MODELING OF MANAGERIAL DECISION-MAKING IN ENTERPRISE SALES MANAGEMENT BASED ON FUZZY LOGIC AND SELF-MANAGEMENT PRINCIPLES

Abstract

The article is devoted to solving a topical scientific and practical problem — improving the efficiency of managerial decision-making in the sales sector by incorporating self-management principles under conditions of high market uncertainty. The relevance of the study is driven by the need to find flexible management tools capable of integrating both quantitative financial indicators and qualitative factors of human influence. The authors analyzed existing methods for evaluating sales activities, including financial-economic, marketing, and expert approaches, and justified their limitations in dynamic market conditions. The paper proposes a comprehensive approach to modeling a decision support system (DSS) based on the apparatus of fuzzy logic. A distinctive feature of the developed model is the inclusion of the "staff self-management level" indicator among the input parameters, which allows for the formalization of the impact of employees' self-organization, prioritization, and time management skills on the final efficiency of sales processes. The model includes four key input variables: service demand level, degree of competition, direct sales costs and self-management level. The scientific novelty of the study lies in the development of a fuzzy model architecture using the Mamdani algorithm, which employs triangular membership functions to describe linguistic variables. This enables the conversion of subjective expert assessments into an objective numerical value of the integral indicator of the feasibility of a managerial decision. The practical significance of the results is confirmed by simulating a scenario for the leader of the Ukrainian logistics market — "Nova Poshta" LLC. The simulation results demonstrated that the implementation of the proposed tools allows for an increase in forecast accuracy by 15–18% and a reduction in strategic sales planning costs by 8–10% due to the automation of qualitative market factor analysis. The model is universal and can be adapted for enterprises in various industries striving for sustainable development in the context of digitalization.