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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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    as
    1. Baindur, Deepak & Macário, Rosário M., 2013. "Mumbai lunch box delivery system: A transferable benchmark in urban logistics?," Research in Transportation Economics, Elsevier, vol. 38(1), pages 110-121.
    2. Giacomo Lozzi & Valerio Gatta & Edoardo Marcucci, 2018. "European urban freight transport policies and research funding: are priorities and H2020 calls aligned?," REGION, European Regional Science Association, vol. 5, pages 53-71.
    3. Wei Qi & Lefei Li & Sheng Liu & Zuo-Jun Max Shen, 2018. "Shared Mobility for Last-Mile Delivery: Design, Operational Prescriptions, and Environmental Impact," Manufacturing & Service Operations Management, INFORMS, vol. 20(4), pages 737-751, October.
    4. Wang, Yi & Szeto, W.Y. & Han, Ke & Friesz, Terry L., 2018. "Dynamic traffic assignment: A review of the methodological advances for environmentally sustainable road transportation applications," Transportation Research Part B: Methodological, Elsevier, vol. 111(C), pages 370-394.
    5. Paul I. Richards, 1956. "Shock Waves on the Highway," Operations Research, INFORMS, vol. 4(1), pages 42-51, February.
    6. 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.
    7. Papageorgiou, Markos, 1998. "Some remarks on macroscopic traffic flow modelling," Transportation Research Part A: Policy and Practice, Elsevier, vol. 32(5), pages 323-329, September.
    8. Newell, G. F., 1993. "A simplified theory of kinematic waves in highway traffic, part III: Multi-destination flows," Transportation Research Part B: Methodological, Elsevier, vol. 27(4), pages 305-313, August.
    9. Newell, G. F., 1993. "A simplified theory of kinematic waves in highway traffic, part II: Queueing at freeway bottlenecks," Transportation Research Part B: Methodological, Elsevier, vol. 27(4), pages 289-303, August.
    10. G. Dantzig & R. Fulkerson & S. Johnson, 1954. "Solution of a Large-Scale Traveling-Salesman Problem," Operations Research, INFORMS, vol. 2(4), pages 393-410, November.
    11. Marcucci, Edoardo & Gatta, Valerio, 2017. "Investigating the potential for off-hour deliveries in the city of Rome: Retailers’ perceptions and stated reactions," Transportation Research Part A: Policy and Practice, Elsevier, vol. 102(C), pages 142-156.
    12. 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.
    13. Amer, Ahmed & Chow, Joseph Y.J., 2017. "A downtown on-street parking model with urban truck delivery behavior," Transportation Research Part A: Policy and Practice, Elsevier, vol. 102(C), pages 51-67.
    14. Newell, G. F., 1993. "A simplified theory of kinematic waves in highway traffic, part I: General theory," Transportation Research Part B: Methodological, Elsevier, vol. 27(4), pages 281-287, August.
    15. 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.
    16. 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.
    17. Marcucci, Edoardo & Le Pira, Michela & Gatta, Valerio & Inturri, Giuseppe & Ignaccolo, Matteo & Pluchino, Alessandro, 2017. "Simulating participatory urban freight transport policy-making: Accounting for heterogeneous stakeholders’ preferences and interaction effects," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 103(C), pages 69-86.
    18. M. W. P. Savelsbergh & M. Sol, 1995. "The General Pickup and Delivery Problem," Transportation Science, INFORMS, vol. 29(1), pages 17-29, February.
    Full references (including those not matched with items on IDEAS)

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    Cited by:

    1. 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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    3. 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).
    4. 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).
    5. 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.
    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. Marisdea Castiglione & Antonio Comi & Rosita De Vincentis & Andreea Dumitru & Marialisa Nigro, 2022. "Delivering in Urban Areas: A Probabilistic-Behavioral Approach for Forecasting the Use of Electric Micromobility," Sustainability, MDPI, vol. 14(15), pages 1-13, July.
    8. Tapia, Rodrigo J. & Kourounioti, Ioanna & Thoen, Sebastian & de Bok, Michiel & Tavasszy, Lori, 2023. "A disaggregate model of passenger-freight matching in crowdshipping services," Transportation Research Part A: Policy and Practice, Elsevier, vol. 169(C).
    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. 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).
    12. 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).
    13. Jose Alejandro Cano & Abraham Londoño-Pineda & Carolina Rodas, 2022. "Sustainable Logistics for E-Commerce: A Literature Review and Bibliometric Analysis," Sustainability, MDPI, vol. 14(19), pages 1-24, September.
    14. 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.
    15. 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).
    16. 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.
    17. 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.
    18. 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).
    19. Sergio Maria Patella & Gianluca Grazieschi & Valerio Gatta & Edoardo Marcucci & Stefano Carrese, 2020. "The Adoption of Green Vehicles in Last Mile Logistics: A Systematic Review," Sustainability, MDPI, vol. 13(1), pages 1-29, December.
    20. 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.
    21. Mancini, Simona & Gansterer, Margaretha, 2022. "Bundle generation for last-mile delivery with occasional drivers," Omega, Elsevier, vol. 108(C).
    22. 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.

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