Title: Sustainable supply chain risk mitigation: a mixed method approach

Authors: Madhukar Chhimwal; Saurabh Agrawal; Girish Kumar

Addresses: Department of Mechanical and Automation Engineering, Maharaja Agrasen Institute of Technology, Delhi, India ' Department of Mechanical, Production and Industrial Engineering, Delhi Technological University, Delhi, India ' Department of Mechanical, Production and Industrial Engineering, Delhi Technological University, Delhi, India

Abstract: The objective of this research is to find a way to minimise risk in the supply chain by identifying the critical success factors and analysing the relationship between sundry critical success factors. The proposed study constructs a model of the critical success factors using the interpretive structural modelling approach and tests the model using regression analysis technique. Analysis of the results indicates that there are some critical success factors which have high driving power and low dependence that require utmost attention and are of great paramount while other cluster consists of those critical success factors which are highly dependent and need futuristic actions. In this work, only regression analysis technique is used to validate the model that is developed using interpretive structural modelling approach. This type of relegation will help the supply chain managers to distinguish between independent and dependent critical success factors and how the relationships among the critical success factors will efficaciously minimise the risk in a supply chain. This study can be considered as a base study for the practitioners and academicians who are working in the area of risk management for achieving sustainability in the supply chain.

Keywords: sustainable supply chain management; SSCM; interpretive structural modelling; ISM; regression analysis; risk mitigation.

DOI: 10.1504/IJIE.2022.121744

International Journal of Intelligent Enterprise, 2022 Vol.9 No.2, pp.142 - 162

Received: 12 Feb 2019
Accepted: 12 Jun 2019
Published online: 07 Apr 2022 *

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