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Joint re-dispatching and pricing on a business-to-consumer ride-hailing platform

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  • Zhang, Jiang-Hua
  • Zhu, Rui
  • Wang, Jing-Peng

Abstract

On-demand B2C ride-hailing platforms have enhanced service efficiency through centralized order dispatching and full-time driver management while diversifying services to meet passengers’ varying needs for service quality. This paper is one of the first that considers a B2C ride-hailing platform that coordinates ordinary and limousine services, integrating re-dispatching and pricing strategies to optimize short-term revenue and strategically determining its fleet size and initial vehicle allocation to enhance long-term system welfare. We establish a two-period framework to capture the decision-making processes of various stakeholders, considering passengers’ heterogeneous preferences for the two services and the impact of re-dispatching limousine vehicles. For the platform’s short-term operational strategy, we identify a critical threshold for the initial allocation proportion of ordinary vehicles. Below this critical threshold, and in markets smaller than a specific size decreasing with the initial ordinary vehicle proportion, a joint re-dispatching and pricing strategy should be adopted. Otherwise, a single pricing strategy suffices. All passengers can be served in smaller markets, while only passengers with stronger preferences for the ordinary (limousine) service place orders in larger markets. The platform can enhance long-term system welfare by strategically managing fleet size and optimizing the initial allocation of vehicles. Larger markets or greater service quality differences promote the platform to choose a larger fleet and fewer initial ordinary vehicles. In contrast, a larger difference in operating costs between limousine and ordinary vehicles has the opposite effect.

Suggested Citation

  • Zhang, Jiang-Hua & Zhu, Rui & Wang, Jing-Peng, 2025. "Joint re-dispatching and pricing on a business-to-consumer ride-hailing platform," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 196(C).
  • Handle: RePEc:eee:transe:v:196:y:2025:i:c:s1366554525000390
    DOI: 10.1016/j.tre.2025.103998
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    References listed on IDEAS

    as
    1. Gérard P. Cachon & Kaitlin M. Daniels & Ruben Lobel, 2017. "The Role of Surge Pricing on a Service Platform with Self-Scheduling Capacity," Manufacturing & Service Operations Management, INFORMS, vol. 19(3), pages 368-384, July.
    2. Vredin Johansson, Maria & Heldt, Tobias & Johansson, Per, 2006. "The effects of attitudes and personality traits on mode choice," Transportation Research Part A: Policy and Practice, Elsevier, vol. 40(6), pages 507-525, July.
    3. Harish Guda & Upender Subramanian, 2019. "Your Uber Is Arriving: Managing On-Demand Workers Through Surge Pricing, Forecast Communication, and Worker Incentives," Management Science, INFORMS, vol. 67(5), pages 1995-2014, May.
    4. Weibo Li & Maria Kamargianni, 2020. "An Integrated Choice and Latent Variable Model to Explore the Influence of Attitudinal and Perceptual Factors on Shared Mobility Choices and Their Value of Time Estimation," Transportation Science, INFORMS, vol. 54(1), pages 62-83, January.
    5. Li, Sen & Tavafoghi, Hamidreza & Poolla, Kameshwar & Varaiya, Pravin, 2019. "Regulating TNCs: Should Uber and Lyft set their own rules?," Transportation Research Part B: Methodological, Elsevier, vol. 129(C), pages 193-225.
    6. Fernando Bernstein & Gregory A. DeCroix & N. Bora Keskin, 2021. "Competition Between Two-Sided Platforms Under Demand and Supply Congestion Effects," Manufacturing & Service Operations Management, INFORMS, vol. 23(5), pages 1043-1061, September.
    7. Terry A. Taylor, 2018. "On-Demand Service Platforms," Manufacturing & Service Operations Management, INFORMS, vol. 20(4), pages 704-720, October.
    8. Zhang, Kenan & Nie, Yu (Marco), 2021. "To pool or not to pool: Equilibrium, pricing and regulation," Transportation Research Part B: Methodological, Elsevier, vol. 151(C), pages 59-90.
    9. Zhong, Yuanguang & Pan, Qi & Xie, Wei & Cheng, T.C.E. & Lin, Xiaogang, 2020. "Pricing and wage strategies for an on-demand service platform with heterogeneous congestion-sensitive customers," International Journal of Production Economics, Elsevier, vol. 230(C).
    10. Dong, Tingting & Xu, Zhengtian & Luo, Qi & Yin, Yafeng & Wang, Jian & Ye, Jieping, 2021. "Optimal contract design for ride-sourcing services under dual sourcing," Transportation Research Part B: Methodological, Elsevier, vol. 146(C), pages 289-313.
    11. Anton Braverman & J. G. Dai & Xin Liu & Lei Ying, 2019. "Empty-Car Routing in Ridesharing Systems," Operations Research, INFORMS, vol. 67(5), pages 1437-1452, September.
    12. Jiayi Joey Yu & Christopher S. Tang & Zuo-Jun Max Shen & Xiqun Michael Chen, 2020. "A Balancing Act of Regulating On-Demand Ride Services," Management Science, INFORMS, vol. 66(7), pages 2975-2992, July.
    13. Kang, Di & Levin, Michael W., 2021. "Maximum-stability dispatch policy for shared autonomous vehicles," Transportation Research Part B: Methodological, Elsevier, vol. 148(C), pages 132-151.
    14. Wang, Hai & Yang, Hai, 2019. "Ridesourcing systems: A framework and review," Transportation Research Part B: Methodological, Elsevier, vol. 129(C), pages 122-155.
    15. Huang, Youlin & Qian, Lixian, 2021. "Consumer adoption of electric vehicles in alternative business models," Energy Policy, Elsevier, vol. 155(C).
    16. Niels Agatz & Soo-Haeng Cho & Hao Sun & Hai Wang, 2024. "Transportation-Enabled Services: Concept, Framework, and Research Opportunities," Service Science, INFORMS, vol. 16(1), pages 1-21, March.
    17. Zhong, Yuanguang & Lan, Yibo & Chen, Zhi & Yang, Jiazi, 2023. "On-demand ride-hailing platforms with heterogeneous quality-sensitive customers: Dedicated system or pooling system?," Transportation Research Part B: Methodological, Elsevier, vol. 173(C), pages 247-266.
    18. Jiaru Bai & Kut C. So & Christopher S. Tang & Xiqun (Michael) Chen & Hai Wang, 2019. "Coordinating Supply and Demand on an On-Demand Service Platform with Impatient Customers," Manufacturing & Service Operations Management, INFORMS, vol. 21(3), pages 556-570, July.
    19. Perboli, Guido & Ferrero, Francesco & Musso, Stefano & Vesco, Andrea, 2018. "Business models and tariff simulation in car-sharing services," Transportation Research Part A: Policy and Practice, Elsevier, vol. 115(C), pages 32-48.
    20. Ke, Jintao & Li, Xinwei & Yang, Hai & Yin, Yafeng, 2021. "Pareto-efficient solutions and regulations of congested ride-sourcing markets with heterogeneous demand and supply," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 154(C).
    21. Ren, Shuyun & Luo, Fengji & Lin, Lei & Hsu, Shu-Chien & LI, Xuran Ivan, 2019. "A novel dynamic pricing scheme for a large-scale electric vehicle sharing network considering vehicle relocation and vehicle-grid-integration," International Journal of Production Economics, Elsevier, vol. 218(C), pages 339-351.
    22. Yu, Xinlian & Gao, Song & Hu, Xianbiao & Park, Hyoshin, 2019. "A Markov decision process approach to vacant taxi routing with e-hailing," Transportation Research Part B: Methodological, Elsevier, vol. 121(C), pages 114-134.
    23. Omar Besbes & Francisco Castro & Ilan Lobel, 2021. "Surge Pricing and Its Spatial Supply Response," Management Science, INFORMS, vol. 67(3), pages 1350-1367, March.
    24. Li, Xiaonan & Li, Xiangyong & Wang, Hai & Shi, Junxin & Aneja, Y.P., 2022. "Supply regulation under the exclusion policy in a ride-sourcing market," Transportation Research Part B: Methodological, Elsevier, vol. 166(C), pages 69-94.
    25. Jacob, Jagan & Roet-Green, Ricky, 2021. "Ride solo or pool: Designing price-service menus for a ride-sharing platform," European Journal of Operational Research, Elsevier, vol. 295(3), pages 1008-1024.
    26. Cai, Zeen & Mo, Dong & Tang, Wei & Chen, Yong & Chen, Xiqun (Michael), 2023. "A two-period game-theoretical model for heterogeneous ride-sourcing platforms with asymmetric competition and mixed fleets," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 178(C).
    27. Li, Xinwei & Ke, Jintao & Yang, Hai & Wang, Hai & Zhou, Yaqian, 2024. "An aggregate matching and pick-up model for mobility-on-demand services," Transportation Research Part B: Methodological, Elsevier, vol. 190(C).
    28. Thurner, Thomas & Fursov, Konstantin & Nefedova, Alena, 2022. "Early adopters of new transportation technologies: Attitudes of Russia’s population towards car sharing, the electric car and autonomous driving," Transportation Research Part A: Policy and Practice, Elsevier, vol. 155(C), pages 403-417.
    29. Wang, Jing-Peng & Huang, Hai-Jun, 2022. "Operations on an on-demand ride service system with express and limousine," Transportation Research Part B: Methodological, Elsevier, vol. 155(C), pages 348-373.
    30. Zhan, Xingbin & Szeto, W.Y. & (Michael) Chen, Xiqun, 2022. "The dynamic ride-hailing sharing problem with multiple vehicle types and user classes," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 168(C).
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