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Taxi market equilibrium with third-party hailing service

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  • Qian, Xinwu
  • Ukkusuri, Satish V.

Abstract

With the development and deployment of new technologies, the oligopolistic taxi industry is transforming into a shared market with coexistence of both traditional taxi service (TTS) and app-based third-party taxi service (ATTS). The ATTS is different from TTS in both entry policy and fare setting, and brings competition into the market. To account for the revolution of the taxi industry, in this study, we analyze the characteristics of the TTS and ATTS, model the taxi market as a multiple-leader-follower game at the network level, and investigate the equilibrium of taxi market with competition (TMC Equilibrium). In particular, passengers are modeled as the leaders who seek to minimize their travel cost associated with taxi rides. Followers involve TTS and ATTS drivers, who compete for passengers to maximize their revenue. The network model captures selfish behavior of passengers and drivers in the taxi market, and we prove the existence of TMC Equilibrium for the proposed model using variational inequality formulations. An iterative algorithm is further developed to find the TMC Equilibrium, which corresponds to the strongly stationary point of the multi-leader-follower game. Based on numerical results, it is observed that fleet size and pricing policy are closely associated with the level of competition in the market and may have significant impact on total passengers cost, average waiting time, and fleet utilization.

Suggested Citation

  • Qian, Xinwu & Ukkusuri, Satish V., 2017. "Taxi market equilibrium with third-party hailing service," Transportation Research Part B: Methodological, Elsevier, vol. 100(C), pages 43-63.
    • Handle: RePEc:eee:transb:v:100:y:2017:i:c:p:43-63
    DOI: 10.1016/j.trb.2017.01.012
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    References listed on IDEAS

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    Cited by:

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    6. Wu, Tian & Zhang, Mengbo & Tian, Xin & Wang, Shouyang & Hua, Guowei, 2020. "Spatial differentiation and network externality in pricing mechanism of online car hailing platform," International Journal of Production Economics, Elsevier, vol. 219(C), pages 275-283.
    7. Qian, Xinwu & Zhang, Wenbo & Ukkusuri, Satish V. & Yang, Chao, 2017. "Optimal assignment and incentive design in the taxi group ride problem," Transportation Research Part B: Methodological, Elsevier, vol. 103(C), pages 208-226.
    8. Li, Baicheng & Szeto, W.Y., 2021. "Modeling and analyzing a taxi market with a monopsony taxi owner and multiple rentee-drivers," Transportation Research Part B: Methodological, Elsevier, vol. 143(C), pages 1-22.
    9. Mingyang Du & Lin Cheng & Xuefeng Li & Jingzong Yang, 2019. "Investigating the Influential Factors of Shared Travel Behavior: Comparison between App-Based Third Taxi Service and Free-Floating Bike Sharing in Nanjing, China," Sustainability, MDPI, vol. 11(16), pages 1-18, August.
    10. Thorsten Heilker & Gernot Sieg, 2017. "A duopoly of transportation network companies and traditional radio-taxi dispatch service agencies," Working Papers 24, Institute of Transport Economics, University of Muenster.
    11. Sun, Luoyi & Teunter, Ruud H. & Babai, M. Zied & Hua, Guowei, 2019. "Optimal pricing for ride-sourcing platforms," European Journal of Operational Research, Elsevier, vol. 278(3), pages 783-795.
    12. Li, Baicheng & Szeto, W.Y., 2019. "Taxi service area design: Formulation and analysis," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 125(C), pages 308-333.
    13. Xiaohui Wu & Ren He & Meiling He, 2021. "Chaos Analysis of Urban Low-Carbon Traffic Based on Game Theory," IJERPH, MDPI, vol. 18(5), pages 1-12, February.
    14. 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.
    15. Ting Wang & Yong Zhang & Meiye Li & Lei Liu, 2019. "How Do Passengers with Different Using Frequencies Choose between Traditional Taxi Service and Online Car-Hailing Service? A Case Study of Nanjing, China," Sustainability, MDPI, vol. 11(23), pages 1-18, November.
    16. Li, Jianbin & Zheng, Yuting & Dai, Bin & Yu, Jiang, 2020. "Implications of matching and pricing strategies for multiple-delivery-points service in a freight O2O platform," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 136(C).
    17. Di, Xuan & Ban, Xuegang Jeff, 2019. "A unified equilibrium framework of new shared mobility systems," Transportation Research Part B: Methodological, Elsevier, vol. 129(C), pages 50-78.
    18. Djavadian, Shadi & Chow, Joseph Y.J., 2017. "An agent-based day-to-day adjustment process for modeling ‘Mobility as a Service’ with a two-sided flexible transport market," Transportation Research Part B: Methodological, Elsevier, vol. 104(C), pages 36-57.
    19. Lu Ling & Xinwu Qian & Satish V. Ukkusuri, 2023. "Impact of Transportation Network Companies on Labor Supply and Wages for Taxi Drivers," Papers 2307.13620, arXiv.org.
    20. Roger B. Chen & Christopher Valant, 2023. "Stability and Convergence in Matching Processes for Shared Mobility Systems," Networks and Spatial Economics, Springer, vol. 23(2), pages 469-486, June.
    21. Bian, Zheyong & Liu, Xiang, 2019. "Mechanism design for first-mile ridesharing based on personalized requirements part I: Theoretical analysis in generalized scenarios," Transportation Research Part B: Methodological, Elsevier, vol. 120(C), pages 147-171.
    22. Nourinejad, Mehdi & Ramezani, Mohsen, 2020. "Ride-Sourcing modeling and pricing in non-equilibrium two-sided markets," Transportation Research Part B: Methodological, Elsevier, vol. 132(C), pages 340-357.

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