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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:

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    2. 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.
    3. 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.
    4. 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).
    5. 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).
    6. 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.
    7. Mancini, Simona & Gansterer, Margaretha, 2022. "Bundle generation for last-mile delivery with occasional drivers," Omega, Elsevier, vol. 108(C).

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