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Measuring generalised transport costs as an indicator of accessibility changes over time

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  • Koopmans, Carl
  • Groot, Wim
  • Warffemius, Pim
  • Annema, Jan Anne
  • Hoogendoorn-Lanser, Sascha

Abstract

Accessibility in transport policy documents is usually measured through partial indicators such as road speeds, traffic queues or train fares. In the literature, more advanced indicators are found, based on e.g. market potential or utility-based methods. This paper presents a generalised transport costs indicator for policy making which incorporates financial costs, travel times, and reliability of travel times. It calculates the average costs per kilometre of trips by transport mode, trip purpose, trip distance, region and time-of-day.

Suggested Citation

  • Koopmans, Carl & Groot, Wim & Warffemius, Pim & Annema, Jan Anne & Hoogendoorn-Lanser, Sascha, 2013. "Measuring generalised transport costs as an indicator of accessibility changes over time," Transport Policy, Elsevier, vol. 29(C), pages 154-159.
    • Handle: RePEc:eee:trapol:v:29:y:2013:i:c:p:154-159
    DOI: 10.1016/j.tranpol.2013.05.005
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    References listed on IDEAS

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    Cited by:

    1. Lionjanga, Nahungu & Venter, Christo, 2018. "Does public transport accessibility enhance subjective well-being? A study of the City of Johannesburg," Research in Transportation Economics, Elsevier, vol. 69(C), pages 523-535.
    2. Barde, Sylvain & Klein, Alexander, 2021. "Transportation Costs in the Age of Highways: Evidence from United States 1955-2010," CAGE Online Working Paper Series 597, Competitive Advantage in the Global Economy (CAGE).
    3. Cohen, Tom & Shrewsbury, John, 2018. "A novel metric for responding to transport inequality," OSF Preprints 8ypht, Center for Open Science.
    4. Beria, Paolo & Debernardi, Andrea & Ferrara, Emanuele, 2017. "Measuring the long-distance accessibility of Italian cities," Journal of Transport Geography, Elsevier, vol. 62(C), pages 66-79.
    5. Cavallaro, Federico & Dianin, Alberto, 2022. "Combining transport and digital accessibilities in the evaluation of regional work opportunities," Journal of Transport Geography, Elsevier, vol. 98(C).
    6. Rui Zhao & Linchuan Yang & Xinrong Liang & Yuanyuan Guo & Yi Lu & Yixuan Zhang & Xinyun Ren, 2019. "Last-Mile Travel Mode Choice: Data-Mining Hybrid with Multiple Attribute Decision Making," Sustainability, MDPI, vol. 11(23), pages 1-15, November.
    7. Feixiong Liao & Bert van Wee, 2017. "Accessibility measures for robustness of the transport system," Transportation, Springer, vol. 44(5), pages 1213-1233, September.
    8. Fulton, Lewis & Compostella, Junia & Kothawala, Alimurtaza, 2020. "Estimating the Costs of New Mobility Travel Options: Monetary and Non-Monetary Factors," Institute of Transportation Studies, Working Paper Series qt8tc6v0b5, Institute of Transportation Studies, UC Davis.
    9. Cohen, Tom, 2020. "Tools for addressing transport inequality: A novel variant of accessibility measurement," Journal of Transport Geography, Elsevier, vol. 88(C).
    10. Márquez, Luis & Cantillo, Víctor & Paternina-Arboleda, Carlos D., 2024. "Temporal accessibility and freight generation of agricultural products: An empirical study in Colombia," Research in Transportation Economics, Elsevier, vol. 104(C).

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