IDEAS home Printed from https://ideas.repec.org/a/eee/transe/v149y2021ics1366554520308516.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1366554520308516
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.tre.2020.102209?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Chao Chen & Shenle Pan, 2016. "Using the Crowd of Taxis to Last Mile Delivery in E-Commerce: a methodological research," Post-Print hal-01480533, HAL.
    2. Devari, Aashwinikumar & Nikolaev, Alexander G. & He, Qing, 2017. "Crowdsourcing the last mile delivery of online orders by exploiting the social networks of retail store customers," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 105(C), pages 105-122.
    3. Tho V. Le & Satish V. Ukkusuri, 2019. "Influencing factors that determine the usage of the crowd-shipping services," Papers 1902.08681, arXiv.org.
    4. Punel, Aymeric & Stathopoulos, Amanda, 2017. "Modeling the acceptability of crowdsourced goods deliveries: Role of context and experience effects," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 105(C), pages 18-38.
    5. Michele D. Simoni & Edoardo Marcucci & Valerio Gatta & Christian G. Claudel, 0. "Potential last-mile impacts of crowdshipping services: a simulation-based evaluation," Transportation, Springer, vol. 0, pages 1-22.
    6. Allahviranloo, Mahdieh & Baghestani, Amirhossein, 2019. "A dynamic crowdshipping model and daily travel behavior," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 128(C), pages 175-190.
    7. 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.
    8. Amy Cohn & Sarah Root & Alex Wang & Douglas Mohr, 2007. "Integration of the Load-Matching and Routing Problem with Equipment Balancing for Small Package Carriers," Transportation Science, INFORMS, vol. 41(2), pages 238-252, May.
    9. Arslan, A.M. & Agatz, N.A.H. & Kroon, L.G. & Zuidwijk, R.A., 2016. "Crowdsourced Delivery: A Dynamic Pickup and Delivery Problem with Ad-hoc Drivers," ERIM Report Series Research in Management ERS-2016-003-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    10. Archetti, Claudia & Savelsbergh, Martin & Speranza, M. Grazia, 2016. "The Vehicle Routing Problem with Occasional Drivers," European Journal of Operational Research, Elsevier, vol. 254(2), pages 472-480.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Alnaggar, Aliaa & Gzara, Fatma & Bookbinder, James H., 2024. "Compensation guarantees in crowdsourced delivery: Impact on platform and driver welfare," Omega, Elsevier, vol. 122(C).
    2. 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).
    3. 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.
    4. 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.
    5. 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).
    6. 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).
    7. 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.
    8. 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).
    9. Mancini, Simona & Gansterer, Margaretha, 2022. "Bundle generation for last-mile delivery with occasional drivers," Omega, Elsevier, vol. 108(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Nils Boysen & Stefan Fedtke & Stefan Schwerdfeger, 2021. "Last-mile delivery concepts: a survey from an operational research perspective," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 43(1), pages 1-58, March.
    2. Pourrahmani, Elham & Jaller, Miguel, 2021. "Crowdshipping in last mile deliveries: Operational challenges and research opportunities," Socio-Economic Planning Sciences, Elsevier, vol. 78(C).
    3. Cleophas, Catherine & Cottrill, Caitlin & Ehmke, Jan Fabian & Tierney, Kevin, 2019. "Collaborative urban transportation: Recent advances in theory and practice," European Journal of Operational Research, Elsevier, vol. 273(3), pages 801-816.
    4. Xiao, Fei & Wang, Haijun & Guo, Shuojia & Guan, Xu & Liu, Baoshan, 2021. "Efficient and truthful multi-attribute auctions for crowdsourced delivery," International Journal of Production Economics, Elsevier, vol. 240(C).
    5. Mancini, Simona & Gansterer, Margaretha, 2022. "Bundle generation for last-mile delivery with occasional drivers," Omega, Elsevier, vol. 108(C).
    6. Behrend, Moritz & Meisel, Frank, 2018. "The integration of item-sharing and crowdshipping: Can collaborative consumption be pushed by delivering through the crowd?," Transportation Research Part B: Methodological, Elsevier, vol. 111(C), pages 227-243.
    7. Alireza Ermagun & Ali Shamshiripour & Amanda Stathopoulos, 2020. "Performance analysis of crowd-shipping in urban and suburban areas," Transportation, Springer, vol. 47(4), pages 1955-1985, August.
    8. Ermagun, Alireza & Stathopoulos, Amanda, 2018. "To bid or not to bid: An empirical study of the supply determinants of crowd-shipping," Transportation Research Part A: Policy and Practice, Elsevier, vol. 116(C), pages 468-483.
    9. Shen, Hui & Lin, Jane, 2020. "Investigation of crowdshipping delivery trip production with real-world data," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 143(C).
    10. Raúl Martín-Santamaría & Ana D. López-Sánchez & María Luisa Delgado-Jalón & J. Manuel Colmenar, 2021. "An Efficient Algorithm for Crowd Logistics Optimization," Mathematics, MDPI, vol. 9(5), pages 1-19, March.
    11. Allahviranloo, Mahdieh & Baghestani, Amirhossein, 2019. "A dynamic crowdshipping model and daily travel behavior," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 128(C), pages 175-190.
    12. Wanjie Hu & Jianjun Dong & Bon-gang Hwang & Rui Ren & Zhilong Chen, 2019. "A Scientometrics Review on City Logistics Literature: Research Trends, Advanced Theory and Practice," Sustainability, MDPI, vol. 11(10), pages 1-27, May.
    13. Punel, Aymeric & Stathopoulos, Amanda, 2017. "Modeling the acceptability of crowdsourced goods deliveries: Role of context and experience effects," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 105(C), pages 18-38.
    14. Behrend, Moritz & Meisel, Frank & Fagerholt, Kjetil & Andersson, Henrik, 2019. "An exact solution method for the capacitated item-sharing and crowdshipping problem," European Journal of Operational Research, Elsevier, vol. 279(2), pages 589-604.
    15. Pasirayi, Simbarashe & Fennell, Patrick B. & Sen, Argha, 2023. "The effect of third-party delivery partnerships on firm value," Journal of Business Research, Elsevier, vol. 167(C).
    16. Ghaderi, Hadi & Zhang, Lele & Tsai, Pei-Wei & Woo, Jihoon, 2022. "Crowdsourced last-mile delivery with parcel lockers," International Journal of Production Economics, Elsevier, vol. 251(C).
    17. Mohri, Seyed Sina & Nassir, Neema & Thompson, Russell G. & Lavieri, Patricia Sauri, 2024. "Public transportation-based crowd-shipping initiatives: Are users willing to participate? Why not?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 182(C).
    18. 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).
    19. Fessler, Andreas & Thorhauge, Mikkel & Mabit, Stefan & Haustein, Sonja, 2022. "A public transport-based crowdshipping concept as a sustainable last-mile solution: Assessing user preferences with a stated choice experiment," Transportation Research Part A: Policy and Practice, Elsevier, vol. 158(C), pages 210-223.
    20. 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.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:transe:v:149:y:2021:i:c:s1366554520308516. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/600244/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.