Type of the article: Research Article
Abstract
The study aims to empirically group European countries based on competitiveness determinants and adult education demand to form a generalized cluster representation of their socio-economic characteristics. The sample covers 36 European countries from 2015 to 2024. The information base was formed using a set of indicators derived from the Global Competitiveness Index (GCI), together with an indicator reflecting adult education demand. The methodology includes standardization of indicators, selection of relevant variables using principal component analysis, and cluster analysis. The first two principal components explain 76.3% of the total variance, allowing a substantial reduction in the dimensionality of the dataset while preserving most of the information contained in the initial indicators. Clustering was conducted using Ward’s hierarchical method and the k-means algorithm, with verification of differences between clusters by analysis of variance (p < 0.05). To examine structural changes over time, clustering was performed for three benchmark years: 2015, 2020, and 2024. The results reveal five clusters of countries differing in institutional development, innovation potential, business environment characteristics, and adult education participation. A relatively stable core of highly competitive economies was identified, including Austria, Belgium, Germany, France, Ireland, Luxembourg, Denmark, the Netherlands, Norway, Sweden, Finland, and Switzerland. Other clusters show greater variability in composition. Across the benchmark years selected within the 2015–2024 observation period, Ukraine remained within the cluster characterized by the lowest values of competitiveness determinants and adult education demand, reflecting persistent structural constraints in the development of human capital and lifelong learning systems.