Growth in a number of the supply chain (SC) disruptions threatens the enterprises globally. Earlier studies and reports say that many organizations go out of businesses within two or three years after they experience a major disruption. Therefore, companies in today’s volatile business arena need to possess the necessary resilience level to combat supply china disruptions. This is even more important for organizations of developing nations, which are constantly struggling to gain the advantages of globalization and to grab the new opportunities. Thus, this paper aims to help organizations understand their SC resilience level through a framework.
The methodology comprises integrated Delphi – fuzzy logic approach in identifying formative elements of SC resilience from a diverse resilience related body of knowledge and distinguish key obstacles of SC resilience based on their performance level.
Findings reveal that SC flexibility components such as sourcing, manufacturing and logistic flexibility are the major contributors of SC resilience index of case organization. Similarly, lack of risk management culture, inter-organizational relationships, information sharing and integration of SC stakeholders are the major inhibitors of resilience. Thus, the organization needs to overcome these identified obstacles to enhance their SC resilience level.
Present study offers a novel focus of research on SC resilience measurement that is significant for understanding the level of immunity enterprises possess to unanticipated SC interruptions, and the ability to bounce back after an unforeseen event.
This paper proposes an integrated Delphi – fuzzy logic framework for measuring SC resilience. In doing so, the study identifies key potential inhibitors of SC resilience of the case company under study.
The authors thank the anonymous referees, the associate editor and chief editor for their comments and suggestions.
Kumar, S. and Anbanandam, R. (2019), "An integrated Delphi – fuzzy logic approach for measuring supply chain resilience: an illustrative case from manufacturing industry", Measuring Business Excellence, Vol. 23 No. 3, pp. 350-375. https://doi.org/10.1108/MBE-01-2019-0001
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