Making Management Decisions under Risk Conditions

This article examines the theoretical and practical aspects of decision-making under conditions of risk and uncertainty. It analyzes the key conditions for risk emergence: the presence of random factors with given probability distributions, the ability to quantify probabilities and damage, and the need to select an optimal behavior strategy. Particular attention is paid to the classification of risks by industry, including production, financial, information, and environmental risks, as well as an analysis of common sources of technological accidents at enterprises. Methods for statistically assessing the probabilities of negative events and modeling optimal risk mitigation strategies through cost and damage analysis are presented, enabling the development of a systems approach to risk management in the modern economy. The practical section is devoted to calculating an optimal strategy based on industry data and modeling overall risk minimization for the mechanical engineering industry. The proposed models and methodologies can be used to improve the effectiveness of risk management at industrial enterprises.