Myachin Valentin, PhD (Technics), Associate Professor of the of the Department of Industrial Economics and Organization of Production, Ukrainian State University of Chemistry and Technology, Dnipro, Ukraine

ORCID ID: 0000-0002-1491-5100

Cluster Analysis of Innovation-Active Enterprises Using Kohonen Maps as a Prerequisite for Strategic Planning

Abstract. Introduction. Formation of prerequisites for innovative development of industrial enterprises includes strategic planning, which is one of the components of the management system. The choice of the strategy of innovative development of the portfolio of strategies for innovation-active enterprises depends on their internal and external environment.

Purpose. The aim of the study is to develop conceptual approaches to clustering of innovation-active machine-building enterprises, to analyze the clusters in order to identify their significant differences, and on this basis to develop appropriate strategies for each cluster of enterprises.

Results. A conceptual approach to the clustering of innovation-active machine-building enterprises in order to identify the degree of their readiness for innovation. Clustering was carried out for thirty innovation-active enterprises on two indicators – the level of the crisis and the indicator of the use of strategic capabilities of enterprises. By means of the correlation analysis the relative dependence of input factors is established and by its results it is shown that the incoming factors are practically independent from each other. The use of cluster analysis on the basis of modern research methods using neural networks – Kohonen maps allowed to differentiate the innovation-active enterprises according to the degree of their readiness for innovation. The method of neural networks – Kohonen maps was used for clustering. Clustering is carried out on the basis of two input indicators – an indicator of the level of crisis and an indicator of the use of strategic opportunities.These clusters are called «0», «1», «2», «3» and «4». The largest cluster «0»  included 13 machine-building innovation-active enterprises, the smallest cluster «1» included one innovation-active enterprise. The enterprises of cluster «3» have average strategic opportunities with moderate negative dynamics of the crisis indicator. In General, this is one of the largest crisis groups of enterprises among the thirty studied innovation-active enterprises. Enterprises of clusters «1» and «2» have average strategic opportunities with stable positive dynamics of the crisis state indicator. These two clusters include only three enterprises out of the thirty innovation-active enterprises under study.

Conclusions. All thirty studied enterprises are divided into five clusters, which differ significantly in parameters. For machine-building innovative-active machine-building enterprises of each cluster the corresponding innovative strategy is offered.

Keywords: innovation-active enterprises; cluster analysis; Kohonen maps; strategic planning; neural networks.

References:

1. Kniazevych, A. & Britchenko, I. (2015). Сluster approach to the creating of innovative infrastructure of the country. Naukovyi visnyk Mukachivskoho derzhavnoho universytetu. Seriia Ekonomika, 2, 24-29 [in Ukrainian].
2. Niekrasova, L. & Popenko, S. (2014). Cluster formation  as  the direction of innovative economic development. EKONOMIKA: realii chasu, 2, 132-138 [in Ukrainian].
3. Prokhorchuk, S. V. (2016). The functioning of the innovative cluster in the region. Naukovyi visnyk Uzhhorodskoho natsionalnoho universytetu, 6 (3), 12-16 [in Ukrainian].
4. Butenko, А. І. & Lazareva, Y. V. (2009). The phenomenon of the cluster in the formation of an innovative model of the regional economy. Investytsii: praktyka ta dosvid, 2, 25-28 [in Ukrainian].
5. Illjashenko, S. M. (2008). Marketing innovation and innovation in marketing. Sumy: VTD “Universytets’ka knyga” [in Ukrainian].
6. Kryvovyazyuk, І. V. & Strilchuk, R. M. (2016). Strategic opportunities management at engineering enterprises. Actual problems of economics, 9, 144-155 [in Ukrainian].
7. Kryvovyazyuk, І. V. & Strilchuk, R. M. (2016). Evaluation of strategic position of engineering enterprises in the context of their opportunities’ diagnostics. Actual problems of economics, 8, 146-155 [in Ukrainian].
8. Kryvovyazyuk, І. V. & Strilchuk, R. M. (2016). Diagnostics of a crisis state of innovation-active machine-building enterprises based on discriminant model. Actual problems of economics, 7, 454-465 [in Ukrainian].
9. Yakovlev, V. B. (2017). Data analysis in Deductor Studio. Мoscow: ОntоPrint [in Russian].
10. Kohonen, Т. (2013). Essentials of the self-organizing map. Neural Networks, 37, 52-65.