ECONOMETRIC MODELING OF TURIST COMPANIES' FINANCIAL RESULTS: MULTIFACTOR REGRESSION ANALYSIS AND SCENARIO FORECASTING

The article considers strategic modeling of the competitive capabilities of tourism companies in a dynamic market. The purpose is to design an effective model for assessing competitiveness, using materials from the case study of the tour operator “Join UP!” and applying correlation and regression analysis methods. The constructed model is an effective tool for identifying the most significant factors influencing the company's net income, including the unemployment rate, the number of inbound and outbound tourists, and income from excursion activities. The study findings confirm a close relationship between the dynamics of tourist flows, macroeconomic conditions, and the financial results of tourism industry entities. Based on scenario forecasting (optimistic, realistic, and pessimistic), the author proposes management strategies that contribute to increasing the company's efficiency in its activities, particularly through the development of domestic tourism, diversification of services, and anti-crisis management. The elements of scenario forecasting of the competitive potential of tourism companies are described. The net income from the sale of products (goods, works, services) of the “Join UP!” travel company has been calculated according to three scenarios. The practical value of the study lies in the adaptability of the developed model for making strategic management decisions in the tourism sector. The integration of economic and statistical analysis with correlation and regression modeling allows the identification of the most significant factors that affect the net income of tourism companies in a dynamic market environment. The constructed model can serve as a basis for further research and improvement of strategic approaches to managing competitive potential in the tourism industry and its optimization.