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Resilience by teaming in supply network formation and re-configuration

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  • Reyes Levalle, Rodrigo
  • Nof, Shimon Y.

Abstract

In an increasingly interconnected world, physical, service, and digital supply networks are becoming progressively more complex, dynamic, and interdependent. Moreover, sustainability concerns push for higher efficiency in the use of resources, reducing protective redundancies and making supply networks more susceptible to disruptions. Supply network resilience is an emerging concept related to the inherent ability of a network to tolerate and overcome disruptions, a central capacity to achieve long term-sustainable operations. However, current understanding of the impact of network formation and re-configuration mechanisms on resilience is at its early stages.

Suggested Citation

  • Reyes Levalle, Rodrigo & Nof, Shimon Y., 2015. "Resilience by teaming in supply network formation and re-configuration," International Journal of Production Economics, Elsevier, vol. 160(C), pages 80-93.
    • Handle: RePEc:eee:proeco:v:160:y:2015:i:c:p:80-93
    DOI: 10.1016/j.ijpe.2014.09.036
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    References listed on IDEAS

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    Cited by:

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    2. Raquel Sanchis & Raúl Poler, 2019. "Enterprise Resilience Assessment—A Quantitative Approach," Sustainability, MDPI, vol. 11(16), pages 1-13, August.
    3. Zahiri, Behzad & Zhuang, Jun & Mohammadi, Mehrdad, 2017. "Toward an integrated sustainable-resilient supply chain: A pharmaceutical case study," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 103(C), pages 109-142.
    4. Zavitsas, Konstantinos & Zis, Thalis & Bell, Michael G.H., 2018. "The impact of flexible environmental policy on maritime supply chain resilience," Transport Policy, Elsevier, vol. 72(C), pages 116-128.
    5. Dixit, Vijaya & Verma, Priyanka & Tiwari, Manoj Kumar, 2020. "Assessment of pre and post-disaster supply chain resilience based on network structural parameters with CVaR as a risk measure," International Journal of Production Economics, Elsevier, vol. 227(C).
    6. Marzena Kramarz & Mariusz Kmiecik, 2022. "Quality of Forecasts as the Factor Determining the Coordination of Logistics Processes by Logistic Operator," Sustainability, MDPI, vol. 14(2), pages 1-23, January.
    7. Nguyen, Win P.V. & Nof, Shimon Y., 2020. "Strategic lines of collaboration in response to disruption propagation (CRDP) through cyber-physical systems," International Journal of Production Economics, Elsevier, vol. 230(C).
    8. Wang, Jiepeng & Zhou, Hong & Sun, Xinlei & Yuan, Yufei, 2023. "A novel supply chain network evolving model under random and targeted disruptions," Chaos, Solitons & Fractals, Elsevier, vol. 170(C).
    9. Jiakuan Chen & Haoyu Wen, 2023. "The application of complex network theory for resilience improvement of knowledge-intensive supply chains," Operations Management Research, Springer, vol. 16(3), pages 1140-1161, September.
    10. Hosseini, Seyedmohsen & Ivanov, Dmitry & Dolgui, Alexandre, 2019. "Review of quantitative methods for supply chain resilience analysis," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 125(C), pages 285-307.
    11. Yang, Qihui & Scoglio, Caterina M. & Gruenbacher, Don M., 2021. "Robustness of supply chain networks against underload cascading failures," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 563(C).

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