In education systems under a strong and prolonged influence of crisis conditions, undergoing processes of consolidation and organizational restructuring of universities, and, in some cases, relocation processes caused by the ongoing war, ensuring a high level of university competitiveness has become a critical factor, influencing institutional resilience and prospects for future development. Since the beginning of the war, the Ukrainian higher education system has experienced a pronounced structural contraction, driven by the combined effects of wartime disruption, institutional restructuring, and unfavourable demographic trends. The consequences of this influence are primarily related to (Protsyk, 2025; Dubynska et al., 2025; Guariglia et al., 2025): damage and destruction of universities and financial losses, relocation and migration of the students and academic teachers either abroad or to safer regions within Ukraine, war-related stress among university lecturers and students, decrease in publications and research productivity, relocation of higher education institutions, and ongoing processes of organizational consolidation and reorganization. In recent decades, the concept of university competitiveness has gained increasing attention in the literature on higher education systems, reflecting intensified competition for students, funding, academic staff, and international recognition (Hart & Rodgers, 2024; Maral, 2025). Broadly, university competitiveness is understood as a multidimensional construct capturing an institution’s ability to achieve and sustain superior performance in education, research, and societal engagement within a dynamic and often globalized environment (Pucciarelli & Kaplan, 2016; Musselin, 2018). In this context, composite indices have become an increasingly prominent tool in higher education policy and research, shaping funding allocation, strategic management, and international benchmarking of universities (Shin, Toutkoushian & Teichler, 2011; Hazelkorn, 2015). By aggregating multiple dimensions of performance into synthetic measures, composite indices offer a comparable assessment of institutional competitiveness. However, the growing reliance on international bibliometric databases and global rankings has also raised concerns regarding their limited coverage of national higher education systems, particularly in countries with heterogeneous institutional profiles and uneven research capacity. As a result, large segments of national university systems remain analytically underrepresented, while performance assessments tend to privilege internationally visible research-intensive institutions. Existing empirical literature reflects this imbalance. The majority of quantitative studies either focus on elite universities included in global rankings or adopt case-study approaches centered on a small number of institutions or countries (Marginson, 2014; Hazelkorn & Gibson, 2018). System-wide quantitative analyses that encompass all universities within a national system remain relatively rare. This gap is especially pronounced in contexts of higher education systems, affected by structural shocks, where institutional diversity and asymmetric adaptation processes challenge standard ranking-based assessments. This study addresses this gap by developing a system-wide competitiveness index for all public Ukrainian universities with a focused analysis of research-enhanced competitiveness, examined within a subsample of institutions with sustained research activity. Methodologically, the analysis applies the CRITIC–TOPSIS approach. By doing so, the study contributes to the literature on higher education competitiveness by moving beyond elite-centered rankings and providing a comprehensive quantitative perspective on system-level dynamics under crisis conditions. Based on an analysis of theoretical and empirical studies, four hypotheses have been formulated for verification in this study:

H1. University competitiveness exhibits substantial heterogeneity across the higher education system, reflecting structural differences between HEIs.

H2. Universities with stronger research performance demonstrate higher levels of overall competitiveness under crisis conditions than institutions with weaker research profiles.

H3. The competitiveness of the universities changes significantly in wartime, with the magnitude and direction of change varying across institutions.

H4. The negative impact of war on competitiveness is uneven across dimensions, indicating differentiated resilience patterns within universities.

The assessment of the competitiveness of higher education institutions requires a multidimensional approach that takes into account a variety of criteria relating to institutional resources as well as the results of research, teaching, and organisational activities. To this end, MCDA methods are used to translate complex data into structured comparative results (Yüksel Kayadelen & Antmen, 2023; Maral, 2024). Setting the weights of the criteria is one of the key challenges in MCDA analysis. In research on higher education and university competitiveness, multi‑criteria decision‑making techniques such as CRITIC, ENTROPY, AHP, FAHP, IVN‑AHP, FDM, CIMAS, BWM, and BBWM are widely employed to derive criterion weights. In this regard, the significant advantages of the CRITIC method are: consideration of data variability, reduction of the influence of highly correlated indicators, and greater weighting of criteria that provide more unique information. As a result, weights are determined objectively and reflect differences in empirical data (Zavadskas, Turskis & Kildienė, 2014; Maral, 2024). In the procedures for comparing alternatives, the TOPSIS, VIKOR, and WASPAS methods offer a transparent way of constructing rankings. Among them, TOPSIS is widely used in ranking analyses of higher education institutions and studies of competitive advantages (Opricovic & Tzeng, 2004; Vrat, 2025). The TOPSIS method allows each unit to be evaluated in relation to the ideal solution (the best possible result) and the anti-ideal solution (the worst possible result), which significantly improves the interpretation of results for stakeholders (universities, policy makers, students). Taking the above arguments into account, a hybrid approach is adopted in this study: the weights of the criteria were determined using the CRITIC method, which avoids the subjectivity of expert assessments, and the university ranking was constructed using TOPSIS, which ensures the transparency and interpretability of the results.

Due to the multidimensional nature of university competitiveness, the study adopts a two-tier analytical design distinguishing between system-wide and research-enhanced competitiveness. The baseline specification applies the CRITIC–TOPSIS procedure to the full sample of 115 public universities operating under the authority of the Ministry of Education and Science of Ukraine in 2021-2024, using a system-relevant set of indicators: publications per academic staff member, student-to-staff ratio, graduate employment rate, share of international students, and institutional visibility. The extended specification is estimated for a research-active subsample of 76 universities with bibliometric data available in the Elsevier SciVal database. In addition to the core indicators, it incorporates citations per publication and field-weighted citation impact, enabling a more direct assessment of research quality and international scientific influence. This framework enables comparative analysis of competitiveness dynamics under prolonged crisis conditions and highlights structural differences between teaching-oriented and research-intensive institutions. In conclusion, the study empirically evaluates university competitiveness in a higher education system operating in wartime, offering evidence relevant not only for Ukraine but also for other higher education systems in crisis conditions.

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