The hypercompetitive global economy of the 21st century is a hub of innovation, technology, talent, skills, speed, efficiency, productivity, and satisfaction. Within this context, the organizations are looking intensely for people with skills and talents that can differentiate themselves in all that noise. The human capital became slowly but surely a mean of efficiency and growth, especially through the premises of digitization, and a key issue of sustainability. The current research is meant to identify and highlight any correlations that might appear between the population’s welfare of 11 Central and Eastern European Countries (CEECs) which are members of the European Union (EU), and the components of the digitization trend, including the new human cloud industry, ICT, and the connectivity to the Internet of Things. In order to achieve the needed insights, the multiple regression analysis was employed, and the latter tested the panel models with fixed effects, both from a temporal and country perspective. The results showcased a positive connection between the dependent and independent variables, confirming that the digitization of the economy and the developed human capital will ultimately lead to the increase of population’s welfare. Moreover, the findings are consistent with specific insights for each of the 11 CEECs, showing that digitization and the influence of human capital is differentiated across the latter in terms of their overall effect and amplitude. The research is limited by the timeframe and countries included in the study, and it can be furthered by determining the impact of digitization on the economies of the EU28 countries grouped by level of development, and by using other significant indicators for analysis.

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.

Sustainable tourism, in the cultural context, is a fundamental element for the economic development of some local communities. There are many factors that can influence the success of this type of tourism, but any action or strategy adopted should be closely related to the satisfaction of the tourist. This research focuses on a heritage destination of an archaeological nature, and is aimed at analyzing the profile of the cultural tourist and his/her level of satisfaction after visiting the site. Information was collected using a closed questionnaire given to tourists. An ANOVA analysis has been used to determine the relationship between sociodemographic characteristics and satisfaction, with significant results found in relation to gender and income level. This study has helped to highlight what underlies the differences in tourists’ post-visit satisfaction. These analyses have provided information that can be used in the planning of future sustainable tourism marketing strategies; thus, this study provides some recommendations on how to improve the provision of services and the management of these types of heritage elements.

The current work aims to analyze the main themes related to artificial intelligence (AI) and sustainable development during the pandemic period. This study provides an overview of the specialized literature related to AI and sustainability from the beginning of the pandemic through 2023. The present paper analyses scientific literature emphasizing both artificial intelligence's positive and negative impacts on sustainable development objectives (SDGs). To conduct the research, we employed bibliometric analysis and text-mining techniques to identify the major themes in the literature indexed in the Web of Science and Scopus databases. Firstly, we used descriptive measures to identify the authors' impact, the article production by country, the main keywords used, and other descriptive data. We further used data reduction methods based on co-word analysis (such as multiple correspondence analysis) on authors' keywords to show patterns in the themes explored in the literature. Bibliometric analysis was supplemented by text mining using Latent Dirichlet allocation (LDA) and structural topic modeling on abstracts to provide a comprehensive view of scientific debates on AI and sustainable development. Our research has identified various themes in the literature related to AI and sustainable development. These themes include social sustainability, health-related issues, AI technologies for energy efficiency, sustainability in industry and innovation, IoT technologies for smart and sustainable cities, urban planning, technologies for education and knowledge production, and the impact of technologies on SDGs. We also found that there is a significant positivity bias in the literature when discussing the impact of AI on sustainable development. Despite acknowledging certain risks, the literature tends to focus on the potential benefits of AI across various sectors. In addition, the analysis shows a growing emphasis on energy efficiency, which is facilitated by the use of AI technologies. Our study contributes to a better understanding of current scholarly discussion trends and emerging scientific avenues regarding AI and sustainable development. It also highlights the areas where research is needed and the implications for practitioners and policymakers.

In the current digital era, digital technologies develop and emerge rapidly, businesses, especially the electronic sector more connected to information technology, facing challenges in the terms of its technology infrastructure and tactical directions. That’s why most of them adopt the latest digital technology (DT) and design novel business strategies and models. The growing significance of AI in the transformation of manufacturing operations and the demand for a thorough knowledge of the variables affecting its adoption serve as the driving forces behind the study. Several researchers have presented that digital technology can lead toward AI adoption. Though, previous studies lack an efficient transformation pathway. Therefore, this study establishes an inventive approach and aims to investigate the direct link between digital technology and AI adoption, the mediating function of knowledge sharing (KS) between them, and explore the moderating impact of privacy and security that assist in the acceleration of AI adoption in electronics manufacturing enterprises through the antecedent of digital technology. This study is quantitative in nature, random sampling method and questionnaire is used as a survey tool. Depending on 298 questionnaire data from electronic firms of Saudi Arabia, this study performs multi-level correlation and regression analysis to evaluate study hypotheses. Findings confirm that digital technology has a positive influence on AI adoption. In addition, outcomes corroborate that knowledge sharing mediates in the linkage between digital technology and AI adoption. The results also proved that privacy and security have a positive moderation impact on the association between digital technology and AI adoption. This study enlighten that the adoption of this framework enables electronic manufacturing companies to strategically integrate digital-technologies to promote effective AI adoption, increase its operational efficiency, and sustain a competitive advantage in the constantly evolving manufacturing landscape. The outcomes as well supplement the previous study on the linkage between digital technology and AI adoption, expand application space and theoretical boundary from the perspective of knowledge sharing, privacy and security at the managerial level, and give reference for AI adoption in, as electronics manufacturing firms.

Innovation requires creativity, risk-taking, and the ability to manage change effectively, all of which are closely linked to emotional intelligence. Individuals with high levels of emotional intelligence are more flexible, adaptable, and resilient in technological advancements and are better able to respond effectively to new challenges and opportunities. Thus, this study aims to recognize the significant role of emotional intelligence, along with the mediation of innovative work behavior (IWB) and the moderation role of cultural intelligence in the attainment of innovation performance. This is quantitative research and for data collection, a questionnaire was used in healthcare institutions. The result shows that emotional intelligence is an antecedent of innovation performance. The finding also proved that IWB mediates the linkage between emotional intelligence and innovation performance. In addition, the outcomes show that cultural intelligence strengthens the relationship between emotional intelligence and innovation performance. However, the current dynamic business world has created an urgency to understand the linkage between the employee’s emotional intelligence and employee innovative performance, particularly taking into consideration the mediation effect of IWB. Emotional intelligence and innovation are closely linked, and innovative work behavior connects this link in a stronger way. This study offered a unique framework for achieving innovation performance through the nexus of emotional intelligence, innovative work behavior, and cultural intelligence.