This paper provides a comprehensive review of slacks‐based measure (SBM) models within the nonparametric data envelopment analysis (DEA) framework. The review reveals that the development and modifications of SBM models have progressed in multiple directions. Key areas of modification include (1) the nature of inputs and outputs, (2) data specificity, (3) super‐efficiency for ranking decision‐making units, (4) the inclusion of networks in organizational structures or production processes, (5) the dynamic nature of the analysis, and (6) various other methodological aspects. Increasingly, complex SBM models addressing multiple aspects, such as input/output characteristics and data specificity, are appearing in the literature. Another notable trend is the integration of various methodological proposals from different authors into unified SBM models. Some publications even attempt to forecast future efficiency levels and incorporate large datasets (big data). Despite numerous modifications and advancements, SBM models still lack robust statistical inference capabilities, unlike radial models, which possess more developed statistical foundations.

The growing complexity and intertwining of different socio-economic issues both in individual countries and internationally mean that single-theme analyses do not consider all the relationships and thus have cognitive limitations. Therefore, studies that combine several research areas are increasingly common in the literature to clarify the connections and relationships. In this study, considering the sequential nature of the stages, a combined analysis of eco-efficiency, eco-innovation, and Sustainable Development Goals (SDGs) was performed. The analysis was carried out for 27 European Union countries in 2017–2019. Dynamic Network SBM and Dynamic Divisional Malmquist Index were used for the study. The research results show that the EU countries achieve relatively higher efficiency results in eco-innovation and SDG than ecoefficiency. The average overall efficiency level for all EU countries was only 0.63. The change in productivity was influenced by both the frontier shift and catch-up effect, but only with regard to eco-efficiency and eco-innovation. At the same time, the frontier-shift effect did not affect the change in SDG productivity.

The aim of this article was to estimate the total efficiency of teaching activity carried out in Polish higher education institutions in 2015. The study used the EBM model belonging to the nonparametric DEA method. The output of the education process was measured by the number of graduates of the first-cycle and second-cycle studies and long-cycle studies, the number of doctoral degrees awarded, the number of postgraduate studies certificates issued, and the number of academic teachers and the total value of teaching activity revenue, the total value of state budget subsidies along with fees for educational services and fixed assets. Efficiency measurement was made for two variants: M1 and M2. The obtained research results indicate that on average, the difference between the indicators of the total efficiency of teaching activity under the two empirical models is 0.00. This is due to the fact that the share of budget subsidies and fees paid by students of part-time studies, in the revenues from teaching activity is at the level of 87%. There is also a positive but weak correlation between the total efficiency ratios and financial results obtained from teaching activities.

Changes introduced to Poland's education system in 2011 and 2014 amid efforts to adjust it to the needs of the labour market had an effect on the country's institutions of higher learning. This paper provides an analysis of the efficiency of public and private Polish universities and examines the impact of selected factors in the years that followed. To estimate this efficiency, a Banker, Charnes and Cooper (BCC) model of the Data Envelopment Analysis (DEA) method was used. To gauge the impact of environmental variables on the efficiency of universities, a truncated regression analysis was performed. The results of the study indicate that public universities were more efficient in terms of the number of graduates they produced but less efficient when considering the level of graduate salaries. The opposite was true for private institutions. The level of efficiency was affected by variables related to specific universities and the socio-economic situation of the region in which they operate. The study analyses the efficiency of educational activities of public and private universities, both in terms of the number of graduates and the quality of education and in the context of the labour market. The analysis also considers the level of graduate earnings.

In the 21st century knowledge-based economy, long-term economic growth and development depend on the ability to use the knowledge and technology so as to create product, process, organisational, marketing and even social innovations. The knowledge and technology, human resources and social capital (facilitating the transfer of technology from the world of science to the economy), comprise the most important production factors today. Research and development (R&D) activities are among the diverse determinants affecting the economy’s ability to innovate. They are carried out by public technical universities. One of the tasks that these entities face is to conduct basic, industrial (applied) research and development works. Their results can then be transferred to industrial and service enterprises as novel solutions. Research and development activities of universities are financed mainly from public sources, which suggests the need to assess the efficiency of this task. This can be done with the use of various methods, e.g. the non-parametric DEA method. The purpose of the paper is to measure the efficiency of research and development activities of public technical universities in Poland with the aid of the DEA method. The fourteen universities which in the years 2015–2017 reported to the Ministry of Science and Higher Education (MNiSW) were included in the study. The efficiency of the universities in filing new patent solutions and being granted patents was analysed. The results acquired indicate very low and low efficiency of most Polish technical universities. This is due both to a small number of patent applications and a small number of patents granted. In the examined period, the group of most efficient technical universities in both aspects comprised 4 to 5 universities.

The aim of this review was to present research work on the development of the Malmquist index (MI) in various aspects based on the Data Envelopment Analysis (DEA) method. The MI is one of the three methods of dynamic analysis and also the main one, as it is the most commonly used to measure productivity changes. However, over the years, from being a simple productivity index like the models within the DEA method, it has become a more complex and useful index as it has seen many developments and extensions. Modifications and developments of the MI have taken place in many directions. A review of MI studies from 1990 to 2025 shows that the authors considered various aspects of the MI: Alternative ways of decomposing, different ways of measuring, different types of efficiency, different nature of data and variables and network structure or combined dynamic analysis methods into a single framework. The direction of changes and modifications of the MI can be divided into three groups: Adapting DEA solutions within the MI, presenting new MI solutions without being inspired by the DEA method and combining two methods of dynamic analysis into one framework.