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Interpreting the Inequality of the State Support for Development of Small-Sized Business, Using the Means of Iterative Clustering
Strilets V. Y.

Strilets, Victoriia Yu. (2019) “Interpreting the Inequality of the State Support for Development of Small-Sized Business, Using the Means of Iterative Clustering.” Business Inform 2:252–258.
https://doi.org/10.32983/2222-4459-2019-2-252-258

Section: Problems of Business

UDC 338.242

Abstract:
The article is aimed at interpreting the inequality of the State support for development of small-sized business using the instruments of iterative cluster analysis and proving the need to take into view peculiarities of its management in different territories in order to achieve a balanced and equally intensive development of small-sized business with the participation of the State. The hypothesis about inequality of the State support for development of small-sized business in the territory of Ukraine is proposed, the proof of which presupposes evaluation of symmetry and intensity of the State support of development of small-sized business by the means of cluster analysis. The scientific novelty of this article is the construction of the algorithm of using the results of clustering in achieving the uniform State support for the small-sized business development in Ukraine, providing allocation of the permanent and variative components of the algorithm. The carried out clustering of the administrative-territorial units of Ukraine allowed to allocate the list of problem points and similarities in the State support of the small-sized business development.

Keywords: development of small-sized business, the State support of development, small-sized entrepreneurship, clustering, iterative cluster analysis.

Fig.: 3. Tabl.: 2. Bibl.: 8.

Strilets Victoriia Yu. – Candidate of Sciences (Economics), Associate Professor, Department of Finance and Banking, Poltava University of Economics and Trade (3 Ivana Banka Str., Poltava, 36003, Ukraine)
Email: [email protected]

List of references in article

Vorona, P. V., and Muchnyk, A. M. “Mekhanizmy derzhavnoi pidtrymky maloho i serednyoho biznesu (zarubizhnyi dosvid)“ [Mechanisms of state support for small and medium-sized businesses (foreign experience)]. Naukovyi visnyk Poltavskoho universytetu spozhyvchoi kooperatsii Ukrainy, no. 4 (2010): 52-58.
Kalmykov, O. V. “Udoskonalennia systemy derzhavnoho rehuliuvannia maloho biznesu v suchasnykh umovakh“ [Improvement of the system of state regulation of small business in modern conditions]. Naukovi pratsi NDFI, no. 4 (2010): 93-100.
Kimurzhii, M. I., Pedchenko, N. S., and Strilets, V. Yu. “Iteratsiinyi klasternyi analiz K-means yak instrument sehmentatsii pidpryiemstv ZhKH za rivnem potentsialu yikh rozvytku“ [Iterative cluster analysis of K-means as a tool for segmentation of housing and utilities enterprises by the level of potential of their development]. Naukovyi visnyk Poltavskoho universytetu ekonomiky i torhivli. Seriia : Ekonomichni nauky, no. 2 (2018): 55-64.
Pizhuk, O. I. “Derzhavna pidtrymka maloho pidpryiemnytstva yak vazhlyva umova rozvytku sfery posluh v Ukraini“ [State support for small business as an important condition for the development of the service sector in Ukraine]. Ekonomichnyi prostir, no. 93 (2015): 150-164.
Popskyi, A. “Derzhavna polityka rozvytku, pidtrymky maloho ta serednyoho pidpryiemnytstva u konteksti yevropeiskoi intehratsii“ [State policy of development, support of small and medium enterprises in the context of European integration]. Efektyvnist derzhavnoho upravlinnia, vol. 2, no. 1 (2017): 260-268.
Sotska, Yu. I. “Metodolohichni zasady klasternoho analizu konkurentospromozhnosti bankiv Ukrainy“ [Methodological principles of cluster analysis of the competitiveness of Ukrainian banks]. Finansovo-kredytna diialnist: problemy teorii ta praktyky, no. 2 (2015): 177-185. DOI: http://dx.doi.org/10.18371/fcaptp.v2i19.57261
Majhi, S. K., and Biswal, S. “Optimal cluster analysis using hybrid K-Means and Ant Lion Optimizer“. Karbala International Journal of Modern Science, vol. 4, no. 4 (2018): 347-360.
Sardar, T. H., and Ansari, Z. “An analysis of MapReduce efficiency in document clustering using parallel K-means algorithm“. Future Computing and Informatics Journal, vol. 3, no. 2 (2018): 200-209.

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