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With growing awareness of the net‐zero target, clothing brands are striving to reduce carbon emissions in their supply chains (SCs). Besides, social sustainability is gaining increasing attention to meet the Sustainable Development Goals (SDGs). Therefore, SC strategies are becoming more intertwined with environmental and social dimensions of sustainability. To address this issue, this research develops a dynamic supplier selection and order allocation (SSOA) model for the textile recycling industry by integrating the Best–Worst Method (BWM) with mixed‐integer nonlinear programming (MINLP) approach. The overall SC cost is minimised while ensuring that sustainability indices remain above target thresholds. Results indicate that if the sustainability target surpasses a critical level, total SC cost rises drastically. A stress test is conducted to identify critical suppliers, at different tiers, so that strategies for SC resilience can be planned. The findings provide strategic insights into cost–sustainability trade‐offs, enabling managers to design resilient and sustainable sourcing strategies. The study highlights the importance of supplier criticality assessment and targeted sustainability adoption in textile recycling SCs.
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Karmakar et al. (2026) studied this question.
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