Regional Development in Poland
Purpose: The multidimensionality of regional development allows its issues to be viewed from various perspectives. The article aims to quantify the research area named in the title and to classify the voivodeships in Poland; that is, to segment the studied regions into subsets where development similarity is preserved. Design/Methodology/Approach: For this research, which showcases the current level of regional development in Poland, Ward's hierarchical agglomeration method was employed. As the EU regional policy primarily hinges on the NUTS 2 level, this study equates a region in Poland with each of its sixteen voivodeships. Findings: The intricacies and vagueness of measuring regional development present challenges in its identification. The need for a theoretical description and actual measurement of the contemplated process of continuous socio-economic transformation in the regions, the limited availability of complete satistical data and non-uniform criteria for evaluating the improvement of the existing state necessitate the individual selection of a specific set of tools. Quantifying the research area and employing the right classification method allowed for segmenting the voivodeships in Poland into groups of similar development, effectively presenting a statistical snapshot of this multifaceted phenomenon. Practical Implications: Taxonomic methods can are effective for regional development studies. The outlined theoretical considerations and analysis results enhance the understanding of the economic category in the title, offer insights into Poland’s current state,, and can guide socio-economic decisions and future development strategy planning. Originality/Value: The article highlights that the different levels of generalization, dynamic or spatial approaches, as well as the plurality of regional changes, mean that, taking into account the specific factors of regional development, it is examined from a variety of aspects. However, descriptions are attainable, and multivariate statistical analysis techniques prove beneficial for empirical studies.