Moscow State University. M.V. Lomonosov (Department of Socio-Cultural Design and Development of Territories, Professor)
Moskva, Moscow, Russian Federation
UDK 338.24 Управление экономикой
The relevance of the presented study is determined by the fact that in modern geopolitical and economic conditions, achieving technological leadership of the country is of great importance for the development of the national economy. At the same time, in determining the ways to achieve technological leadership of the country, strategic analysis of the development prospects of companies as managed socio-economic systems of the microeconomic level is of fundamental importance. A significant place among the methods of strategic analysis of the development prospects of managed socio-economic systems is played by the method based on the matrix of P. Kralic. However, there are limitations in using the matrix of P. Kralic for making rational management decisions based on a strategic analysis of the development prospects of the socio-economic systems under consideration, due to the traditional use of qualitative indicators for assessing the state and development prospects of managed systems. Due to the noted limitations, the goal of the presented research is the formation of quantitative indicators for assessing the state and prospects for strategic development of managed socio-economic systems using data from the P. Kralić matrix. The scientific novelty of the obtained results lies in the formation of a function that provides a quantitative assessment of the economic efficiency of the management decisions under consideration regarding the strategic development of production in the socio-economic system under consideration using new technologies. The practical significance of the obtained results lies in the possibility of their use in choosing a rational management decision on the strategic development of production in the socio-economic system under consideration through their transformation on the path to technological leadership.
decision-making modeling, achieving technological leadership, using P. Kralić's matrix
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