The rapid development of artificial intelligence (AI) has affected higher education. Students now receive new tools that optimize the performance of current tasks. Universities have also begun implementing AI technologies to help university teachers and improve the quality of educational services and solve the Sustainable Development Goal 4. Hypothetically, it is possible to replace university teachers by using AI technologies. This is a hidden conflict of Sustainable Development Goal 4 and Sustainable Development Goal 8. This research aimed to examine the perceptions of Eastern European students about the possibility of replacing university teachers through AI technologies. The authors used an information study with a bibliometric analysis of 2000 sources, planning the experiments and compiling the questionnaire, surveying 599 students using an electronic questionnaire and cloud technologies, statistical processing questionnaires using Excel tables, and verifying statistical hypotheses. Verification of statistical hypotheses for replies of 599 respondents showed that more than 10% of the surveyed students from Eastern European universities are confident that AI will replace university teachers in five years. It was shown that the opinions of students in the 1st stage (undergraduate study) from the countries of the European Union and countries outside the European Union have significant differences. The obtained results were proven using one-sided testing and standard hypothesis testing level, α = 0.05. The article was completed with multilevel managerial and pedagogical recommendations. These recommendations are designed to increase higher education’s sustainability in AI implementation.

The article aims to analyze the impact of green investments and the development of renewable energy on greenhouse gas emissions based on 223 countries in 2011–2021. The information base is the International Renewable Energy Agency, Our World in Data, Climate Policy Initiative, and FTSE Russell. Correlation analysis was used to check the data multicollinearity, multivariate regression analysis with stepwise variable entry—to formalize functional relationships. All variables characterizing the dynamics of green investments and the development of alternative energy, the number of annual investments in off-grid renewable energy has the largest impact on the amount of CO₂ and N₂O. Thus, an annual investment increase of USD 1 million leads to a CO₂ emission increase of 4.5 kt and an N₂O emission increase of 0.272 kt. Simultaneously, the green economy’s market capitalization level has the largest impact on the amount of CH₄. In this case, a capitalization increases of USD 1 trillion leads to a CH₄ emission increase of 129.53 kt. The dynamics of renewable energy development have a statistically significant effect on only one of the three studied greenhouse gases—CO₂ emissions. Here, 1 MW growth of an absolute increase in off-grid renewable energy capacity leads to a 1171.17 kt reduction of CO₂ emissions. Checking input data for lags confirmed a time lag of one year between the level of green investments and the level of greenhouse gas emissions. That is, the impact of green investments on the level of greenhouse gas emissions is delayed by one year. The results of regression models taking into account lags confirmed that an increase in the level of green investments has a positive effect on reducing the level of greenhouse gas emissions (an increase in off-grid renewable energy annual investments of USD 1 million leads to a decrease in CO₂ of 1.18 kt and N₂O of 1.102 kt; the increase in green economy market capitalization of USD 1 trillion leads to a decrease in CH₄ emissions of 0.64 kt).

Background: To explain the link between household finances and the quality of the relationship between married or cohabitating partners and their life satisfaction, the Family Stress Model (FSM) was used and placed within the theoretical framework of the Couples and Finances Theory (CFT). Methods: The measures used to examine the relationship between partners were the Financial Management Behaviour Scale, the Marriage Questionnaire (KDM-2) adapted to a version for cohabitating couples, The Shared Goals and Values Scale, Harsh Start-up Scale, and the Satisfaction With Life Scale (SWLS). In order to find out the relationship between variables, artificial neural networks (ANN) were applied. The research was conducted on a sample of 500 couples living in Poland (384 married and 116 cohabitating couples). Results: The results indicate that overall life satisfaction is most influenced by fundamental, direct, current ways of dealing with the daily financial routine and by saving and investing behaviours. Credit management and insurance behaviours are the most important for the quality of the relationship between partners. Conclusions: The research shows that financial management behaviours have an impact on the quality of relationships as well as on the subjective well-being of people in a relationship, and their relationship dynamics. This finding may be used to highlight the psychological importance of financial management behaviours.

Literature shows that parental financial socialisation plays an important role in attaining financial literacy as well as in shaping sustainable financial behaviours and that both translate into increased well-being indicators and financial security on micro- and macroeconomic levels. However, debt literacy and debt behaviour seem to be unique. Very little is known about the childhood financial socialisation process through which adults’ sustainable debt behaviour is shaped and how debt behaviour may affect well-being. This study tests a hierarchical model of childhood financial socialisation consisting of five levels: the anticipatory parental socialisation, and later life financial learning outcomes (particularly, debt literacy levels), financial attitudes, debt behaviour, and well-being. Using data collected from a purposive sample of young adult Poles (N = 600) during the period from 10 to 13 November 2018 and employing structural equation modelling, we have found evidence confirming the hierarchical relationship of literacy–attitude–behaviour. Our data do not support, however, either the hypothesised positive relationship between parental socialisation and objectively measured debt literacy or the assumed relationships between debt behaviour and well-being indicators. We posit that country-specific factors related to generational differences entailed by system-wide transition and the specificity of debt behaviour, respectively, are key for explaining these empirical deviations from the assumed conceptual framework. Finally, we found no significant differences between the models estimated separately for maternally conditioned and paternally conditioned respondents.