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:: Volume 2, Issue 1 (5-2015) ::
IJSOM 2015, 2(1): 548-568 Back to browse issues page
A Fuzzy AHP-TOPSIS Framework for the Risk Assessment of Green Supply Chain Implementation in the Textile Industry
Muhammad Nazam * 1, Jiuping Xu 2, Zhimiao Tao 2, Jamil Ahmad 2, Muhammad Hashim 3
1- University of Agriculture, Faisalabad, Pakistan ,
2- Sichuan University, Chengdu, China
3- National Textile University, Faisalabad, Pakistan
Abstract:   (2713 Views)
In the emerging supply chain environment, green supply chain risk management plays a significant role than ever. Risk is an inherent uncertainty and has tendency to disrupt the typical green supply chain management (GSCM) operations and eventually reduce the success rate of industries. In order to mitigate the consequences, a fuzzy multi-criteria group decision making modeling (FMCGDM) which could evaluate the potential risks in the context of (GSCM) is needed from the industrial point of view. Therefore, this research proposes a combined fuzzy analytical hierarchy process (AHP) to calculate the weight of each risk criterion and sub-criterion and technique for order performance by similarity to ideal solution (TOPSIS) methodology to rank and assess the risks associated with implementation of (GSCM) practices under the fuzzy environment. The proposed fuzzy risk-oriented evaluation model is applied to a practical case of textile manufacturing industry. Finally, the proposed model helps the researchers and practitioners to understand the importance of conducting appropriate risk assessment when implementing green supply chain initiatives.
Keywords: Fuzzy AHP, Fuzzy TOPSIS, Risk assessment, Green initiatives, Textile sector
Type of Study: مقاله پژوهشی |
ePublished: 2017/09/28
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Nazam M, Xu J, Tao Z, Ahmad J, Hashim M. A Fuzzy AHP-TOPSIS Framework for the Risk Assessment of Green Supply Chain Implementation in the Textile Industry. IJSOM. 2015; 2 (1) :548-568

Volume 2, Issue 1 (5-2015) Back to browse issues page
International Journal of Supply and Operations Management International Journal of Supply and Operations Management
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