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Could psychosocial variables help assess pro-cycling policies?

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  • Piras, Francesco
  • Sottile, Eleonora
  • Tuveri, Giovanni
  • Meloni, Italo

Abstract

Although recent studies have recognised that psychosocial factors could affect the choice to bike to work, most have tended to focus only on the statistical significance of psychosocial variables, often making no attempt to analyse the magnitude of their effect before suggesting policy strategies based on these variables in too general a manner. Additionally, different studies have failed to distinguish between the choice to commute by bike and cycle for non-commuting purposes, mixing their results. Given the above discussion, the current studyaims at understandingand interpreting the relationship between the psychosocial factors related to bike use, commute mode choice and cycling for non-commuting purposes. To analyse the relationship among all these choice dimensions, we specified and estimated an integrated choice and latent variable (ICLV) model using a dataset drawn from a survey conducted in Sardinia (Italy). The model estimation highlights several very interesting aspects, some of which confirm the findings of previous studies, while others are new contributions to the literature. First, we find that the perception of the benefits of cycling and that of bike comfort positively influence the probability of using a bike for commuting and non-commuting purposes, albeit in different ways. Another important point is how modelling results can be employed to develop effective strategies for promoting cycling. We show that the implementation of structural measures aimed at reducing travel time may only be effective for commuters who travel more than 5 km, while the success of behavioural measures seems to be independent of distance. At the same time, by running different test scenarios, we indicate how to increase the efficacy of behavioural measures depending on the target population.

Suggested Citation

  • Piras, Francesco & Sottile, Eleonora & Tuveri, Giovanni & Meloni, Italo, 2021. "Could psychosocial variables help assess pro-cycling policies?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 154(C), pages 108-128.
  • Handle: RePEc:eee:transa:v:154:y:2021:i:c:p:108-128
    DOI: 10.1016/j.tra.2021.10.003
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    References listed on IDEAS

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    1. Maarten Kroesen & Susan Handy, 2014. "The relation between bicycle commuting and non-work cycling: results from a mobility panel," Transportation, Springer, vol. 41(3), pages 507-527, May.
    2. Susan Handy & Bert van Wee & Maarten Kroesen, 2014. "Promoting Cycling for Transport: Research Needs and Challenges," Transport Reviews, Taylor & Francis Journals, vol. 34(1), pages 4-24, January.
    3. Habib, Khandker Nurul & Mann, Jenessa & Mahmoud, Mohamed & Weiss, Adam, 2014. "Synopsis of bicycle demand in the City of Toronto: Investigating the effects of perception, consciousness and comfortability on the purpose of biking and bike ownership," Transportation Research Part A: Policy and Practice, Elsevier, vol. 70(C), pages 67-80.
    4. Bhat, Chandra R. & Dubey, Subodh K. & Nagel, Kai, 2015. "Introducing non-normality of latent psychological constructs in choice modeling with an application to bicyclist route choice," Transportation Research Part B: Methodological, Elsevier, vol. 78(C), pages 341-363.
    5. Rafael Maldonado-Hinarejos & Aruna Sivakumar & John Polak, 2014. "Exploring the role of individual attitudes and perceptions in predicting the demand for cycling: a hybrid choice modelling approach," Transportation, Springer, vol. 41(6), pages 1287-1304, November.
    6. Muñoz, Begoña & Monzon, Andres & López, Elena, 2016. "Transition to a cyclable city: Latent variables affecting bicycle commuting," Transportation Research Part A: Policy and Practice, Elsevier, vol. 84(C), pages 4-17.
    7. Aurélie Glerum & Lidija Stankovikj & Michaël Thémans & Michel Bierlaire, 2014. "Forecasting the Demand for Electric Vehicles: Accounting for Attitudes and Perceptions," Transportation Science, INFORMS, vol. 48(4), pages 483-499, November.
    8. Xing, Yan & Handy, Susan L. & Mokhtarian, Patricia L., 2010. "Factors Associated with Proportions and Miles of Bicycling for Transportation and Recreation in Six Small U.S. Cities," Institute of Transportation Studies, Working Paper Series qt74n4j1p0, Institute of Transportation Studies, UC Davis.
    9. Begoña Muñoz & Andres Monzon & Ricardo A. Daziano, 2016. "The Increasing Role of Latent Variables in Modelling Bicycle Mode Choice," Transport Reviews, Taylor & Francis Journals, vol. 36(6), pages 737-771, November.
    10. Wardman, Mark & Tight, Miles & Page, Matthew, 2007. "Factors influencing the propensity to cycle to work," Transportation Research Part A: Policy and Practice, Elsevier, vol. 41(4), pages 339-350, May.
    11. Thorhauge, Mikkel & Kassahun, Habtamu Tilahun & Cherchi, Elisabetta & Haustein, Sonja, 2020. "Mobility needs, activity patterns and activity flexibility: How subjective and objective constraints influence mode choice," Transportation Research Part A: Policy and Practice, Elsevier, vol. 139(C), pages 255-272.
    12. Hyochul Park & Yong Lee & Hee Shin & Keemin Sohn, 2011. "Analyzing the time frame for the transition from leisure-cyclist to commuter-cyclist," Transportation, Springer, vol. 38(2), pages 305-319, March.
    13. Hess, Stephane & Spitz, Greg & Bradley, Mark & Coogan, Matt, 2018. "Analysis of mode choice for intercity travel: Application of a hybrid choice model to two distinct US corridors," Transportation Research Part A: Policy and Practice, Elsevier, vol. 116(C), pages 547-567.
    14. Álvaro Fernández-Heredia & Sergio Jara-Díaz & Andrés Monzón, 2016. "Modelling bicycle use intention: the role of perceptions," Transportation, Springer, vol. 43(1), pages 1-23, January.
    15. Ciccone, A. & Fyhri, A. & Sundfør, H.B., 2021. "Using behavioral insights to incentivize cycling: Results from a field experiment," Journal of Economic Behavior & Organization, Elsevier, vol. 188(C), pages 1035-1058.
    16. van Wee, Bert & Börjesson, Maria, 2015. "How to make CBA more suitable for evaluating cycling policies," Transport Policy, Elsevier, vol. 44(C), pages 117-124.
    17. Kaplan, Sigal & Manca, Francesco & Nielsen, Thomas Alexander Sick & Prato, Carlo Giacomo, 2015. "Intentions to use bike-sharing for holiday cycling: An application of the Theory of Planned Behavior," Tourism Management, Elsevier, vol. 47(C), pages 34-46.
    18. Vij, Akshay & Walker, Joan L., 2016. "How, when and why integrated choice and latent variable models are latently useful," Transportation Research Part B: Methodological, Elsevier, vol. 90(C), pages 192-217.
    19. Gatersleben, Birgitta & Appleton, Katherine M., 2007. "Contemplating cycling to work: Attitudes and perceptions in different stages of change," Transportation Research Part A: Policy and Practice, Elsevier, vol. 41(4), pages 302-312, May.
    20. Kamargianni, Maria & Dubey, Subodh & Polydoropoulou, Amalia & Bhat, Chandra, 2015. "Investigating the subjective and objective factors influencing teenagers’ school travel mode choice – An integrated choice and latent variable model," Transportation Research Part A: Policy and Practice, Elsevier, vol. 78(C), pages 473-488.
    21. Jie Gao & Dick Ettema & Marco Helbich & Carlijn B. M. Kamphuis, 2019. "Travel mode attitudes, urban context, and demographics: do they interact differently for bicycle commuting and cycling for other purposes?," Transportation, Springer, vol. 46(6), pages 2441-2463, December.
    22. 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.
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