DECISION-MAKING UNDER RISK AND UNCERTAINTY
DOI:
https://doi.org/10.32999/ksu2307-8030/2026-59-2Keywords:
management decisions, risk, uncertainty, decision-making, cognitive biases, psychological factors, bounded rationality, decision support systems, artificial intelligenceAbstract
The article explores the theoretical and applied dimensions of economic decision-making under conditions of risk and uncertainty, which are increasingly characteristic of modern volatile, complex, and unpredictable socio-economic environments. It systematizes and generalizes the evolution of scientific approaches to decision-making, tracing the transition from classical rational choice theories, which assume perfect information and full rationality of agents, to contemporary behavioral and cognitive paradigms that incorporate bounded rationality, heuristic thinking, and systematic cognitive biases. Special attention is paid to the conceptual distinction between risk and uncertainty, highlighting their different epistemological and practical implications for managerial decision-making. The study identifies and systematizes key psychological determinants of economic behavior, including cognitive biases (such as overconfidence, anchoring, and loss aversion), emotional states, social-psychological effects, and behavioral attitudes. These factors significantly affect the perception of risk, the evaluation of alternatives, and the quality of final managerial decisions. It is emphasized that under conditions of crisis and heightened uncertainty, decision-makers are particularly vulnerable to information overload, cognitive fatigue, and ambiguity effects, which reduce analytical capacity and strategic foresight. The necessity of integrating modern analytical and digital decision-support tools is substantiated. These include decision support systems (DSS), business intelligence (BI), artificial intelligence (AI) and machine learning technologies, scenario analysis, predictive modeling, and stress-testing approaches. Such tools enhance the accuracy, speed, and adaptability of decision-making processes by improving data processing capabilities and reducing the influence of subjective cognitive distortions. The research also highlights the importance of combining behavioral insights with digital technologies to form hybrid decision-making frameworks. This integration allows for more robust and adaptive management strategies capable of responding effectively to rapidly changing external conditions. The findings demonstrate that improving the effectiveness of economic decision-making requires a comprehensive approach that unites cognitive-behavioral, analytical, and technological components. This integrated perspective contributes to increasing the validity, resilience, and adaptability of managerial decisions in conditions of high uncertainty and environmental turbulence.
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