The objective of this research was to identify the main factors of influence and their level in terms of framing ‘Ștefan cel Mare’ University of Suceava into the pattern of the sustainable university. Firstly, we have thoroughly examined the literature and correlated it with the local practices in entrepreneurship and education. This resulted in a set of key issues which we have investigated as variables throughout a questionnaire that has been applied to 348 students from ‘Ștefan cel Mare’ University of Suceava (USV) in Romania. By running the Principal Components Analysis (PCA) in SPSS, we have identified which type of academic skills and competencies acquired by students are influencing the development of the university and the development of students' entrepreneurial abilities. Results indicated that a high degree of material resources available to use by respondents is associated with a high level of academic training, thus this should be a good strategy to intensify. For the second part of the analysis, we have applied the logistic regression method to measure the combined influence of factors identified throughout the PCA. Statistical analyses showed that respondents who recorded higher interactions related to the university context gained higher entrepreneurial skills and competencies.

This paper is a feed-in regulatory analysis for the ongoing EU legislation on Artificial Intelligence (AI). The main argument is that accounting was left behind by this EU proposal for regulation and its three risk categories. The future of the Artificial Intelligence Act is both inclusive (specifically addressing many activities) and exclusive (takes out from the scope of regulation certain industries and applications). Despite the rather extensive sphere of (non)application of the proposal of regulation, accounting falls in a third category of unaddressed industries. Our argument is that accounting should be taken into consideration and be included in one of the categories, according to the regulatory proposal classification. By creating a regulatory framework for accounting in AI, a certain sense of certainty can be created in the markets and in the profession. Accounting is a decision-making tool with control capacity over financial and social behaviour, due to its informing capacity and pro-cyclicity influencing value, hence being able to create risks and possible moral hazards.

Purpose: This study investigates the perspective of small and medium-sized enterprises (SMEs) in the North-East Region of Romania regarding the adoption of artificial intelligence (AI) systems. The research aims to examine the competencies required for employees from the perspective of both the business environment and the educational sector, focusing on aligning educational programmes with the needs of Industry 4.0. Design/methodology/approach: A qualitative research method was employed, using data obtained from interviews conducted with managers from SMEs (160 interviews) and teaching staff (85 interviews) in the North-East Region of Romania. The interviews were processed using NVivo software. The study evaluates both the business environment’s perception of necessary employee skills and the educational environment’s perspective on developing relevant competencies for the workforce. Findings: The results indicate a growing demand for meta-competencies related to AI usage among employees. Additionally, there is a recognized need for coordinated efforts between the educational sector and industry to better align educational programmes with the competency requirements of Industry 4.0. Research limitations/implications: The study is limited to the North-East Region of Romania, focusing specifically on SMEs and educational institutions in that area. Originality/value: This study fills a gap in the existing literature by providing a focused analysis of AI adoption at the SME level. By examining the intersection of AI technology, workforce competencies and educational preparation in the context of Industry 4.0, this research contributes to understanding the evolving role of AI in shaping both employee profiles and organizational needs.

Healthcare service providers face recurrent systemic disruptions (e.g., pandemics, reimbursement delays, supply shortages, and regulatory shocks), yet firm-level resilience monitoring remains underdeveloped due to limited explainability and weak out-of-time validation in prior work. We develop an explainable machine learning pipeline to predict firm-level financial resilience (a financial health/robustness proxy) for outpatient healthcare providers. Using annual data for 2600 Romanian firms (Nomenclature of Economic Activities - NACE 8622) over 2014–2023, resilience is operationalised as an ordered three-class label derived from a Principal Component Analysis (PCA)-based composite score built from eight capital structure and asset composition ratios, with train-only frozen thresholds and a strict anti-leakage protocol. We evaluate multinomial logistic regression (baseline), Random Forest (RF), and HistGradientBoosting (HGB) (primary) on a prospective 2023 hold-out using Accuracy, Balanced Accuracy, and Macro-F1, with bootstrap uncertainty for key contrasts. The primary model achieves Balanced Accuracy = 0.943 and Macro-F1 = 0.944 in 2023, outperforming the linear baseline and RF; errors concentrated between adjacent classes. Model-faithful permutation importance on HGB highlights working-capital disciplines (receivables, cash, inventory, asset structure), while RF–SHAPley Additive Explanations (SHAP) is used only for auxiliary pattern exploration and stability checks, with Individual Conditional Expectation (ICE)/Partial Dependency Plot (PDP) confirming key nonlinear regimes on HGB. Overall, the results support governance-ready, interpretable resilience monitoring while maintaining a clear separation between predictive explanations and causal claims.

The exponential development of information and communication technology (ICT) through computer networks, Wi-Fi systems, wireless signals, and information storage systems has contributed to the transition to the so-called new economy, which is becoming increasingly digital and global. Due to the COVID-19 pandemic, teleworking has begun to dramatically change the work dynamics for all stakeholders. The aim of this research was to identify the main impacting factors and their level of influence in relation to the macroeconomic context of teleworking, public policies, and the legal framework regarding quality of life, as well as the effects of teleworking on employees and employers. Through empirical research, we explored the perspectives of employees and employers as main stakeholders who had operated in the teleworking field within Suceava County in Romania during 2020. In this regard, we undertook exploratory research, the results of which were processed using SPSS v.20. The insightful results have practical implications for the labor market, where an obvious increase in the share of teleworking in the total forms of work has already occurred, and the relations between employer and employee are expected to become based more and more on cooperation and less on subordination. The results also revealed an important tendency of employees to appreciate the positive effects of teleworking on other aspects of life.

The paper investigates the relationship between ESG transparency/performance and financial performance in tourism, with a focus on profitability (ROA), capital structure (D/E), and cost of capital (WACC). The empirical analysis uses a 2019–2024 panel for 10 listed tourism companies—Booking Holdings, Expedia Group, Airbnb, Marriott International, Hilton Worldwide, Hyatt Hotels, InterContinental Hotels Group, Wyndham Hotels & Resorts, TUI Group, and Carnival Corporation—covering distinct sub-sectors (OTA/Platform, Hotels, Tour Operator, Cruise). The study is based on a quantitative methodology that includes descriptive analyses and the application of advanced econometric models. Methodologically, the paper applies panel econometric models with fixed effects (firm and year), sectoral controls and robustness tests (ESG × Sector interactions, alternative size specifications). The results indicate, on average, a positive association between ESG and profitability (ROA) scores, as well as a negative relationship with WACC (indicating a lower cost of capital for firms with higher ESG), after controlling for size, country and sector. The effects are heterogeneous across sub-sectors, with the ESG–performance relationship more pronounced in hotels (where capital intensity and operational exposure are higher) and less pronounced for OTA platforms, but remain directional and statistically significant in most specifications. Overall, ESG compliance and performance emerge not only as reporting obligations, but also as strategic tools associated with sustainable competitive advantage in tourism. Therefore, the CSRD is not just a reporting obligation, but also a strategic tool that boosts financial performance and managerial innovation. The study provides directions for future research on the use of artificial intelligence in the evaluation of ESG reporting and the expansion of the analysis to other economic branches.