn & Saberi, Meead, 2025. "Cycling route choice preferences: A taste heterogeneity and exogenous segmentation analysis based on age, gender, Geller typology, and e-bike use," Transportation Research Part A: Policy and Practice, Elsevier, vol. 201(C).
  • Handle: RePEc:eee:transa:v:201:y:2025:i:c:s0965856425003106
    DOI: 10.1016/j.tra.2025.104679
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0965856425003106
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.tra.2025.104679?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

    for a different version of it.

    References listed on IDEAS

    as
    1. Frejinger, E. & Bierlaire, M., 2007. "Capturing correlation with subnetworks in route choice models," Transportation Research Part B: Methodological, Elsevier, vol. 41(3), pages 363-378, March.
    2. Rachel Aldred & Bridget Elliott & James Woodcock & Anna Goodman, 2017. "Cycling provision separated from motor traffic: a systematic review exploring whether stated preferences vary by gender and age," Transport Reviews, Taylor & Francis Journals, vol. 37(1), pages 29-55, January.
    3. Menghini, G. & Carrasco, N. & Schüssler, N. & Axhausen, K.W., 2010. "Route choice of cyclists in Zurich," Transportation Research Part A: Policy and Practice, Elsevier, vol. 44(9), pages 754-765, November.
    4. Hess, Stephane & Quddus, Mohammed & Rieser-Schüssler, Nadine & Daly, Andrew, 2015. "Developing advanced route choice models for heavy goods vehicles using GPS data," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 77(C), pages 29-44.
    5. Park, Yujin & Akar, Gulsah, 2019. "Why do bicyclists take detours? A multilevel regression model using smartphone GPS data," Journal of Transport Geography, Elsevier, vol. 74(C), pages 191-200.
    6. Lu, Wei & Scott, Darren M. & Dalumpines, Ron, 2018. "Understanding bike share cyclist route choice using GPS data: Comparing dominant routes and shortest paths," Journal of Transport Geography, Elsevier, vol. 71(C), pages 172-181.
    7. Łukawska, Mirosława & Paulsen, Mads & Rasmussen, Thomas Kjær & Jensen, Anders Fjendbo & Nielsen, Otto Anker, 2023. "A joint bicycle route choice model for various cycling frequencies and trip distances based on a large crowdsourced GPS dataset," Transportation Research Part A: Policy and Practice, Elsevier, vol. 176(C).
    8. Cubells, Jerònia & Miralles-Guasch, Carme & Marquet, Oriol, 2023. "Gendered travel behaviour in micromobility? Travel speed and route choice through the lens of intersecting identities," Journal of Transport Geography, Elsevier, vol. 106(C).
    9. Thomas Götschi & Jan Garrard & Billie Giles-Corti, 2016. "Cycling as a Part of Daily Life: A Review of Health Perspectives," Transport Reviews, Taylor & Francis Journals, vol. 36(1), pages 45-71, January.
    10. Boeing, Geoff, 2017. "OSMnx: New Methods for Acquiring, Constructing, Analyzing, and Visualizing Complex Street Networks," SocArXiv q86sd, Center for Open Science.
    11. Mirosława Łukawska, 2024. "Quantitative modelling of cyclists’ route choice behaviour on utilitarian trips based on GPS data: associated factors and behavioural implications," Transport Reviews, Taylor & Francis Journals, vol. 44(5), pages 1045-1076, September.
    12. Broach, Joseph & Dill, Jennifer & Gliebe, John, 2012. "Where do cyclists ride? A route choice model developed with revealed preference GPS data," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(10), pages 1730-1740.
    13. John Pucher & Ralph Buehler, 2017. "Cycling towards a more sustainable transport future," Transport Reviews, Taylor & Francis Journals, vol. 37(6), pages 689-694, November.
    14. Ben Beck & Meghan Winters & Trisalyn Nelson & Chris Pettit & Simone Z Leao & Meead Saberi & Jason Thompson & Sachith Seneviratne & Kerry Nice & Mark Stevenson, 2023. "Developing urban biking typologies: Quantifying the complex interactions of bicycle ridership, bicycle network and built environment characteristics," Environment and Planning B, , vol. 50(1), pages 7-23, January.
    15. Meister, Adrian & Felder, Matteo & Schmid, Basil & Axhausen, Kay W., 2023. "Route choice modeling for cyclists on urban networks," Transportation Research Part A: Policy and Practice, Elsevier, vol. 173(C).
    16. Cubells, Jerònia & Miralles-Guasch, Carme & Marquet, Oriol, 2023. "E-scooter and bike-share route choice and detours: Modelling the influence of built environment and sociodemographic factors," Journal of Transport Geography, Elsevier, vol. 111(C).
    17. Ipek Sener & Naveen Eluru & Chandra Bhat, 2009. "An analysis of bicycle route choice preferences in Texas, US," Transportation, Springer, vol. 36(5), pages 511-539, September.
    18. Elise Desjardins & Christopher D. Higgins & Darren M. Scott & Emma Apatu & Antonio Páez, 2022. "Correlates of bicycling trip flows in Hamilton, Ontario: fastest, quietest, or balanced routes?," Transportation, Springer, vol. 49(3), pages 867-895, June.
    19. Duncan, Lawrence Christopher & Watling, David Paul & Connors, Richard Dominic & Rasmussen, Thomas Kjær & Nielsen, Otto Anker, 2020. "Path Size Logit route choice models: Issues with current models, a new internally consistent approach, and parameter estimation on a large-scale network with GPS data," Transportation Research Part B: Methodological, Elsevier, vol. 135(C), pages 1-40.
    20. Lin, Jen-Jia & Wei, Yi-Hsuan, 2018. "Assessing area-wide bikeability: A grey analytic network process," Transportation Research Part A: Policy and Practice, Elsevier, vol. 113(C), pages 381-396.
    21. John R. Hauser, 1978. "Testing the Accuracy, Usefulness, and Significance of Probabilistic Choice Models: An Information-Theoretic Approach," Operations Research, INFORMS, vol. 26(3), pages 406-421, June.
    22. Arellana, Julián & Saltarín, María & Larrañaga, Ana Margarita & González, Virginia I. & Henao, César Augusto, 2020. "Developing an urban bikeability index for different types of cyclists as a tool to prioritise bicycle infrastructure investments," Transportation Research Part A: Policy and Practice, Elsevier, vol. 139(C), pages 310-334.
    23. Bass, Pablo & Donoso, Pedro & Munizaga, Marcela, 2011. "A model to assess public transport demand stability," Transportation Research Part A: Policy and Practice, Elsevier, vol. 45(8), pages 755-764, October.
    24. Fitch, Dillon T. & Handy, Susan L., 2020. "Road environments and bicyclist route choice: The cases of Davis and San Francisco, CA," Journal of Transport Geography, Elsevier, vol. 85(C).
    25. repec:osf:socarx:q86sd_v1 is not listed on IDEAS
    26. Alexander Shapiro & Jos Berge, 2002. "Statistical inference of minimum rank factor analysis," Psychometrika, Springer;The Psychometric Society, vol. 67(1), pages 79-94, March.
    27. David Hensher & William Greene, 2003. "The Mixed Logit model: The state of practice," Transportation, Springer, vol. 30(2), pages 133-176, May.
    Full references (including those not matched with items on IDEAS)

    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. Cubells, Jerònia & Miralles-Guasch, Carme & Marquet, Oriol, 2023. "E-scooter and bike-share route choice and detours: Modelling the influence of built environment and sociodemographic factors," Journal of Transport Geography, Elsevier, vol. 111(C).
    2. Scott, Darren M. & Lu, Wei & Brown, Matthew J., 2021. "Route choice of bike share users: Leveraging GPS data to derive choice sets," Journal of Transport Geography, Elsevier, vol. 90(C).
    3. Łukawska, Mirosława & Paulsen, Mads & Rasmussen, Thomas Kjær & Jensen, Anders Fjendbo & Nielsen, Otto Anker, 2023. "A joint bicycle route choice model for various cycling frequencies and trip distances based on a large crowdsourced GPS dataset," Transportation Research Part A: Policy and Practice, Elsevier, vol. 176(C).
    4. Łukawska, Mirosława & Jensen, Anders Fjendbo & Rodrigues, Filipe, 2025. "Context-aware Bayesian mixed multinomial logit model," Journal of choice modelling, Elsevier, vol. 54(C).
    5. Ospina, Juan P. & Duque, Juan C. & Botero-Fernández, Verónica & Montoya, Alejandro, 2022. "The maximal covering bicycle network design problem," Transportation Research Part A: Policy and Practice, Elsevier, vol. 159(C), pages 222-236.
    6. Saha, Bijoy & Fatmi, Mahmudur Rahman, 2025. "Modeling bicyclists' destination location choice: Spatial-temporal constraint for choice set generation," Journal of Transport Geography, Elsevier, vol. 129(C).
    7. Chung, Jaehoon & Yao, Enjian & Pan, Long & Ko, Joonho, 2024. "Understanding the route choice preferences of private and dock-based public bike users using GPS data in Seoul, South Korea," Journal of Transport Geography, Elsevier, vol. 116(C).
    8. Zhang, Lihong & Liu, Yan & Lieske, Scott N. & Corcoran, Jonathan, 2022. "Using modality styles to understand cycling dissonance: The role of the street-scale environment in commuters' travel mode choice," Journal of Transport Geography, Elsevier, vol. 103(C).
    9. Fitch, Dillon T. & Handy, Susan L., 2020. "Road environments and bicyclist route choice: The cases of Davis and San Francisco, CA," Journal of Transport Geography, Elsevier, vol. 85(C).
    10. Chung, Jaehoon & Yao, Enjian & Ko, Joonho & Namkung, Ok Stella, 2024. "Investigation of private and public bikes usage patterns considering GPS trajectory based cycling features," Journal of Transport Geography, Elsevier, vol. 118(C).
    11. Roig-Costa, Oriol & Miralles-Guasch, Carme & Marquet, Oriol, 2025. "Unpacking the docked bike-sharing experience. A bike-along study on the infrastructural constraints and determinants of everyday bike-sharing use," Journal of Transport Geography, Elsevier, vol. 125(C).
    12. Broach, Joseph & Dill, Jennifer & Gliebe, John, 2012. "Where do cyclists ride? A route choice model developed with revealed preference GPS data," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(10), pages 1730-1740.
    13. Passmore, Reid & Watkins, Kari & Guensler, Randall, 2024. "Using shortest path routing to assess cycling networks," Journal of Transport Geography, Elsevier, vol. 117(C).
    14. Giulia Reggiani & Tim Oijen & Homayoun Hamedmoghadam & Winnie Daamen & Hai L. Vu & Serge Hoogendoorn, 2022. "Understanding bikeability: a methodology to assess urban networks," Transportation, Springer, vol. 49(3), pages 897-925, June.
    15. Stefan Flügel & Nina Hulleberg & Aslak Fyhri & Christian Weber & Gretar Ævarsson, 2019. "Empirical speed models for cycling in the Oslo road network," Transportation, Springer, vol. 46(4), pages 1395-1419, August.
    16. Cai, Yangqian & Moreno, Ana Tsui, 2024. "Identifying non-universal heterogeneity of preferences of leisure cyclists for rural highway environments: A latent-class model," Transportation Research Part A: Policy and Practice, Elsevier, vol. 186(C).
    17. Anowar, Sabreena & Eluru, Naveen & Hatzopoulou, Marianne, 2017. "Quantifying the value of a clean ride: How far would you bicycle to avoid exposure to traffic-related air pollution?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 105(C), pages 66-78.
    18. Rupi, Federico & Freo, Marzia & Poliziani, Cristian & Postorino, Maria Nadia & Schweizer, Joerg, 2023. "Analysis of gender-specific bicycle route choices using revealed preference surveys based on GPS traces," Transport Policy, Elsevier, vol. 133(C), pages 1-14.
    19. Meister, Adrian & Felder, Matteo & Schmid, Basil & Axhausen, Kay W., 2023. "Route choice modeling for cyclists on urban networks," Transportation Research Part A: Policy and Practice, Elsevier, vol. 173(C).
    20. Orvin, Muntahith Mehadil & Fatmi, Mahmudur Rahman & Chowdhury, Subeh, 2021. "Taking another look at cycling demand modeling: A comparison between two cities in Canada and New Zealand," Journal of Transport Geography, Elsevier, vol. 97(C).

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:eee:transa:v:201:y:2025:i:c:s0965856425003106. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/547/description#description .

    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.