Regional economic processes determine the scale of functioning and performance of small and medium-sized enterprises due to their specific involvement in the economy of a territorial entity and quick response to changes in the external environment. The unevenness and high differentiation of economic development in the territories determine the heterogeneity and differences in the level of entrepreneurship development in Russia. In this regard, the aim of our study is to arrange Russian regions into clusters according to indicators reflecting the development of small and medium-sized enterprises and macroeconomic parameters characterizing the economic environment of their functioning, which either acts as a driving force or creates obstacles. The novelty of the approach consists not only in the fact that it integrates enterprises’ development indicators and indicators of the external economic environment of their functioning into the clustering parameters, but also in the formation of final clusters, taking into account the grouping of regions for each year of the period under consideration. This makes it possible to determine the stability of the territory in the group or to track the movement between groups. The k-means method is chosen for clustering. Clustering was carried out according to Federal State Statistics Service data from 2015 to 2021 in 85 regions of Russia. Five clusters have been obtained, whose features confirm the assumption that the development of small and medium-sized enterprises is determined by the economic development of the territory as an external environment of their functioning. Nevertheless, a special second cluster was identified, with the presence of restrictions on the use of the potential of the economic environment, which includes regions that differ in the average level of development of small and medium-sized enterprises against the background of high economic development. The results obtained can be used in the elaboration and implementation of policies to improve the sphere of small and medium-sized businesses at the level of the state as a whole and at the level of a particular region. Further development of our findings may consist in changing indicators or including other clustering algorithms, further typologizing regions or conducting correlation and regression analysis within individual clusters
Keywords
regions of russia, clustering, regions of Russia, small and medium-sized entrepreneurship, organizations of small and medium-sized entrepreneurship, grouping of regions, nonhierarchical cluster analysis, k-means method