CLUSTER ANALYSIS OF EUROPEAN COUNTRIES IN THE VALUE ADDED SECTOR
Authors:   Mariupol State University, Peresichnyi O. , Bezzubchenko O. ,   Mariupol State University
Published: November 2024

The article is devoted to an in-depth analysis of the economic activity of European countries based on two types of cluster analysis: general clustering and component analysis. The aim of the research was to identify the main trends and differences in the structure of economic activity in the region, which allows for a better understanding of economic interaction and development potential of European countries. The first type of analysis, general clustering, demonstrated a clear correlation between the economic and geographical proximity of countries within clusters. It was found that the level of economic and social development has a significant impact on the formation of clusters. In particular, countries with developed industries and financial sectors are grouped into one cluster, while the most developed countries in Europe form a separate cluster. The uneven distribution of countries into groups reflects the diversity of economic development. The key indicators that influence clustering are the share of value added in export and the amount of value added generated per unit of labor force employed. The analysis of the share of import of intermediate products showed that this indicator has the least impact on clustering, as the distances between clusters are the smallest according to this parameter. The second type of analysis, component analysis, is aimed at identifying the specific economic activities of countries by economic sector. This approach allows for a more detailed assessment of the efficiency and competitiveness of various industries. The analysis showed that the indicator of value added in agriculture doesn’t have a sufficient impact on the clustering results, so it was excluded from further analysis. The results of clustering reflect the correlation between the leading sectors of value added and the level of socioeconomic development of countries. There is also an optimization of the composition of clusters, in particular, the expansion of cluster 2 by moving countries from cluster 1 and optimizing the composition of cluster 3. The results for the outliers are also revealing, showing a significant predominance of cluster 2 countries in the overall sample. Cluster 2 has the largest variation in values, while cluster 1 countries no longer have a symmetrical distribution around the mean, indicating internal economic diversity. Clusters 3 and 5 have low scores in the finance and services sectors, which confirms the existence of unrealized potential of the economically active population in these regions. To summarize, both analyses show that the economic development of European countries largely depends on the level of involvement in the process of value creation. The results indicate the need for further research on the relationship between economic activity and socioeconomic indicators. It is recommended to focus on the development of economic development strategies that take into account the specifics of each country and its place in the cluster structure. Further research could also include an analysis of the impact of international trade and investment on economic activity and the development of individual sectors. This will help to identify priority areas of cooperation between countries and increase their competitiveness in the global market. Keywords: global value chains, clustering, international economic relations, exports, employment, international specialization