The textile and apparel industry is among the most environmentally intensive industrial sectors, making the adoption of green supply chain management (GSCM) essential for achieving sustainable production, but the implementation of these management practices in emerging economies is hindered by multiple organizational, technological, and economic barriers. However, Industry 4.0 technologies offer significant opportunities to enhance sustainability and operational efficiency across supply chains. This study investigates the major barriers to GSCM implementation in the textile and apparel industry of Bangladesh and evaluates the effectiveness of Industry 4.0 tools in overcoming these barriers. An integrated multicriteria decision‐making framework combining ISM, MICMAC analysis, VIKOR, and TOPSIS was employed. Twelve barriers were identified through literature review and expert consultation. ISM–MICMAC analysis revealed that lack of top management commitment was the most influential driving barrier with high driving power and low dependence. The identified influential barriers were subsequently used as evaluation criteria for assessing the effectiveness of seven Industry 4.0 technologies. VIKOR results indicated that Internet of Things (IoT) and big data and artificial intelligence provided the most effective compromise solutions for mitigating GSCM barriers, while TOPSIS ranked big data and artificial intelligence as the best‐performing technology followed closely by IoT. The findings demonstrate that data‐centric and real‐time monitoring technologies possess strong potential to improve traceability, decision‐making, communication, and sustainability performance within textile supply chains. This study contributes to the GSCM literature by integrating causal barrier analysis with Industry 4.0 technology prioritization and provides practical insights for policymakers and textile manufacturers seeking sustainable industrial transformation.
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Almas et al. (2026) studied this question.
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