Economic development has been a major priority for the European Commission, with significant amounts of Structural and Cohesion Funds being allocated in this direction. With the enlargements of the Union in 2004, 2007 and 2013, the Regional Development Policy faced a new challenge, with the disparity between new members and the community average being a notable one. The literature is divided with respect to the impact generated by funds allocated through the Regional Development Policy, as some authors claim the existence of positive effects, others identify conditional positive effects and other authors identify only negative effects and say that the whole support system needs to be rethought. This research presents an empirical approach to the issue of the effectiveness of the European Community’s support system for business environments. An analysis is performed at the microeconomic level in order to quantify observable effects at the level of the SMEs that have benefited from non-reimbursable financial aid. The data obtained indicate that Structural and Cohesion Funds for business environments have a significant effect in the medium and long terms, contributing to the achievement of the general objective of the Regional Development Policy (reducing economic disparities between EU member states).

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 world experience proves that the development of the innovational society is directly linked to the concept of human capital through the development of the sectors where the accumulation of human capital takes place and primarily in the sphere of education and science. This paper is an exploratory research based on the analysis of macroeconomic indicators on digital performance, highlighting the progress made in terms of digital competitiveness, as well as on the digital framework and systemic conditions for education. The educational system is in a continuous dynamic; to cope with changes, this system is forced to make intensive use of creative techniques at all levels of it. However, in this context, many teachers are concerned about standardised processes and tests, compared to creative ones. Creativity has been and is combined with science: art and technology turn people’s ideas into facts. At the beginning of the twenty-first century, the importance of innovation for growth (especially economic growth) was recognized, but the question of non-technological innovation is also raised. To this end, consideration was given to the processing and systematisation of secondary data taken from official reports prepared and published by the European Commission. Thus, we refer to the reports of the Digital Economy and Society Index (DESI) and the Human Capital Index (HCI) with reference to Romania, in the time horizon 2018-2020. The DESI 2020 reports are based on 2019 data. The UK is still included in the DESI 2020 and the EU averages are calculated for 28 member states. The DESI has been recalculated for previous years to reflect changes in the choice of indicators and corrections to the data. Human capital is a key trigger for sustainable, inclusive economic growth, but investment in health and education has not received the well-deserved attention. The index establishes a direct link between improved outcomes in health and education, productivity and economic growth.

Conventional macroeconomic indicators are released with a time lag and may therefore provide limited information about rapidly changing market expectations, creating a need for complementary high-frequency indicators capable of capturing the informational content of financial narratives. This study examines whether sentiment extracted from unstructured financial text contains incremental predictive information for short-horizon market dynamics in the context of Eastern Europe’s green and digital transition. Using financial news and discourse collected between May 2025 and May 2026, a FinBERT-based Daily Sentiment Index (DSI) is constructed for selected technology, energy, and sustainability-related narratives and linked to market indicators and representative assets, including the DAX, UiPath, and OMV Petrom. The empirical strategy combines Granger predictability tests, vector autoregression (VAR), GARCH(1,1) models with sentiment effects, lead–lag analysis, Bai–Perron structural-break tests, and Markov-switching specifications to assess predictive temporal relationships, volatility dynamics, and time variation in sentiment–market interactions. Forecasting utility is further evaluated through an expanding-window out-of-sample exercise in which a sentiment-augmented VAR is compared with a benchmark autoregressive specification using one-day-ahead DAX returns, with relative predictive accuracy evaluated via the Diebold–Mariano test. The results indicate that lagged sentiment contains statistically significant predictive information for subsequent market returns and that incorporating the DSI significantly improves out-of-sample forecast accuracy relative to the benchmark specification. The evidence also reveals heterogeneous and time-varying responses across the selected cases: technology-related assets exhibit comparatively differentiated sensitivity to macro-sentiment conditions, whereas the energy case displays stronger exposure to transition-related narratives. Structural-break and regime-dependent estimates further suggest instability in the relationship between ESG sentiment and market performance over the sample period, but do not establish a permanent structural transformation in investor preferences. The study contributes to the narrative-economics and computational-finance literature by providing applied evidence that domain-specific textual sentiment contains incremental short-horizon information beyond conventional market dynamics and can complement lagged macroeconomic indicators in financial forecasting and risk-monitoring applications.

This research explores the structural transformation of contemporary financial mar-kets as they pivot from traditional fundamental indicators toward a "narrative eco-nomics" paradigm, where informational flows and collective sentiment strongly cor-relate with asset price discovery. The primary objective is to evaluate the efficacy of Computational Sentiment Analysis as a real-time early warning mechanism for mar-ket volatility, specifically addressing the critical latency gap inherent in official mac-roeconomic "hard data". Adopting a quantitative methodology rooted in Data Science, the study utilizes the FinBERT deep learning architecture to analyze a 12-month lon-gitudinal dataset (May 2025 – May 2026) of financial news and discourse. Framed strictly as an exploratory, multi-entity case study rather than a sector-wide analysis, the investigation focuses on strategic proxies of the 'Twin Transition' in Eastern Eu-rope: Technology (UiPath), Energy (OMV Petrom/Hidroelectrica), and Banking (Transilvania Bank). Consequently, the findings highlight localized, context-specific dynamics rather than establishing broad, sector-wide behavioral rules. The findings provide exploratory support for a potential "regime shift" in market behavior regard-ing sustainability; ESG narratives transitioned from being perceived as a systemic risk in late 2025 to a primary factor associated with market value by early 2026. The evi-dence indicates patterns consistent with a "digital resilience" effect, wherein technolo-gy assets successfully decoupled from the industrial stagnation of traditional proxies, such as the German Deutscher Aktienindex(DAX). Conversely, the energy sector dis-played diminishing marginal impact of economic narratives regarding geopolitical shocks, with investors increasingly prioritizing long-term transition risks and indus-trial demand over short-term alarmist headlines. The study concludes that unstruc-tured textual data serves as a vital leading indicator for market dynamics, underscor-ing the imperative for integrating advanced Natural Language Processing (NLP) into modern economic forecasting and resilient risk management strategies.