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Investigating next generation's cycling ridership to promote sustainable mobility in different types of cities

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  • Kamargianni, Maria

Abstract

The aim of this paper is to develop a mode to school choice model to quantitatively evaluate the impact of various bicycle services and facilities on adolescents' mode choice behaviour. Stated preference (SP) scenarios specifically designed for this survey were used to elicit preferences for bicycle facilities and infrastructure, such as bike-lanes and bicycle parking places, and also for the availability of safety courses for school goers. The estimated mode choice model, which explicitly considers taste heterogeneity and panel effects, was tested with data collected in different types of cities (urban, rural and insular) of two different countries Greece and Cyprus, enabling comparisons in adolescents' travel behaviour across different geographical areas. The sample consisted of 9554 adolescent who yielded 20,432 SP responses for model estimation. Our results show that the prevalent factors affecting bicycle choice differ across different types of cities. Bad weather conditions affect the most the choice of bicycle in urban areas, while the most significant variable for rural areas is the percentage of cycleway coverage in the route between home and school. The availability of bicycle parking spaces at the schoolyard and the availability of school courses regarding how to walk and cycle with safety, also increased the bicycle utility in all five areas considered. Finally, three policy scenarios were tested to investigate modal split under various cycling policies.

Suggested Citation

  • Kamargianni, Maria, 2015. "Investigating next generation's cycling ridership to promote sustainable mobility in different types of cities," Research in Transportation Economics, Elsevier, vol. 53(C), pages 45-55.
    • Handle: RePEc:eee:retrec:v:53:y:2015:i:c:p:45-55
    DOI: 10.1016/j.retrec.2015.10.018
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    Cited by:

    1. Melinda Matyas & Maria Kamargianni, 2019. "The potential of mobility as a service bundles as a mobility management tool," Transportation, Springer, vol. 46(5), pages 1951-1968, October.
    2. Li, Weibo & Kamargianni, Maria, 2018. "Providing quantified evidence to policy makers for promoting bike-sharing in heavily air-polluted cities: A mode choice model and policy simulation for Taiyuan-China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 111(C), pages 277-291.
    3. Haimei Li & Li Han & Yibin Ao & Yan Wang & Tong Wang, 2022. "Influences of the Built Environment on Rural School Children’s Travel Mode Choice: The Case of Chengdu," IJERPH, MDPI, vol. 19(15), pages 1-18, July.
    4. Waintrub, Natan & Peña, Carolina & Niehaus, Markus & Vega, Rodrigo & Galilea, Patricia, 2016. "Understanding cyclist traffic behaviour: Contrasting cycle path designs in Santiago de Chile," Research in Transportation Economics, Elsevier, vol. 59(C), pages 228-235.
    5. Melinda Matyas & Maria Kamargianni, 2019. "Survey design for exploring demand for Mobility as a Service plans," Transportation, Springer, vol. 46(5), pages 1525-1558, October.
    6. 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.
    7. Dehdari Ebrahimi, Zhila & Momenitabar, Mohsen & Nasri, Arefeh A. & Mattson, Jeremy, 2022. "Using a GIS-based spatial approach to determine the optimal locations of bikeshare stations: The case of Washington D.C," Transport Policy, Elsevier, vol. 127(C), pages 48-60.
    8. Yuhei Ito & Malcolm Morgan & Robin Lovelace, 2023. "Where to invest in cycle parking: A portfolio management approach to spatial transport planning," Environment and Planning B, , vol. 50(6), pages 1438-1454, July.
    9. Jacek Oskarbski & Krystian Birr & Karol Żarski, 2021. "Bicycle Traffic Model for Sustainable Urban Mobility Planning," Energies, MDPI, vol. 14(18), pages 1-36, September.
    10. Bergantino, Angela Stefania & Intini, Mario & Tangari, Luca, 2021. "Influencing factors for potential bike-sharing users: an empirical analysis during the COVID-19 pandemic," Research in Transportation Economics, Elsevier, vol. 86(C).
    11. 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.
    12. Hudyeron Rocha & António Lobo & José Pedro Tavares & Sara Ferreira, 2023. "Exploring Modal Choices for Sustainable Urban Mobility: Insights from the Porto Metropolitan Area in Portugal," Sustainability, MDPI, vol. 15(20), pages 1-20, October.
    13. Blitz, Andreas & Lanzendorf, Martin, 2020. "Mobility design as a means of promoting non-motorised travel behaviour? A literature review of concepts and findings on design functions," Journal of Transport Geography, Elsevier, vol. 87(C).

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    More about this item

    Keywords

    Bicycle; Cycle lanes/ways; Cycling to school; Policies; Adolescents; Different types of cities; Sustainable mobility;
    All these keywords.

    JEL classification:

    • R41 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Transportation: Demand, Supply, and Congestion; Travel Time; Safety and Accidents; Transportation Noise
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities

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