Exploring Digital Twin platforms across industries: A multiaspect SNA

Digital Twins have emerged as a transformative solution enabling organizations across sectors to digitally replicate physical assets and processes to extract operational insights. Implementing Digital Twin systems involves diverse stakeholders, ranging from providers to end-user developers and adopters. At the crux of Digital Twin implementation lies the need of Digital Twin platform – the foundational infrastructure on which solutions are built, integrations are executed, and data flows are managed. While substantial research targets advancing Digital Twin platforms’ capabilities, investigations analyzing real-world implementations spanning industries remain scarce. This research profiles 19 platforms harnessing data aggregated from provider websites, white papers, press releases and user documentation to compile understanding on platform purpose, inbuilt security and interaction mechanisms, integration architectures, predominant use cases, real users’ locations, and supported solutions. Social Network Analysis (SNA) conducted in Pajek detected valuable adoption patterns in the Digital Twin platforms market while community identification analysis linked predominant platform-capability combinations to industry and locational preferences, arming stakeholders to strategize road mapping. Results showed that Azure Cloud, IBM Cloud, and MindSphere were ranked highest in centrality among the platforms mapped. In parallel, to determine platform capability dimensions and their acceptance across geographies and use contexts, normalized centrality metrics were performed for other data types. Also, 58 solutions provided by platforms were classified into five categorical purpose groupings. The findings expand visibility into the dynamics of Digital Twin platforms and can be evolved by expanding sample diversity and blending functional, operational, and economic perspectives in future studies supporting stakeholders in implementation processes.