Deterministic and Stochastic Models: A Comparative Analysis in the Context of Enterprise Management

The need for effective managerial decisions in conditions of uncertainty and risk is a challenge faced by modern enterprises. Very often, managers use economic and mathematical modeling to justify these decisions, which enables the forecasting of the possible consequences. In this regard, the two main groups of approaches to this process are deterministic and stochastic models, each having its advantages, limitations, and areas of effective use. The proposed article presents a comparative analysis of these two types of models in the context of their application in management activities within an enterprise, depending on the organization’s needs and the conditions in which it operates. Using systematic and synergetic approaches, methods of analysis and synthesis, induction and deduction, comparative and content analysis, it has been determined that fixed parameters ensuring the stability of results are the foundation of deterministic models. In stable economic conditions, this type of model allows for clearly forecasted results. At the same time, a weak point of deterministic models is their failure to account for the factor of uncertainty, which reduces their efficiency in dynamic conditions. Stochastic models, in contrast to the aforementioned, take into account all risks and factors that exist in a dynamic environment. This approach allows for the generation of more diverse scenarios, which in turn provides greater flexibility in managerial decisions. However, the need for a large volume of information and the complexity of stochastic models limit their use. The main objective of this article is to highlight the developed recommendations regarding the efficiency of choosing such models in specific situations. Our scientific research offers a reasoned analysis of the features of dynamic and stochastic models, their advantages, weaknesses, and limitations. Such practical recommendations may be useful for analysts, managers, or other specialists aiming to enhance the efficiency of managerial decisions through economic and mathematical modeling.