Objective: The research objective of this article is to compare the European Union member countries in terms of achieving the sustainable development goal of economic growth and decent work during the Covid-19 pandemic. Research Design & Methods: The study used a set of quantitative data, the realization of indicators proposed for Goal 8 of the document Transforming Our World: The 2030 Agenda for Sustainable Development signed at the summit in New York, 25-27 September 2015 by the leaders of the UN member countries for all 27 EU member states. The analysis was based on the tools of multivariate statistical analysis, a model method for linear ordering of objects proposed by Ching-Lai Hwang and Kwangsun Yoon – the technique for order of preference by similarity to ideal solution (TOPSIS). Findings: The grouping of member countries according to the degree of implementation of the above-mentioned indicated a very good position of five countries with the highest value of the synthetic measure (Netherlands, Ireland, Luxembourg, Denmark, Sweden) and a good one for Germany, Belgium, Finland, Austria, France, Slovenia, the Czech Republic, and Malta. Bulgaria and Greece fared particularly negatively against the analysed group of countries. The hypothesis stating that under the conditions of the Covid-19 pandemic most of the indicators for achieving Sustainable Development Goal 8 worsened in most European Union member states was verified positively. In the era of the Covid-19 pandemic, varying percentage changes were observed in individual indicators of achieving the above-mentioned goal in the studied group of countries. Implications & Recommendations: The results obtained under the individual indicators of Sustainable Development Goal 8 indicate the need for differentiated economic policy measures in individual countries for improving the situation in selected areas of the economy. These require a pragmatic and holistic approach that takes into account, on the one hand, local development conditions and the possibility of economic improvement, and, on the other hand, the need to ensure the health and well-being of the population under the risk of a recurrence of the Covid-19 pandemic. Contribution & Value Added: The value added of the work is the classification of the European Union member countries according to their progress in achieving the Sustainable Development Goal of economic growth and decent work (SDG 8) and the analysis of changes in indicators monitoring changes in these areas under conditions of the Covid-19 pandemic.

Objective: The aim of the article was to forecast the necessary pace of changes in the share of RES in the V4 countries resulting from the EU’s renewable energy sources directive compared to other European Union countries. Research Design & Methods: The research area included all EU Member States, and in particular the Visegrad Group countries. Forecasts of future RES share values were based on two models: Holt-Winters and the autoregressive (AR) model based on EUROSTAT statistical data. Findings: The potential failure to meet the recommendations of the RES share in gross final energy consumption for 2022 concerns 19 of the 27 Member States, of which 2 countries belong to the Visegrad Group. Implications & Recommendations: The research has implications mainly to raise awareness of the direction of RES development in the European Union countries. Contribution & Value Added: The study contributes to the estimation of the future value of the share of renewable energy sources in the V4 countries compared to other countries European Union on the basis of the current activities of these Member States. The forecast makes it possible to initially determine the possibility of meeting the specific target regarding the share of renewable energy sources in the final energy consumption set out in the European Union directive.Article type: research article

Objective: The objective of the article is to classify European Union (EU) member states according to similarity in the area of sustainable development goal 7 (SDG7) of the United Nations (UN) Agenda 2030 on affordable and clean energy. Research Design & Methods: We conducted a hierarchy of EU countries using the linear ordering method due to the level of achievement of sustainable development goal 7 based on indexes available in the Eurostat database for the years 2015 and 2021. We preceded the selection of the method for ordering objects by applying several procedures (Hellwig method (HELLWIG); Technique for order of preference by similarity to ideal solution (TOPSIS); standardized value Sums method (SSW); zeroed unitarization method (IUCN) proposed in the literature. Next, we used a procedure to support the selection of the method based on the measure of inter-ranking comparisons. Moreover, we singled out high-performing countries and countries that require increased attention and support to facilitate the transition to a greener energy economy. Findings: The article presents the ranking of countries by level of achievement of SDG 7 in 2021 and 2015 using the IUCN method. The hypotheses that proclaim the Scandinavian countries (Sweden and Denmark) as leaders in the implementation of SDG7 in the European Union and forming the cluster with the highest degree of SDG7 implementation were verified positively. The results obtained for each group of countries indicate strong development disparities among member countries in the area of clean and accessible energy in its various aspects. Implications & Recommendations: The econometric optics proposed in the study and its results can help classify EU member states in terms of achieving SDG7 for researchers and policymakers. Scholars may supplement the proposed research approach with further measures of clean and accessible energy beyond the SDG7 monitoring indexes. Such indexes could include energy prices, which affect the scale of energy poverty, or the level of greenhouse gas emissions on which environmental well-being depends, among others. Contribution & Value Added: The study narrowed the knowledge gap on the choice of the linear ordering method for objects, often used in socio-economic research. The use of an original research approach different from previous work for the new timeframe supports filling the research gap in empirical studies concerning the classification of European Union member states in terms of SDG7 implementation. . .

One of the key elements in the development of countries is energy stability particularly related to ensuring, among other things, continuity of power supply. The European Commission is trying to protect the security of energy supply by introducing internal conditions regarding the share of RES in everyday life. The aim of this article is to forecast the share of RES in electricity production for all the EU member states. The study covers the years 1985-2021, the research is based on two models: the autoregressive (AR) model and the Holt-Winters model, whereas the prediction values were determined for the period 2022-2030. The prediction values showed that Denmark, as the only one of the community countries, may turn out to be self-sufficient in terms of electricity production from RES already at the turn of 2026-2027. In the case of Poland, there is a high probability that the projected RES share for 2030 will not be met. Potentially, for most EU countries, the energy produced from RES will satisfy at least 50% of electricity demand by 2030. A projection of the chances of meeting the commitments presented in the National Energy and Climate Plans regarding the share of renewable energy sources in electricity production in the EU member states in 2030 indicates that they will not be met in most EU economies.

The objective of this study is to explore the relationship between selected indicators of SDG7, supplemented by the variables of GDP and carbon dioxide emission contract prices, and the consumption of energy from renewable sources in the European Union. The research problem of the study is whether it is possible to explain the consumption of energy from renewable sources in the European Union from 2010 to 2020 within the group of selected indicators for SDG 7 supplemented by GDP variable and variable CO2 emission futures contracts. Based on conducted econometric research, it was proved that there was a certain interdependence and causality of selected factors on the development of renewable energy sources, which varied depending on the EU Member State. By making a critical evaluation of the obtained models, it was found that only in 10 cases (countries) can they be considered correct.

Objective: To assess the financial situation of selected enterprises included in the WIG-food index in 2019–2021 from the point of view of the risk of bankruptcy. Research Design & Methods: Four models of multidimensional discriminatory analysis were used to assess potential bankruptcy risk (Dorota Hadasik’s Model, Model Z6 INE PAN, Model Z7 INE PAN and the so-called Poznań Model). The entities selected for the study were all Polish companies traded on the WIG-food index in all quarters of the years 2019–2021. This condition had to be met due to the volatility of the composition of the WIG-food index on a quarterly basis (quarterly revision of the index portfolio). Two research hypotheses were formulated in the article. First, selected discriminant analysis models are an effective tool for assessing companies included in the WIG-food index for the risk of bankruptcy. And second, multidimensional discriminant analysis is a valuable and complementary tool to other methods of assessing the risk of company bankruptcy. Findings: Companies included in the WIG-food index in 2019–2021 were in a very good financial situation with the exception of two companies, which faced the threat of bankruptcy in 2019: ZPC Otmuchów SA and Pamapol SA. Three of the models used indicated that the companies were moving in the wrong direction: Z6 INE PAN and Z7 INE PAN (ZPC Otmuchów SA) and the Poznań Model (Pamapol SA). This may suggest that these models were highly sensitive. Hadasik’s Model did not show any company to be at risk of bankruptcy in the analysed period. Implications / Recommendations: One implication of the research is that the number of variables in discriminant analysis models does not work to exaggerate their efficiency. Two of the models used (Z6 INE PAN and Z7 INE PAN) returned similar results. This is mainly due to their being constructed similarly. Furthermore, none of the selected models showed high sensitivity to detecting the threat of bankruptcy among the companies analysed, though they could be used to faster warn about potential and actual problems. Contribution: The research contributes to the development of knowledge on the use of discriminatory analysis models to assess bankruptcy risk of food industry enterprises in Poland.