Mathematical Modeling of Relationships between Indicators of the Financial and Economic State of a Region’s Industry to Formulate a Management Strategy for IT

The research aims to develop a methodology for creating a matrix that analyzes the pairwise influence of financial and economic coefficients of IT industry enterprises, total profit, and the amount of taxes paid. This methodology is designed to implement optimized dynamic modeling of regional development using a fuzzy cognitive model. Based on financial analysis, economic theory, and logical reasoning, and considering industry characteristics and enterprise size, experts constructed vectors representing the influence coefficients of indicators from three groups: financial stability, liquidity, and efficiency of enterprises. Additionally, they examined the mutual influence of total profit and the amount of taxes paid within the industry. Based on the obtained vectors, the authors constructed matrices of pairwise influence of indicators and carried out dynamic modeling of the development of the situation based on a fuzzy cognitive model, using the IGLA DSS. Dynamic modeling showed that to optimize the overall situation in a group of enterprises in the industry, it is enough to increase one, two, or three financial ratios. Due to the complex relationships reflected by the matrices of pairwise influence, this will lead to an improvement in the situation. The authors conclude that it is essential to develop a set of accessible government support measures for each financial and economic indicator, depending on its evaluation. These measures will help improve the assessment of these indicators. Additionally, for each activity, it is necessary to conduct an expert assessment of its effectiveness.