Aktuálne číslo: 2/2025
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CLUSTER ANALYSIS OF THE EU REGIONAL COMPETITIVENESS INDEX OF NUTS-2 REGIONS
This research investigates the complex dynamics of regional development within the European Union by performing a cluster analysis of the EU Regional Competitiveness Index (RCI 2.0) across 234 NUTS-2 regions. The central issue addressed is the "Capital City Bias" and the challenge of balancing industrial productivity with the quality of life for residents. Furthermore, the study explores the "middle-income trap," a problematic state where regions transitioning through developmental stages may face a policy vacuum if basic infrastructure is neglected before innovation ecosystems are fully mature. The primary objective is to identify hidden patterns and specific similarities within regional groupings to move beyond simple rankings and better understand the unique developmental needs of different clusters. To achieve this, the study utilizes the k-means++ clustering algorithm, an advanced iteration of Lloyd’s algorithm that employs a heuristic for more effective centroid seeding to improve both running time and solution quality. The research focuses on the three core sub-indices of the RCI: Basic (including institutions and infrastructure), Efficiency (labor market and higher education), and Innovation (technological readiness and business sophistication). To determine the optimal number of clusters for each sub-index, the Calinski-Harabasz criterion (variance ratio criterion) is applied, ensuring that the resulting data partitions are both dense and well-separated. Furthermore, Non-negative Matrix Factorization (NNMF) is employed as a sophisticated visualization tool, allowing for the transformation of multidimensional regional data into a two-dimensional plane while preserving essential Euclidean norms. The results demonstrate a persistent geographical divide in Europe, characterized by a stark "elitism" in capital cities compared to their stagnating peripheries, providing critical insights for the tailoring of future Cohesion Policies.
Vydanie: 2025/2 Strany: 68-80 Klasifikácia JEL: M12, M54, O32
DOI: https://doi.org/10.52665/ser20250207
Kľúčové slová: cluster analysis, Regional Competitiveness Index, k-means++ clustering
Sekcia:
Kontakty:
Pavol Oršanský, Mgr. PhD.,
Department of Economics and Economy,
Faculty of Socio-Economic Relations,
Alexander Dubček University of Trenčín in Trenčín
Študentská 3
911 50, Trenčín
e-mail: pavol.orsansky@tnuni.sk
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