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Purpose The authors develop a methodology to select appropriate sustainable supply chain indicators (SSCIs) to measure Sustainable Development Goals (SDGs) in the global supply chain. Design/methodology/approach SSCIs are identified by reviewing the extant literature and topic modeling. Further, they are evaluated based on existing SDGs and ranked using the fuzzy technique for order preference by similarity to ideal solution (TOPSIS) method. Notably, the evaluation of indicators is a multi-criteria decision-making (MCDM) process within a fuzzy environment. The methodology has been explained using a case study from the automobile industry. Findings The case study identifies appropriate SSCIs and differentiates them among peer suppliers for gaining a competitive advantage. The results reveal that top-ranked sustainability indicators include the management of natural resources, energy, greenhouse gas (GHG) emissions and social investment. Practical implications The study outcome will enable suppliers, specialists and decision makers to understand the criteria that improve supply chain sustainability in the automobile industry. The analysis provides a comprehensive understanding of the competitive package of indicators for gaining strategic advantage. This proactive sustainability indicator selection promotes and enhances sustainability reporting while fulfilling regulatory requirements and increasing collaboration potential with trustworthy downstream partners. This study sets the stage for further research in SSCIs’ competitive strategy in the automobile industry along with its supply chains. Originality/value This study is unique as it provides a framework for determining relevant SSCIs, which can be distinguished from peer suppliers, while also matching economic, environmental and social metrics to achieve a competitive advantage.
Kumar et al. (Mon,) studied this question.