ADAPTIVE VALUE-BASED MANAGEMENT OF FOREIGN TRADE LOGISTICS SYSTEMS UNDER MARTIAL LAW: THE SDAC FRAMEWORK FOR PRODUCTION RISK MITIGATION

Abstract

The martial law in Ukraine has created unprecedented challenges for the functioning of logistics systems in foreign economic activity (FEA). The destruction of transport infrastructure, blockage of export corridors, instability of customs procedures, and security restrictions have led to a sharp increase in uncertainty in managing material flows. The aim of the article is to develop and empirically validate a model of adaptive value-oriented production risk management in logistics systems of foreign economic activity under martial law, based on the SDAC (Smart Data Adaptive Control) architecture. The study is grounded in a systemic approach to logistics system management, principles of information theory (entropy analysis), and methods of economic and mathematical modeling. To test the hypotheses, Monte Carlo simulation with elements of scenario analysis was employed. The research addresses a relevant scientific and practical problem of adaptive management of production risks in logistics systems of foreign trade under martial law conditions. It has been determined that martial law transforms the logistics environment from a deterministic one into a highly entropic system, where classical risk management models lose their adequacy due to the inability to estimate probabilities based on historical data. An extended model of production risk is proposed, which for the first time integrates a war entropy coefficient and a digital system maturity index. It is proven that the maturity index of the adaptive digital control system is the only controllable parameter capable of compensating for the increase in external uncertainty. The SDAC (Smart Data Adaptive Control) system architecture has been developed, consisting of five integrated modules (data collection, predictive analytics, prescriptive optimization, ex-ante verification, and adaptive feedback). A value creation chain has been substantiated, ensuring the transformation of environmental uncertainty into manageable financial outcomes through a value-oriented decision verification mechanism. The practical significance of the research results lies in the fact that the developed model and SDAC architecture can be used by: – export-oriented enterprises to justify investments in digitalization as a tool for hedging wartime risks; – logistics operators to design monitoring and decision support systems under conditions of instability; – financial directors to integrate logistics scenarios into strategic financial planning.