Towards scalable supply chain digital twins: a review and maturity assessment framework

Supply Chain Digital Twins (SCDTs) are increasingly explored as tools for enhancing visibility, coordination and decision support across complex supply networks. However, their implementation remains fragmented and uneven across processes and industries. This study conducts a systematic literature review based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework, covering 47 peer-reviewed SCDT applications published between 2020 and 2025. The selected studies are mapped across the Supply Chain Operations Reference (SCOR) process spectrum and evaluated through the development and systematic application of a three-dimensional maturity model, encompassing Scope of Modelling, Decision-Making Capability and Data Integration & Management Deployment. The analysis reveals a strong concentration of intermediate-maturity implementations, limited multi-echelon data integration and significant underrepresentation of Source and Return processes. The study contributes by developing a SCOR-anchored benchmarking maturity model for systematically assessing SCDT development and identifying structural asymmetries that constrain end-to-end digital twin deployment.