Can Digital Twin Technology Enhance Supply-Chain Resilience? A Systematic Literature Review

Digital twin technology (DTT) creates a virtual replica of a physical object, system, or process and uses real-time data to support monitoring, analysis, and control. Although DTT is increasingly discussed as a means to enhance supply-chain resilience, prior evidence is fragmented and lacks an integrated view across disruption stages. This study conducts a systematic literature review of 89 peer-reviewed articles on DTT and supply-chain resilience, applying relevance-based screening to retain studies with substantive theoretical and practical implications. The review indicates that DTT applications for resilience are emergent but gaining momentum, and that their contribution differs by resilience stage. Specifically, DTT capabilities support preparedness through enhanced visibility, risk sensing, and scenario testing; resistance through real-time monitoring, early warning, and evaluation of mitigation options; rebound through response coordination, recovery planning, and adaptive reconfiguration; and growth through post-disruption learning and network redesign. The synthesis also identifies key barriers to adoption, including data quality limitations, high implementation costs, shortages of specialised skills, and governance challenges, and suggests that integration with complementary digital technologies often enables more advanced functionality. Overall, the study provides a stage-based consolidation of DTT capabilities, benefits, and barriers to guide research and managerial deployment.