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Pricing for a Last-Mile Transportation System

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  • Chen, Yiwei
  • Wang, Hai

Abstract

The Last-Mile Problem refers to the provision of travel service from the nearest public transportation node to a home or other destination. Last-Mile Transportation System (LMTS), which has recently emerged, provide on-demand shared transportation. We consider an LMTS with multiple passenger types—adults, senior citizens, children, and students. The LMTS designer determines the price for the passengers, last-mile service vehicle capacity, and service fleet size (number of vehicles) for each last-mile region to maximize the social welfare generated by the LMTS. The level of last-mile service (in terms of passenger waiting time) is approximated by using a batch arrival, batch service, multi-server queueing model. The LMTS designer's optimal decisions and optimal social welfare are obtained by solving a constrained nonlinear optimization problem. Our model is implemented in numerical experiments by using real data from Singapore. We show the optimal annual social welfare gained is large. We also analyze a counterpart LMTS in which the LMTS designer sets an identical price for all passenger types. We find that in the absence of price discounts for special groups of passengers, social welfare undergoes almost no change, but the consumer surplus of passengers in special groups suffers significantly.

Suggested Citation

  • Chen, Yiwei & Wang, Hai, 2018. "Pricing for a Last-Mile Transportation System," Transportation Research Part B: Methodological, Elsevier, vol. 107(C), pages 57-69.
    • Handle: RePEc:eee:transb:v:107:y:2018:i:c:p:57-69
    DOI: 10.1016/j.trb.2017.11.008
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    7. Tai-Yu Ma & Sylvain Klein, 2020. "Integrated ridesharing services with chance-constrained dynamic pricing and demand learning," Papers 2001.09151, arXiv.org, revised Jun 2020.
    8. Liu, Junrong & Duan, Qihong & Ma, Wen-Xiu, 2020. "The evolution of a clogging sidewalk caused by a dockless bicycle-sharing system: A stochastic particles model," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 177(C), pages 516-526.
    9. Ke, Jintao & Yang, Hai & Li, Xinwei & Wang, Hai & Ye, Jieping, 2020. "Pricing and equilibrium in on-demand ride-pooling markets," Transportation Research Part B: Methodological, Elsevier, vol. 139(C), pages 411-431.
    10. Wang, Hai & Yang, Hai, 2019. "Ridesourcing systems: A framework and review," Transportation Research Part B: Methodological, Elsevier, vol. 129(C), pages 122-155.
    11. Ke, Jintao & Zhu, Zheng & Yang, Hai & He, Qiaochu, 2021. "Equilibrium analyses and operational designs of a coupled market with substitutive and complementary ride-sourcing services to public transits," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 148(C).
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    13. Matija Kovačić & Maja Mutavdžija & Krešimir Buntak, 2022. "New Paradigm of Sustainable Urban Mobility: Electric and Autonomous Vehicles—A Review and Bibliometric Analysis," Sustainability, MDPI, vol. 14(15), pages 1-23, August.
    14. Zhu, Zheng & Qin, Xiaoran & Ke, Jintao & Zheng, Zhengfei & Yang, Hai, 2020. "Analysis of multi-modal commute behavior with feeding and competing ridesplitting services," Transportation Research Part A: Policy and Practice, Elsevier, vol. 132(C), pages 713-727.
    15. Zhu, Zheng & Xu, Ailing & He, Qiao-Chu & Yang, Hai, 2021. "Competition between the transportation network company and the government with subsidies to public transit riders," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 152(C).
    16. 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.
    17. Mostafa Pazoki & Hamed Samarghandi & Mehdi Behroozi, 2023. "Increasing Supply Chain Resiliency Through Equilibrium Pricing and Stipulating Transportation Quota Regulation," Papers 2308.00681, arXiv.org, revised Oct 2023.
    18. Hu, Shichun & Dessouky, Maged M. & Uhan, Nelson A. & Vayanos, Phebe, 2021. "Cost-sharing mechanism design for ride-sharing," Transportation Research Part B: Methodological, Elsevier, vol. 150(C), pages 410-434.
    19. Lv, Chang & Zhang, Chaoyong & Lian, Kunlei & Ren, Yaping & Meng, Leilei, 2022. "A two-echelon fuzzy clustering based heuristic for large-scale bike sharing repositioning problem," Transportation Research Part B: Methodological, Elsevier, vol. 160(C), pages 54-75.
    20. Jaâfar Berrada & Alexis Poulhès, 2021. "Economic and socioeconomic assessment of replacing conventional public transit with demand responsive transit services in low-to-medium density areas," Post-Print hal-03325200, HAL.
    21. Yang, Hye-jeong & Fang, Mingjie & Yao, Jinge & Su, Miao, 2023. "Green cooperation in last-mile logistics and consumer loyalty: An empirical analysis of a theoretical framework," Journal of Retailing and Consumer Services, Elsevier, vol. 73(C).
    22. Berrada, Jaâfar & Poulhès, Alexis, 2021. "Economic and socioeconomic assessment of replacing conventional public transit with demand responsive transit services in low-to-medium density areas," Transportation Research Part A: Policy and Practice, Elsevier, vol. 150(C), pages 317-334.
    23. Nocera, Silvio & Pungillo, Giuseppe & Bruzzone, Francesco, 2021. "How to evaluate and plan the freight-passengers first-last mile," Transport Policy, Elsevier, vol. 113(C), pages 56-66.
    24. 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.

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