Green supply chain practices evaluation in the mining industry using a joint rough sets and fuzzy TOPSIS methodology

Kusi-Sarpong, Simonov, Bai, Chunguang, Sarkis, Joseph and Wang, Xuping (2015) Green supply chain practices evaluation in the mining industry using a joint rough sets and fuzzy TOPSIS methodology. Resources Policy, 46, 86-100. (doi:10.1016/j.resourpol.2014.10.011).

Abstract

Environmental issues from the extractive industries and especially mining are prevalent and maleficent. An effective way to manage these pernicious environmental problems is through organizational practices that include the broader supply chain. Green supply chain practices and their role in mining industry strategy and operations have not been comprehensively addressed. To address this gap in the literature, and building upon the literature in general green supply chain management and environmental decision tools, we introduce a comprehensive framework for green supply chain practices in the mining industry. The framework is categorized into six areas of practice, with detailed practices described and summarized. The green supply chain practices framework is useful for practical managerial decision making purposes such as programmatic evaluation. The framework may also be useful as a theoretical construct for empirical research on green supply chain practices in the mining industry. To exemplify the practical utility of the framework we introduce a multiple criteria evaluation of green supply programs using a novel multiple criteria approach that integrates rough set theory elements and fuzzy TOPSIS. Using illustrative data we provide an example of how the methodology can be used with the green supply chain practices framework for the mining industry. This paper sets the foundation for significant future research in green supply chain practices in the mining industry.

This record has no associated files available for download.

Contributors

Download statistics