چکیده:
In the emerging supply chain environment, green supply chain risk management plays a
significant role more than ever. Risk is an inherent uncertainty and has a 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.
خلاصه ماشینی:
A fuzzy AHP-TOPSIS framework for the risk assessment of green supply chain implementation in the textile industry Muhammad Nazam a*, Jiuping Xu b, Zhimiao Tao b, Jamil Ahmad b and Muhammad Hashim c a Institute of Business Management Sciences, University of Agriculture, Faisalabad, Pakistan b Uncertainty Decision-Making Laboratory, Business school Sichuan University, Chengdu, China c Department of Business Administration, National Textile University, Faisalabad, Pakistan Abstract In the emerging supply chain environment, green supply chain risk management plays a significant role more than ever.
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.
Finally, the proposed model helps the researchers and practitioners to understand the importance of conducting appropriate risk assessment when implementing green supply chain initiatives.
The chosen case example company seeks to prioritize the (GSCM) initiatives; it also wants to understand the fuzzy logic between the criterions for each paired comparison that will improve its green supply chain success rate.
Section 3 briefly explains the methodology, and Section 4 formulates the combined fuzzy AHP-TOPSIS framework, for risk assessment when implementing green supply chain initiatives.
Keeping in view this background, we proposed the hybrid fuzzy AHP-TOPSIS approach for the risk assessment of green supply chain implementation in textiles sector which has the following five phases.