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Entropy-based model for the ripple effect: managing environmental risks in supply chains

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  • Eugene Levner
  • Alexander Ptuskin

Abstract

Due to increasing diversity and growing size of modern industrial supply chains, today problems of identification, assessment and mitigation of disruption risks become challenging goals of the supply chain risk management. In this paper, we focus on environmental (ecological) risks in supply chains which represent threats of adverse effects on living organisms, facilities and environment by effluents, emissions, wastes, resource depletion, etc. arising due to supply chain’s activities. Harmful environmental disruptions may ripple through the supply chain components like a wave. The paper presents the entropy-based optimisation model for reducing the supply chain model size and assessing the economic loss caused by the environmental risks subject to the ripple effect. A main advantage of the suggested entropy-based approach is that it permits to essentially simplify the hierarchical tree-like model of the supply chain, at the same time retaining the basic knowledge about main risk sources.

Suggested Citation

  • Eugene Levner & Alexander Ptuskin, 2018. "Entropy-based model for the ripple effect: managing environmental risks in supply chains," International Journal of Production Research, Taylor & Francis Journals, vol. 56(7), pages 2539-2551, April.
    • Handle: RePEc:taf:tprsxx:v:56:y:2018:i:7:p:2539-2551
    DOI: 10.1080/00207543.2017.1374575
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    Cited by:

    1. Vimal K.E.K & Simon Peter Nadeem & Mahadharsan Ravichandran & Manavalan Ethirajan & Jayakrishna Kandasamy, 2022. "Resilience strategies to recover from the cascading ripple effect in a copper supply chain through project management," Operations Management Research, Springer, vol. 15(1), pages 440-460, June.
    2. Dmitry Ivanov, 2022. "Viable supply chain model: integrating agility, resilience and sustainability perspectives—lessons from and thinking beyond the COVID-19 pandemic," Annals of Operations Research, Springer, vol. 319(1), pages 1411-1431, December.
    3. Ivanov, Dmitry & Dolgui, Alexandre, 2021. "OR-methods for coping with the ripple effect in supply chains during COVID-19 pandemic: Managerial insights and research implications," International Journal of Production Economics, Elsevier, vol. 232(C).
    4. Mohamed El Abdellaoui & Gilles Pache, 2019. "Effects of disruptive events within the supply chain on perceived logistics performance," Economics Bulletin, AccessEcon, vol. 39(1), pages 41-54.
    5. Nishat Alam Choudhary & Shalabh Singh & Tobias Schoenherr & M. Ramkumar, 2023. "Risk assessment in supply chains: a state-of-the-art review of methodologies and their applications," Annals of Operations Research, Springer, vol. 322(2), pages 565-607, March.
    6. Ming Zhang & Jianjun Zhu & Ponnambalam Kumaraswamy & Hehua Wang, 2019. "Evolutionary Game Analysis of the Effects of Problem Size and the Problem Proposing Mechanism on the Problem Processing Mechanism in a New Main Manufacturer–Supplier Collaborative System," Mathematics, MDPI, vol. 7(7), pages 1-19, July.
    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. Dmitry Ivanov & Boris Sokolov, 2019. "Simultaneous structural–operational control of supply chain dynamics and resilience," Annals of Operations Research, Springer, vol. 283(1), pages 1191-1210, December.
    9. Liu, Ming & Liu, Zhongzheng & Chu, Feng & Dolgui, Alexandre & Chu, Chengbin & Zheng, Feifeng, 2022. "An optimization approach for multi-echelon supply chain viability with disruption risk minimization," Omega, Elsevier, vol. 112(C).
    10. Alexander Pavlov & Dmitry Ivanov & Frank Werner & Alexandre Dolgui & Boris Sokolov, 2022. "Integrated detection of disruption scenarios, the ripple effect dispersal and recovery paths in supply chains," Annals of Operations Research, Springer, vol. 319(1), pages 609-631, December.
    11. Chih-Hung Hsu & Ru-Yue Yu & An-Yuan Chang & Wan-Ling Liu & An-Ching Sun, 2022. "Applying Integrated QFD-MCDM Approach to Strengthen Supply Chain Agility for Mitigating Sustainable Risks," Mathematics, MDPI, vol. 10(4), pages 1-41, February.
    12. Chih-Hung Hsu & Xu He & Ting-Yi Zhang & An-Yuan Chang & Wan-Ling Liu & Zhi-Qiang Lin, 2022. "Enhancing Supply Chain Agility with Industry 4.0 Enablers to Mitigate Ripple Effects Based on Integrated QFD-MCDM: An Empirical Study of New Energy Materials Manufacturers," Mathematics, MDPI, vol. 10(10), pages 1-35, May.

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