This study aims to investigate the influence of emerging digital technologies, such as artificial intelligence (AI), the Internet of Things (IoT), and cloud computing, on the digital intensity index (DII). The research method employed involves quantitative analysis of the indicators regarding DII and emerging digital technologies, conducted based on data published by Eurostat for EU members in 2021. During our research, we formulated and tested hypotheses about the relationship between the DII and emerging digital technologies, and the effect on the DII of using AI-based technologies in various economic processes. The formulated hypotheses were validated via four regression models designed during this study, using the most relevant factors. Our research results demonstrate that the DII is positively influenced by emerging IoT and cloud computing digital technologies, as well as the use of AI technologies based on machine learning and AI-based robotic process automation (RPA) software. Furthermore, the same positive influence was identified in human resource management and recruitment processes compared to the intensity with which these technologies are used in other economic processes. Based on these findings, this study offers persuasive arguments for implementing emerging digital technologies at the EU organizational level to achieve significant increases in digitalization levels.

The adoption of Industry 4.0 technologies supports the digital transformation of production processes, making them more efficient. This study examines how digital infrastructure, digital skills, and the use of cloud technologies influence labor productivity in European Union countries. Using econometric methods, including linear regressions and fixed-effects panel regressions, the analysis highlights the important role digital skills play in boosting productivity. It also identifies the adoption of cloud solutions as a catalyst for process efficiency, while widespread high-speed internet coverage supports the connectivity of smart systems. However, variations in the development of digital infrastructure and workforce readiness across EU member states present challenges to overall labor productivity. The study concludes that strategic investments in automation and digital infrastructure, along with improving the workforce’s digital skills, are essential to making Industry 4.0 a key pillar of economic competitiveness. By examining how workforce digital skills and certain Industry 4.0 technologies affect labor productivity, this research adds valuable insights to the specialized literature.

The goal of this paper is to conduct a bibliometric analysis of the scientific literature about the sustainability of digitalization in the energy sector in order to capture the main challenges and trends in the transition towards it. The bibliometric analysis of the scientific literature was carried out by interrogating the Scopus database, using a set of keywords considered relevant for the analyzed field and for the goal of the proposed research. The purpose of the study was, on the one hand, the depth of the research into these topics during the 2013–2021 period, in terms of the number of scientific papers, the topic, abstract and keywords associated, the geographical area of origin and the authors’ affiliation and on the other hand, an analysis of the existence of possible links between these topics formulated through three hypotheses. The results obtained reveal the researchers’ concerns for digitalization in the energy sector, the existing correlations between the keywords analyzed and the tendencies registered in the field of digitalization in the energy industry in order to ensure higher sustainability.

This article aims to establish an overview of sustainable development practices within organizations in Romania, to analyze how these practices are connected to GRI (Global Reporting Initiative) indexes, and to identify the connection between the efforts made to ensure sustainable processes and the economic performance of the enterprise. Given the ever more prevalent digitalization of the company processes, implementing a sustainability management system and a sustainability monitoring system becomes more accessible, and there is increasing transparency of the information on the activities supporting sustainability. Using the methodology, the authors carried out a quantitative and qualitative analysis of the content of the sustainability reports published by Romanian companies in the top 500 by the number of employees. The economic and financial data on these companies were taken from the topfirme.ro platform. Based on the sustainability reports published by the companies, the sustainability score was calculated using the reported data, according to the GRI (Global Reporting Initiative) standard and analyzed considering the industry in which the organizations operate, specific industries being more sensitive to environmental issues due to certain specificities of their economic activity that is based on processes prone to hurt the environment. During the research, hypotheses were formulated and tested regarding the factors that could influence the reporting of activities in support of sustainability (the sustainability report score and the page count of the sustainability report) and the economic performance of organizations (profit, income). One of the study’s conclusions was related to the financial performance of companies expressed by the net profit. It is positively influenced, although to a small degree, but promising in terms of the future of company policies on freedom of association and collective bargaining, expressed in the sustainability report through the GRI index. Regarding the company belonging to a particular industry sector, the research proved that the companies’ sustainability policies are not influenced by it, which could point to the idea that sustainability issues are equally crucial for all industries. Furthermore, an essential conclusion of the research is that the performance and the reliability of sustainability policies must be monitored and implemented within an integrated sustainability management system, which would ensure a high level of coherence and transparency of the guidelines, the provided data, but also of the monitoring within companies or by the stakeholders. Finally, the research offers results regarding the interest of Romanian organizations in the measures and actions taken to ensure the sustainable development of the economic environment.

The goal of this paper is to conduct an analysis of the scientific literature on the green economy in Romania and to capture the main challenges in making the transition towards it. Despite the barriers and incomplete legislation, Romania has sufficient resources and the potential to increase the percentage of the green economy, especially as the UE offers incentives for aligning to European standards. An analysis of the scientific literature was conducted via exploratory research in the Scopus database, based on key topics within the thematic range of the green economy. The study focused on the one hand the depth of the research regarding these topics in Romania during the 2007–2021 period and on the other hand, an analysis of the existence of possible links between these topics. The connections between the topics were analyzed through nine hypotheses. The results obtained reveal the researchers’ concerns for the way the principles of the green economy are applied in Romania and the existing correlations between these analyzed topics and how they are reflected in the economic reality. These results can represent a starting point as regards the diversification of policies and measures aimed at improving the implementation of the principles of the green economy in Romania.

Technological advancements in algorithmic personalization are widely believed to influence user behavior on online gambling platforms. This study explores how such developments, potentially including AI-driven mechanisms, may affect cognitive and motivational processes, especially in relation to risk perception, decision-making, and betting persistence. Using ordinary least squares (OLS) and panel regression models applied to behavioral data from a gambling platform, we examine patterns that are consistent with increased personalization between two distinct time periods, 2016 and 2021. The datasets do not contain any direct metadata regarding AI interventions. However, we interpret changes in user behavior over time as indicative of evolving personalization dynamics within a broader technological and contextual landscape. Accordingly, our conclusions about algorithmic personalization are inferential and exploratory, drawn from temporal comparisons between 2016 and 2021. Our findings show that users receiving personalized bonuses or making early cash-out decisions tend to adjust their stake sizes and betting frequency in systematic ways, which may reflect indirect effects of technological reinforcement strategies. These behavioral patterns raise important ethical and regulatory questions, particularly regarding user autonomy, algorithmic transparency, and the protection of at-risk users. This research contributes to the literature on digital behavior influencing gambling by framing the analysis as observational and quasi-experimental and suggests that further studies use experimental and log-level data to more specifically analyze the algorithmic effects. However, no causal claims can be made about AI influence as the temporal contradictions are interpreted as broad phenomena of technological developments, since they are not measured as algorithmic interventions. Further studies should also investigate the development of predictive models aimed at countering gambling addiction; evaluate the long-term ethical implications of algorithmic personalization; and discuss potential solutions codeveloped to foster a responsible gambling climate.