Department of Mathematics, Ardabil Branch, Islamic Azad University, Ardabil, Iran
Abstract
Sustainable supply chain management (SSCM) has become the key concept for every industry in managing their supply chain system by focusing on three aspects: economics, social, and environmental. Even though the implementation of SSCM will help the industry increase the efficiency of supply chain management, some challenges make the firms cannot implement the SSCM concept well and unsuccessful. Although research has examined several SSCM viewpoints, the barriers that prevent emerging economies from adopting SSCM in the textile sector to meet the Sustainable Development Goals (SDGs) are not sufficiently highlighted in the empirical literature that has already been published. This study analyzes different barriers and investigates how they are interconnected. From the literature research, main barriers were first identified in the process. The barriers were then prioritized in order of significance using a combination of fuzzy theory, Pareto analysis, and the Decision-Making Trial and Evaluation Laboratory (DEMATEL) framework. Finally, the cause-and-effect relationships among these barriers were established. A lack of commitment from the supplier’s top management, insufficient financial incentives, and the absence of supportive government standards and regulations were identified as the three topmost significant barriers to SSCM adoption. These findings reveal the multifaceted impact of policies on SSCM, providing policymakers with a clearer perspective to formulate more precise policies for guiding the direction of SSCM development and accelerating its innovation pace
fazli,M. (2025). Assessing relationships in industry and optimizing related decisions with the help of fuzzy properties. (e232603). Journal of Industrial and Systems Engineering, (), e232603
MLA
fazli,M. . "Assessing relationships in industry and optimizing related decisions with the help of fuzzy properties" .e232603 , Journal of Industrial and Systems Engineering, , , 2025, e232603.
HARVARD
fazli M. (2025). 'Assessing relationships in industry and optimizing related decisions with the help of fuzzy properties', Journal of Industrial and Systems Engineering, (), e232603.
CHICAGO
M. fazli, "Assessing relationships in industry and optimizing related decisions with the help of fuzzy properties," Journal of Industrial and Systems Engineering, (2025): e232603,
VANCOUVER
fazli M. Assessing relationships in industry and optimizing related decisions with the help of fuzzy properties. jise, 2025; (): e232603.