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OR/MS Methods for Structural Dynamics in Supply Chain Risk Management

In: Structural Dynamics and Resilience in Supply Chain Risk Management

Author

Listed:
  • Dmitry Ivanov

    (Berlin School of Economics and Law)

Abstract

In this Chapter, we analyze state-of-the-art research streams on managing operational and disruption risks in supply chain design and planning. It structures and classifies existing research and practical applications of different quantitative methods subject to recently derived empirical frameworks. We identify gaps in current research and delineate future research avenues. The results of this literature analysis are twofold. Supply chain managers can observe which quantitative tools are available for different applications. On the other hand, from the point of view of operational research, limitations and future research needs can be identified for decision-supporting methods in supply chain risk management domains.

Suggested Citation

  • Dmitry Ivanov, 2018. "OR/MS Methods for Structural Dynamics in Supply Chain Risk Management," International Series in Operations Research & Management Science, in: Structural Dynamics and Resilience in Supply Chain Risk Management, chapter 0, pages 115-159, Springer.
    • Handle: RePEc:spr:isochp:978-3-319-69305-7_5
    DOI: 10.1007/978-3-319-69305-7_5
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    Cited by:

    1. Dmitry Anokhin & Payman Dehghanian & Miguel A. Lejeune & Jinshun Su, 2021. "Mobility‐As‐A‐Service for Resilience Delivery in Power Distribution Systems," Production and Operations Management, Production and Operations Management Society, vol. 30(8), pages 2492-2521, August.
    2. Rozhkov, Maxim & Ivanov, Dmitry & Blackhurst, Jennifer & Nair, Anand, 2022. "Adapting supply chain operations in anticipation of and during the COVID-19 pandemic," Omega, Elsevier, vol. 110(C).
    3. Aldrighetti, Riccardo & Battini, Daria & Ivanov, Dmitry & Zennaro, Ilenia, 2021. "Costs of resilience and disruptions in supply chain network design models: A review and future research directions," International Journal of Production Economics, Elsevier, vol. 235(C).

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