Nadiia Artyukhova

The 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.

During the pandemic and russia’s war against Ukraine, higher education shifted to hybrid and distance learning, with some universities forced to adapt or relocate from occupied territories. This article analyzes the institutional, spatial, and financial aspects of Ukraine’s higher education market (1990–2023), focusing on financial data from 2020–2023 across 24 regions and Kyiv, excluding occupied territories. The calculated results based on concentration levels and the Herfindahl-Hirschman index for the number of educational institutions, students, and postgraduate students showed that the higher education market is highly competitive, with an uneven geographical distribution between regions. The analysis of the level of concentration of financial resources among higher education institutions, calculated based on state funding, showed that the distribution of financial resources among universities is relatively even (in 2023, the 20 largest higher education institutions accumulated more than 43.5% of total state funding). The share of state resources aimed at developing the scientific potential of higher education institutions decreased for the 20 largest higher education institutions from 58% in 2020 to 55% in 2022. Non-parametric correlation analysis revealed a low correlation between the amount of general funding for higher education institutions and the amount of revenues to the special fund for research, which indicates insufficient support and prioritization of the scientific sector in the country. These conclusions can be used in implementing the reform (balancing and optimization) of the existing educational network in Ukraine, which has been actively pursued in recent years.

Type of the article: Research Article

Abstract
This study investigates the structural relationships between educational and scientific regulatory interventions and socio-economic development in countries affected by armed conflict and political instability, using the framework of Sustainable Development Goals (SDGs), specifically SDG 4 (Quality Education), SDG 8 (Decent Work and Economic Growth), and SDG 9 (Industry, Innovation and Infrastructure). Rather than focusing on regulatory interventions in a narrow administrative sense, SDG 4 is conceptualized as a reflection of national efforts to improve access to and quality of education, including institutional reforms, policy initiatives, and capacity-building measures in post-conflict settings. The analysis covers 16 countries affected by conflict and instability across Eastern Europe, including Ukraine; the Balkans (Albania, Bosnia and Herzegovina, Croatia, Montenegro, North Macedonia, Serbia, Slovenia); the Middle East (Israel, Jordan, Lebanon, Syrian Arab Republic, Turkey); and the South Caucasus (Armenia, Azerbaijan, Georgia), using data from 2011 to 2020. Employing multivariate confirmatory factor analysis (CFA), the study reveals statistically significant and conceptually meaningful covariances between the selected SDGs. The strongest relationship is observed between SDG 8 and SDG 9, underscoring the interdependence of economic growth, industrial development, and innovation. Moderate but significant correlations between SDG 4 and both SDG 8 and SDG 9 highlight the foundational role of education in enabling socio-economic recovery and technological advancement. Key indicators such as primary school completion, secondary and tertiary enrollment, employment in industry and services, and high-tech value-added production serve as measurable proxies for these dynamics. The findings emphasize the importance of aligning education policy with broader development strategies to support resilience and sustainable growth in fragile contexts.

Acknowledgments and research funding
This research was funded by the European Union grants “NextGenerationEU through the Recovery and Resilience Plan for Slovakia” (No. 09I03-03-V01-00130) and “Immersive Marketing in Education: Model Testing and Consumers’ Behavior” (No. 09I03-03-V04-00522/2024/VA). This research was also prepared as part of project 0124U000545.