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Assessment of pre and post-disaster supply chain resilience based on network structural parameters with CVaR as a risk measure

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  • Dixit, Vijaya
  • Verma, Priyanka
  • Tiwari, Manoj Kumar

Abstract

The present study assesses supply chain resilience based on network structural parameters. Resilience is computed as a composite effect of density, centrality, connectivity, and network size of the network. A simulation-based approach is adopted, wherein networks of 23 firms operating in India are subjected to risk combinations of five mutually inclusive independent scenarios of probability levels and five mutually exclusive and exhaustive impact levels. The worst-case performance of the supply chain network when subjected to high impact and low probability risks is captured using conditional-value at risk (CVaR). Results reveal that the firm which has the lowest density and centrality and the highest connectivity and network size, exhibits the highest resilience. Whereas, the firm which has the highest density and high centrality due to an aggregation node exhibits the lowest resilience.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:proeco:v:227:y:2020:i:c:s0925527320300517
    DOI: 10.1016/j.ijpe.2020.107655
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    as
    1. Ivanov, Dmitry & Sokolov, Boris, 2013. "Control and system-theoretic identification of the supply chain dynamics domain for planning, analysis and adaptation of performance under uncertainty," European Journal of Operational Research, Elsevier, vol. 224(2), pages 313-323.
    2. Alexandre Dolgui & Dmitry Ivanov & Boris Sokolov, 2018. "Ripple effect in the supply chain: an analysis and recent literature," International Journal of Production Research, Taylor & Francis Journals, vol. 56(1-2), pages 414-430, January.
    3. Seyed Mohammad Khalili & Fariborz Jolai & Seyed Ali Torabi, 2017. "Integrated production–distribution planning in two-echelon systems: a resilience view," International Journal of Production Research, Taylor & Francis Journals, vol. 55(4), pages 1040-1064, February.
    4. Rudberg, Martin & Olhager, Jan, 2003. "Manufacturing networks and supply chains: an operations strategy perspective," Omega, Elsevier, vol. 31(1), pages 29-39, February.
    5. Dmitry Ivanov, 2018. "Supply Chain Management and Structural Dynamics Control," International Series in Operations Research & Management Science, in: Structural Dynamics and Resilience in Supply Chain Risk Management, chapter 0, pages 1-18, Springer.
    6. 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.
    7. Salehi Sadghiani, N. & Torabi, S.A. & Sahebjamnia, N., 2015. "Retail supply chain network design under operational and disruption risks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 75(C), pages 95-114.
    8. Belarmino Adenso-Díaz & Julio Mar-Ortiz & Sebastián Lozano, 2018. "Assessing supply chain robustness to links failure," International Journal of Production Research, Taylor & Francis Journals, vol. 56(15), pages 5104-5117, August.
    9. Michael Lim & Mark S. Daskin & Achal Bassamboo & Sunil Chopra, 2010. "A facility reliability problem: Formulation, properties, and algorithm," Naval Research Logistics (NRL), John Wiley & Sons, vol. 57(1), pages 58-70, February.
    10. 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.
    11. Sawik, Tadeusz, 2013. "Selection of resilient supply portfolio under disruption risks," Omega, Elsevier, vol. 41(2), pages 259-269.
    12. Kevin P. Scheibe & Jennifer Blackhurst, 2018. "Supply chain disruption propagation: a systemic risk and normal accident theory perspective," International Journal of Production Research, Taylor & Francis Journals, vol. 56(1-2), pages 43-59, January.
    13. Lichun Chen & Elise Miller-Hooks, 2012. "Resilience: An Indicator of Recovery Capability in Intermodal Freight Transport," Transportation Science, INFORMS, vol. 46(1), pages 109-123, February.
    14. Chowdhury, Md. Maruf Hossan & Quaddus, Mohammed A., 2015. "A multiple objective optimization based QFD approach for efficient resilient strategies to mitigate supply chain vulnerabilities: The case of garment industry of Bangladesh☆,☆☆☆This manuscript was pro," Omega, Elsevier, vol. 57(PA), pages 5-21.
    15. Huang, Dashan & Zhu, Shushang & Fabozzi, Frank J. & Fukushima, Masao, 2010. "Portfolio selection under distributional uncertainty: A relative robust CVaR approach," European Journal of Operational Research, Elsevier, vol. 203(1), pages 185-194, May.
    16. Angappa Gunasekaran & Nachiappan Subramanian & Shams Rahman, 2015. "Supply chain resilience: role of complexities and strategies," International Journal of Production Research, Taylor & Francis Journals, vol. 53(22), pages 6809-6819, November.
    17. Boris Sokolov & Dmitry Ivanov & Alexandre Dolgui & Alexander Pavlov, 2016. "Structural quantification of the ripple effect in the supply chain," International Journal of Production Research, Taylor & Francis Journals, vol. 54(1), pages 152-169, January.
    18. Brusset, Xavier & Teller, Christoph, 2017. "Supply chain capabilities, risks, and resilience," International Journal of Production Economics, Elsevier, vol. 184(C), pages 59-68.
    19. John R. Macdonald & Christopher W. Zobel & Steven A. Melnyk & Stanley E. Griffis, 2018. "Supply chain risk and resilience: theory building through structured experiments and simulation," International Journal of Production Research, Taylor & Francis Journals, vol. 56(12), pages 4337-4355, June.
    20. Benjamin R. Tukamuhabwa & Mark Stevenson & Jerry Busby & Marta Zorzini, 2015. "Supply chain resilience: definition, review and theoretical foundations for further study," International Journal of Production Research, Taylor & Francis Journals, vol. 53(18), pages 5592-5623, September.
    21. Emma Brandon-Jones & Brian Squire & Yvonne G.T. Van Rossenberg, 2015. "The impact of supply base complexity on disruptions and performance: the moderating effects of slack and visibility," International Journal of Production Research, Taylor & Francis Journals, vol. 53(22), pages 6903-6918, November.
    22. Kamalahmadi, Masoud & Parast, Mahour Mellat, 2016. "A review of the literature on the principles of enterprise and supply chain resilience: Major findings and directions for future research," International Journal of Production Economics, Elsevier, vol. 171(P1), pages 116-133.
    23. Jihee Han & KwangSup Shin, 2016. "Evaluation mechanism for structural robustness of supply chain considering disruption propagation," International Journal of Production Research, Taylor & Francis Journals, vol. 54(1), pages 135-151, January.
    24. Ritesh Ojha & Abhijeet Ghadge & Manoj Kumar Tiwari & Umit S. Bititci, 2018. "Bayesian network modelling for supply chain risk propagation," International Journal of Production Research, Taylor & Francis Journals, vol. 56(17), pages 5795-5819, September.
    25. Yi-Kuei Lin & Cheng-Fu Huang & Yi-Chieh Liao & Chih-Ching Yeh, 2017. "System reliability for a multistate intermodal logistics network with time windows," International Journal of Production Research, Taylor & Francis Journals, vol. 55(7), pages 1957-1969, April.
    26. Cardoso, Sónia R. & Paula Barbosa-Póvoa, Ana & Relvas, Susana & Novais, Augusto Q., 2015. "Resilience metrics in the assessment of complex supply-chains performance operating under demand uncertainty," Omega, Elsevier, vol. 56(C), pages 53-73.
    27. Nader Azad & Georgios Saharidis & Hamid Davoudpour & Hooman Malekly & Seyed Yektamaram, 2013. "Strategies for protecting supply chain networks against facility and transportation disruptions: an improved Benders decomposition approach," Annals of Operations Research, Springer, vol. 210(1), pages 125-163, November.
    28. Snoeck, André & Udenio, Maximiliano & Fransoo, Jan C., 2019. "A stochastic program to evaluate disruption mitigation investments in the supply chain," European Journal of Operational Research, Elsevier, vol. 274(2), pages 516-530.
    29. Alexander, S. & Coleman, T.F. & Li, Y., 2006. "Minimizing CVaR and VaR for a portfolio of derivatives," Journal of Banking & Finance, Elsevier, vol. 30(2), pages 583-605, February.
    30. Dias, Alexandra, 2016. "The economic value of controlling for large losses in portfolio selection," Journal of Banking & Finance, Elsevier, vol. 72(S), pages 81-91.
    31. Rockafellar, R. Tyrrell & Uryasev, Stan & Zabarankin, Michael, 2006. "Master funds in portfolio analysis with general deviation measures," Journal of Banking & Finance, Elsevier, vol. 30(2), pages 743-778, February.
    32. Dmitry Ivanov, 2017. "Simulation-based single vs. dual sourcing analysis in the supply chain with consideration of capacity disruptions, big data and demand patterns," International Journal of Integrated Supply Management, Inderscience Enterprises Ltd, vol. 11(1), pages 24-43.
    33. Dmitry Ivanov, 2018. "Structural Dynamics and Resilience in Supply Chain Risk Management," International Series in Operations Research and Management Science, Springer, number 978-3-319-69305-7, January.
    34. Rockafellar, R. Tyrrell & Uryasev, Stanislav, 2002. "Conditional value-at-risk for general loss distributions," Journal of Banking & Finance, Elsevier, vol. 26(7), pages 1443-1471, July.
    35. Kelle, Peter & Schneider, Helmut & Yi, Huizhi, 2014. "Decision alternatives between expected cost minimization and worst case scenario in emergency supply – Second revision," International Journal of Production Economics, Elsevier, vol. 157(C), pages 250-260.
    36. Chowdhury, Md Maruf H. & Quaddus, Mohammed, 2017. "Supply chain resilience: Conceptualization and scale development using dynamic capability theory," International Journal of Production Economics, Elsevier, vol. 188(C), pages 185-204.
    37. Sarah Yini Gao & David Simchi-Levi & Chung-Piaw Teo & Zhenzhen Yan, 2019. "Disruption Risk Mitigation in Supply Chains: The Risk Exposure Index Revisited," Operations Research, INFORMS, vol. 67(3), pages 831-852, May.
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