UDC 316.334.52


Acknowledgements: this paper was written with financial support from an RFBR grant (project No. 16-36-60041).

Keywords: region; social potential; cluster analysis; indices of regions’ development; correlation

Introduction: in the context of the separation of powers between the Federal Center and the constituent entities of the Russian Federation accompanied by charging many social expenses to regional responsibilities, Russia’s regions have become a source of territorial inequality. Territorial inequality, manifested in the different levels of industrial development, different infrastructure availability, and different dimensions of regional social benefits, etc., increases manifestations of individual and family inequalities.

Materials and Methods: cluster analysis was used as the main method of data pro-cessing and analysis. The necessary statistical data were taken from the collected papers “Regions of Russia. Socio-economic indexes. 2016”. Calculations and visualization were carried out with the support of the Deductor program. For clustering three indices were chosen: index of economic development of a region, index of security of a region, index of infrastructure availability in a region. When examining the results of cluster formation (matrices of clusters similarity, cluster profiles, statistical data), the EM-clustering algorithm, being an iterative procedure, was chosen.

Results: seven clusters were identified: the zero one — 3 regions (3.5 %), the first — 7 (7.1 %), the second — 32 (37.6 %), the third — 24 (28.2 %), the fourth — 7 (8.2 %), the fifth — 5 (5.9 %) and the sixth — 8 (9.4 %). By means of the method of grouping, the level of development of social potential of the regions included into a particular cluster was characterized as “very high”, “high”, “medium”, “low” and “very low”. The description was made with respect to each index: index of economic development, index of security and index of infrastructure availability, with the use of descriptive statistics and cluster comparison matrices.

Discussion and Conclusions: data analysis of clustering Russia’s regions according to the level of development of social potential allowed to identify relevant areas for further work. The work on cluster identification will be continued in order to achieve high impact of each of the indices on the formation of clusters as well as to get closer to the minimum values in the comparison matrix. In the next stage of work, correlations of the above mentioned indices of development of social potential of the regions will be revealed and the influence of the constituent elements of each index on its value as a whole will be studied. Comparison of the 2015 data with those from previous periods will give an idea of the dynamics of development of the social potential of Russia’s regions.


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Contribution of the authors:

Aleksandra G. Filipova — academic advising, critical evaluation of the materials, interpretation of the results of clustering, final revision of the text of the article.

Anna V. Eskova — search for analytical materials, making calculations in the Deductor program, writing the initial draft text of the article.

Alexei V. Inzartsev — standardization of the data, making calculations using the method of grouping data.

About the authors:

Aleksandra G. Filipova, Doctor of Sociological Sciences, Associate Professor, Professor at the Department of Social and Psychological Sciences, Far Eastern Federal University (Bldg A(24) FEFU Campus, Russky Island, Vladivostok, 690922, Russia) (е-mail: alexgen77@list.ru). ORCID: http://orcid.org/0000-0002-7475-1961. Researcher ID: d-5384-2015.

Anna V. Eskova, Candidate of Engineering Sciences, Head of the Department of Information Systems, Komsomolsk-on-Amur State Technical University (27 Lenina Ave., Komsomolsk-on-Amur, 681013, Russia) (е-mail: eskann68@gmail.com). ORCID: http://orcid.org/0000-0001-5762-5579

Alexei V. Inzartsev, Candidate of Engineering Sciences, Associate Professor at the Department of Information Systems, Komsomolsk-on-Amur State Technical University (27 Lenina Ave., Komsomolsk-on-Amur, 681013, Russia) (е-mail: ainzarcev@mail.ru). ORCID: http://orcid.org/0000-0001-7012-3450

For citation: Filipova A.G., Eskova A.V., Inzartsev A.V. Social Potential of a Region: Experience of Using Cluster Analysis. REGIONOLOGIYA = REGIONOLOGY. 2017; 3(25):438—455.

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