Open AccessTO THE PROBLEM OF USING CLASTER ANALYSIS IN THE PROCESS OF DRAFTING REGIONAL STRATEGIC DOCUMENTS
Author(s) -
Aisa Anatolievna Mantsaeva,
Elza Mantaeva
Publication year - 2017
Publication title -
vestnik astrahanskogo gosudarstvennogo tehničeskogo universiteta. seriâ: èkonomika
Language(s) - English
Resource type - Journals
eISSN - 2309-9798
pISSN - 2073-5537
DOI - 10.24143/2073-5537-2017-1-23-30
Subject(s) - cluster (spacecraft) , agriculture , cluster analysis , government (linguistics) , industrial organization , production (economics) , value (mathematics) , business , process (computing) , cluster development , investment (military) , business cluster , economic geography , regional science , agricultural economics , economy , economics , engineering , geography , computer science , work (physics) , mathematics , statistics , political science , philosophy , law , macroeconomics , linguistics , archaeology , programming language , mechanical engineering , politics , operating system , epistemology , mechanism (biology)
This article focuses on the problem how to classify regions according to their industry specialization using cluster analysis methods. There were selected 12 relative indicators as clustering parameters characterizing the importance of seven different sectors for the regional economies and the degree of state support of enterprises in these sectors. The classification procedure allowed to divide the studied regions into six clusters, each cluster received its working title. The first cluster is titled agro-industrial; it is characterized by the excessive national average indicators of the degree of state support in agriculture and power engineering in 2.4 and 1.6 times, respectively. The second cluster - industrial-presents regions with a high proportion of manufacturing activity using mainly imported raw materials. In the regions of the second cluster the federal government actively develops not only manufacturing and power engineering but power generation as well, 30.06% and 14.48% of total public investment, respectively. The third cluster - agricultural and construction - consists of traditionally agricultural regions and regions with rapidly developing construction sector. However, despite the fact that the value of agricultural industry in the third cluster regions is 2 times higher than the national average value, the degree of public support for the industry is still quite low. The fourth cluster - industrial and mining - brings together fifteen largest industrial regions, their activities are almost entirely provided by the domestic raw materials and energy stocks, which qualitatively distinguishes them from the second cluster regions. The fifth cluster - oil and gas production - is formed by seven richest regions in the federal districts of the Urals and the Far East, as well as the Nenets Autonomous District; these regions are characterized by the highest rates in mining industry. The sixth clusters - transport and power engineering - presents the group of regions with well-developed transport infrastructure and power engineering, many of them are major transport junctions in Russia. The results obtained are quite logical, appropriate and prove the effectiveness of the cluster analysis when processing large data sets. This fact confirms the validity and applicability of the cluster analysis in drafting regional strategic documents.