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Optimizing Taxi-Pooling Operations to Enhance Efficiency and Revenue: A Queuing Model Approach

Author

Listed:
  • Chaojun Wang

    (Smart Urban Mobility Institute, University of Shanghai for Science and Technology, Shanghai 200090, China)

  • Jingwei Wang

    (Department of Traffic Engineering, Huaiyin Institute of Technology, Huaian 223003, China)

  • Yi Zhang

    (Shanghai Municipal Institute of Urban and Rural Construction and Transportation Development, Shanghai 200032, China)

  • Jairus Odawa Malenje

    (School of Computing and Informatics, Masinde Muliro University of Science and Technology, Kakamega 190-50100, Kenya)

  • Yin Han

    (Smart Urban Mobility Institute, University of Shanghai for Science and Technology, Shanghai 200090, China)

Abstract

This study investigates the optimization of taxi-pooling operations using the M / M /1/ m queuing model, aiming to enhance efficiency and revenue for taxi service platforms. Traditional taxi operations face challenges during peak periods, including inefficiency and increased operational costs. Taxi-pooling, by accommodating multiple passengers with similar travel demands, offers a solution that reduces travel costs, operational expenses, and urban congestion. The study develops an optimization model to balance operational costs and passenger waiting times, identifying the utilization rate of taxis as a critical factor in platform revenue. By modeling the taxi-pooling service as a queuing system, we derive mathematical expressions for passenger waiting times and platform revenue under varying conditions. Our findings highlight the importance of optimal vehicle investment strategies and pricing decisions to maximize revenue. The study provides theoretical support for improving taxi-pooling platforms’ efficiency and competitiveness, contributing to better urban transportation solutions.

Suggested Citation

  • Chaojun Wang & Jingwei Wang & Yi Zhang & Jairus Odawa Malenje & Yin Han, 2024. "Optimizing Taxi-Pooling Operations to Enhance Efficiency and Revenue: A Queuing Model Approach," Mathematics, MDPI, vol. 12(20), pages 1-22, October.
    • Handle: RePEc:gam:jmathe:v:12:y:2024:i:20:p:3210-:d:1497923
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    References listed on IDEAS

    as
    1. Amirmahdi Tafreshian & Neda Masoud & Yafeng Yin, 2020. "Frontiers in Service Science: Ride Matching for Peer-to-Peer Ride Sharing: A Review and Future Directions," Service Science, INFORMS, vol. 12(2-3), pages 44-60, June.
    2. 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.
    3. Judd Cramer & Alan B. Krueger, 2016. "Disruptive Change in the Taxi Business: The Case of Uber," American Economic Review, American Economic Association, vol. 106(5), pages 177-182, May.
    4. Berger, Thor & Chen, Chinchih & Frey, Carl Benedikt, 2018. "Drivers of disruption? Estimating the Uber effect," European Economic Review, Elsevier, vol. 110(C), pages 197-210.
    5. Saif Benjaafar & Guangwen Kong & Xiang Li & Costas Courcoubetis, 2019. "Peer-to-Peer Product Sharing: Implications for Ownership, Usage, and Social Welfare in the Sharing Economy," Management Science, INFORMS, vol. 65(2), pages 477-493, February.
    6. 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.
    7. Wenbo Zhang & Satish V. Ukkusuri & Jian John Lu, 2017. "Impacts of urban built environment on empty taxi trips using limited geolocation data," Transportation, Springer, vol. 44(6), pages 1445-1473, November.
    8. Cordeau, Jean-François & Laporte, Gilbert, 2003. "A tabu search heuristic for the static multi-vehicle dial-a-ride problem," Transportation Research Part B: Methodological, Elsevier, vol. 37(6), pages 579-594, July.
    9. Wang, Xiaolei & He, Fang & Yang, Hai & Oliver Gao, H., 2016. "Pricing strategies for a taxi-hailing platform," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 93(C), pages 212-231.
    10. 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.
    11. Baojun Jiang & Lin Tian, 2018. "Collaborative Consumption: Strategic and Economic Implications of Product Sharing," Management Science, INFORMS, vol. 64(3), pages 1171-1188, March.
    12. Nanry, William P. & Wesley Barnes, J., 2000. "Solving the pickup and delivery problem with time windows using reactive tabu search," Transportation Research Part B: Methodological, Elsevier, vol. 34(2), pages 107-121, February.
    13. 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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