A fuzzy multi-criteria model with Pareto analysis for prioritizing sustainable supply chain barriers in the textile industry: Evidence from an emerging economy

Abstract

The textile industry supply chains (SC) face numerous risks and disruptions due to the changing dynamics of high demand and limited resources. The impact of epidemics and regional conflicts further complicates global business operations, especially in emerging economies. In this context, the textile sector in these economies must prioritize Sustainable Supply Chain Management (SSCM) to achieve cost reduction, enhance productivity, and improve profitability to sustain their business. 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, 17 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. For the textile sector, governments, and policymakers in emerging economies, the study's results are helpful since they will assist them create mitigation strategies to get rid of these barriers and achieve long-term sustainability.