Abstract
Supply chain risk management embroils quite a lot of situations of managerial decision-making under uncertainties. As contemporary supply chains are intricate networks exposed to ample vulnerabilities, a resilient supply chain with inbuilt capabilities for responding to unanticipated events can assume significance. This paper proposes a decision support model for managers for knowing, measuring and improving the level of resilience in manufacturing supply chains. A novel computational methodology involving the incidence analysis and grey theory is proposed in this study. Using the methodology of advanced analysis of grey incidences, the level of resilience of supply chains can be measured. Various strategies and attributes imparting resilience, particularly relevant to the manufacturing industry are analyzed in this research. A framework considering five strategies and twenty-three attributes contributing to supply chain resilience is also constructed. And a case evaluation has been conducted to implementing the proposed methodology. Managers can ascertain their supply chain resilience capabilities by means of synthetic resilience index, as recommended in this study. From the measures of resilience for the bygone period, top management can assess and improve the resilience capabilities of their supply chain, by taking strategic level decisions.
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The author sincerely thanks the Editor in Chief, Prof. Endre Boros, the special issue Editors, Prof. Samuel Fosso Wamba, Prof. Maciel M. Queiroz and Prof. Ashley Braganza and the two unknown reviewers for their insightful comments to improving the quality of the manuscript to a greater extent.
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Rajesh, R. A novel advanced grey incidence analysis for investigating the level of resilience in supply chains. Ann Oper Res 308, 441–490 (2022). https://doi.org/10.1007/s10479-020-03641-5
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DOI: https://doi.org/10.1007/s10479-020-03641-5