STATISTICAL JUSTIFICATION OF FACTORS AND RISKS OF A PRIVATE ENTERPRISE EFFICIENCY USING INFORMATION SYSTEMS

Анотація

The article provides a statistical justification of the factors and risks affecting the performance efficiency of a private enterprise using information systems. Based on economic and statistical methods, in particular factor, correlation, and regression analysis, the impact of operational and financial indicators on the level of capital profitability is investigated. Statistical models are developed that allow for a quantitative assessment of the influence of key factors and financial risks and support the formation of well-grounded managerial decisions aimed at improving the efficiency of enterprise performance. In the context of economic instability, increased uncertainty and intensified financial risks, improving the efficiency of private enterprises becomes a key prerequisite for sustainable development. For small and medium-sized enterprises, efficiency is closely linked to the ability to identify and manage operational and financial risks. Therefore, the application of statistical methods combined with information systems is essential for conducting comprehensive economic analysis and supporting managerial decision-making. The purpose of the article is to provide a statistical justification of the factors and risks influencing the efficiency of a private enterprise by applying factor and regression analysis using information systems, as well as to assess the impact of key financial and economic indicators on enterprise performance. The study applies economic and statistical methods, including factor, correlation and regression analysis, to examine the influence of operational and financial indicators on capital profitability. Factor models, including DuPont analysis, made it possible to determine the role of profitability, asset turnover, capital structure and liquidity in shaping enterprise efficiency and related financial risks. The results of regression modeling confirmed the existence of statistically significant relationships between efficiency indicators and selected explanatory variables. The constructed models demonstrated high explanatory power and reliability, enabling quantitative assessment of the impact of efficiency factors and financial risks. The use of information systems ensured accurate data processing, model estimation and validation of statistical significance. The findings confirm that enterprise efficiency is determined by a combination of interrelated financial and operational factors that simultaneously form the level of economic risk. The integration of statistical methods with information systems enhances the quality of economic analysis and risk assessment, providing a sound analytical basis for managerial decisions aimed at improving efficiency and reducing financial risks in private enterprises.

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