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Using bilateral trading to increase ridership and user permanence in ridesharing systems

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  • Masoud, Neda
  • Lloret-Batlle, Roger
  • Jayakrishnan, R.

Abstract

One of the main obstacles that has challenged peer-to-peer (P2P) ridesharing systems in operating as stand-alone systems is reaching a critical mass of participants. Toward this goal, we propose what we call the P2P ride exchange mechanism to increase matching rate and customer retention in a ridesharing system. This mechanism gives riders the opportunity to purchase other riders’ itineraries while it provides suitable alternative rides to the sellers, thus increasing the service rate in a ridesharing system. The proposed mechanism aims to maximize expected user surplus, is robust towards selfish user manipulation, and has very low information requirements. Using numerical experiments, we demonstrate what type of ridesharing systems can benefit the most from P2P ride exchange. Furthermore, we study the impact of customer flexibility on the rate of exchange. If implemented properly, P2P ride exchange can effectively increase the number of served riders and enhance customer loyalty by engaging customers in the ride-matching process.

Suggested Citation

  • Masoud, Neda & Lloret-Batlle, Roger & Jayakrishnan, R., 2017. "Using bilateral trading to increase ridership and user permanence in ridesharing systems," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 102(C), pages 60-77.
    • Handle: RePEc:eee:transe:v:102:y:2017:i:c:p:60-77
    DOI: 10.1016/j.tre.2017.04.007
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    References listed on IDEAS

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    1. Masoud, Neda & Jayakrishnan, R., 2017. "A decomposition algorithm to solve the multi-hop Peer-to-Peer ride-matching problem," Transportation Research Part B: Methodological, Elsevier, vol. 99(C), pages 1-29.
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    Citations

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    Cited by:

    1. Tafreshian, Amirmahdi & Masoud, Neda, 2022. "A truthful subsidy scheme for a peer-to-peer ridesharing market with incomplete information," Transportation Research Part B: Methodological, Elsevier, vol. 162(C), pages 130-161.
    2. Rasulkhani, Saeid & Chow, Joseph Y.J., 2019. "Route-cost-assignment with joint user and operator behavior as a many-to-one stable matching assignment game," Transportation Research Part B: Methodological, Elsevier, vol. 124(C), pages 60-81.
    3. 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).
    4. Hua, Shijia & Zeng, Wenjia & Liu, Xinglu & Qi, Mingyao, 2022. "Optimality-guaranteed algorithms on the dynamic shared-taxi problem," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 164(C).
    5. Masoud, Neda & Jayakrishnan, R., 2017. "A real-time algorithm to solve the peer-to-peer ride-matching problem in a flexible ridesharing system," Transportation Research Part B: Methodological, Elsevier, vol. 106(C), pages 218-236.
    6. Bian, Zheyong & Liu, Xiang & Bai, Yun, 2020. "Mechanism design for on-demand first-mile ridesharing," Transportation Research Part B: Methodological, Elsevier, vol. 138(C), pages 77-117.
    7. Yuanyuan Zhang & Yuming Zhang, 2018. "Examining the Relationship between Household Vehicle Ownership and Ridesharing Behaviors in the United States," Sustainability, MDPI, vol. 10(8), pages 1-24, August.
    8. Ma, Jie & Xu, Min & Meng, Qiang & Cheng, Lin, 2020. "Ridesharing user equilibrium problem under OD-based surge pricing strategy," Transportation Research Part B: Methodological, Elsevier, vol. 134(C), pages 1-24.
    9. Mohammad Asghari & Seyed Mohammad Javad Mirzapour Al-E-Hashem & Yacine Rekik, 2022. "Environmental and social implications of incorporating carpooling service on a customized bus system," Post-Print hal-03598768, HAL.
    10. Mourad, Abood & Puchinger, Jakob & Chu, Chengbin, 2019. "A survey of models and algorithms for optimizing shared mobility," Transportation Research Part B: Methodological, Elsevier, vol. 123(C), pages 323-346.
    11. Guo, Jiantao & Zhang, Juliang & Cheng, T.C.E. & Zhao, Shouting, 2022. "Truthful double auction mechanisms for online freight platforms with transaction costs," Transportation Research Part B: Methodological, Elsevier, vol. 158(C), pages 164-186.
    12. Yuanyuan Zhang & Yuming Zhang, 2018. "Exploring the Relationship between Ridesharing and Public Transit Use in the United States," IJERPH, MDPI, vol. 15(8), pages 1-23, August.
    13. 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.
    14. Bian, Zheyong & Liu, Xiang, 2019. "Mechanism design for first-mile ridesharing based on personalized requirements part II: Solution algorithm for large-scale problems," Transportation Research Part B: Methodological, Elsevier, vol. 120(C), pages 172-192.
    15. Hou, Liwen & Li, Dong & Zhang, Dali, 2018. "Ride-matching and routing optimisation: Models and a large neighbourhood search heuristic," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 118(C), pages 143-162.

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