A multisectoral systematic literature review of digital twins in supply chain management

Purpose The study aims to provide a comprehensive review of digital twin (DT) literature and examine how various industrial sectors utilize the potential of DT. Design/methodology/approach This study’s systematic literature review (SLR) and bibliometric analysis focus on utilizing DT in the supply chain (SC) and its applications across various industries between 2017 and 2024. The use of DT for information management and risk management in SCM, which have been investigated in many sectors, is the primary focus of this article. The article also examines the various digital technologies used in digital twin literature. Findings The following are the main conclusions drawn from the research on digital twins and their implementation: Digital twins have been studied to improve visibility, traceability, resilience, risk identification and assessment, information sharing and decision-making in SC of various sectors. According to the literature review, most research was conducted in the manufacturing industry. Also, the integration of DT with digital technologies (like AI, BD, AI, ML and CPS) in SC has been explored less. Originality/value A multisectoral examination has been done to identify any needs or requirements and unknown areas of study and make recommendations for future directions for study on the interface between SC and DT.