This study aims to examine the dynamic connection among economic growth, CO₂ emissions, energy consumption, and foreign direct investments (FDIs). The panel section considers the period of 2000–2020 for 25 EU Member States excluding Malta and Croatia. The annual data are retrieved from the World Bank and Eurostat databases. The empirical analysis used estimation procedures such as first- and second-generation panel unit root tests (CIPS) and panel ARDL based on the three estimators PMG, MG, and DFE. The Hausman test indicated that the PMG estimator is the most efficient. The PMG and DFE estimators suggested that there exist only short-run causalities from CO₂ emissions, energy consumption, and FDIs to GDP growth rate, while the MG estimator proved the existence of both short-run and long-run causalities. Three hypotheses on the positive correlation between the three regressors and GDP growth rate were in general confirmed. The identified causalities may represent recommendations for policymakers to stimulate the renewable energy sector to improve sustainable development.

This study provides a bibliometric analysis of the Triple Bottom Line (TBL) framework in sustainable development, highlighting its ethical dimensions and corporate responsibility. Using R Studio and VOSviewer, we examine research trends from 2001 to 2023, revealing a 23.23% annual growth in publications, strong global engagement, and increasing interdisciplinarity. Thematic analysis shows a shift from broad management concepts to specialized areas such as circular economy, life cycle assessment, and climate impact, demonstrating TBL’s transition from a theoretical model to an actionable sustainability framework. Our findings provide practical insights for policymakers and organizations, supporting data-driven decision-making in sustainability strategies. By integrating ethical accountability with economic, social, and environmental goals, TBL offers a structured approach to guiding sustainable business practices and informing policy development.

Sustainable economic growth is desired to be achieved by governments targeting economic, social, and environmental benefits. The idea of circular economy model is to consider feedback effects from proper waste management instead of one-way effects typical with the classical linear model. Several sectors of society contribute to circular economy and its monetary and environmental outputs in a sustainable way. The aim of this paper is to analyze the dependencies and causalities of circular economy and economic developments in the EU. The research objectives include testing (i) whether research and development (R&D) expenditure, GDP per capita and generation of municipal waste per capita influence the recycling rate of municipal waste, and (ii) whether R&D expenditure, generation of municipal waste per capita and the recycling rate of municipal waste influence the GDP per capita. The relevant indicators are obtained from Eurostat. The research methods of fixed effects and Tobit approach are used to study the statistical relevance of the two models. The pairwise causality of variables is tested by Dumitrescu–Hurlin causality test. One result of the study is that technology development, by a decreasing life of products, leads to an increase of waste generation. Therefore, environmentally friendly technologies should be produced.

Purpose: Digitalization has been the driving change in creating jobs and increasing economic growth in recent years. However, the digitalization of countries and sectors is uneven. The paper focuses on various factors that have an impact on the economic development and well-being in EU countries. Its purpose is to show the evolution of EU countries in terms of digital transformation and how other indicators, such as e-government, human development index, labour productivity, and economic growth influenced the well-being in EU countries in 2019–2021.Design/methodology/approach: The dataset consists of 15 numerical indicators extracted from Eurostat and World Bank databases. We apply principal component analysis and cluster analysis.Findings and Practical Implications: The main research results show that the first dimension – named the impact of innovation on well-being – is dominated by e-government, the percentage of ICT specialists in total, internet use by individuals, the Human Development Index, the Digitalization Index, the Happiness Indicator, human capital, and the integration of digital technology. The second dimension is characterized by government expenses and productivity. Finally, the third dimension is dominated by the GDP growth rate. 77.67% of the total variance is explained by the first three principal components.Originality: Four clusters have been identified by means of the K-Means clustering algorithm. All four clusters are well determined, with cluster 1 including the three Nordic countries ranking first, followed by cluster 3 of well-developed countries and cluster 4 containing mainly emerging economies.