This study investigates managers’ perceptions of digitalization and artificial intelligence (AI) adoption within the framework of Industry 4.0, emphasizing the relationship between technological modernization, organizational culture, and sustainability. Drawing on empirical data collected in 2025 from 150 Romanian companies ’managers by applying a structured questionnaire, followed by a multivariate analytical approach supported by the Benjamini–Hochberg correction, the research identifies critical managerial perceptions that influence the success of digital transformation. The findings show that managers recognize digitalization as a strategic opportunity for process optimization and competitiveness. At the same time, they perceive it as a structural challenge driven by legacy systems, financial constraints, and limited digital competencies. Similarly, managers view AI as a valuable tool for data analysis and market forecasting, while also expressing concerns related to ethical, technical, and cybersecurity risks. The study further reveals managerial ambivalence toward Industry 4.0. Although automation and IoT are considered inevitable for maintaining competitiveness, their implementation remains constrained by logistical and cultural barriers. By integrating technological, organizational, and human dimensions, this research contributes to the literature on sustainable digital transformation. It provides an in-depth understanding of how managerial perceptions mediate the balance between innovation, responsibility, and long-term resilience. Finally, the results offer actionable insights for policymakers and business leaders seeking to align digitalization and AI initiatives with sustainable development objectives.

In order to evaluate the impact of k-means clustering on portfolio optimization, this study groups enterprises based on profitability, liquidity, and solvency indicators. The study confirms the positive correlation between risk, return, and risk-adjusted performance through an analysis of historical financial records. After the companies were divided into two groups, equal-weighted portfolios were created using these groupings. Although they produced higher returns, cluster 1 portfolios, which included more risky companies, also showed more volatility. Cluster 0 portfolios, on the other hand, offered less risk and more consistent results. Portfolios clustered by ROA, OCFM, and GPM outperformed the market benchmark and produced the highest returns adjusted for risk, according to Sharpe Ratio analysis. Furthermore, the study emphasizes that although solvency and liquidity metrics play a role in portfolio selection, increased liquidity does not always translate into improved risk-adjusted performance. In terms of methodology, Silhouette Analysis outperformed the Elbow technique in determining the optimal number of clusters. All things considered, the results show how data-driven clustering techniques may be used to align portfolio strategies to investors’ risk tolerances.

Ensuring a balance between economic growth and environmental sustainability is crucial to reduce the impact of CO₂ emissions and ensure sustainable economic development for future generations. The goal of this study is to investigate the influences of the adjusted gross dispensable income (GDI) per capita, the gross domestic product (GDP) per capita, energy consumption per capita, economic inequality in the population (GINI), and the median age on the carbon emissions in 27 European countries. In the dynamic panel analysis, CO₂ emissions represent the dependent variable, while adjusted GDI/capita, GDP/capita, energy use/capita, median age, and GINI are the independent variables. The valid results of the model show us that only the past values of CO₂ emissions, GDP/capita, and median age significantly influence the carbon emissions in the European countries analyzed. The median age and the GDP/capita have inversely proportional impacts on the carbon emissions in Europe. A 1% increase in GDP/capita produced a 0.006% decrease in carbon emissions in Europe. The younger the population is, the higher the carbon emissions. In contrast, the adjusted gross disposable income/capita, the energy consumption/capita, and economic inequality do not significantly influence CO₂ emissions/capita in the European countries and period analyzed.

Corporate sustainability has become integral to business strategy worldwide, including in Romania. With growing awareness of environmental impacts and the need for sustainable development, Romanian corporations are increasingly adopting green policies. This study explores how Romanian companies balance economic goals with environmental responsibilities and examines how managers’ perceptions of financial outcomes, innovation, and proactive orientations influence sustainability practices. The research adopts a novel management-focused perspective to analyze factors driving sustainable practices within organizations. A two-pronged methodology was employed: qualitative data were collected via a questionnaire administered to 149 CEOs and CFOs, providing insights into financial health and strategies and performing the statistical analysis to comprehensively evaluate long-term environmental and economic sustainability. The results show moderate to strong positive correlations between financial performance, proactive orientation, innovation, and ecological performance. While proactive and innovation parameters significantly impact ecological policies, financial performance plays a more moderate, indirect role. Key findings reveal that transport companies are the least likely to adopt green strategies, while the age of companies does not play a vital role. The study underscores the complex interplay between corporate sustainability and economic performance, offering valuable insights into the challenges and opportunities for Romanian businesses in advancing green policies.

This chapter examines how artificial intelligence (AI) and RFID technologies enhance efficiency, transparency, and sustainability in public sector processes, focusing on municipal waste management. Using the city of Oradea, Romania, as a case study, the chapter analyses the design, implementation, and outcomes of a Pay-As-You-Throw pilot project based on RFID-enabled identification and AI-supported monitoring. The analysis shows that integrating AI and RFID improves waste traceability, enables fair and data-driven billing, optimizes collection routes, and supports environmentally responsible behaviour. AI-based object recognition and predictive analytics further automate operational processes and reduce costs. Despite technical, organisational, and investment-related challenges, the Oradea pilot demonstrates the scalability of AI-enabled solutions and provides practical insights for municipalities seeking to modernize public services through digital transformation.

The living standards of Europeans have been facing serious chal­lenges starting with the Covid-19 pandemic, and continuing with the Rus­sia-Ukraine war and all its threats. Europe is facing one of its outcomes in the current gas shortage problem, impacting negatively various aspects of the Europeans’ lives, such as rising inflation. However, the rising trend of in­flation was noticed even before the problems related to the Russian gas sup­ply. The current paper presumes the Covid-19 pandemic’s lockdown and the changes in consumption behaviour also have a relevant contribution to the rising inflation; in this respect, the authors used both deductive – by collecting data regarding the national indicators – and inductive methods, as well – by conducting a survey in the Western part of Romania investigat­ing the consumption patterns. The pandemic challenged individuals, insti­tutions, entire systems, countries and regions to adapt to hardship and to create new ways of overcoming the restrictions imposed by the lockdown; although considering the stressful times and situations created by this phe­nomenon, it also enhanced negative adaptive and coping behaviours. This paper’s focus falls on the level and ways of spending during the pandem­ic, to assess if the rising inflation started with the irrational spending during the pandemic