The new technologies, the digitalisation of processes and automation of work will change the manner of doing business, working and living. The effects of digitalisation on the economy, society and quality of life imply significant challenges of the labour market. All the participants will be concerned: authorities, companies and ordinary people. The objective of this research is to analyse the perceptions of the EU citizens about digitalisation and to highlight the differences among specific socio-demographic groups. The analysis is grounded on a composite methodology, comprising several statistical and econometric methods that provide scientific support to achieved conclusions: statistical analysis (with the primary goal to shed light on the EU citizens' perceptions about their digital technology skills), TwoStep Cluster Analysis (TSCA) (with the purpose to identify the ‘digital vulnerable groups’ and then the ‘digital vulnerable countries’ in terms of the exposure to digital divide) and logistic regression (with the main aim to quantify the impact of the relevant factors on citizens’ perceptions about digitalisation). We identified a group of respondents evaluating themselves as having meagre digital skills, very afraid that robots could steal their jobs and with low usage of the internet. They are elderly, with a low level of education, manual workers or not working, with a relatively low level of income and little Internet use. The originality of our approach is given by the fact that we focused on investigating if digital divide leads to the creation of vulnerable groups (citizens and/or countries) and if there are specific patterns in terms of the perception on being skilled in the use of digital technologies in daily life or at work and of the understanding that robots replace human on the labour market. We aim to find relevant factors for the labour market to assume targeted measures that should be taken for a better match of supply and demand on the labour market and for creating a smart labour market. It is highly needed to increase the people's confidence in their skills level and to make the most of digitalisation of the societies. The results show consistent patterns in term of socio-demographic characteristics and perception towards digitalisation. The latter will have a meaningful impact on the economy and the society in the European Union in the next period. That is why a positive attitude towards digitalisation is essential for transforming this relatively new challenge into an excellent opportunity for the future.

The aim of the study is to deep dive into the potential of green entrepreneurship and its drivers in a time of multiple challenges when green growth seeks to reconcile economic and sustainable development goals. The need for responsible business models has become evident in recent years, and companies that offer green products or services are creative, eco-friendly growth incubators and important economic actors that can change the future of society. We used a logistic regression model for 7326 companies from 36 European countries to identify what influences the decision to go green, including supply and demand factors, measures for resource efficiency and targeted policies. We found that the company’s age, its financial performance, the country’s level of development, as well as the incentive measures have a significant potential of stimulating green entrepreneurship. Our results highlight the overwhelming importance of financing. Firms in less developed countries face difficulties in developing green products and services, so support programs are needed to build green entrepreneurship in some regions. Many entrepreneurs in less developed countries are highly educated, creative, and innovative, so they can successfully run sustainable business models if the transfer of good practices is accompanied by an infusion of capital.

The development of renewable energy sources is justified by keeping a clean environment, by assurance of energy security, by job creation, all these contributing to sustainable economic growth. The paper presents the development level of renewable energy sector in Romania and the benefits of its extension, starting from the potential of Romania in this field. From natural point of view, Romania has a high potential for development of renewable energy, in the hydro, wind, solar, geothermal, and biomass fields. The research results show that even if there are certain limitations in expansion of this field, the natural potential and the advantages obtained by development of renewable energy sources require continued investments and public–private efforts to support it.

The purpose of the study is to investigate the impact of digitalization on greenhouse gas (GHG) emissions, taking into consideration the mediating effect of renewable energy consumption in the 27 European Union (EU) countries between 2000 and 2021, by employing generalized method of moments (GMM), panel-corrected standard error (PCSE) estimators, and mediating effect models. The findings show that digitization has both a direct and a partially mediating effect on net GHG emissions. This means that to reduce GHG emissions, digitalization should be used along with clean energy, environmentally friendly innovations, and low-carbon technologies. Digitalization represents a driver for increased energy consumption towards renewable energy, which in turn has a significant contribution to pollution reduction. However, the effect could be mixed, depending on the way in which digitalization is used and the country’s economic model. These findings suggest that EU countries should create a secure environment conducive to digitalization and innovation, support digital and green startups, digital transformation, and traditional industry upgrades. Also, EU governments should consider renewable energy caused by digitalization as a critical factor in preventing pollution and climate change policies, in addition to energy savings, energy efficiency, and innovation. Additionally, EU countries should improve their research and innovation policies to develop green technologies, which are essential for accelerating the transition to clean energy, improving environmental quality, and preventing climate change. Furthermore, the EU countries should consider information and communication technology (ICT) trade as an important driver for their clean energy policies.

The purpose of this paper is to draw the first lessons from the on-going coronavirus crisis and to identify viable solutions for what should become the goal of any country: transforming their own economies into sensitive and responsive economies regarding public health problems. The originality of our approach is given by its objective as well as the strategy employed for verifying research hypotheses. The objective is twofold: detecting the indicators that may constitute signals for the vulnerability of countries in times of health crisis and highlighting the underlying factors of the resilience capacity. Many indicators have been considered: six indicators concerning Covid-19 pandemic and 27 socio-economic indicators. Three main hypotheses have been formulated and tested using various statistical methods. Our findings provide deep insights for understanding how Covid-19 crisis is correlated to specific economic (urbanization, sectorial employment, health system) and demographic factors (aging, mortality). The study has succeeded in identifying the pattern of a country with greater resilience and better ability to cope with a health crisis. Our results could be useful when forecasting the spread of another pandemic wave, its impact on people’s health and estimating how some markets will be reshaped.

This article addresses the problem of the main factors driving sectoral unemployment in the Mediterranean countries most affected by this phenomenon. The choice of the four countries (Greece, Italy, Spain and Portugal) relies on the fact that they are dealing with the highest unemployment rates in the European Union and a certain typology of the economic structure. The originality of our research is offered by its direction, less tackled until now, namely the focus on the particularities of the economic sectors, trying to capture differences between them. The importance and the impact of the results are supported by the methods used to produce them, indicators and econometric models that are on trend and bring extra information to available studies. Descriptive statistics and mismatch indexes are used to outline the economic and labour market structure, while the econometric models built on panel data capture the impact of factors such as GVA growth, specialization and labour market mismatches on the unemployment rate at six economic sectors level. Our paper makes three contributions to the literature. First, we have demonstrated that agriculture is the sector of activity less sensitive to output fluctuations in terms of unemployment and can become a buffer for the jobless in times of recessions. Second, we have proved that industry, as a whole, is highly responsive to economic developments and bad specialization could worsen unemployment situation in this sector. Third, we showed that educational mismatches have a significant impact on unemployment in those sectors of activity that employ low educated workforce.