Theoretical Platform for Integrating the Defense-Industrial Complex into the National Economic System
Abstract
Purpose. To substantiate the theoretical platform for integrating the defense-industrial complex (DIC) into the national economic system through the implementation of intelligent management technologies, specifically digital twins and dynamic cognitive scenarios.
Method. The study employs methods of parametric systems theory, logical-linguistic modeling, a frame-based approach for knowledge representation, and systemic-situational analysis to classify management levels of complex national economy objects.
Findings. The concept of a "digital twin" of a DIC enterprise is formulated as a tool for proactive response to strategic challenges; a three-level structure of situational management (strategic, operational, executive) is developed; the use of frame models for structuring resource flows is proposed. The role of the Dynamic Cognitive Scenario as a backward logical inference tool for modeling alternative paths to goal achievement under resource constraints is identified.
Theoretical implications. The work deepens the parametric systems theory by distinguishing between attributive and relational concepts within the DIC context. The scientific novelty of applying logical-linguistic models (production, frame, semantic) to replicate the complexity of subject-object interaction in the defense sector is revealed.
Practical implications. The proposed models and tools (DCS, DSN, AMM) enable the automation of problem situation recognition at DIC enterprises, optimization of production schedules, and synchronization of industry resource complexes in real-time, which is critical for strengthening national resilience.
Originality. For the first time, an integrated approach to DIC management is proposed through an adaptive management mechanism that combines methods of mathematical linguistics and fuzzy logic to create a "bridge" between theoretical economic system parameters and the practical activities of state management bodies.
Research limitations. Limitations relate to the complexity of algorithmizing backward logical inference under highly dynamic legislation and the requirement for high-quality input data (Big Data) for the correct functioning of industrial digital twins.
Paper type. Theoretical-methodological / Research.
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References
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