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A crowdsourcing solution to collect e-commerce reverse flows in metropolitan areas

Author

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  • Shenle Pan

    (CGS i3 - Centre de Gestion Scientifique i3 - Mines Paris - PSL (École nationale supérieure des mines de Paris) - PSL - Université Paris Sciences et Lettres - I3 - Institut interdisciplinaire de l’innovation - CNRS - Centre National de la Recherche Scientifique)

  • Chao Chen

    (Chongqing University [Chongqing])

  • Ray Y. Zhong

    (HKU - The University of Hong Kong)

Abstract

On the forward side, the growth of E-commerce in recent years substantially generates additional packets and parcels for distribution; meanwhile, on the reverse side, collecting returned goods is also becoming a preoccupation of sustainability, especially in metropolitan areas. Inspired by the concepts of crowdsourcing and the Physical Internet, in this paper, we propose an innovative solution that seeks to exploit the extra loading capacity and constant mobility from taxis in metropolitan areas to collect and delivery the e-commerce returns from final consumption points back to retailers. We assume that, on one hand, e-retailers will have incentive to outsource this task; on the other hand, taxi drivers will also be motivated because they can earn a little extra money from the shipments that they have fulfilled. As an alternative to the traditional ways, the solution proposed is more sustainable because it could simultaneously reduce the economical (pickup and transportation costs), environmental (CO 2 emissions, energy consumption, traffic congestion in city), and social (the wastes of the impulse buying, reduced incitation of online shopping) impacts resulted from reverse flows management in metropolitan areas. As the first qualitative and quantitative study of the concept, this paper uses open databases of taxi GPS traces and locations of shops in a large city in China for investigating the feasibility and viability of the solution proposed. Two collection strategies are proposed and evaluated by an optimization-based simulation model. The results generate several useful insights to the implementability and managerial issues of the concept.

Suggested Citation

  • Shenle Pan & Chao Chen & Ray Y. Zhong, 2015. "A crowdsourcing solution to collect e-commerce reverse flows in metropolitan areas," Post-Print hal-01148227, HAL.
  • Handle: RePEc:hal:journl:hal-01148227
    Note: View the original document on HAL open archive server: https://minesparis-psl.hal.science/hal-01148227v1
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    File URL: https://minesparis-psl.hal.science/hal-01148227v1/document
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    References listed on IDEAS

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    1. Fleischmann, Moritz & Bloemhof-Ruwaard, Jacqueline M. & Dekker, Rommert & van der Laan, Erwin & van Nunen, Jo A. E. E. & Van Wassenhove, Luk N., 1997. "Quantitative models for reverse logistics: A review," European Journal of Operational Research, Elsevier, vol. 103(1), pages 1-17, November.
    2. Nathalie Bostel & Pierre Dejax & Zhiqiang Lu, 2005. "The Design, Planning, and Optimization of Reverse Logistics Networks," Springer Books, in: André Langevin & Diane Riopel (ed.), Logistics Systems: Design and Optimization, chapter 0, pages 171-212, Springer.
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    Cited by:

    1. Vladimir Todorovic & Marinko Maslaric & Sanja Bojic & Maja Jokic & Dejan Mircetic & Svetlana Nikolicic, 2018. "Solutions for More Sustainable Distribution in the Short Food Supply Chains," Sustainability, MDPI, vol. 10(10), pages 1-27, September.
    2. 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).
    3. 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).
    4. Pourrahmani, Elham & Jaller, Miguel, 2021. "Crowdshipping in last mile deliveries: Operational challenges and research opportunities," Socio-Economic Planning Sciences, Elsevier, vol. 78(C).
    5. Siragusa, Chiara & Mangiaracina, Riccardo & Tumino, Angela, 2020. "Environmental sustainability in B2C e-commerce: The impact of multiitem shopping," Chapters from the Proceedings of the Hamburg International Conference of Logistics (HICL), in: Jahn, Carlos & Kersten, Wolfgang & Ringle, Christian M. (ed.), Data Science in Maritime and City Logistics: Data-driven Solutions for Logistics and Sustainability. Proceedings of the Hamburg International Conferen, volume 30, pages 71-95, Hamburg University of Technology (TUHH), Institute of Business Logistics and General Management.
    6. Mashalah, Heider Al & Hassini, Elkafi & Gunasekaran, Angappa & Bhatt (Mishra), Deepa, 2022. "The impact of digital transformation on supply chains through e-commerce: Literature review and a conceptual framework," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 165(C).

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    Keywords

    E-commerce reverse logistics; Crowdsourcing; Physical Internet; Collection problem;
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