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The integration of item-sharing and crowdshipping: Can collaborative consumption be pushed by delivering through the crowd?

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  • Behrend, Moritz
  • Meisel, Frank

Abstract

Item-sharing and crowdshipping are two concepts of the sharing economy. In item-sharing, members of a sharing community can temporarily rent items such as tools or leisure equipment from one another. In crowdshipping, private drivers offer to execute delivery jobs for other people on trips they would make anyway. Since the peer-to-peer exchange in item-sharing involves repeated, inefficient ‘last-mile’ transports of small shipments, we investigate here whether the integration of item-sharing and crowdshipping has the potential to facilitate collaborative consumption. To this end, the decision making for an integrated item-sharing and crowdshipping platform is modeled. This platform matches supplies, requests, and planned trips of the community members. We develop mathematical models and heuristics for maximizing the platform’s profit and the number of fulfilled requests. Our results quantify and confirm the substantial benefit of integrating item-sharing and crowdshipping.

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  • 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.
  • Handle: RePEc:eee:transb:v:111:y:2018:i:c:p:227-243
    DOI: 10.1016/j.trb.2018.02.017
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    1. 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.
    2. Michael Z. Spivey & Warren B. Powell, 2004. "The Dynamic Assignment Problem," Transportation Science, INFORMS, vol. 38(4), pages 399-419, November.
    3. Stiglic, Mitja & Agatz, Niels & Savelsbergh, Martin & Gradisar, Mirko, 2016. "Making dynamic ride-sharing work: The impact of driver and rider flexibility," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 91(C), pages 190-207.
    4. 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.
    5. 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.
    6. Fleura Bardhi & Giana M. Eckhardt, 2012. "Access-Based Consumption: The Case of Car Sharing," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 39(4), pages 881-898.
    7. Furuhata, Masabumi & Dessouky, Maged & Ordóñez, Fernando & Brunet, Marc-Etienne & Wang, Xiaoqing & Koenig, Sven, 2013. "Ridesharing: The state-of-the-art and future directions," Transportation Research Part B: Methodological, Elsevier, vol. 57(C), pages 28-46.
    8. Jean-François Cordeau & Gilbert Laporte, 2007. "The dial-a-ride problem: models and algorithms," Annals of Operations Research, Springer, vol. 153(1), pages 29-46, September.
    9. Agatz, Niels & Erera, Alan & Savelsbergh, Martin & Wang, Xing, 2012. "Optimization for dynamic ride-sharing: A review," European Journal of Operational Research, Elsevier, vol. 223(2), pages 295-303.
    10. Lee, Alan & Savelsbergh, Martin, 2015. "Dynamic ridesharing: Is there a role for dedicated drivers?," Transportation Research Part B: Methodological, Elsevier, vol. 81(P2), pages 483-497.
    11. 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.
    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. 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.
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    Cited by:

    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. Shang, Dawei & Wu, Weiwei, 2022. "Does green morality lead to collaborative consumption behavior toward online collaborative redistribution platforms? Evidence from emerging markets shows the asymmetric roles of pro-environmental self," Journal of Retailing and Consumer Services, Elsevier, vol. 68(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. Valerio Gatta & Edoardo Marcucci & Marialisa Nigro & Sergio Maria Patella & Simone Serafini, 2018. "Public Transport-Based Crowdshipping for Sustainable City Logistics: Assessing Economic and Environmental Impacts," Sustainability, MDPI, vol. 11(1), pages 1-14, December.
    5. 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.
    6. Agnieszka Szmelter-Jarosz & Jagienka Rześny-Cieplińska, 2019. "Priorities of Urban Transport System Stakeholders According to Crowd Logistics Solutions in City Areas. A Sustainability Perspective," Sustainability, MDPI, vol. 12(1), pages 1-19, December.
    7. 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.
    8. Marlin Ulmer & Martin Savelsbergh, 2020. "Workforce Scheduling in the Era of Crowdsourced Delivery," Transportation Science, INFORMS, vol. 54(4), pages 1113-1133, July.
    9. Boysen, Nils & Emde, Simon & Schwerdfeger, Stefan, 2022. "Crowdshipping by employees of distribution centers: Optimization approaches for matching supply and demand," European Journal of Operational Research, Elsevier, vol. 296(2), pages 539-556.
    10. 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).
    11. John Olsson & Daniel Hellström & Henrik Pålsson, 2019. "Framework of Last Mile Logistics Research: A Systematic Review of the Literature," Sustainability, MDPI, vol. 11(24), pages 1-25, December.
    12. Behrend, Moritz & Meisel, Frank & Fagerholt, Kjetil & Andersson, Henrik, 2021. "A multi-period analysis of the integrated item-sharing and crowdshipping problem," European Journal of Operational Research, Elsevier, vol. 292(2), pages 483-499.
    13. Wang, Li & Xu, Min & Qin, Hu, 2023. "Joint optimization of parcel allocation and crowd routing for crowdsourced last-mile delivery," Transportation Research Part B: Methodological, Elsevier, vol. 171(C), pages 111-135.
    14. Mancini, Simona & Gansterer, Margaretha, 2022. "Bundle generation for last-mile delivery with occasional drivers," Omega, Elsevier, vol. 108(C).
    15. Bathke, Henrik & Hartmann, Evi, 2021. "Accepting a crowdsourced delivery - A choice-based conjoint analysis," Chapters from the Proceedings of the Hamburg International Conference of Logistics (HICL), in: Jahn, Carlos & Kersten, Wolfgang & Ringle, Christian M. (ed.), Adapting to the Future: Maritime and City Logistics in the Context of Digitalization and Sustainability. Proceedings of the Hamburg International Conf, volume 32, pages 65-95, Hamburg University of Technology (TUHH), Institute of Business Logistics and General Management.

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