A DEA-based Malmquist Productivity Index for Analysing University Performance and Competitiveness

Objective: To conduct a comparative analysis of university performance and competitiveness for leading Polish and Ukrainian universities using the constant returns to scale (CRS) results-oriented model and DEA-based Malmquist productivity index. Research Design & Methods: Using the CRS results-oriented model and DEA-based Malmquist productivity index, an assessment of the efficiency of Polish and Ukrainian higher education institutions in 2019–2021 has been carried out. Sources of data include reports from university rectors, international educational rankings and data from the SciVal Scopus database. The use of input and output indicators, which characterise the didactic and research activities of universities and affect their efficiency, has been justified. Input indicators are the number of university teachers, total university costs calculated per employee, total university costs calculated per student, and output indicators including the number of graduates, the annual number of employee publications in Scopus indexed journals, and the number of citations of employee publications according to SciVal Scopus. Findings: First, the productivity of some Polish and Ukrainian universities differ, as do the factors of the growth of that productivity. Second, more reputable universities (including benchmarking units) have less potential for productivity growth than less productive regional universities. The relevance of the results obtained was guaranteed by the size of the group of universities analysed. That number was larger than the minimum for maintaining a sufficient number of degrees of freedom. Implications / Recommendations: As a result of analysis with the application of performance-oriented CRS model and Malmquist index, it was found that large reputable universities have less potential for productivity growth (this applies to benchmarking units mainly in Poland). Ukrainian universities are not only more diversified in terms of indicator dynamics, but have greater reserves of productivity growth. Contribution: The article contributes to the scientific literature on university performance and the evaluation of competitiveness. The use of the CRS model and Malmquist index in the analysis of university competitiveness enables better characterisation and evaluation of the input and output indicators, identify benchmarking units and productivity growth reserves.