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The cost of travel time variability: three measures with properties

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  • Engelson, Leonid
  • Fosgerau, Mogens

Abstract

This paper explores the relationships between three types of measures of the cost of travel time variability: measures based on scheduling preferences and implicit departure time choice, Bernoulli type measures based on a univariate function of travel time, and mean-dispersion measures. We characterise measures that are both scheduling measures and mean-dispersion measures and measures that are both Bernoulli and mean-dispersion. There are no measures that are both scheduling and Bernoulli. We consider the impact of requiring that measures are additive or homogeneous, proving also a new strong result on the utility rates in an additive scheduling measure. These insights are useful for selecting cost measures to use in applications.

Suggested Citation

  • Engelson, Leonid & Fosgerau, Mogens, 2016. "The cost of travel time variability: three measures with properties," MPRA Paper 72255, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:72255
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    Cited by:

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    2. Beaud, Mickael & Blayac, Thierry & Stéphan, Maïté, 2016. "The impact of travel time variability and travelers’ risk attitudes on the values of time and reliability," Transportation Research Part B: Methodological, Elsevier, vol. 93(PA), pages 207-224.
    3. Li, Zheng & Hensher, David A. & Rose, John M., 2010. "Willingness to pay for travel time reliability in passenger transport: A review and some new empirical evidence," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 46(3), pages 384-403, May.
    4. Taylor, Michael A.P., 2017. "Fosgerau's travel time reliability ratio and the Burr distribution," Transportation Research Part B: Methodological, Elsevier, vol. 97(C), pages 50-63.
    5. Xiao, Yu & Coulombel, Nicolas & Palma, André de, 2017. "The valuation of travel time reliability: does congestion matter?," Transportation Research Part B: Methodological, Elsevier, vol. 97(C), pages 113-141.
    6. Fosgerau, Mogens & Jiang, Gege, 2019. "Travel time variability and rational inattention," Transportation Research Part B: Methodological, Elsevier, vol. 120(C), pages 1-14.
    7. Durrmeyer, Isis & Martinez, Nicolas, 2022. "The Welfare Consequences of Urban Traffic Regulations," TSE Working Papers 22-1378, Toulouse School of Economics (TSE).
    8. Gu, Yu & Fu, Xiao & Liu, Zhiyuan & Xu, Xiangdong & Chen, Anthony, 2020. "Performance of transportation network under perturbations: Reliability, vulnerability, and resilience," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 133(C).
    9. Chen, Bi Yu & Li, Qingquan & Lam, William H.K., 2016. "Finding the k reliable shortest paths under travel time uncertainty," Transportation Research Part B: Methodological, Elsevier, vol. 94(C), pages 189-203.
    10. Adrian Barchański & Renata Żochowska & Marcin Jacek Kłos, 2022. "A Method for the Identification of Critical Interstop Sections in Terms of Introducing Electric Buses in Public Transport," Energies, MDPI, vol. 15(20), pages 1-37, October.
    11. Li, Zhi-Chun & Huang, Hai-Jun & Yang, Hai, 2020. "Fifty years of the bottleneck model: A bibliometric review and future research directions," Transportation Research Part B: Methodological, Elsevier, vol. 139(C), pages 311-342.
    12. Hess, Stephane & Daly, Andrew & Dekker, Thijs & Cabral, Manuel Ojeda & Batley, Richard, 2017. "A framework for capturing heterogeneity, heteroskedasticity, non-linearity, reference dependence and design artefacts in value of time research," Transportation Research Part B: Methodological, Elsevier, vol. 96(C), pages 126-149.

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    More about this item

    Keywords

    value; travel time; variability; reliability;
    All these keywords.

    JEL classification:

    • D1 - Microeconomics - - Household Behavior
    • D8 - Microeconomics - - Information, Knowledge, and Uncertainty
    • R4 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics

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