Quality of life (QoL) as a category, which is an overarching goal of sustainable development, dependent on many factors both objective and subjective, should be subjected to constant monitoring in various spatial, temporal and thematic arrangements. This study assesses the spatial differentiation of European Union countries in terms of QoL and housing conditions (HCs) of their populations. Interactions between the studied phenomena were also determined. A multi-criteria decision-making (MCDM) method—the TOPSIS method—and Spearman rank correlation coefficients were used to achieve the objectives of this study. The analysis was conducted using 2019 and 2022 data from the Eurostat database (including the EU-SILC survey) and TheGlobalEconomy.com. The research showed that the housing conditions and QoL of the populations of EU countries vary spatially, being more favorable in Austria, Ireland and Slovenia and the Scandinavian countries of Denmark, Finland and Sweden and less favorable in Greece and some of the countries that joined the EU in 2004 and in 2007, viz. Bulgaria, Hungary and Romania. This study noted a very strong positive correlation between the positions of countries in the rankings created with QoL in 2019 and 2022 (0.947) and with living conditions in the years under study (0.828), as well as a rather weak correlation between QoL and HCs in both 2019 (0.272) and 2022 (0.292). This article fills a research gap because, to our knowledge, the indicated phenomena have not been analyzed to date in the contexts presented in this article.

This article aims to determine the specificity of spatial conflicts related to spatial plans concerning wind power plants. To achieve the aim of the article, all spatial plans in force in Poland were analysed, distinguishing those which determine the possibility of realisation of wind power plants. The research concerns the whole country. The literature review carried out for this article verifies approaches to spatial conflicts and identifies how planning barriers to the implementation of wind power investments are defined. The results identified Polish municipalities where spatial plans containing provisions for implementing wind power plants have been enacted. Then, through survey research, an attempt was made to identify critical spatial conflicts occurring in these municipalities. The last part of the research involved identifying and analysing Polish court decisions concerning spatial plans permitting wind power plants. These were recognised as a particular stage of spatial conflicts. The article’s novelty is the attempt to isolate regional spatial conflicts concerning wind power plants comprehensively. This applies to a broader scientific discussion (also applicable to other countries). In addition, the treatment of court cases as the final stage of spatial conflicts related to the location of wind power plants should be considered innovative. An important contribution to the international discussion is the proposal for broader (quantitative) research on the role of courts in spatial planning. Possible classifications in court settlements of parties to spatial conflicts, reasons for spatial conflicts, and ways of ending conflicts have been proposed.

The changing demographics of the global population represent a significant challenge for humanity. Such changes have an impact on the functioning of the economy, including the housing market, and necessitate constant monitoring. This study evaluated the spatial diversity of all the large and medium-sized cities in the West Pomeranian Voivodeship, situated in the north-west of Poland, in terms of three key factors: demographic potential, housing stock and their price levels. Furthermore, the interactions between the cities’ positions in the rankings, which were created on the basis of the aforementioned phenomena, were identified. In order to achieve the objectives of the study, the linear object ordering method, the Hellwig pattern method and Kendall’s tau rank correlation coefficient were employed. The research was conducted using data from the years 2018 to 2022, sourced from the databases of the Polish Statistical Office and the Analysis and Monitoring System of the Real Estate Market. The study observed a relatively strong positive correlation between the positions of cities in the ranking created for demographic potential and the level of residential property prices for the year 2020. The correlation between the positions of cities in the rankings for demographic potential and housing real estate stock was found to be very weak. The case of Koszalin was identified as an optimal location for residence due to the existing residential property stock and its prices. This was corroborated by the city’s residents, who also enabled the city to be ranked at the top of a ranking created for this phenomenon through the diagnostic variables for demographic potential. This article addresses a research gap, as, to the best of our knowledge, the indicated relationships have not yet been analysed in the contexts presented in the article.

Energy efficiency (EE) is an important driver of quality of life (QoL), which is an overarching goal of sustainable development (SD). The levels of these phenomena in the European Union (EU) vary. Previous analyses presented in the literature have focused mainly on a one-dimensional view of EE and QoL. The authors of this article, given the multidimensional nature of the phenomena under study, present both categories from a holistic perspective. The purpose of this study was to identify the level of QoL in the context of EE and to compare the results of the classification of EU countries in terms of the analyzed phenomena. The study was conducted using the ELECTRE Tri method, one of the advanced techniques of multi-criteria decision analysis (MCDA). The classification procedure used made it possible to assign countries to predefined decision-making categories on the basis of preference threshold values and dominance relations to reference profiles. The 27 EU member states were analyzed on the basis of empirical data from 2023, using a set of 20 indicators characterizing EE and QoL. Countries were assigned to one of five classes, differentiating the level of development in both analyzed areas. Optimistic and pessimistic approaches were used to assess the stability of the classifications. The analysis showed the presence of countries with consistent results (e.g., Poland and Germany), extreme countries (Ireland and the Netherlands—high QoL with low EE; Romania and Croatia—inversely), as well as non-unique cases (e.g., Malta, the Czech Republic/Czechia, and Finland). The spatial approach indicated regions requiring special support. The results of the study can be a useful tool to support the process of designing public policies aimed at integrating social, economic, energy, and environmental goals within SD.

Energy poverty (EP) is a complex socio-economic phenomenon of growing importance in European Union (EU) countries. The level of EP, along with the health of the population and the level of perceived well-being (H&W), is a fundamental element of socioeconomic development and a determinant of the quality of life of individuals and entire societies. In this study, two main research objectives were set: a comparison of country classification results obtained using a classical method (QGIS) and a method based on artificial intelligence (SOM) and assessment of the complementarity of both approaches in studying the diversity of EU countries in terms of EP and H&W. The classification results made it possible to demonstrate changes in the studied phenomena over time. The analysis was carried out using data from the Eurostat database from 2019 and 2023. The results presented in this study indicate that countries with the highest EP levels are located in two distinct regions: Eastern and Southern Europe. Countries with the lowest EP levels are located in Northern and Central Europe. In the case of H&W, higher levels were observed in northern and western European countries, while lower levels were observed in eastern and central European countries. The use of an AI-based method in socio-economic research and the comparison of the results with those obtained using the traditional method provides a more complete picture of the diversity of EU countries in terms of EP and H&W, broadening knowledge in empirical and methodological terms.