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Potential last-mile impacts of crowdshipping services: a simulation-based evaluation

Author

Listed:
  • Michele D. Simoni

    (University of Texas at Austin
    Center for Transportation and Logistics, Massachusetts Institute of Technology)

  • Edoardo Marcucci

    (University of Roma Tre)

  • Valerio Gatta

    (University of Roma Tre)

  • Christian G. Claudel

    (University of Texas at Austin)

Abstract

Crowdsourced delivery services (crowdshipping) represent a shipping alternative to traditional delivery systems, particularly suitable for e-commerce. Although some benefits in terms of reduced pollution and congestion could be obtained by replacing dedicated freight trips, the impacts of crowdshipping are unclear and depend on several factors such as the transport mode used, the match between supply and demand, length of detours, and possible induced demand. For example, private drivers could modify their existing routes or engage in new trips to pick up and drop off packages; similarly, public transport users could carry along packages on their trips and drop them off at lockers installed around the stations. In this paper, we analyze by means of a simulation-based approach the potential impacts of alternative implementation frameworks. In order to account more realistically for last-mile delivery operations, a hybrid dynamic traffic simulation is adopted such that the macroscopic features of traffic (triggering of congestion, queue spillbacks and interactions with traffic signals) are reproduced in combination with the microscopic features of delivery operations (delivery vehicles are tracked along their routes). The effects on traffic and emissions are investigated for the adoption of crowdshipping by carriers delivering parcels in the city center of Rome, Italy. Results show that not only is the mode employed by crowdshippers crucial for the sustainability of such a measure, but also operational aspects involving the length of detour, parking behavior, and daily traffic variations. Crowdsourced deliveries by car have generally higher negative impacts than corresponding deliveries by public transit. However, limiting the deviations of crowdshippers from the original trips, providing adequate parking options, and incentivizing off-peak deliveries, could significantly reduce crowdshipping externalities.

Suggested Citation

  • Michele D. Simoni & Edoardo Marcucci & Valerio Gatta & Christian G. Claudel, 2020. "Potential last-mile impacts of crowdshipping services: a simulation-based evaluation," Transportation, Springer, vol. 47(4), pages 1933-1954, August.
    • Handle: RePEc:kap:transp:v:47:y:2020:i:4:d:10.1007_s11116-019-10028-4
    DOI: 10.1007/s11116-019-10028-4
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    Cited by:

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    4. Boshuai Zhao & Kai Wang & Wenchao Wei & Roel Leus, 2024. "The Dial-a-Ride Problem with Limited Pickups per Trip," Papers 2408.07602, arXiv.org, revised Aug 2024.
    5. 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).
    6. Gleb V. Savin, 2021. "The smart city transport and logistics system: Theory, methodology and practice," Upravlenets, Ural State University of Economics, vol. 12(6), pages 67-86, October.
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    8. Veronika Harantová & Ambróz Hájnik & Alica Kalašová & Tomasz Figlus, 2022. "The Effect of the COVID-19 Pandemic on Traffic Flow Characteristics, Emissions Production and Fuel Consumption at a Selected Intersection in Slovakia," Energies, MDPI, vol. 15(6), pages 1-21, March.
    9. Giacomo Lozzi & Gabriele Iannaccone & Ila Maltese & Valerio Gatta & Edoardo Marcucci & Riccardo Lozzi, 2022. "On-Demand Logistics: Solutions, Barriers, and Enablers," Sustainability, MDPI, vol. 14(15), pages 1-21, August.
    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. Garola, Giovanni & Seghezzi, Arianna & Siragusa, Chiara & Mangiaracina, Riccardo, 2022. "Sustainability in urban logistics: A literature review," Chapters from the Proceedings of the Hamburg International Conference of Logistics (HICL), in: Kersten, Wolfgang & Jahn, Carlos & Blecker, Thorsten & Ringle, Christian M. (ed.), Changing Tides: The New Role of Resilience and Sustainability in Logistics and Supply Chain Management – Innovative Approaches for the Shift to a New , volume 33, pages 709-730, Hamburg University of Technology (TUHH), Institute of Business Logistics and General Management.
    12. Ranjbari, Andisheh & Diehl, Caleb & Dalla Chiara, Giacomo & Goodchild, Anne, 2023. "Do parcel lockers reduce delivery times? Evidence from the field," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 172(C).
    13. Mancini, Simona & Gansterer, Margaretha, 2022. "Bundle generation for last-mile delivery with occasional drivers," Omega, Elsevier, vol. 108(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. 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).
    16. Sören Lauenstein & Christoph Schank, 2022. "Design of a Sustainable Last Mile in Urban Logistics—A Systematic Literature Review," Sustainability, MDPI, vol. 14(9), pages 1-14, May.
    17. Reed, Sara & Campbell, Ann Melissa & Thomas, Barrett W., 2024. "Does parking matter? The impact of parking time on last-mile delivery optimization," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 181(C).
    18. Beckers, Joris & Cardenas, Ivan & Sanchez-Diaz, Ivan, 2022. "Managing household freight: The impact of online shopping on residential freight trips," Transport Policy, Elsevier, vol. 125(C), pages 299-311.
    19. Xiao, Haohan & Xu, Min & Wang, Shuaian, 2023. "A game-theoretic model for crowd-shipping operations with profit improvement strategies," International Journal of Production Economics, Elsevier, vol. 262(C).
    20. Akbar, Usman & Jain, Avi Anand & Bråthen, Svein, 2024. "Sustainability assessment of inter-urban crowdshipping - A case study approach," Research in Transportation Economics, Elsevier, vol. 103(C).
    21. 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).
    22. Iznoorhakmal bin Ibrahim & Siti Ayu Jalil & Siti Salwa Salleh, 2023. "A Conceptual Model for Sustainable Green Port Practices: A Case Study of Northport (Malaysia) Berhad," Information Management and Business Review, AMH International, vol. 15(3), pages 267-279.

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