Pavlo Rubanov
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Analysis of trends in the structure of higher education market of European countries
Nadiia Artyukhova , Anna Vorontsova , Artem Artyukhov , Yuliia Yehorova , Sergej Vasić , Pavlo Rubanov , Tetiana Vasylieva doi: http://dx.doi.org/10.21511/kpm.08(2).2024.08Knowledge and Performance Management Volume 8, 2024 Issue #2 pp. 91-108
Views: 63 Downloads: 9 TO CITE АНОТАЦІЯThe structure of the higher education market in 2012–2021 in 38 European countries was analyzed using concentration levels and Herfindahl-Hirschman indices based on the number of higher education institutions and their share in the QS World University Rankings, and the number of students. This market in 2021 has a low concentration: the 3 countries with the largest number of higher education institutions (Germany, Ukraine, France) covered about 36% of the market in total; the 3 countries with the largest number of universities in the QS (United Kingdom, Germany, Italy) – 5%; the 3 countries with the largest number of students (Germany, France, United Kingdom) – 37%; and the 3 countries with the largest number of foreign students (United Kingdom, Germany, France) – 5%. Using parametric and non-parametric comparison tests, it was found that although the number of higher education institutions and students does not generally depend on the population’s income level, the number of universities ranked in the QS and foreign students does. The correlation analysis revealed that GDP and GNI, population, and separately the employment and unemployment rates (for ranked universities and foreign students) are important factors that determine the uneven structure of the higher education market. The identified factors formed the basis for clustering countries using Ward’s hierarchical method, which revealed the clear existence of 3 clusters: the smallest of them accumulates the 4 largest European economies with the most ranked universities; the largest (24 countries) is quite diverse, which indicates relatively equal opportunities in the market and its unification.
Acknowledgment
Tetiana Vasylieva and Artem Artyukhov thank project 0122U000772, and Nadiia Artyukhova thanks project 0124U000545 for carrying out their part of this research.
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