Formation of an Adaptive Management Mechanism for Competitive Advantages Using Digital Twins of Industrial Enterprises

The relevance of the study is driven by the growing need for industrial enterprises to enhance their adaptability to dynamic market fluctuations, which necessitates the development of effective tools for the formation and support of competitive advantages. In this context, digital twins are considered a promising solution for integrating real and virtual production environments, enabling greater accuracy, speed, and justification of managerial decisions. The lack of systematized approaches to embedding digital duplication into strategic and operational management frameworks highlights a methodological gap that requires scientific attention. The purpose of the study is to substantiate and construct an integrated mechanism of adaptive management for competitive advantages of industrial enterprises through the use of digital twins, which would ensure effective responses to environmental challenges and sustainable performance under conditions of uncertainty. The research methodology combines systems analysis, structuralfunctional modeling, and analytical evaluation of the effectiveness of digital twin implementation. A comparative experimental observation was conducted, analyzing the performance of production units with and without digital twin deployment. The study revealed that digital twins significantly reduce the time to detect production deviations, lower the number of unplanned stoppages, improve forecasting accuracy, and optimize resource utilization. It was identified that the main barriers to large-scale adoption include insufficient technical infrastructure, limited digital competence of personnel, and the absence of unified regulatory frameworks. The scientific novelty lies in the development of a structured mechanism for integrating digital twins into adaptive management systems that align production, analytical, and strategic components within a unified digital enterprise environment. The conclusions confirm that the implementation of digital twins facilitates a shift towards proactive management and the emergence of a new quality of competitive advantages based on predictive analytics, organizational flexibility, and informational transparency. The prospects for further research involve the unification of digital twin architectures, the use of artificial intelligence algorithms to enhance decision-making processes, and the development of standards for the secure and scalable implementation of digital models in industrial systems.