Theoretical background: Many years have passed since the publication of the first multidimensional model (Z-score) of early bankruptcy warning by E.I. Altman in 1968. New models have since emerged in different countries. In this research stream, the share of econometric modelling based on the assumptions of discriminant analysis, i.e. MDA – Multiple Discriminant Analysis – one of the multidimensional classification methods categorised as empirical-induction methods, plays a particularly important role. Purpose of the article: The article assesses the capacity of the Altman Z-Score to forecast (1 year ahead) insolvency of enterprises on the Polish market. Research methods: Due to the sample size (i.e. over 2,700 bankrupt entities in Poland), the study constitutes one of the broadest studies carried out so far on the assessment of the predictive capacity of early warning models in Polish economy. Main findings: The authors, conducting research in this area, put forward a hypothesis that the variables that were well identified and introduced to discriminatory models in one economy work equally well in other countries. Despite the economic differences in these countries and the phases of the business cycle, the financial-analysis indicators that allow effective forecasting of enterprise bankruptcy are valid for different economies. The discriminant-function variability ranges that are characteristic of failing and healthy economic entities change but the variables themselves are good predictors.

The importance of studying civilization diseases manifests itself in the impact of changing lifestyles, on the number of deaths and causes of death. Technology transfer plays an important role in the prevention and treatment of these diseases. Through this, it is possible to transfer new treatments and diagnostics to clinics and hospitals more quickly and effectively, which leads to better healthcare for patients. Technology transfer can also aid in the development of new drugs and therapies that can be effective in the treatment of civilization diseases. The paper aims to evaluate the technology transfer process in the field of civilization diseases, using COVID-19 as an example of a pandemic that requires quick development and transfer of technology. To achieve the assumed goal, we propose a multivariate synthetic ratio in the field of civilization diseases (SMTT—Synthetic Measure of Technology Transfer) to analyze data from the Global Data database. We used sub-measures like SMTT_value (Synthetic Measure of Technology Transfer_value) and SMTT_quantity (Synthetic Measure of Technology Transfer_quantity) to measure technology transfer and put the data into a graph. Our analysis focuses on 14 diseases over a period of 10 years (2012–2021) and includes nine forms of technology transfer, allowing us to create a tool for analysing the process in multiple dimensions. Our results show that COVID-19 is similar in terms of technology transfer to diseases such as diabetes, cardiovascular diseases, neurodegenerative diseases, and breast cancer, even though data for COVID-19 is available for only 2 years.

The authors of the study put forward a hypothesis that it is possible to extend the forecast period for the models of discriminant analysis used to assess the risk of enterprise bankruptcy, focusing on the components of these functions in the form of one-dimensional predictors, i.e. the indicators most frequently included in the discriminant functions developed in Poland. Early warning about the growing risk of bankruptcy would be very valuable for any company. The dataset was constructed from all enterprises in Poland that went bankrupt in the years 2007-2013, which was the end of the research project period. Out of the 4,750 business entities that went bankrupt at that time, 2,739 filed financial statements with commercial courts. The main objective was realized using dynamic assessment of the variability of selected one-dimensional predictors of bankruptcy for all of these enterprises. Assessment of the time variability of the indicators under analysis allows conclusions on the predictive possibilities associated with early warning against insolvency of business entities. The results constitute input to the discussion on determination of the longest prognostic horizon that can be adopted in the models of discriminant analysis used to assess the risk of enterprise bankruptcy. Most of them cover an annual forecasting horizon. Only a few authors have attempted to construct models based on data from the two, three, or even four years preceding bankruptcy. The study showed that the main symptoms of the growing risk of bankruptcy in most of the surveyed enterprises are visible much earlier than one year before bankruptcy. This provides an opportunity to correct the predictive models and more time to restructure the company, to prevent bankruptcy. Therefore, the authors of the study have assessed the possibility of extending this forecast period.