ALGORITHM FOR IDENTIFYING THE PROSPECTS OF CREATING A REGIONAL ECONOMIC CLUSTER

• Main Authors: Elza Mantaeva, Aisa Mantsaeva
• Format: Article
• Language: Russian
• Published: Volgograd State University 2018-01-01
• Series: Vestnik Volgogradskogo Gosudarstvennogo Universiteta. Seriâ 3, Èkonomika,Èkologiâ
• Subjects: cluster policy; regional economic cluster; identification; cluster analysis
• Online Access: http://ges.jvolsu.com/index.php/ru/component/attachments/download/1209

Studying the theory of regional economic clusters allows to state that in the Russian practice cluster policy is mostly aimed at the creation and support of new clusters rather than the development and support of the already existing ones. The artificial creation of a regional cluster is a long and resource-intensive process, therefore the selection of industries on the basis of which the creation of the cluster will be effective becomes an important task. It is also necessary to predict and compare the various options for the development of events, firstly, to make optimal management decisions, and secondly, to make timely changes and corrections in order to avoid undesirable results. This article presents the authors’ methodology for identifying the prospects for creating a regional economic cluster, which is a three-stage algorithm. The first two stages of the algorithm are devoted to the classification of Russian regions using hierarchical cluster analysis. For each of these stages, a system of indicators has been developed, which makes it possible to adequately break up the objects into groups in accordance with the goal. At the third stage, an imitation model for the functioning of the cluster is constructed, with the help of which it is possible to play various scenario scenarios, and the most optimal option will serve as a guide for the cluster policy of the region. This stage involves the formalization of links between the main elements that characterize the industry (GRP, investments, etc.), and largely depends on the specifics of this industry. The advantages of this technique, in our opinion, lie in the availability of indicators to a wide circle of researchers, as well as the versatility of research tools – cluster analysis and simulation.