Decision-making is a fundamental process in management and plays a crucial role in the success and sustainability of any organization. Effective decision-making enables managers to solve problems, allocate resources efficiently, and achieve organizational goals. This article explores the fundamental principles of decision-making theory, focusing on its key concepts, models, and processes.

The study examines different types of decisions, including strategic, tactical, and operational decisions, and highlights their importance in various management levels. In addition, the paper discusses major decision-making models such as the rational model, bounded rationality model, and intuitive model. Each model provides a different perspective on how decisions are made in real-life situations.

Furthermore, the article analyzes the main stages of the decision-making process, including problem identification, data collection, generation of alternatives, evaluation of options, selection of the best solution, implementation, and performance assessment. Special attention is given to the factors influencing decision-making, such as uncertainty, risk, time constraints, and the availability of information.

The findings suggest that effective decision-making requires not only analytical skills but also experience, intuition, and the ability to adapt to changing environments. Understanding the theoretical foundations of decision-making helps managers improve their problem-solving abilities and make more informed and efficient decisions.

Overall, this study emphasizes the importance of applying decision-making theories in practice to enhance organizational performance and achieve long-term success.

Decision-making, Management, Decision-making theory, Strategic decisions, Tactical decisions, Operational decisions, Rational model, Bounded rationality, Intuition, Problem-solving, Risk management, Uncertainty, Organizational performance, Data analysis, Leadership

Agrawal, A., Gans, J., & Goldfarb, A. (2018). Prediction Machines: The Simple Economics of Artificial Intelligence. Harvard Business Review Press.

Damasio, A. R. (1994). Descartes' Error: Emotion, Reason, and the Human Brain. Putnam Publishing.

Davenport, T. H. (2018). The AI Advantage: How to Put the Artificial Intelligence Revolution to Work. MIT Press.

Gigerenzer, G. (2007). Gut Feelings: The Intelligence of the Unconscious. Viking Press.

Kahneman, D. (2011). Thinking, Fast and Slow. Farrar, Straus and Giroux.

Savage, L. J. (1954). The Foundations of Statistics. John Wiley & Sons.

Simon, H. A. (1955). A Behavioral Model of Rational Choice. The Quarterly Journal of Economics, 69(1), 99-114.

Tversky, A., & Kahneman, D. (1974). Judgment under Uncertainty: Heuristics and Biases. Science, 185(4157), 1124-1131.

von Neumann, J., & Morgenstern, O. (1944). Theory of Games and Economic Behavior. Princeton University Press.