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Mobility-as-a-service (MaaS) system as a multi-leader-multi-follower game: A single-level variational inequality (VI) formulation

Author

Listed:
  • Rui Yao
  • Xinyu Ma
  • Kenan Zhang

Abstract

This study models a Mobility-as-a-Service (MaaS) system as a multi-leader-multi-follower game that captures the complex interactions among the MaaS platform, service operators, and travelers. We consider a coopetitive setting where the MaaS platform purchases service capacity from service operators and sells multi-modal trips to travelers following an origin-destination-based pricing scheme; meanwhile, service operators use their remaining capacities to serve single-modal trips. As followers, travelers make both mode choices, including whether to use MaaS, and route choices in the multi-modal transportation network, subject to prices and congestion. Inspired by the dual formulation for traffic assignment problems, we propose a novel single-level variational inequality (VI) formulation by introducing a virtual traffic operator, along with the MaaS platform and multiple service operators. A key advantage of the proposed VI formulation is that it supports parallel solution procedures and thus enables large-scale applications. We prove that an equilibrium solution always exists given the negotiated wholesale price of service capacity. Numerical experiments on a small network further demonstrate that the wholesale price can be tailored to align with varying system-wide objectives. The proposed MaaS system demonstrates potential for creating a "win-win-win" outcome -- service operators and travelers are better off compared to the "without MaaS" scenario, meanwhile the MaaS platform remains profitable. Such a Pareto-improving regime can be explicitly specified with the wholesale capacity price. Similar conclusions are drawn from the experiment of an extended multi-modal Sioux Falls network, which also validates the scalability of the proposed model and solution algorithm.

Suggested Citation

  • Rui Yao & Xinyu Ma & Kenan Zhang, 2026. "Mobility-as-a-service (MaaS) system as a multi-leader-multi-follower game: A single-level variational inequality (VI) formulation," Papers 2601.19880, arXiv.org.
  • Handle: RePEc:arx:papers:2601.19880
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    References listed on IDEAS

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    1. Fosgerau, Mogens & Frejinger, Emma & Karlstrom, Anders, 2013. "A link based network route choice model with unrestricted choice set," Transportation Research Part B: Methodological, Elsevier, vol. 56(C), pages 70-80.
    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. Xi, Haoning & Aussel, Didier & Liu, Wei & Waller, S.Travis. & Rey, David, 2024. "Single-leader multi-follower games for the regulation of two-sided mobility-as-a-service markets," European Journal of Operational Research, Elsevier, vol. 317(3), pages 718-736.
    4. 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.
    5. Markard, Jochen & Raven, Rob & Truffer, Bernhard, 2012. "Sustainability transitions: An emerging field of research and its prospects," Research Policy, Elsevier, vol. 41(6), pages 955-967.
    6. Mai, Tien & Fosgerau, Mogens & Frejinger, Emma, 2015. "A nested recursive logit model for route choice analysis," Transportation Research Part B: Methodological, Elsevier, vol. 75(C), pages 100-112.
    7. Siddhartha Banerjee & Chamsi Hssaine & Qi Luo & Samitha Samaranayake, 2025. "Plan Your System and Price for Free: Fast Algorithms for Multimodal Transit Operations," Transportation Science, INFORMS, vol. 59(1), pages 13-27, January.
    8. Ding, Xiaoshu & Qi, Qi & Jian, Sisi & Yang, Hai, 2023. "Mechanism design for Mobility-as-a-Service platform considering travelers’ strategic behavior and multidimensional requirements," Transportation Research Part B: Methodological, Elsevier, vol. 173(C), pages 1-30.
    9. 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.
    10. Oyama, Yuki & Hara, Yusuke & Akamatsu, Takashi, 2022. "Markovian traffic equilibrium assignment based on network generalized extreme value model," Transportation Research Part B: Methodological, Elsevier, vol. 155(C), pages 135-159.
    11. Zhang, Kenan & Nie, Yu (Marco), 2021. "Inter-platform competition in a regulated ride-hail market with pooling," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 151(C).
    12. Liu, Bingqing & Chow, Joseph Y. J., 2024. "On-demand mobility-as-a-Service platform assignment games with guaranteed stable outcomes," Transportation Research Part B: Methodological, Elsevier, vol. 188(C).
    13. Josef Hofbauer & William H. Sandholm, 2002. "On the Global Convergence of Stochastic Fictitious Play," Econometrica, Econometric Society, vol. 70(6), pages 2265-2294, November.
    14. Michael Patriksson, 2004. "Sensitivity Analysis of Traffic Equilibria," Transportation Science, INFORMS, vol. 38(3), pages 258-281, August.
    15. Thomson, William, 1994. "Cooperative models of bargaining," Handbook of Game Theory with Economic Applications, in: R.J. Aumann & S. Hart (ed.), Handbook of Game Theory with Economic Applications, edition 1, volume 2, chapter 35, pages 1237-1284, Elsevier.
    16. Tien Mai & Emma Frejinger, 2022. "Undiscounted Recursive Path Choice Models: Convergence Properties and Algorithms," Transportation Science, INFORMS, vol. 56(6), pages 1469-1482, November.
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