Supply Chain Resilience: A Critical Review of Risk Mitigation, Robust Optimisation, and Technological Solutions and Future Research Directions

This study systematically evaluates the literature of supply chain resilience by integrating bibliometric and network analysis techniques. This analysis is conducted following the dynamic capability, as a theoretical lens, to understand and analyse supply chain resilience. We extracted and curated 294 peer‐reviewed articles from leading academic databases, Web of Science and Scopus, covering the period from January 2000 to 2024. We applied two complementary network analysis methods, a keyword co‐occurrence network (KCON) to analyse the frequency and interrelationships among key terms, and a research focus parallelship network (RFPN) to map the connectivity among research streams. These analytical approaches revealed three distinct research clusters, optimisation for supply chain resilience, technology adoption for supply chain resilience, and resilience strategies against disruptions and risk management. By linking emerging trends in digital transformation with traditional risk management practices, this study offers a new perspective for both academic inquiry and managerial practice. Practically, integrating digital technologies, especially digital twin and machine learning, into risk management processes offers a strategic roadmap for real-time monitoring and decision-making in supply chain resilience. Furthermore, this study identifies significant research gaps, including an exploration of micro‐level dynamics within organisations, and the development of advanced simulation techniques and robust approaches to manage uncertainties.