Resilience in closed-loop supply chain: a systematic literature review

Purpose As global supply chains shift from linear to circular models, resilience in reverse logistics and closed-loop supply chains (RL and CLSC) remains underexplored and fragmented, despite its critical role in mitigating disruptions. This study addresses this gap by systematically reviewing and synthesising the existing literature. Design/methodology/approach A review of 194 studies published between 2005 and 2024 was conducted, reflecting the earliest study returned by the search. Through thematic analysis and synthesis, a three-component conceptual framework was developed, comprising: (1) risk types, (2) mitigation strategies for different risk types and (3) mitigation development approaches. Findings The review identifies 16 risk types specific to RL and CLSC, with waste management, collection processes and natural resource scarcity risks being particularly distinctive. Proactive mitigation strategies dominate the field, but there is a need for greater emphasis on real-time and reactive approaches to enhance adaptability. Quantitative, especially model-based techniques, prevail in mitigation development, while data-driven methods remain largely underutilised, signalling an opportunity for future research. Originality/value This study consolidates fragmented RL and CLSC resilience literature into a comprehensive framework, mapping key interactions across risk types, mitigation strategies and development approaches. It also highlights seven research directions: (1) developing risk identification and classification systems; (2) investigating risk interdependencies using complex systems and network analysis; (3) focusing on concurrent mitigation strategies; (4) integrating real-time, concurrent and reactive resilience strategies; (5) exploring new data sources for resilience enhancement; (6) applying and developing data-driven methods; and (7) conducting cross-sectoral comparative studies to generate both generalisable and contextual insights.