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Identifying non-universal heterogeneity of preferences of leisure cyclists for rural highway environments: A latent-class model

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  • Cai, Yangqian
  • Moreno, Ana Tsui

Abstract

Leisure cycling on rural highways is becoming popular for promoting health and addressing socialization needs. Unlike urban contexts, perception studies of rural leisure cyclists are scarce. This research aims to understand how leisure cyclists perceive rural highway environments accounting for heterogeneous preferences of different cyclist types. An online survey collected 519 complete responses from individuals who cycle for leisure/fitness on rural highways in the US. The results of a mixed-logit model, a mixed-logit model with systematic variation, and a latent-class model with psychometric indicators suggest that self-stated interest and confidence levels (e.g., “enthused and confident”, “strong and fearless”) were not significant enough for segmenting rural cyclists. Instead, distinct groups were segmented based on gender and the relative importance of activity volume, pavement conditions, and environmental conditions. Two classes were identified: Utility-driven enjoyment-seeker and Traffic-indifferent performance-focused. The two classes presented different choice heuristics (random utility maximization vs. attribute non-attendance) and different preferences of design attributes (context class, scenery, shoulder width, or pavement conditions). Agencies can use the results of this research to identify bicycle facility needs in the rural network accounting for leisure rural cyclist population heterogeneous preferences.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:transa:v:186:y:2024:i:c:s0965856424001770
    DOI: 10.1016/j.tra.2024.104129
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    1. Kim, Sung Hoo & Mokhtarian, Patricia L., 2023. "Finite mixture (or latent class) modeling in transportation: Trends, usage, potential, and future directions," Transportation Research Part B: Methodological, Elsevier, vol. 172(C), pages 134-173.
    2. 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.
    3. Balbontin, Camila & Hensher, David A. & Collins, Andrew T., 2019. "How to better represent preferences in choice models: The contributions to preference heterogeneity attributable to the presence of process heterogeneity," Transportation Research Part B: Methodological, Elsevier, vol. 122(C), pages 218-248.
    4. 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.
    5. David Hensher & William Greene, 2010. "Non-attendance and dual processing of common-metric attributes in choice analysis: a latent class specification," Empirical Economics, Springer, vol. 39(2), pages 413-426, October.
    6. Efthimios Bakogiannis & Thanos Vlastos & Konstantinos Athanasopoulos & Avgi Vassi & Georgia Christodoulopoulou & Christos Karolemeas & Stefanos Tsigdinos & Charalampos Kyriakidis & Maria-Stella Noutso, 2020. "Exploring Motivators and Deterrents of Cycling Tourism Using Qualitative Social Research Methods and Participative Analytical Hierarchy Process (AHP)," Sustainability, MDPI, vol. 12(6), pages 1-15, March.
    7. Cabral, Laura & Kim, Amy M., 2020. "An empirical reappraisal of the four types of cyclists," Transportation Research Part A: Policy and Practice, Elsevier, vol. 137(C), pages 206-221.
    8. 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).
    9. Hess, Stephane & Palma, David, 2019. "Apollo: A flexible, powerful and customisable freeware package for choice model estimation and application," Journal of choice modelling, Elsevier, vol. 32(C), pages 1-1.
    10. Fitch, Dillon T. & Carlen, Jane & Handy, Susan L., 2022. "What makes bicyclists comfortable? Insights from a visual preference survey of casual and prospective bicyclists," Transportation Research Part A: Policy and Practice, Elsevier, vol. 155(C), pages 434-449.
    11. Riccardo Scarpa & Timothy J. Gilbride & Danny Campbell & David A. Hensher, 2009. "Modelling attribute non-attendance in choice experiments for rural landscape valuation," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 36(2), pages 151-174, June.
    12. Motoaki, Yutaka & Daziano, Ricardo A., 2015. "A hybrid-choice latent-class model for the analysis of the effects of weather on cycling demand," Transportation Research Part A: Policy and Practice, Elsevier, vol. 75(C), pages 217-230.
    13. Griswold, Julia B. & Yu, Mengqiao & Filingeri, Victoria & Grembek, Offer & Walker, Joan L., 2018. "A behavioral modeling approach to bicycle level of service," Transportation Research Part A: Policy and Practice, Elsevier, vol. 116(C), pages 166-177.
    14. Hurtubia, Ricardo & Nguyen, My Hang & Glerum, Aurélie & Bierlaire, Michel, 2014. "Integrating psychometric indicators in latent class choice models," Transportation Research Part A: Policy and Practice, Elsevier, vol. 64(C), pages 135-146.
    15. Ben-Akiva, Moshe & McFadden, Daniel & Train, Kenneth & Börsch-Supan, Axel, 2002. "Hybrid Choice Models: Progress and Challenges," Sonderforschungsbereich 504 Publications 02-29, Sonderforschungsbereich 504, Universität Mannheim;Sonderforschungsbereich 504, University of Mannheim.
    16. Chen, Ching-Fu & Chen, Pei-Chun, 2013. "Estimating recreational cyclists’ preferences for bicycle routes – Evidence from Taiwan," Transport Policy, Elsevier, vol. 26(C), pages 23-30.
    17. Francisco Rejón-Guardia & María Antonia García-Sastre & Margarita Alemany-Hormaeche, 2018. "Motivation-based behaviour and latent class segmentation of cycling tourists," Tourism Economics, , vol. 24(2), pages 204-217, March.
    18. Ovidiu R. Ciascai & Ștefan Dezsi & Karina A. Rus, 2022. "Cycling Tourism: A Literature Review to Assess Implications, Multiple Impacts, Vulnerabilities, and Future Perspectives," Sustainability, MDPI, vol. 14(15), pages 1-18, July.
    19. Rossetti, Tomás & Guevara, C. Angelo & Galilea, Patricia & Hurtubia, Ricardo, 2018. "Modeling safety as a perceptual latent variable to assess cycling infrastructure," Transportation Research Part A: Policy and Practice, Elsevier, vol. 111(C), pages 252-265.
    20. Tomás Rossetti & Ricardo Daziano, 2023. "How does self-assessed health status relate to preferences for cycling infrastructure? A latent class and latent variable approach," Transportation, Springer, vol. 50(3), pages 913-928, June.
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