Digital Twin Capabilities: From Decision Support to Organizational Value

Digital Twin (DT) technology offers an advanced information infrastructure capable of supporting decision-making processes by integrating digital representations of physical systems with real-time data, analytics, prediction, and simulation capabilities. However, the existing literature largely focuses on the technical architectures and sectoral applications of DT; the mechanisms by which technological capabilities are transformed into decision support capacity and organizational value are not sufficiently explained. This study develops a conceptual model to address this gap by examining digital twin-based decision support from a Management Information Systems (MIS) perspective. Design Science Research (DSR) provides the design logic for the model development process, while Task–Technology Fit (TTF) is used as the theoretical perspective explaining the fit between digital twin capabilities and the requirements of decision tasks. Based on an integrative synthesis of the literature, Information Quality, Real-Time Visibility, Predictive Capability, and Simulation Capability are conceptualized as four analytically synthesized DT capability dimensions relevant to decision support. The proposed model suggests that these capabilities can support Decision Quality through Decision Support Capability, initiating a cascading value-creation process that extends through Organizational Agility to Organizational Performance. The study thus presents an integrated MIS framework in which organizational value emerges through a value-creation process that transforms technological capabilities into usable decision support aligned with decision-task requirements and subsequently into organizational outcomes.