In the past two decades the topic of “green jobs” has drawn particular attention, resulting in a widely diverse and relatively large number of published papers. Although a determinant for the increase of knowledge, the heterogeneity of these studies may raise the issue of a systematic documentation of the key contributions in this field. In this context, the present research focuses on analyzing the scientific literature published in the last five years on the topic of “green jobs” with the aim to identify definitions and meanings associated with the concept of “green jobs”, the connected terms, areas of research interest and the main theoretical and practical results. The results reveal that although there is no uniformity in the definition of the concept, there is still a convergence towards the initial meaning offered by the UNEP/ILO/IOE/ITUC Report of 2008. Moreover, using scientific software VOSViewer our research shows that the concept of “green jobs” is most linked with the following terms: sustainable development, the green economy, the circular economy, the welfare economy, the European Green Pact, energy, renewable energy, economic development, and employment. Furthermore, our analysis reveals that the studies focused on “green jobs” are mainly concerned with the following issues: green jobs creation, work-life balance, correlations between green business and green jobs and the role of local government in supporting green jobs.

The current pandemic crisis, which is far from being over, has led to a significant paradigm shift in economics. In a turbulent environment in which the labor market has encountered a long series of changes generated by the processes of automation, robotization and digitalization, the COVID-19 pandemic has revealed that a workforce with digital skills can quickly adjust to new circumstances. Since novel issues, such as restrictions on internal movement and distorted supply chains, put major stress on the labor market, it seems that there is an urgent need for reshaping economies and following up-to-date technological trends. Moreover, prior to the COVID-19 pandemic, a significant number of scholars and policymakers expressed their concerns about the volatility of employment and the weak ability of labor to adapt to new types of jobs. Within this framework, our paper aims to analyze the plausible impacts of digital efficiency on the future development of the labor market. Based upon the assumption that employment is facing ongoing challenges and the labor market is constantly being reshaped by technological trends, our study attempts to provide a pragmatic analysis of the effects of digital skills and the use of the Internet on salaries and wages in EU member states. Since, according to our results, the levels of salaries and wages are strongly correlated with digital proficiency and Internet usage, a consistent effort to increase the digital skills of individuals may be required to achieve a more effective and flexible labor market.

Increases in productivity and competitiveness of an economy are based mostly on the actions of companies in terms of providing technical capital to workers and of operations efficiency (management, financial, recruitment, finding markets and suppliers, internal and external communication, etc.) through digitalization. This paper deals with the way in which the economies and companies in Central and Eastern European (CEE) countries manage to adapt to the trend that started, mostly after 2000, in digitalization; also, it analyzes the extent to which an increase in the degree of business upgrading via integrating digital technology into the business model leads to a surge in economic performances (productivity, exports) and, consequently, to a greater attractivity to foreign capital flows.

Education for sustainable development (ESD) has presented long-lasting interest for researchers and policy makers. Despite a significant body of research, more in depth empirical studies are required for a better understanding of how sustainable development goals are applied in higher education and how sustainable behavior could be shaped via ESD. The need for this kind of research arises from, first, the scarceness of existing studies that explore economic and business higher education, and, second, the necessity to properly assess the connection between ESD principles and students’ behavior. Following this rationale, the present paper aims to provide an overview of how students’ sustainable behaviors are shaped via their perception of sustainable campus initiatives, teaching staff involvement and curricula. Statistical and econometric analysis applied on data collected via a survey on students from Bucharest University of Economic Studies (N = 1253) provides findings on the extent to which the awareness of sustainable development-specific issues acquired through education leads to sustainable behavior among students. According to the results, we argue that an increasing share of sustainable development topics combined with teaching staff involvement to raise awareness of sustainability issues are crucial to students’ sustainable behavior. However, on-campus actions are unlikely to change behavior unless they are optional rather than compulsory. Our findings ratify that, since education is one of the main drivers of sustainable development, there is an urgent need for coherence in shaping higher education according to sustainability issues.

Subjective well-being (SWB) has presented long-lasting interest for researchers and the recent focus on the economic approach to SWB led to increased awareness of the topic. Despite the significant number of studies, conceptualizing and assessing SWB, along with finding predictors of SWB, need further empirical exploration. Following this rationale, using statistical and econometric methods (correlation analysis, Principal Component Analysis (PCA), Multinomial Logistic Regression (MLR)) applied on data collected via a survey on students from Bucharest University of Economic Studies (363 respondents), this study explores and provides insights that support a better understanding of defining and measuring SWB. Additionally, the study offers valuable information on the main determinants of SWB for a particular group, in this case, Romanian business students. According to findings, we argue that: (1) when assessing perception of life satisfaction and happiness, Romanian students tend to make slight distinctions between these two concepts; (2) question order effect is not significant, whereas negative sentiments (such as pessimism) impact self-assessment of happiness, but not of life satisfaction; (3) the main predictors for SWB are satisfaction with current activities, level of optimism/pessimism, health, and safety of the neighborhood. This paper proposes a new approach to modeling SWB by MLR, which features expressing the dependent variable with respect to the principal factors obtained by PCA.

Artificial intelligence (AI) and its impact on a large array of economic and social facets has recently become one of the most debated topics both in academic and civic environment. Existing literature varies from topics touching on the AI ethics to the future of the labor market. Current research highlights significant divergences and a lack of consensus on the future implications of AI, leading to a heterogeneous perception among the general public. In this context, our research explores the intersection between AI and its profound impact on the labor market, focusing on business students’ perceptions of AI impact on skills, productivity and employment dynamics. The study examines how personal AI competencies, risk perception, and anticipated economic effects of AI technologies shape labor market expectations using structural equations modelling. Seven hypotheses were tested which summarize the correlations between six reflective constructs. Findings reveal that students generally perceive AI positively, recognizing its potential to increase organizational efficiency and work productivity. Our research highlights the dual impact of AI, exploring students’ perceptions of the effects of AI on society, organizations and the labor market and revealing the key links between these views and efficiency.