ECONOMIC-MATHEMATICAL MODEL OF FORMATION OF INNOVATION AND ENGINEERING INDUSTRIAL CLUSTER

Abstract

The subject of the article is the use of industrial clusters as tools for innovative economic growth. The purpose of the article is to develop an economic-mathematical model of the formation of an industrial cluster, and to create an algorithm for cluster zoning of the economy. Tasks to be solved – analysis of the principles of innovative growth, development of a model of an innovation-engineering industrial cluster, formulation of a methodology for the formation of a regional innovation-engineering cluster, analysis and assessment of the features that arise in clusters, use of cluster analysis for systematization, classification and reduction of the number of features. Applied methods: system analysis, project approach, institutional theory, clustering methods, Bartlett’s sphericity criterion and Kaiser–Meyer–Olkin sampling adequacy criterion, multivariate regression analysis, Fisher’s F-test. The results obtained: it was determined that the best approach to unification of the main components of innovative development, namely state bodies, business and development institutes, is the creation of innovation and engineering clusters. The principles of creation and functioning of such clusters are described. It is shown that the basis of the cluster construction algorithm of regions is the integration of quantitative and qualitative methods of identification and clustering of the economy. This makes it possible, in contrast to existing approaches, not only to identify cluster elements, but also to model the levels of interaction between them. It is proposed to use the synergistic effect from the use of the newly formed structure as an assessment of the efficiency of the cluster. Conclusions: the use of regional innovation and engineering clusters allows for the formation of an effective strategy for the development of the region’s economy. The developed algorithm of cluster zoning integrates quantitative and qualitative methods of determining the clustering possibilities of the region’s economy. The complex interaction of economic and political factors leads to a synergistic effect and allows modeling cluster formation with the identification of the composition of participants and the level of interaction between them.