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Private Market Participation in Urban Mass Transportation: Application of Computable Equilibrium Models of Network Competition

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  • Patrick T. Harker

    (University of Pennsylvania, Philadelphia, Pennsylvania)

Abstract

Urban mass transportation is a major recipient of local, state and federal capital and operating subsidies. In this era of increasing pressure to reduce budget deficits at all levels of government comes the call to return part of the urban mass transit industry to the private sector. This paper presents the theory and application of a computable equilibrium model of urban mass transportation which is designed to address the issues of sustainability and distributional equity in this market. This model also serves as an illustration of how computable equilibrium models can be employed in the analysis of network-based competition. A series of examples from the Philadelphia region are presented to illustrate the model's potential as a policy analysis tool and to shed some light on the efficiency versus distributional equity debate which is currently underway in the transportation/public policy community.

Suggested Citation

  • Patrick T. Harker, 1988. "Private Market Participation in Urban Mass Transportation: Application of Computable Equilibrium Models of Network Competition," Transportation Science, INFORMS, vol. 22(2), pages 96-111, May.
  • Handle: RePEc:inm:ortrsc:v:22:y:1988:i:2:p:96-111
    DOI: 10.1287/trsc.22.2.96
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    Cited by:

    1. Liu, Qi & Chow, Joseph Y.J., 2022. "Efficient and stable data-sharing in a public transit oligopoly as a coopetitive game," Transportation Research Part B: Methodological, Elsevier, vol. 163(C), pages 64-87.
    2. Pantelidis, Theodoros P. & Chow, Joseph Y.J. & Rasulkhani, Saeid, 2020. "A many-to-many assignment game and stable outcome algorithm to evaluate collaborative mobility-as-a-service platforms," Transportation Research Part B: Methodological, Elsevier, vol. 140(C), pages 79-100.
    3. Zhi-Chun Li & William Lam & S. Wong, 2012. "Optimization of Number of Operators and Allocation of New Lines in an Oligopolistic Transit Market," Networks and Spatial Economics, Springer, vol. 12(1), pages 1-20, March.
    4. Lu, Xiao-Yun & Gosling, Geoffrey D. & Ceder, Avi & Tung, Steven & Tso, Kristin & Shladover, Steven & Xiong, Jing & Yoon, Sangwon, 2009. "A Combined Quantitative and Qualitative Approach to Planning for Improved Intermodal Connectivity at California Airports," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt1r7227tt, Institute of Transportation Studies, UC Berkeley.
    5. Richard Kalis & Daniel Dujava, 2019. "Choosing the Mode of Transport – Case Study of Bratislava Region," Department of Economic Policy Working Paper Series 019, Department of Economic Policy, Faculty of National Economy, University of Economics in Bratislava.
    6. Theodoros P. Pantelidis & Joseph Y. J. Chow & Saeid Rasulkhani, 2019. "A many-to-many assignment game and stable outcome algorithm to evaluate collaborative Mobility-as-a-Service platforms," Papers 1911.04435, arXiv.org, revised Jun 2020.
    7. Zubieta, Lourdes, 1998. "A network equilibrium model for oligopolistic competition in city bus services," Transportation Research Part B: Methodological, Elsevier, vol. 32(6), pages 413-422, August.
    8. Zhou, Jing & Lam, William H.K. & Heydecker, Benjamin G., 2005. "The generalized Nash equilibrium model for oligopolistic transit market with elastic demand," Transportation Research Part B: Methodological, Elsevier, vol. 39(6), pages 519-544, July.
    9. Chavis, Celeste & Daganzo, Carlos F., 2013. "Analyzing the structure of informal transit: The evening commute problem," Research in Transportation Economics, Elsevier, vol. 39(1), pages 277-284.

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