Sustainable supply chains under risk in the manufacturing firms: an extended double normalization-based multiple aggregation approach under an intuitionistic fuzzy environment

Abstract

PurposeIn recent years, a number of researchers have attempted to make an integration of sustainability with supply chain risk management. These studies have led to valued insights into this issue, though there is still a lack of knowledge about the mechanisms by which sustainability-related issues are materialized as risks in the supply chain management.Design/methodology/approachThe paper aims to provide a comprehensive framework to evaluate the sustainability risk in the supply chain management mechanism. To do so, a novel approach using the double normalization-based multiple aggregation (DNMA) approach under the intuitionistic fuzzy (IF) environment is extended to identify, rank and evaluate the sustainability risk factors in supply chain management.FindingsTo provide comprehensive sustainability risk factors, this study has conducted a survey using interview and literature review. In this regard, this study identified 36 sustainability risk factors in supply chain management of the manufacturing firms in five different groups of risk, including sustainable operational risk factors, economic risk factors, environmental risk factors, social risk factors, and sustainable distribution and recycling risk factors. The results of this paper found that the poor planning and scheduling was the important sustainability risk in supply chain management of the manufacturing firms, followed by the environmental accidents, production capacity risk, product design risk and exploitative hiring policies. In addition, the results of the study found that the extended approach was effective and efficient in evaluating the sustainability risk factors in supply chain management of the manufacturing firms.Originality/valueThree aggregation methods based on the normalization techniques are discussed. A DNMA method is proposed under intuitionistic fuzzy sets (IFSs). To propose a broad procedure for identifying and classifying sustainability risk factors (ESFs) in supply chain management. To rank the sustainability risk factor, the authors utilize a procedure for evaluating the significance degree of the sustainability risk factor in supply chain management.