Ms Jigani Adina-Iuliana (p), Ms Ciucu (Durnoi) Alexandra-Nicoleta, Ms Vlad Anca-Elena

How happy are Europeans, and what exactly contributes to their well-being? This study aims to identify whether there are common patterns among European countries and the main factors associated with the level of happiness. The analysis is based on seven indicators considered relevant for assessing well-being, selected from the World Happiness Report for the period 2015–2022 and correlated with seven of the 17 Sustainable Development Goals (SDGs), including good health and well-being, decent work and economic growth, partnership for the goals and reduced inequalities. The analyzed indicators are also directly correlated with the indicators proposed by the European Union in the cohesion strategy for 2021–2027, which aims to reduce disparities between European countries. The results showed that the applied methods illustrate two clusters among analyzed countries. To highlight similarities between countries, cluster analysis was applied. The results indicate the existence of two distinct groups of countries. The first cluster mainly includes Western European countries, characterized by a higher standard of living. The second cluster brings together most Central and Eastern European countries, as well as cases such as Spain and Portugal. The differences between groups are particularly visible in the case of indicators regarding the perception of corruption, healthy life expectancy at birth, logarithmic GDP, and freedom to make choices. The results suggest that well-being in Europe is not distributed evenly, and institutional and socio-economic factors play an important role in shaping the level of happiness at the national level. They can also provide useful pointers for Cohesion Policy post-2027, which places a special emphasis on people and their needs, aiming to "leave no one behind", and serves as a primary tool for European solidarity. The results of happiness research in Europe contribute to achieving the cohesion objective PO5 – a Europe closer to its citizens, by providing direct information about the needs and perceptions of each nation. The study's results help in developing policies tailored to the specifics of each country, supporting their sustainable and integrated development.

Ms. Ioana Ioanas, Dr. Lucian Vilcea, Ms. Andra Sandu, Ms Adriana Cosac, Prof. Liviu-Adrian Cotfas (p)

Cohesion policy, as a cornerstone of the European Union's strategy for reducing regional disparities, increasingly relies on evidence-based diagnostics of labour market competencies to guide investments in human capital development and smart specialisation. Yet, generating granular, comparable, and timely data on skill demands across regions remains a persistent methodological challenge, particularly when traditional instruments such as surveys and official statistical classifications struggle to capture the rapid evolution of occupational requirements.
This paper addresses this gap by presenting an automated, scalable workflow for extracting and classifying labour market intelligence from large volumes of job posting data, using locally deployed open-weight large language models. Drawing on a corpus of over 56,000 job advertisements collected from a major Romanian recruitment platform over a period of nearly nine months, the pipeline combines web data extraction with a multi-stage semantic enrichment process. This includes occupational classification aligned with the ESCO taxonomy — the EU's standardised framework for Skills, Competences, Qualifications and Occupations — as well as automated skill extraction and mapping.
The resulting dataset covers 2,152 validated IT job postings, classified across 75 ESCO occupations and enriched with 2,797 unique skills mapped to 881 ESCO skill concepts. By anchoring the output to ESCO, the methodology directly enables cross-regional and cross-national comparisons, a key requirement for cohesion policy monitoring and evaluation. The approach runs entirely on consumer-grade hardware without reliance on commercial cloud APIs, making it replicable and cost-effective for regional development agencies, managing authorities, and research institutions in less developed regions operating under tighter resource constraints.
From a cohesion policy perspective, the methodology offers a practical instrument for tracking skill mismatches, supporting the design of European Social Fund Plus interventions, and aligning regional educational and vocational training strategies with actual employer demand. The paper discusses how continuous application of this pipeline can serve as a monitoring tool for smart specialisation strategies and contribute to a more dynamic, data-driven approach to reducing territorial inequalities in the digital economy.

Ms Diana-Elena Popescu (p), Mr Adrian Domenteanu

This research analyses airport passenger traffic across European Union airports from 2020 to 2025 using monthly data from the Eurostat database. This work examines the impact of the COVID-19 crisis and the subsequent recovery dynamics as reflected in traffic seasonality, operational efficiency indicators, airport clustering structures, passenger traffic forecasts, and the evolution of international traffic shares. A particular focus is placed on the role of the European Union's cohesion policy in supporting air traffic development by investing in airport infrastructure, enhancing regional connectivity, attracting new airlines, and reducing regional disparities through increased mobility in these areas. The analysis is based on a curated dataset covering more than 100 airports from 12 European countries. Data preprocessing and statistical analysis were done in Python, using performance indicators, clustering techniques, Principal Component Analysis (PCA), and the Holt-Winters exponential smoothing model to capture trend and seasonal dynamics. The results indicate a strong recovery in air traffic following the COVID-19 crisis, with predictable seasonal variations and heterogeneous development trajectories across airports and countries. Trend-based forecasts suggest continued traffic growth toward 2030, particularly in tourism-oriented and marginal regions of Europe. The findings highlight the contribution of cohesion policy investments to improved regional accessibility and sustained air transportation development within the European Union.

Prof. Camelia Delcea (p), Prof. Daniela Luminița Constantin, PhD Student Bianca Cibu, PhD Student Ioana Ioanăș, PhD Student Andra Sandu

This paper aims to bring light into the process of transforming the strategic innovation capacity into sustainable development outcomes in the case of the European Union (EU) Member States, with the aim of identifying territorial typologies relevant for the design of EU Cohesion Policy post-2027. In a context marked by geopolitical uncertainty, green and digital transitions, and increasing pressure on public budgets, understanding the efficiency of this transformation process becomes crucial for shaping more targeted and performance-oriented policy interventions.
Using Eurostat data, two composite dimensions are constructed, namely an input dimension measuring the strategic innovation capacity of the member states, and an output dimension related to sustainable development outcomes. Considering that the extracted data are either benefit-type or cost-type variables, a normalization or an inverse normalization step was performed prior to using the indicators for the analysis.
Grey systems theory, through the grey clustering method, offers a distinct tool for complex and uncertain situations, characterized by limited data. Over years, it has been proven that grey systems theory has proved its applicability in a wide range of domains, which have made it the primarily option for the researchers in the field when dealing with incomplete data.
To capture the complexity of the innovation-to-sustainability nexus, multiple weighting scenarios are developed, ranging from full emphasis on innovation capacity to full emphasis on sustainable outcomes. Additionally, a four-year dynamic perspective is incorporated using a grey clustering approach, allowing the observation of countries’ movements across clusters. Robustness is ensured through 100,000 simulations with slightly varying coefficients, enabling an assessment of cluster stability.
The results reveal distinct territorial typologies. “Systematic leaders” demonstrate a consistent ability to translate innovation inputs into sustainable outcomes. Other groups include countries with strong innovation capacity but limited sustainability performance, as well as states achieving relatively good outcomes despite weaker innovation inputs. These asymmetric patterns suggest that innovation capacity alone does not automatically guarantee sustainable transformation.
The findings provide evidence for a more nuanced, place-based approach to EU Cohesion Policy post-2027. Rather than uniform support mechanisms, differentiated strategies are needed to address structural inefficiencies in the innovation-to-sustainability conversion process and to foster upward convergence across Member States.