IDEAS home Printed from https://ideas.repec.org/a/eee/transa/v154y2021icp108-128.html
   My bibliography  Save this article

Could psychosocial variables help assess pro-cycling policies?

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0965856421002494
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.tra.2021.10.003?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. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    15. 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.
    16. 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.
    17. 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.
    18. 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.
    19. 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.
    20. 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.
    21. 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.
    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.
    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. Piras, Francesco & Sottile, Eleonora & Tuveri, Giovanni & Meloni, Italo, 2021. "Could there be spillover effects between recreational and utilitarian cycling? A multivariate model," Transportation Research Part A: Policy and Practice, Elsevier, vol. 147(C), pages 297-311.
    2. Biehl, Alec & Ermagun, Alireza & Stathopoulos, Amanda, 2019. "Utilizing multi-stage behavior change theory to model the process of bike share adoption," Transport Policy, Elsevier, vol. 77(C), pages 30-45.
    3. Weibo Li & Maria Kamargianni, 2020. "An Integrated Choice and Latent Variable Model to Explore the Influence of Attitudinal and Perceptual Factors on Shared Mobility Choices and Their Value of Time Estimation," Transportation Science, INFORMS, vol. 54(1), pages 62-83, January.
    4. Tatiana Cantillo & Andrés Vargas & Víctor Cantillo & José Ramos, 2020. "What determines university student’s willingness to pay for bikeways?," Transportation, Springer, vol. 47(5), pages 2267-2286, October.
    5. Márquez, Luis & Soto, Jose J., 2021. "Integrating perceptions of safety and bicycle theft risk in the analysis of cycling infrastructure preferences," Transportation Research Part A: Policy and Practice, Elsevier, vol. 150(C), pages 285-301.
    6. Gustavo García-Melero & Rubén Sainz-González & Pablo Coto-Millán & Alejandra Valencia-Vásquez, 2021. "Sustainable Mobility Policy Analysis Using Hybrid Choice Models: Is It the Right Choice?," Sustainability, MDPI, vol. 13(5), pages 1-16, March.
    7. Scorrano, Mariangela & Danielis, Romeo, 2021. "Active mobility in an Italian city: Mode choice determinants and attitudes before and during the Covid-19 emergency," Research in Transportation Economics, Elsevier, vol. 86(C).
    8. Luis Márquez & Víctor Cantillo & Julián Arellana, 2020. "Assessing the influence of indicators’ complexity on hybrid discrete choice model estimates," Transportation, Springer, vol. 47(1), pages 373-396, February.
    9. Danique Ton & Lara-Britt Zomer & Florian Schneider & Sascha Hoogendoorn-Lanser & Dorine Duives & Oded Cats & Serge Hoogendoorn, 2020. "Latent classes of daily mobility patterns: the relationship with attitudes towards modes," Transportation, Springer, vol. 47(4), pages 1843-1866, August.
    10. 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.
    11. Khashayar Kazemzadeh & Aliaksei Laureshyn & Lena Winslott Hiselius & Enrico Ronchi, 2020. "Expanding the Scope of the Bicycle Level-of-Service Concept: A Review of the Literature," Sustainability, MDPI, vol. 12(7), pages 1-30, April.
    12. Verma, Meghna & Rahul, T.M. & Reddy, Peesari Vamshidhar & Verma, Ashish, 2016. "The factors influencing bicycling in the Bangalore city," Transportation Research Part A: Policy and Practice, Elsevier, vol. 89(C), pages 29-40.
    13. Ton, Danique & Bekhor, Shlomo & Cats, Oded & Duives, Dorine C. & Hoogendoorn-Lanser, Sascha & Hoogendoorn, Serge P., 2020. "The experienced mode choice set and its determinants: Commuting trips in the Netherlands," Transportation Research Part A: Policy and Practice, Elsevier, vol. 132(C), pages 744-758.
    14. Kim, Seheon & Rasouli, Soora, 2022. "The influence of latent lifestyle on acceptance of Mobility-as-a-Service (MaaS): A hierarchical latent variable and latent class approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 159(C), pages 304-319.
    15. Hong, Jinhyun & Philip McArthur, David & Stewart, Joanna L., 2020. "Can providing safe cycling infrastructure encourage people to cycle more when it rains? The use of crowdsourced cycling data (Strava)," Transportation Research Part A: Policy and Practice, Elsevier, vol. 133(C), pages 109-121.
    16. Bouscasse, H., 2018. "Integrated choice and latent variable models: A literature review on mode choice," Working Papers 2018-07, Grenoble Applied Economics Laboratory (GAEL).
    17. Ma, Xinwei & Zhang, Shuai & Wu, Tao & Yang, Yizhe & Yu, Jiajie, 2023. "Can dockless and docked bike-sharing substitute each other? Evidence from Nanjing, China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 188(C).
    18. Dandan Xu & Yang Bain & Shinan Shu & Xiaodong Zhang, 2022. "Staged Transition Process from Driving to Bicycling Based on the Effects of Latent Variables," Sustainability, MDPI, vol. 14(18), pages 1-14, September.
    19. Mahdi Rashidi & Seyed-Mohammad Seyedhosseini & Ali Naderan, 2023. "Defining Psychological Factors of Cycling in Tehran City," Sustainability, MDPI, vol. 15(4), pages 1-17, February.
    20. Ruiz, Tomás & Bernabé, José C., 2014. "Measuring factors influencing valuation of nonmotorized improvement measures," Transportation Research Part A: Policy and Practice, Elsevier, vol. 67(C), pages 195-211.

    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:154:y:2021:i:c:p:108-128. 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.