{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,7]],"date-time":"2026-07-07T03:07:12Z","timestamp":1783393632890,"version":"3.54.6"},"reference-count":140,"publisher":"MDPI AG","issue":"23","license":[{"start":{"date-parts":[[2025,11,29]],"date-time":"2025-11-29T00:00:00Z","timestamp":1764374400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sustainability"],"abstract":"<jats:p>This article addresses the role of human capital in socio-economic development processes during Europe\u2019s energy transition. The main empirical objectives are firstly to diagnose the overall level of human capital in the energy transition economy based on the original synthetic measure, HCIe, and secondly to analyse and assess the variation in its spatial distribution across the European socio-economic landscape, which serves as a foundation for developing a targeted policy typology directly linked to the identified cluster profiles and their specific weaknesses. The general research question is: what is the level and degree of variation in the internal structure of human capital across the European socio-economic landscape? What actions should individual European countries take to support the development of human capital in the context of the energy transition? The research concept adopted also raises additional questions. Firstly, how can the importance of human capital be captured in an economy undergoing an energy transition? Secondly, are there appropriate indicators for measuring this based on the adopted research approach? European countries were selected as the subjects of the study. In the empirical section, taxonomic methods were employed to develop a proprietary synthetic measure of human capital in a transforming energy economy (HCIe), which was then used for the hierarchical classification of entities. The internal structure of human capital was explored using multi-criteria cluster analysis with the k-means algorithm. This approach resulted in a non-hierarchical classification of entities (typologisation). The main data sources used to construct the synthetic measures were international databases: IRENA, OECD, EUROSTAT, and the World Bank. Analysis of the HCIe measure and the clustering of European countries revealed that the key risk factor for transformation is the absence of integrated human capital within individual groups of countries. This highlights the urgent need for targeted investment in health and the development of systemic and green competencies.<\/jats:p>","DOI":"10.3390\/su172310710","type":"journal-article","created":{"date-parts":[[2025,12,1]],"date-time":"2025-12-01T08:13:49Z","timestamp":1764576829000},"page":"10710","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Human Capital and the Sustainable Energy Transition: A Socio-Economic Perspective"],"prefix":"10.3390","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4351-7304","authenticated-orcid":false,"given":"Maria","family":"Klonowska-Matynia","sequence":"first","affiliation":[{"name":"Department of Economics, Faculty of Economic Sciences, Koszalin University of Technology, 75-453 Koszalin, Poland"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,11,29]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Carney, J., Hudson, R., and Lewis, J. 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