Mathematical and Analytical Support for the Functioning of the Anti-Crisis Management System in the Context of Ensuring Economic Security

Abstract

The article develops mathematical and analytical support for the functioning of the anti crisis management system, focused on maintaining the economic security of the enterprise under the simultaneous action of financial, operational, market, and credit shocks. The proposed approach combines the normalization of indicators, entropy determination of local weights, the analytic hierarchy process for coordinating the weights of functional components, the multiplicative index of economic security, a dynamic model of the state of the enterprise, and optimization of the structure of anti-crisis actions using the Conditional Value-at-Risk criterion. The scientific idea is to transition from a static assessment of the financial condition to a controlled trajectory of economic security, for which the inertia of the internal state, the mutual influence of functional components, crisis load, limited anti-crisis budget, and the risk of adverse scenarios are taken into account. For testing, a transparent model dataset representing 10 hypothetical industrial enterprises and 16 indicators was formed. 5 000 scenario runs were performed with a reproducible random disturbance generator. The results confirmed that a uniform distribution of the anti-crisis resource is not rational for enterprises with different vulnerability structures. Optimized solutions reduced CVaR and the probability of falling below the critical threshold and generally increased the expected final index of economic security, although the effect de pended on the enterprise’s initial vulnerability profile. It was found that an increase in the normalized intensity of the anti-crisis budget from 0.08 to 0.18 for an enterprise with an average initial state increases the expected index at the end of the horizon from 0.427 to 0.593, and CVaR decreases from 0.941 to 0.407. The practical value of the model lies in the formation of a quantitative basis for choosing priorities for liquidity, operational recovery, supply diversification, market adaptation, and analytical and coordination support.