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Carpooling with heterogeneous users in the bottleneck model

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  • Yu, Xiaojuan
  • van den Berg, Vincent A.C.
  • Verhoef, Erik T.

Abstract

We investigate the effects of carpooling in a dynamic equilibrium model of congestion, which captures various dimensions of heterogeneity: heterogeneity in the preference for and cost of carpooling, heterogeneity in values of time and values of schedule delay. We investigate various policy scenarios: no-toll, first-best pricing, and subsidization of carpooling. The optimally differentiated subsidy equals each type of users’ marginal external benefit (MEB) of switching to m-person carpooling or carpooling, which turns out to be heterogeneous for “ratio heterogeneity”, where the ratios of the values of time and schedule delay vary, and homogeneous for “proportional heterogeneity”, where these values vary in fixed proportion over the population. If such differentiation over users is impossible, the subsidy is a weighted average of the MEB’s, with the weights reflecting the relative sensitivity of the group size of carpoolers to the subsidy. Using a numerical example, we investigate the welfare effects and distributional effects of different policies. The relative efficiency of the differentiated subsidization first increases and then falls with the degree of ratio heterogeneity, and decreases over the entire parameter range and more with the degree of proportional heterogeneity.

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  • Yu, Xiaojuan & van den Berg, Vincent A.C. & Verhoef, Erik T., 2019. "Carpooling with heterogeneous users in the bottleneck model," Transportation Research Part B: Methodological, Elsevier, vol. 127(C), pages 178-200.
  • Handle: RePEc:eee:transb:v:127:y:2019:i:c:p:178-200
    DOI: 10.1016/j.trb.2019.07.003
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    2. Senlai Zhu & Hantao Yu & Congjun Fan, 2024. "Travel Plan Sharing and Regulation for Managing Traffic Bottleneck Based on Blockchain Technology," Sustainability, MDPI, vol. 16(4), pages 1-20, February.
    3. Konagane, Joji & Kono, Tatsuhito, 2021. "Heterogeneous Households’ Choices of Departure Time and Residential Location in a Multiple-origin Single-destination Rail System: Market Equilibrium and the First-best Solution," MPRA Paper 108507, University Library of Munich, Germany.
    4. Xiao, Ling-Ling & Liu, Tian-Liang & Huang, Hai-Jun & Liu, Ronghui, 2021. "Temporal-spatial allocation of bottleneck capacity for managing morning commute with carpool," Transportation Research Part B: Methodological, Elsevier, vol. 143(C), pages 177-200.
    5. R. Lamotte & A. de Palma & N. Geroliminis, 2020. "Impacts of Metering-Based Dynamic Priority Schemes," THEMA Working Papers 2020-14, THEMA (THéorie Economique, Modélisation et Applications), Université de Cergy-Pontoise.
    6. André de Palma & Lucas Javaudin & Patrick Stokkink & Léandre Tarpin-Pitre, 2022. "Ride-sharing with inflexible drivers in the Paris metropolitan area," Post-Print hal-03880692, HAL.
    7. Wu, Jiyan & Tian, Ye & Sun, Jian, 2023. "Managing ridesharing with incentives in a bottleneck model," Research in Transportation Economics, Elsevier, vol. 101(C).
    8. Hu, Shichun & Dessouky, Maged M. & Uhan, Nelson A. & Vayanos, Phebe, 2021. "Cost-sharing mechanism design for ride-sharing," Transportation Research Part B: Methodological, Elsevier, vol. 150(C), pages 410-434.
    9. de Palma, André & Stokkink, Patrick & Geroliminis, Nikolas, 2022. "Influence of dynamic congestion with scheduling preferences on carpooling matching with heterogeneous users," Transportation Research Part B: Methodological, Elsevier, vol. 155(C), pages 479-498.
    10. 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.
    11. André de Palma & Lucas Javaudin & Patrick Stokkink & Léandre Tarpin-Pitre, 2021. "Modelling Ridesharing in a Large Network with Dynamic Congestion," THEMA Working Papers 2021-16, THEMA (THéorie Economique, Modélisation et Applications), Université de Cergy-Pontoise.
    12. Sun, Jian & Wu, Jiyan & Xiao, Feng & Tian, Ye & Xu, Xiangdong, 2020. "Managing bottleneck congestion with incentives," Transportation Research Part B: Methodological, Elsevier, vol. 134(C), pages 143-166.

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    More about this item

    Keywords

    Carpooling; Heterogeneity; Bottleneck model; Welfare effects; Distributional effects;
    All these keywords.

    JEL classification:

    • D62 - Microeconomics - - Welfare Economics - - - Externalities
    • H23 - Public Economics - - Taxation, Subsidies, and Revenue - - - Externalities; Redistributive Effects; Environmental Taxes and Subsidies
    • R41 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Transportation: Demand, Supply, and Congestion; Travel Time; Safety and Accidents; Transportation Noise
    • R48 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Government Pricing and Policy

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