Institutional measurement of structural characteristics of residential real estate markets using the method of cluster analysis

The article examines the use of IT technologies and cluster analysis tools to solve the problem of classifying regions of Ukraine according to the level of their institutional development. Recognizing the importance of effective institutional frameworks for economic growth, social stability and governance, the research focuses on using data-driven approaches to assess and classify regional institutional dynamics. Through a combination of data collection, statistical analysis, and machine learning methods, the study aims to provide an understanding of the spatial distribution and characteristics of institutional development in the regions of Ukraine. Using cluster analysis methodologies, such as K-means clustering, the study identifies distinct groups or clusters of regions with similar institutional profiles. In addition, the paper explores the role of IT technologies, including geographic information systems (GIS), data visualization tools, and database management systems, in facilitating the analysis, interpretation, and dissemination of results. In addition, the study examines the potential implications of regional classification for policy formulation, resource allocation, and development planning at the national and local levels. Through its innovative approach, the study contributes to the dissemination of knowledge about regional differences, institutional dynamics and development trajectories in Ukraine, as well as providing practical information for policymakers, researchers and practitioners who seek to promote inclusive and sustainable development across the country.