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Mitigating supply chain disruptions through interconnected logistics services in the Physical Internet

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  • Yanyan Yang
  • Shenle Pan
  • Eric Ballot

Abstract

This paper investigates the resilience of inventory models using interconnected logistics services in the Physical Internet (PI). With traditional supply chain network design, companies define and optimise their own logistics networks, resulting in current logistics systems being a set of independent heterogeneous logistics networks. The concept of PI aims to integrate independent logistics networks into a global, open, interconnected system. Prior research has shown that new inventory models enabled by and applied to PI could help reduce inventory levels thanks to its high flexibility. Continuing along these lines, this paper examines how inventory models applying PI deal with disruptions at hubs and plants. To attain this, a single product inventory problem with uncertain demands and stochastic supply disruptions is studied. A simulation-based optimisation model is proposed to determine inventory control decisions. The results suggest that the PI inventory model, with greater agility and flexibility, outperforms the current classic inventory models in terms of resilience. Moreover, the difference in performance increases when the product value, penalty costs and disruption frequency increases. This paper indicates a novel approach to build a resilient supply network.

Suggested Citation

  • Yanyan Yang & Shenle Pan & Eric Ballot, 2017. "Mitigating supply chain disruptions through interconnected logistics services in the Physical Internet," International Journal of Production Research, Taylor & Francis Journals, vol. 55(14), pages 3970-3983, July.
  • Handle: RePEc:taf:tprsxx:v:55:y:2017:i:14:p:3970-3983
    DOI: 10.1080/00207543.2016.1223379
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    Cited by:

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    2. Nguyen, Tiep & Duong, Quang Huy & Nguyen, Truong Van & Zhu, You & Zhou, Li, 2022. "Knowledge mapping of digital twin and physical internet in Supply Chain Management: A systematic literature review," International Journal of Production Economics, Elsevier, vol. 244(C).
    3. Shoufeng Ji & Pengyun Zhao & Tingting Ji, 2023. "A Hybrid Optimization Method for Sustainable and Flexible Design of Supply–Production–Distribution Network in the Physical Internet," Sustainability, MDPI, vol. 15(7), pages 1-34, April.
    4. Maryam Philsoophian & Peyman Akhavan & Morteza Abbasi, 2021. "Strategic Alliance for Resilience in Supply Chain: A Bibliometric Analysis," Sustainability, MDPI, vol. 13(22), pages 1-25, November.
    5. Kim, Nayeon & Montreuil, Benoit & Klibi, Walid & Zied Babai, M., 2023. "Network inventory deployment for responsive fulfillment," International Journal of Production Economics, Elsevier, vol. 255(C).
    6. Van der Heide, G. & Buijs, P. & Roodbergen, K.J. & Vis, I.F.A., 2018. "Dynamic shipments of inventories in shared warehouse and transportation networks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 118(C), pages 240-257.
    7. K. Katsaliaki & P. Galetsi & S. Kumar, 2022. "Supply chain disruptions and resilience: a major review and future research agenda," Annals of Operations Research, Springer, vol. 319(1), pages 965-1002, December.
    8. Leung, Eric K.H. & Lee, Carmen Kar Hang & Ouyang, Zhiyuan, 2022. "From traditional warehouses to Physical Internet hubs: A digital twin-based inbound synchronization framework for PI-order management," International Journal of Production Economics, Elsevier, vol. 244(C).
    9. Maureen S. Golan & Laura H. Jernegan & Igor Linkov, 2020. "Trends and applications of resilience analytics in supply chain modeling: systematic literature review in the context of the COVID-19 pandemic," Environment Systems and Decisions, Springer, vol. 40(2), pages 222-243, June.
    10. Pan, Fei & Pan, Shenle & Zhou, Wei & Fan, Tijun, 2022. "Perishable product bundling with logistics uncertainty: Solution based on physical internet," International Journal of Production Economics, Elsevier, vol. 244(C).
    11. Guangsheng Zhang & Xiao Wang & Yu Zhang & Jiayun Kang, 2022. "Research on the Emission Reduction Decision of Cost-Sharing Logistics Service Supply Chain in the O2O Model," Sustainability, MDPI, vol. 14(20), pages 1-21, October.

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