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Designing pricing and compensation schemes by integrating matching and routing models for crowd-shipping systems

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  • Le, Tho V.
  • Ukkusuri, Satish V.
  • Xue, Jiawei
  • Van Woensel, Tom

Abstract

This paper’s objective is to identify pricing and compensation schemes under different demand and supply scenarios for crowd-shipping (CS) systems. As such, an integrated framework of matching and routing models have been developed. A routing strategy is established to estimate for distances that couriers need to travel for picking up and delivering packages. A matching model is developed to assign crowd-shipping customers (i.e. senders) to couriers and to maximize the CS platform providers’ benefits. Four different schemes of pricing and compensation are developed and evaluated. CS firms are noticed to have the highest profits when apply the ‘individual’ pricing and compensation schemes. The platform provider’s profits are found more sensitive with the increase of willingness to pay (WTP) than the rise of expected to-be-paid (ETP). The insights are helpful for CS firms to attract and retain customers and couriers in the system, by setting up optimal prices and optimal compensations based on demand and supply levels as well as the firms’ expected profits and platform-users’ presuming surplus.

Suggested Citation

  • Le, Tho V. & Ukkusuri, Satish V. & Xue, Jiawei & Van Woensel, Tom, 2021. "Designing pricing and compensation schemes by integrating matching and routing models for crowd-shipping systems," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 149(C).
    • Handle: RePEc:eee:transe:v:149:y:2021:i:c:s1366554520308516
    DOI: 10.1016/j.tre.2020.102209
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    References listed on IDEAS

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    Cited by:

    1. Martin Savelsbergh & Marlin W. Ulmer, 2024. "Challenges and opportunities in crowdsourced delivery planning and operations—an update," Annals of Operations Research, Springer, vol. 343(2), pages 639-661, December.
    2. Parvez Farazi, Nahid & Zou, Bo & Tulabandhula, Theja, 2022. "Dynamic On-Demand Crowdshipping Using Constrained and Heuristics-Embedded Double Dueling Deep Q-Network," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 166(C).
    3. Stokkink, Patrick & Cordeau, Jean-François & Geroliminis, Nikolas, 2024. "A column and row generation approach to the crowd-shipping problem with transfers," Omega, Elsevier, vol. 128(C).
    4. Peng, Shouguo & Park, Woo-Yong & Eltoukhy, Abdelrahman E.E. & Xu, Min, 2024. "Outsourcing service price for crowd-shipping based on on-demand mobility services," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 183(C).
    5. He, Shan & Dai, Ying & Ma, Zu-Jun, 2023. "To offer or not to offer? The optimal value-insured strategy for crowdsourced delivery platforms," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 173(C).
    6. Martin W.P Savelsbergh & Marlin W. Ulmer, 2022. "Challenges and opportunities in crowdsourced delivery planning and operations," 4OR, Springer, vol. 20(1), pages 1-21, March.
    7. Cebeci, Merve Seher & Tapia, Rodrigo Javier & Kroesen, Maarten & de Bok, Michiel & Tavasszy, Lóránt, 2023. "The effect of trust on the choice for crowdshipping services," Transportation Research Part A: Policy and Practice, Elsevier, vol. 170(C).
    8. Lina Xu & Zhiqing Meng, 2024. "Optimizing Retailer Ordering Strategies: a Comparative Analysis of Membership and Non-Membership Systems," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 15(3), pages 13027-13048, September.
    9. Alnaggar, Aliaa & Gzara, Fatma & Bookbinder, James H., 2024. "Compensation guarantees in crowdsourced delivery: Impact on platform and driver welfare," Omega, Elsevier, vol. 122(C).
    10. Zhang, Huili & Luo, Kelin & Xu, Yao & Xu, Yinfeng & Tong, Weitian, 2022. "Online crowdsourced truck delivery using historical information," European Journal of Operational Research, Elsevier, vol. 301(2), pages 486-501.
    11. Guo, Jiantao & Deng, Lan & Gong, Baichuan, 2024. "An online auction-based mechanism for pricing and allocation of instant delivery services," Transportation Research Part B: Methodological, Elsevier, vol. 190(C).
    12. Sina Mohri, Seyed & Ghaderi, Hadi & Nassir, Neema & Thompson, Russell G., 2023. "Crowdshipping for sustainable urban logistics: A systematic review of the literature," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 178(C).
    13. Rossolov, Oleksandr & Susilo, Yusak O., 2024. "Are consumers ready to pay extra for crowd-shipping e-groceries and why? A hybrid choice analysis for developing economies," Transportation Research Part A: Policy and Practice, Elsevier, vol. 187(C).
    14. Patricija Bajec & Danijela Tuljak-Suban, 2022. "A Strategic Approach for Promoting Sustainable Crowdshipping in Last-Mile Deliveries," Sustainability, MDPI, vol. 14(20), pages 1-17, October.
    15. Yang, Dingtong & Hyland, Michael F. & Jayakrishnan, R., 2024. "Tackling the crowdsourced shared-trip delivery problem at scale with a novel decomposition heuristic," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 188(C).
    16. Mancini, Simona & Gansterer, Margaretha, 2022. "Bundle generation for last-mile delivery with occasional drivers," Omega, Elsevier, vol. 108(C).

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