Development of the industrial sector in the Russian regions − cluster analysis
In the course of the study, a cluster analysis of Russian regions was performed based on characteristics associated with industrial and economic development. As a result, it was established that there is a direct correlation between the level of industrial production and general indicators of econom...
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Publishing House of the State University of Management
2023-12-01
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| Series: | Вестник университета |
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| Online Access: | https://vestnik.guu.ru/jour/article/view/4872 |
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| author | A. A. Nikolaev |
| author_facet | A. A. Nikolaev |
| author_sort | A. A. Nikolaev |
| collection | DOAJ |
| description | In the course of the study, a cluster analysis of Russian regions was performed based on characteristics associated with industrial and economic development. As a result, it was established that there is a direct correlation between the level of industrial production and general indicators of economic well-being of the regions such as gross regional product (hereinafter referred to as GRP) and GRP per capita. Within the framework of the cluster analysis, on the basis of above mentioned characteristics, the regions were divided into three groups. The most numerous of them is the group of regions with the lowest level of development. This is primarily due to the uneven distribution of natural resources throughout the country, when a small number of regions have faster development of the mining sector compared to others. Although it is worth noting that the development of the manufacturing industry also has a significant impact on economic well-being. Therefore, the first group, consisting of the most successful regions in terms of economic and industrial indicators, included not only oil-producing and capital regions, but also large industrial centres such as Tatarstan, Sverdlovsk and Chelyabinsk regions. A qualitative analysis of the results showed the success of the current cluster analysis of Russian regions. Only a few uncharacteristic values of indicators were noted which have significant differences for their cluster groups. This mainly applies to oil-producing regions where the level of the extractive sector development is too high compared to the rest of the regions of its group. Although, in general, regarding the sum of indicators, these regions were classified into a specific cluster. |
| format | Article |
| id | doaj-art-1e1fb7ce40e9453db8bd2f5556604b70 |
| institution | Kabale University |
| issn | 1816-4277 2686-8415 |
| language | English |
| publishDate | 2023-12-01 |
| publisher | Publishing House of the State University of Management |
| record_format | Article |
| series | Вестник университета |
| spelling | doaj-art-1e1fb7ce40e9453db8bd2f5556604b702025-02-04T08:28:18ZengPublishing House of the State University of ManagementВестник университета1816-42772686-84152023-12-0101111512610.26425/1816-4277-2023-11-115-1262949Development of the industrial sector in the Russian regions − cluster analysisA. A. Nikolaev0National University of Science and Technology “MISIS”In the course of the study, a cluster analysis of Russian regions was performed based on characteristics associated with industrial and economic development. As a result, it was established that there is a direct correlation between the level of industrial production and general indicators of economic well-being of the regions such as gross regional product (hereinafter referred to as GRP) and GRP per capita. Within the framework of the cluster analysis, on the basis of above mentioned characteristics, the regions were divided into three groups. The most numerous of them is the group of regions with the lowest level of development. This is primarily due to the uneven distribution of natural resources throughout the country, when a small number of regions have faster development of the mining sector compared to others. Although it is worth noting that the development of the manufacturing industry also has a significant impact on economic well-being. Therefore, the first group, consisting of the most successful regions in terms of economic and industrial indicators, included not only oil-producing and capital regions, but also large industrial centres such as Tatarstan, Sverdlovsk and Chelyabinsk regions. A qualitative analysis of the results showed the success of the current cluster analysis of Russian regions. Only a few uncharacteristic values of indicators were noted which have significant differences for their cluster groups. This mainly applies to oil-producing regions where the level of the extractive sector development is too high compared to the rest of the regions of its group. Although, in general, regarding the sum of indicators, these regions were classified into a specific cluster.https://vestnik.guu.ru/jour/article/view/4872gross regional product (grp)differentiation of regionscluster analysisindustryper capita indicatorssector developmentrussian regions |
| spellingShingle | A. A. Nikolaev Development of the industrial sector in the Russian regions − cluster analysis Вестник университета gross regional product (grp) differentiation of regions cluster analysis industry per capita indicators sector development russian regions |
| title | Development of the industrial sector in the Russian regions − cluster analysis |
| title_full | Development of the industrial sector in the Russian regions − cluster analysis |
| title_fullStr | Development of the industrial sector in the Russian regions − cluster analysis |
| title_full_unstemmed | Development of the industrial sector in the Russian regions − cluster analysis |
| title_short | Development of the industrial sector in the Russian regions − cluster analysis |
| title_sort | development of the industrial sector in the russian regions cluster analysis |
| topic | gross regional product (grp) differentiation of regions cluster analysis industry per capita indicators sector development russian regions |
| url | https://vestnik.guu.ru/jour/article/view/4872 |
| work_keys_str_mv | AT aanikolaev developmentoftheindustrialsectorintherussianregionsclusteranalysis |