Analysis of regional development disparities in Ukraine with fuzzy clustering technique

Disparities in the development of regions in any country affect the entire national economy. Detecting the disparities can help formulate the proper economic policies for each region by taking action against the factors that slow down the economic growth. This study was conducted with the aim of app...

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Main Authors: Gorbatiuk Kateryna, Mantalyuk Olha, Proskurovych Oksana, Valkov Oleksandr
Format: Article
Language:English
Published: EDP Sciences 2019-01-01
Series:SHS Web of Conferences
Online Access:https://www.shs-conferences.org/articles/shsconf/pdf/2019/06/shsconf_m3e22019_04008.pdf
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spelling doaj-3d4a32e001a9401494e2320de2b3a61b2021-02-02T05:49:10ZengEDP SciencesSHS Web of Conferences2261-24242019-01-01650400810.1051/shsconf/20196504008shsconf_m3e22019_04008Analysis of regional development disparities in Ukraine with fuzzy clustering techniqueGorbatiuk KaterynaMantalyuk OlhaProskurovych OksanaValkov OleksandrDisparities in the development of regions in any country affect the entire national economy. Detecting the disparities can help formulate the proper economic policies for each region by taking action against the factors that slow down the economic growth. This study was conducted with the aim of applying clustering methods to analyse regional disparities based on the economic development indicators of the regions of Ukraine. There were considered fuzzy clustering methods, which generalize partition clustering methods by allowing objects to be partially classified into more than one cluster. Fuzzy clustering technique was applied using R packages to the data sets with the statistic indicators concerned to the economic activities in all administrative regions of Ukraine in 2017. Sets of development indicators for different sectors of economic activity, such as industry, agriculture, construction and services, were reviewed and analysed. The study showed that the regional cluster classification results strongly depend on the input development indicators and the clustering technique used for this purpose. Consideration of different partitions into fuzzy clusters opens up new opportunities in developing recommendations on how to differentiate economic policies in order to achieve maximum growth for the regions and the entire country.https://www.shs-conferences.org/articles/shsconf/pdf/2019/06/shsconf_m3e22019_04008.pdf
collection DOAJ
language English
format Article
sources DOAJ
author Gorbatiuk Kateryna
Mantalyuk Olha
Proskurovych Oksana
Valkov Oleksandr
spellingShingle Gorbatiuk Kateryna
Mantalyuk Olha
Proskurovych Oksana
Valkov Oleksandr
Analysis of regional development disparities in Ukraine with fuzzy clustering technique
SHS Web of Conferences
author_facet Gorbatiuk Kateryna
Mantalyuk Olha
Proskurovych Oksana
Valkov Oleksandr
author_sort Gorbatiuk Kateryna
title Analysis of regional development disparities in Ukraine with fuzzy clustering technique
title_short Analysis of regional development disparities in Ukraine with fuzzy clustering technique
title_full Analysis of regional development disparities in Ukraine with fuzzy clustering technique
title_fullStr Analysis of regional development disparities in Ukraine with fuzzy clustering technique
title_full_unstemmed Analysis of regional development disparities in Ukraine with fuzzy clustering technique
title_sort analysis of regional development disparities in ukraine with fuzzy clustering technique
publisher EDP Sciences
series SHS Web of Conferences
issn 2261-2424
publishDate 2019-01-01
description Disparities in the development of regions in any country affect the entire national economy. Detecting the disparities can help formulate the proper economic policies for each region by taking action against the factors that slow down the economic growth. This study was conducted with the aim of applying clustering methods to analyse regional disparities based on the economic development indicators of the regions of Ukraine. There were considered fuzzy clustering methods, which generalize partition clustering methods by allowing objects to be partially classified into more than one cluster. Fuzzy clustering technique was applied using R packages to the data sets with the statistic indicators concerned to the economic activities in all administrative regions of Ukraine in 2017. Sets of development indicators for different sectors of economic activity, such as industry, agriculture, construction and services, were reviewed and analysed. The study showed that the regional cluster classification results strongly depend on the input development indicators and the clustering technique used for this purpose. Consideration of different partitions into fuzzy clusters opens up new opportunities in developing recommendations on how to differentiate economic policies in order to achieve maximum growth for the regions and the entire country.
url https://www.shs-conferences.org/articles/shsconf/pdf/2019/06/shsconf_m3e22019_04008.pdf
work_keys_str_mv AT gorbatiukkateryna analysisofregionaldevelopmentdisparitiesinukrainewithfuzzyclusteringtechnique
AT mantalyukolha analysisofregionaldevelopmentdisparitiesinukrainewithfuzzyclusteringtechnique
AT proskurovychoksana analysisofregionaldevelopmentdisparitiesinukrainewithfuzzyclusteringtechnique
AT valkovoleksandr analysisofregionaldevelopmentdisparitiesinukrainewithfuzzyclusteringtechnique
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