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Exploring the role of individual attitudes and perceptions in predicting the demand for cycling: a hybrid choice modelling approach

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  • Rafael Maldonado-Hinarejos

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  • Aruna Sivakumar

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  • John Polak

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Abstract

Cycling is often promoted as a means of reducing urban congestion and improving health, social and environmental outcomes. However, the quantification of these potential benefits is not well established. This is due in part to practical difficulties in estimating cycling demand and a lack of sound methodologies to appraise cycling initiatives. In this paper we attempt to address this need by developing predictive models of cycle demand, relative to other transport modes, that capture not only the impacts of observed characteristics such as age and travel time but also the role of attitudes and perceptions. Using data from a stated preference survey, we estimate a hybrid choice model for cycle use that incorporates the role of attitudes towards cycling, perceptions of the image associated with cycling, and the stress arising from safety concerns. Model results indicate that the latent attitudes and perceptions explain an important part of the non-observable utility in a simple multinomial logit choice model. We also demonstrate policy analysis using the hybrid choice model, which allows comparisons of ‘hard’ policies such as the provision of parking facilities against ‘soft’ measures such as cycle promotion schemes. Copyright Springer Science+Business Media New York 2014

Suggested Citation

  • 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.
  • Handle: RePEc:kap:transp:v:41:y:2014:i:6:p:1287-1304
    DOI: 10.1007/s11116-014-9551-4
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. 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.
    2. Bhat, Chandra R. & Astroza, Sebastian & Hamdi, Amin S., 2017. "A spatial generalized ordered-response model with skew normal kernel error terms with an application to bicycling frequency," Transportation Research Part B: Methodological, Elsevier, vol. 95(C), pages 126-148.
    3. repec:eee:transb:v:101:y:2017:i:c:p:72-88 is not listed on IDEAS
    4. Bouscasse, H., 2018. "Integrated choice and latent variable models: A literature review on mode choice," Working Papers 2018-07, Grenoble Applied Economics Laboratory (GAEL).
    5. Wang, Jenhung & Tsai, Ching-Hui & Lin, Pei-Chun, 2016. "Applying spatial-temporal analysis and retail location theory to public bikes site selection in Taipei," Transportation Research Part A: Policy and Practice, Elsevier, vol. 94(C), pages 45-61.
    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. Yazdanpanah, Mahdi & Hosseinlou, Mansour Hadji, 2016. "The influence of personality traits on airport public transport access mode choice: A hybrid latent class choice modeling approach," Journal of Air Transport Management, Elsevier, vol. 55(C), pages 147-163.
    8. Hélène Bouscasse, 2018. "Integrated choice and latent variable models: A literature review on mode choice," Working Papers hal-01795630, HAL.

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