In an era of rapidly evolving customer demands and technological advancements, organisations face mounting pressure to enhance their responsiveness. Digital Twins offer novel capabilities by providing comprehensive transparency on customer demands through dynamic and interactive links between real-world entities and their digital counterparts. As a result, Digital Twins have the potential to enable organisations to respond more swiftly and effectively to fluctuating customer demands across volume, process, and product dimensions. However, Digital Twins still lack empirical explorations and theoretical embedment, leading to conceptual ambiguity. Through a case study approach, the study integrates Digital Twins into the framework of Organisational Information Processing Theory (OIPT). Empirical evidence proposes that Digital Twins offer a spectrum of capabilities rather than a one-size-fits-all solution. The findings further emphasise the need for aligning Digital Twin sophistication levels with Information Processing Needs and Constraints, highlighting that the dynamic interplay between Digital Twin advancements, Information Processing Constraints, and Information Processing Capabilities creates a dynamic cycle of adaptation and optimisation. On the whole, the study presents four key implications: (1) Awareness about the versatile application areas of Digital Twins is created. (2) The positive impact of Digital Twins on volume, process, and product responsiveness is outlined. (3) The concept of Information Processing Constraints is introduced to OIPT. And (4) a dynamic cycle of aligning Digital Twin sophistication with Information Processing Capabilities and Constraints is suggested. Therefore, the study contributes not only to a deeper understanding of Digital Twins in demand management but also proposes a new dynamic fit perspective on OIPT.
