ECONOMIC AND MATHEMATICAL MODELING OF THE FACTORS OF FORMATION AND USE OF THE INTELLECTUAL ECONOMIC SYSTEM OF CONSTRUCTION ENTERPRISES

Abstract

Summary. The topicality of the topic of economic-mathematical modeling of the factors of formation and use of the intellectual economic system of construction enterprises is proven. The definition of an intelligent economic system is proposed as a set of economic, geospatial, security, and social components that are developed by applying modern mathematical methods and models, artificial intelligence, information and analytical support and tools and form the basis for making management decisions in the context of the development of construction enterprises. As a result of the evaluation, the average level of the integral indicator of the formation and use of the intelligent economic system at all construction enterprises was determined. This indicates mediocre opportunities for the formation and use of an intelligent economic system, taking into account the economic, geospatial, security, and social aspects of construction enterprises. Along with this, for the formation and implementation of an intellectual economic system, there is a need to develop relevant scientifically based recommendations by applying the tools of economic and mathematical modeling to forecast changes in the integral indicator and its impact on the generalizing factor of the development of construction enterprises.A scientific-methodical approach to determining the influence of the factors of the formation and use of the intellectual economic system on the integral indicator based on economic-mathematical modeling has been developed, which allows predicting changes in the generalizing criterion to create a basis for the development of relevant scientifically based recommendations. Based on the results of the numerical experiment of economic and mathematical modeling, it was concluded that a high correlation is observed between the integral indicator of the formation and use of the intelligent economic system of construction enterprises and economic and safety factors. The regression models built for these factor characteristics are significant and adequate.