Addressing key sustainable supply chain management issues using rough set methodology

Purpose – This paper aims to introduce relatively novel multi‐supply chain activity overview rough set theoretic applications to aid management decision making with an especial focus on green and sustainable supply chain management. Design/methodology/approach – The methodology is a review of recent literature with extensions around rough set or neighborhood rough set methodologies for supply chain management. An overview of how the techniques can be applied to various stages of green supply chain management, selection, evaluation, development is presented in various sections. Findings – The paper finds that rough set methodology is flexible enough to be applied as a selection tool, performance measurement evaluation tool, and a development program evaluation tool. Its application to green supply chain management topics is warranted and valuable. Research limitations/implications – Limitations of the approach provide additional avenues for further research. One major limitation of the research is that a real‐world application to validate the approaches is necessary. Extensions and integration with other tools can also provide avenues for improvement. Practical implications – A three‐staged ecological green supplier management process may help to get a broader corporate social responsibility and general sustainability perspective on the supply chain. Management can use these tools for planning, decision making, and maintenance of green supply chain activities. Social implications – The application of sustainability and environmental issues for supply chain management has significant social impact. Originality/value – Methodologically, this is the first time that neighborhood rough set has been comprehensively evaluated as a tool for managing green suppliers. A comprehensive overview of the green supplier management process considering the sustainability factors helps researchers to identify many opportunities for further investigation.