CHAOS THEORY AND ITS USE IN CRISIS MANAGEMENT

This scientific article focuses on a comprehensive examination of the conceptual and practical potential of applying chaos theory within the domain of crisis management in economic systems. The relevance of this topic is underscored by the growing complexity, interconnectedness, and stochastic nature of contemporary economic processes, which render traditional linear models insufficient for accurately predicting their dynamics. Chaos theory, as a methodological framework, offers the capability to analyze nonlinear dynamic systems that are highly sensitive to initial conditions, thereby proving especially valuable for studying crisis phenomena. The research delves deeply into the foundational principles of chaos theory, encompassing nonlinearity, fractal structures, attractors, bifurcations, and the effect of sensitivity to initial conditions. These concepts enable not only the identification of patterns in complex systems but also the anticipation of sudden shifts between stable and chaotic states. Significant emphasis is placed on the role of bifurcation points, which represent pivotal moments of systemic transformation where alternative developmental trajectories may emerge. An independent section is dedicated to the analysis of fractal models within the context of economic processes. Fractal structures facilitate the recognition of self-similarity across multiple scales, enhancing comprehension of latent interdependencies and improving the precision of forecasting fluctuations in financial markets. Methodological strategies for incorporating fractal analysis into crisis management practices are suggested. Additionally, the article explores the potential of chaos theory in formulating adaptive management strategies under conditions of uncertainty. The necessity of an interdisciplinary approach integrating insights from mathematics, economics, sociology, and information technology is highlighted. The authors stress the importance of developing specialized tools, such as software for simulating nonlinear processes, algorithms for processing large datasets, and techniques for pinpointing critical junctures in system dynamics. The concluding segment of the article outlines conclusions regarding the application of chaos theory in crisis management. The authors assert that this approach holds considerable promise for bolstering decision-making efficacy during crises. Concurrently, the need for further research to broaden the theoretical foundation and refine practical applications is underscored. Special consideration must be given to educating professionals skilled in leveraging chaos theory methodologies in real-world settings.