An integrated fuzzy decision support system for analyzing challenges and pathways to promote green and climate smart mining

Abstract

Green and climate smart mining (GCSM) is a recent advancement in mining that not only alleviates the exacerbating environmental and climate-related impacts but also protects the well-being of the communities in the mining regions. However, there is still a long way to transform current mining practices into GCSM due to many challenges hampering its implementation process. This study applied a three-phase systematic research approach to develop a decision support system to recognize and eradicate these challenges through persuasive strategic pathways. In the first phase, a combination of extensive literature review and the fuzzy Delphi method identifies 9 pathways to overcome 24 challenges divided into five broad categories. The second phase involves an integrated fuzzy decision analysis approach to rank all the challenges, explore their interrelationships, and prioritize the pathways. Finally, the sensitivity analysis is conducted for pathways prioritization against each of the five categories of challenges. The proposed system is illustrated by conducting a case study of the Chinese mining industry to verify its utility and applicability. Analysis unveiled challenges related to government and regulatory and technical and operational categories as the most critical to hamper GCSM implementation, which can be overcome through three best pathways, including low-interest loans and subsidies, cognitive development, and strict codes for newer enterprises. This research is a novel contribution to building connections between mining and sustainability science that provides a comprehensive insight for mining affiliated professionals to implement and promote GCSM, which has not yet been presented in the existing literature.