Cross-domain comparative analysis of digital twins and universalised solutions

Digitalisation is transforming various economic sectors, with the digital twin (DT) being a key manifestation for complex systems. While numerous studies focus on sector-specific DTs, few offer comparative analyses across domains. This paper delivers three major contributions: (1) A six-dimensional characterisation framework that systematically captures DT development processes across conceptual (twinning objects, purposes, system architectures) and implementation (data, modelling, services) dimensions; (2) Cross-domain comparative analysis of DTs across five representative domains (agriculture, manufacturing, construction, healthcare, smart cities) using this framework, revealing universal commonalities in DIKW-based intelligence progression and identifying three key differentiators—digitalisation capability, cost-benefit dynamics, and socio-ethical risks—that explain domain-specific variations in DT maturity and adoption; and (3) A unified Digital Twin Platform-as-a-Service (DT-PaaS) solution that standardises common processes, tools, and applications while accommodating domain-specific variations through interoperable data models, reusable modelling libraries, and cross-domain service orchestration. A case study demonstrates that the proposed DT-PaaS framework enables connected DT ecosystems with capabilities for data synchronisation, co-simulation, collaborative learning, and coordinated decision-making across sectors. This research establishes the first systematic cross-domain DT comparison methodology and provides practical pathways for knowledge transfer between mature and emerging DT domains, ultimately supporting more efficient and interoperable digital transformation.