Digital twins in offsite construction: Current implementations, challenges, and future pathways

Digital Twin (DT) technology is emerging as a critical enabler for Off-Site Construction (OSC). However, current research remains fragmented. This paper synthesizes 50 publications using a mixed-methods approach, combining scientometric mapping with systematic qualitative analysis. Scientometric results reveal a bifurcated landscape, distinctly separating volumetric “Modular Construction” (logistics-focused) from component-based “Prefabrication” (geometry-focused). While applications in scheduling and monitoring are growing, widespread adoption is hindered by “Black-Box” AI opacity, data sovereignty issues, and fragmented standards. Furthermore, sustainability remains an implicit rather than explicit goal. The study concludes with a Strategic Research Roadmap charting the path toward autonomous ecosystems. It emphasizes the need for Neuro-symbolic AI, Operator 5.0 frameworks, and Digital Product Passports to bridge the gap between static monitoring and true Cognitive Digital Twins in OSC. • Combines scientometric and systematic analyses to map the fragmented DT-OSC landscape. • Identifies eight distinct application areas ranging from production scheduling to logistics. • Synthesizes critical barriers including data sovereignty, interoperability, and “black-box” AI. • Proposes a strategic roadmap toward Cognitive Digital Twins and autonomous ecosystems.