Principal Factor Analysis identifies key variables impacting education and innovation performance in Eastern Europe, highlighting strengths and vulnerabilities.
Transformations in HEIs (Higher Education Institutions) in recent years have positioned education alongside research, development, and innovation, creating the necessary framework for achieving a positive impact on society and economies. A Principal Factor Analysis was employed using 19 variables from eight Eastern European countries over a three-year period (2022–2024). The six main factors are noted with F1 (innovation and collaboration in R&D), F2 (performance and investment in academic research), F3 (advanced technological production and talent influx), F4 (evolution over time/systemic progress), F5 (cluster development), and F6 (investment in education). These explain over 83% of the total variance, ensuring a robust representation of the original data. The results of the analysis show, in some countries, strengths in specific areas (e.g., EE in innovation, CZ in academic research, and SK in high-tech manufacturing). Meanwhile, a general trend of decreasing scores at the systemic progress level can be observed in most nations, suggesting a slowdown in the overall development momentum. At the same time, significant volatility was observed in cluster development (F5) and investment in education (F6) across the sample. These findings provide a condensed, multidimensional framework for comparative analysis and policy formulation, highlighting specific strengths and vulnerabilities in the regional innovation landscape.
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Stoenoiu et al. (2025) studied this question.
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