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Challenges and opportunities in crowdsourced delivery planning and operations

Author

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  • Martin W.P Savelsbergh

    (Georgia Institute of Technology)

  • Marlin W. Ulmer

    (Otto-von-Guericke Universität Magdeburg)

Abstract

How to best deliver goods to consumers has been a logistics question since time immemorial. However, almost all traditional delivery models involved a form of company employees, whether employees of the company manufacturing the goods or whether employees of the company transporting the goods. With the growth of the gig economy, however, a new model not involving company employees has emerged: relying on crowdsourced delivery. Crowdsourced delivery involves enlisting individuals to deliver goods and interacting with these individuals using the internet. In crowdsourced delivery, the interaction with the individuals typically occurs through a platform. Importantly, the crowdsourced couriers are not employed by the platform and this has fundamentally changed the planning and execution of the delivery of goods: the delivery capacity is no longer under (full) control of the company managing the delivery. We present the challenges this introduces, review how the research community has proposed to handle some of these challenges, and elaborate on the challenges that have not yet been addressed.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:aqjoor:v:20:y:2022:i:1:d:10.1007_s10288-021-00500-2
    DOI: 10.1007/s10288-021-00500-2
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    References listed on IDEAS

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    1. 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.
    2. Lafkihi, Mariam & Pan, Shenle & Ballot, Eric, 2019. "Freight transportation service procurement: A literature review and future research opportunities in omnichannel E-commerce," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 125(C), pages 348-365.
    3. Marlin Ulmer & Martin Savelsbergh, 2020. "Workforce Scheduling in the Era of Crowdsourced Delivery," Transportation Science, INFORMS, vol. 54(4), pages 1113-1133, July.
    4. Mofidi, Seyed Shahab & Pazour, Jennifer A., 2019. "When is it beneficial to provide freelance suppliers with choice? A hierarchical approach for peer-to-peer logistics platforms," Transportation Research Part B: Methodological, Elsevier, vol. 126(C), pages 1-23.
    5. Alnaggar, Aliaa & Gzara, Fatma & Bookbinder, James H., 2021. "Crowdsourced delivery: A review of platforms and academic literature," Omega, Elsevier, vol. 98(C).
    6. Junyu Cao & Mariana Olvera-Cravioto & Zuo-Jun (Max) Shen, 2020. "Last-Mile Shared Delivery: A Discrete Sequential Packing Approach," Mathematics of Operations Research, INFORMS, vol. 45(4), pages 1466-1497, November.
    7. Warren B. Powell, 1996. "A Stochastic Formulation of the Dynamic Assignment Problem, with an Application to Truckload Motor Carriers," Transportation Science, INFORMS, vol. 30(3), pages 195-219, August.
    8. Miguel Andres Figliozzi & Hani S. Mahmassani & Patrick Jaillet, 2007. "Pricing in Dynamic Vehicle Routing Problems," Transportation Science, INFORMS, vol. 41(3), pages 302-318, August.
    9. Hongyan Dai & Peng Liu, 2020. "Workforce planning for O2O delivery systems with crowdsourced drivers," Annals of Operations Research, Springer, vol. 291(1), pages 219-245, August.
    10. Ozlem Ergun & Gultekin Kuyzu & Martin Savelsbergh, 2007. "Reducing Truckload Transportation Costs Through Collaboration," Transportation Science, INFORMS, vol. 41(2), pages 206-221, May.
    11. Zhen, Lu & Wu, Yiwei & Wang, Shuaian & Yi, Wen, 2021. "Crowdsourcing mode evaluation for parcel delivery service platforms," International Journal of Production Economics, Elsevier, vol. 235(C).
    12. 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.
    13. Mariam Lafkihi & Shenle Pan & Eric Ballot, 2019. "Freight transportation service procurement: A literature review and future research opportunities in omnichannel E-commerce," Post-Print hal-02086154, HAL.
    14. 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).
    15. 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.
    16. 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.
    17. 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.
    18. Alireza Ermagun & Ali Shamshiripour & Amanda Stathopoulos, 0. "Performance analysis of crowd-shipping in urban and suburban areas," Transportation, Springer, vol. 0, pages 1-31.
    19. Powell, Warren B., 1987. "An operational planning model for the dynamic vehicle allocation problem with uncertain demands," Transportation Research Part B: Methodological, Elsevier, vol. 21(3), pages 217-232, June.
    20. Iman Dayarian & Martin Savelsbergh, 2020. "Crowdshipping and Same‐day Delivery: Employing In‐store Customers to Deliver Online Orders," Production and Operations Management, Production and Operations Management Society, vol. 29(9), pages 2153-2174, September.
    21. Tsai, Mei-Ting & Saphores, Jean-Daniel & Regan, Amelia, 2011. "Valuation of freight transportation contracts under uncertainty," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 47(6), pages 920-932.
    22. 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.
    23. Kafle, Nabin & Zou, Bo & Lin, Jane, 2017. "Design and modeling of a crowdsource-enabled system for urban parcel relay and delivery," Transportation Research Part B: Methodological, Elsevier, vol. 99(C), pages 62-82.
    24. 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).
    25. 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.
    26. Wang, Yuan & Zhang, Dongxiang & Liu, Qing & Shen, Fumin & Lee, Loo Hay, 2016. "Towards enhancing the last-mile delivery: An effective crowd-tasking model with scalable solutions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 93(C), pages 279-293.
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    Cited by:

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    2. 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).
    3. Wang, Haibo & Alidaee, Bahram, 2023. "White-glove service delivery: A quantitative analysis," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 175(C).
    4. Ausseil, Rosemonde & Ulmer, Marlin W. & Pazour, Jennifer A., 2024. "Online acceptance probability approximation in peer-to-peer transportation," Omega, Elsevier, vol. 123(C).
    5. Alexander Wyrowski & Nils Boysen & Dirk Briskorn & Stefan Schwerdfeger, 2024. "Public transport crowdshipping: moving shipments among parcel lockers located at public transport stations," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 46(3), pages 873-907, September.
    6. Srinivas R. Chakravarthy & Alexander N. Dudin & Sergey A. Dudin & Olga S. Dudina, 2023. "Queueing System with Potential for Recruiting Secondary Servers," Mathematics, MDPI, vol. 11(3), pages 1-24, January.
    7. Marlin W. Ulmer & Alan Erera & Martin Savelsbergh, 2022. "Dynamic service area sizing in urban delivery," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 44(3), pages 763-793, September.
    8. Zehtabian, Shohre & Larsen, Christian & Wøhlk, Sanne, 2022. "Estimation of the arrival time of deliveries by occasional drivers in a crowd-shipping setting," European Journal of Operational Research, Elsevier, vol. 303(2), pages 616-632.

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