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Modeling and managing heterogeneous ride-sourcing platforms with government subsidies on electric vehicles

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  • Mo, Dong
  • Yu, Jingru
  • Chen, Xiqun Michael

Abstract

This paper formulates duopoly competition between two non-cooperative heterogeneous ride-sourcing platforms considering the adoption of electric vehicles (EV) and government subsidies on EVs. One ride-sourcing platform adopts an EV asset-heavy strategy by undertaking EV depreciation costs, while the other ride-sourcing platform adopts an asset-light strategy by hiring drivers who own vehicles. The first-order conditions of each platform's pricingunder competitive equilibrium are derived based on a game-theoretical model that involves the stakeholders (i.e., riders, drivers, and ride-sourcing platforms). Based on the modeling framework ofduopoly competition between two heterogeneous ride-sourcing platforms, this paper proposes an optimization model with social welfare maximization for the determination of governmentsubsidy strategies. We conduct numerical illustrations to demonstrate how governmental subsidies on EV purchase and charging stations impact the endogenous variables in equilibrium (e.g., price for riders, wage for drivers, and market share for each platform) under different formulations of riders' waiting time cost function, which are increasing returns to scale. Also, a specialmodel with a fixed commission ratio is discussed. The results provide suggestions for decision-makers on how to allocate subsidy within the budget constraint.

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  • Mo, Dong & Yu, Jingru & Chen, Xiqun Michael, 2020. "Modeling and managing heterogeneous ride-sourcing platforms with government subsidies on electric vehicles," Transportation Research Part B: Methodological, Elsevier, vol. 139(C), pages 447-472.
    • Handle: RePEc:eee:transb:v:139:y:2020:i:c:p:447-472
    DOI: 10.1016/j.trb.2020.07.006
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    2. Tang, Wei & Xie, Ningke & Mo, Dong & Cai, Zeen & Lee, Der-Horng & Chen, Xiqun (Michael), 2023. "Optimizing subsidy strategies of the ride-sourcing platform under government regulation," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 173(C).
    3. 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).
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    5. Liu, Haoxiang & Zou, Yuncheng & Chen, Ya & Long, Jiancheng, 2021. "Optimal locations and electricity prices for dynamic wireless charging links of electric vehicles for sustainable transportation," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 152(C).
    6. Mo, Dong & Chen, Xiqun (Michael) & Zhang, Junlin, 2022. "Modeling and Managing Mixed On-Demand Ride Services of Human-Driven Vehicles and Autonomous Vehicles," Transportation Research Part B: Methodological, Elsevier, vol. 157(C), pages 80-119.
    7. Ke, Jintao & Chen, Xiqun (Michael) & Yang, Hai & Li, Sen, 2022. "Coordinating supply and demand in ride-sourcing markets with pre-assigned pooling service and traffic congestion externality," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 166(C).
    8. Sun, Luoyi & Teunter, Ruud H. & Hua, Guowei & Wu, Tian, 2020. "Taxi-hailing platforms: Inform or Assign drivers?," Transportation Research Part B: Methodological, Elsevier, vol. 142(C), pages 197-212.
    9. Jun Tu & Juan Du & Min Huang, 2023. "Competition between Green and Non-Green Travel Companies: The Role of Governmental Subsidies in Green Travel," Sustainability, MDPI, vol. 15(9), pages 1-33, May.
    10. Shao, Jing & Jiang, Changmin & Cui, Yinglong & Tang, Yao, 2023. "A game-theoretic model to compare charging infrastructure subsidy and electric vehicle subsidy policies," Transportation Research Part A: Policy and Practice, Elsevier, vol. 176(C).
    11. 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.
    12. Cai, Zeen & Mo, Dong & Geng, Maosi & Tang, Wei & Chen, Xiqun Michael, 2023. "Integrating ride-sourcing with electric vehicle charging under mixed fleets and differentiated services," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 169(C).
    13. Tian, Lijun & Jiang, Xiaolan & Wu, Wenxiang & Huang, Haijun, 2024. "Becoming a freelancer or contractor? Drivers’ contractual mode and schedule decisions in a dual sourcing market," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 185(C).
    14. Zhao, Meng & Li, Bin & Ren, Jiali & Hao, Zhihua, 2023. "Competition equilibrium of ride-sourcing platforms and optimal government subsidies considering customers’ green preference under peak carbon dioxide emissions," International Journal of Production Economics, Elsevier, vol. 255(C).
    15. Zhao, Dan & Ji, Shou-feng & Wang, He-ping & Jiang, Li-wen, 2021. "How do government subsidies promote new energy vehicle diffusion in the complex network context? A three-stage evolutionary game model," Energy, Elsevier, vol. 230(C).
    16. Meijian Yang & Enjun Xia, 2021. "A Systematic Literature Review on Pricing Strategies in the Sharing Economy," Sustainability, MDPI, vol. 13(17), pages 1-28, August.
    17. Cai, Zeen & Li, Chuanjia & Mo, Dong & Xu, Shuyang & Chen, Xiqun (Michael) & Lee, Der-Horng, 2024. "Optimizing consolidated shared charging and electric ride-sourcing services," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 184(C).

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