Cluster analysis of Russian metallurgical complex enterprises


Savenkov L.D.

Abstract. The article presents a cluster analysis of an enterprise in the Russian metallurgical complex based on 12 selected indicators of the company`s financial and economic activities. In the course of the correlation analysis, three main factors were selected that influence the activities of enterprises in the Russian metallurgical complex. These factors were net profitability, EV and net debt. Dunn`s method was used to determine the most optimal number of clusters. The most optimal number of clusters was three clusters. In the course of the cluster analysis, a transition from one cluster to another of a number of communication companies with an increase in profitability and EV indicators was identified. In 2021 and 2023, significant improvements in the performance of companies in the metallurgical complex are observed. The company PJSC Ashinsky Metallurgical Plant continues to maintain its high position, both in 2016 and in 2021 and 2023. The company PJSC Severstal, unfortunately, has not sufficiently improved its activities by 2021 and 2023. The results obtained indicate that economic conditions and the situation in the country are becoming more balanced, and development is becoming homogeneous in this industry. Keywords: metallurgical complex, correlation, cluster analysis, net profitability, net debt, EV, metallurgical industry, Dunn method. Highlights: ♦ the main factors affecting the activities of enterprises of the metallurgical complex of Russia were the net profitability indicator, EV and net debt indicator; ♦ in 2021, compared with 2016, there are significant improvements in the activities of companies in the metallurgical complex; ♦ three clusters can be considered as the most optimal number of clusters for companies in the metallurgical complex of Russia; ♦ the cluster analysis revealed the transition from one cluster to another number of companies due to the growth of profitability and EV indicators.

Leonid D. Savenkov - Institute of Finance, Economics and Management of Tolyatti State University, Tolyatti, Russia


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