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<p>This study systematically identifies and ranks barriers to circular economy (CE) adoption in the fashion industry and evaluates interventions to address them through a multi‐stakeholder decision framework. Drawing on stakeholder theory, institutional theory and a PESTEL lens, we conceptualise barriers as relational, institutionally mediated and contextually embedded. We conducted a systematic literature review and solicited expert input from multiple stakeholder groups to develop a comprehensive barrier taxonomy. Using a Bayesian Best–Worst Method (BWM) we computed weights for macro- and micro-level barrier dimensions and applied Fuzzy TOPSIS to prioritise interventions. Our findings produce a well-defined hierarchy of constraints and a ranked set of intervention strategies mapped to barrier clusters with designated actors, implementation timelines and key performance indicators (KPIs). Robustness checks including leave-one-expert-out testing, comparison of Bayesian versus classical BWM and prior-sensitivity analyses demonstrate high stability, indicating credible expert consensus. The study contributes threefold: (1) an empirical multi-stakeholder prioritisation of CE barriers in a fashion context in a developing economy; (2) a transparent, theory-grounded decision pipeline integrating Bayesian BWM and Fuzzy TOPSIS; (3) a barrier‐to‐intervention decision map linking theory, strategy and operational practice. For practitioners, fashion firms, regulators and supply-chain actors can use the decision map as a strategic guide to sequence interventions, assign accountability and monitor progress via KPIs thereby facilitating the adoption of circular economy practices in the fashion sector.</p>

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Ranking Barriers and Interventions for Circular Economy in Fashion: A Theory-Anchored Multi-Stakeholder Study

  • 期刊论文

  • 发表日期：

    2026年2月23日

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  • Garima Singh

摘要

This study systematically identifies and ranks barriers to circular economy (CE) adoption in the fashion industry and evaluates interventions to address them through a multi‐stakeholder decision framework. Drawing on stakeholder theory, institutional theory and a PESTEL lens, we conceptualise barriers as relational, institutionally mediated and contextually embedded. We conducted a systematic literature review and solicited expert input from multiple stakeholder groups to develop a comprehensive barrier taxonomy. Using a Bayesian Best–Worst Method (BWM) we computed weights for macro- and micro-level barrier dimensions and applied Fuzzy TOPSIS to prioritise interventions. Our findings produce a well-defined hierarchy of constraints and a ranked set of intervention strategies mapped to barrier clusters with designated actors, implementation timelines and key performance indicators (KPIs). Robustness checks including leave-one-expert-out testing, comparison of Bayesian versus classical BWM and prior-sensitivity analyses demonstrate high stability, indicating credible expert consensus. The study contributes threefold: (1) an empirical multi-stakeholder prioritisation of CE barriers in a fashion context in a developing economy; (2) a transparent, theory-grounded decision pipeline integrating Bayesian BWM and Fuzzy TOPSIS; (3) a barrier‐to‐intervention decision map linking theory, strategy and operational practice. For practitioners, fashion firms, regulators and supply-chain actors can use the decision map as a strategic guide to sequence interventions, assign accountability and monitor progress via KPIs thereby facilitating the adoption of circular economy practices in the fashion sector.