While targeting waste reduction and maintaining the value of products and resources in the system as much as possible, undertaking circular economy practices at the company level is a way of achieving entrepreneurial sustainability. This paper explores entrepreneurial decision models for adopting circular economy practices, focusing on European SMEs. Decision tree models are applied on data from Flash Eurobarometer 441 in order to uncover business strategies in relation to the implementation of circular economy practices at the company level and with the optimal level and nature of investments in the circular economy for improving economic performances of companies. The main findings of the article offer a better understanding of the relation between characteristics of European SMEs and their decisions in the field of circular economy. Such results are relevant from both macro and micro perspectives, as they can be used for customizing circular economy programs and intervention strategies for various groups of SMEs, as well as for supporting sustainable entrepreneurial decisions.

The outbreak of the COVID-19 pandemic has had a wide range of negative consequences for higher education students. We explored the generalizability of the control-value theory of achievement emotions for e-learning, focusing on their antecedents. We involved 17019 higher education students from 13 countries, who completed an online survey during the first wave of the pandemic. A structural equation model revealed that proximal antecedents (e-learning self-efficacy, computer self-efficacy) mediated the relation between environmental antecedents (cognitive and motivational quality of the task) and positive and negative achievement emotions, with some exceptions. The model was invariant across country, area of study, and gender. The rates of achievement emotions varied according to these same factors. Beyond their theoretical relevance, these findings could be the basis for policy recommendations to support stakeholders in coping with the challenges of e-learning and the current and future sequelae of the pandemic.

Sustainable innovation at a company level drives economic, environmental and social improvement at a national level. Recent evidence has shown that businesses have increased the managerial attention and investments dedicated to sustainability. This paper aims to identify the most important drivers supporting companies to develop innovation activities oriented towards making the business models more sustainable. We explore microdata from the 2016 Innobarometer “EU Business Innovation Trends” (Flash Eurobarometer 433), covering 8635 companies from 29 countries. Using statistical classification methods, we identify the most important factors that are related to innovation activities that have the potential to shape the efficiency of raw material usage and environmental protection. The most relevant factors emphasized by our analysis are: innovation performance of the country (innovation), percentage of the company turnover invested in innovation activities, percentage of total turnover invested in acquisition of machines, equipment, software or licenses, percentage of total turnover invested in company reputation and branding, including web design, percentage of total turnover invested in software development.. Also, our analysis highlights the skills that are needed the most by companies in order to support their innovation activities targeting sustainability. Our results are useful for better understanding the attention that is given to sustainability by innovative companies, and what the main factors that boost innovation dedicated to sustainability are.

Trauma scientists have raised the alarm about the devastating consequences of the Ukraine war on mental health. We examined how higher education students—as indirect victims—coped with this conflict and how they emotionally reacted during 2022. We involved 2314 students from 16 countries through an online survey. A structural equation model indicated significant relations between war-related worry about military and macroeconomics domains and two coping strategies (opposition, support giving), in turn significantly linked with six emotions. The model was strongly invariant across gender, study field, and geographic area. The most frequent emotions were anger and anxiety, followed by two future-centred emotions (hopelessness and hope). Emotions were more frequent for females and students of the countries geographically close to the war region. Our findings call for evidence-based policy recommendations to be implemented by institutions to combat the negative short and long-term psychological sequelae of being witnesses of armed conflicts.

Research and development activities are one of the main drivers for progress, economic growth and wellbeing in many societies. This article proposes a text mining approach applied to a large amount of data extracted from job vacancies advertisements, aiming to shed light on the main skills and demands that characterize first stage research positions in Europe. Results show that data handling and processing skills are essential for early career researchers, irrespective of their research field. Also, as many analyzed first stage research positions are connected to universities, they include teaching activities to a great extent. Management of time, risks, projects, and resources plays an important part in the job requirements included in the analyzed advertisements. Such information is relevant not only for early career researchers who perform job selection taking into account the match of possessed skills with the required ones, but also for educational institutions that are responsible for skills development of the future R&D professionals.

Perceived academic self-efficacy represents an important component of students’ mental health and well-being. The link between efficacy beliefs and level of academic performances relies on the fact that they regulate the anxiety and foster motivation, school engagement, effort, and perseverance of students. This paper aims to identify factors that are conducive for more efficacious beliefs in different socio-economic and educational contexts. We build our analysis on data collected from a sample of Romanian upper secondary education students on their beliefs in relation to their ability to perform at the baccalaureate exam. We employ decision tree models in order to unveil the way factors interact and predict perceived academic self-efficacy, with focus on the positive support received from parents and teachers, as well as on features of the school environment. Our results can be useful for building more resilient educational environments that support mental health and academic well-being of students.