The Conceptual Basis for Evaluating and Analyzing the Development Status of the Construction Sector in EU Countries
Chagovets L. O., Oriekhova T. Y.

Chagovets, Liubov O., and Oriekhova, Tetiana Ye. (2025) “The Conceptual Basis for Evaluating and Analyzing the Development Status of the Construction Sector in EU Countries.” The Problems of Economy 4:40–48.
https://doi.org/10.32983/2222-0712-2025-4-40-48

Section: World economy and international relations

UDC 004.94

Abstract:
The article provides an analysis of the key problems and development trends in the construction industry of European Union countries from 2015 to 2024. The article examines the pace of construction production across the EU as a whole and by industry sectors. It is shown that the pandemic caused a significant decline in construction volumes, with a return to pre-crisis levels occurring only after a year and a half. It is noted that the development of the construction sector within the European Union is heterogeneous and largely depends on the structure of activity segments. In recent years, civil engineering construction has begun to demonstrate relatively dynamic growth rates, indicating a reorientation of investment flows toward large infrastructure projects and the modernization of the transport network in EU countries. The analysis of employment in the construction sector highlights regional differences and the need to refine the development directions for the construction sector proposed by the European Commission. To improve the management system of the construction sector, a conceptual framework has been developed for evaluating and analyzing the development status of the construction sector in EU countries, using economic-mathematical modeling methods based on machine learning and Data Science, which enables the enhancement of regulatory and institutional mechanisms for sector modernization to prevent the risk of stagnation. The proposed framework includes models for identifying the current state of development of the construction industry across groups of countries using unsupervised machine learning methods, allowing the identification of the main differences between the selected groups based on individual characteristics; a model for forecasting the development status of the construction sector in EU countries using supervised machine learning methods; and models for evaluating the convergence of EU countries in terms of investment activity in the construction sector.

Keywords: conceptual basis, Data Science methods, modeling, machine learning, EU countries, construction industry.

Fig.: 4. Bibl.: 30.

Chagovets Liubov O. – Candidate of Sciences (Economics), Associate Professor, Associate Professor, Department of Economic Cybernetics and System Analysis, Simon Kuznets Kharkiv National University of Economics (9a Nauky Ave., Kharkіv, 61166, Ukraine)
Email: liubov.chahovets@hneu.net
Oriekhova Tetiana Ye. – Masters Student, Simon Kuznets Kharkiv National University of Economics (9a Nauky Ave., Kharkіv, 61166, Ukraine)
Email: tanyaoriekhova1001@gmail.com

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