| Issue |
SHS Web Conf.
Volume 65, 2019
The 8th International Conference on Monitoring, Modeling & Management of Emergent Economy (M3E2 2019)
|
|
|---|---|---|
| Article Number | 04008 | |
| Number of page(s) | 8 | |
| Section | Mathematical Methods, Models, Informational Systems and Technologies in Economics | |
| DOI | https://doi.org/10.1051/shsconf/20196504008 | |
| Published online | 29 May 2019 | |
Analysis of regional development disparities in Ukraine with fuzzy clustering technique
Khmelnytskyi National University, Department of Automated Systems and Modeling in Economics, Khmelnytski, Ukraine
* Corresponding author: kt_datsyuk@ukr.net
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.
© The Authors, published by EDP Sciences, 2019
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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