Dissertation

(English) Although the member states of the European Union (EU) and their regions are very heterogeneous, they share the same development visions and objectives, follow the EU's regional policy and guidelines and strive for economic convergence. Regional economic transformation, which is a progressive positive process of change in regional economies through structural, technological and institutional transformation, is central to their economic growth and therefore the subject of research in this doctoral thesis. The main objectives are to cluster and classify the regions of post-transition EU member states, to observe the dynamics of their economic transformation and to investigate the impact of knowledge on the economic transformation of each cluster of regions in the period from 2011 to 2021. The application of the k-means clustering method led to a clustering of the observed regions into three groups - regions as production locations, regions with growing yields and regions as knowledge centers. This disproved the first hypothesis of this thesis, according to which there is a difference in the number of clusters obtained by applying classification and clustering methods and according to the hat model of regional competitiveness. In order to test the second hypothesis, according to which significant economic transformation has taken place in the regions of post-transition EU countries during the observed period, a composite index of regional economic transformation was created for each cluster, but also for all post-transition EU regions together. The analysis of this index indicated that the regions experienced significant economic transformations during the observed period, leading to the acceptance of the second hypothesis. The highest index of regional economic transformation was observed in defined regions with growing yields, which is a direct consequence of high gross domestic expenditure on research and experimental development. It was also found that when considering the average of all regions at cluster level, the regions belonging to the cluster of regions with increasing returns achieved the highest index of regional economic transformation. Testing the validity of the third hypothesis, according to which knowledge has a statistically significant positive impact on the constructed index of regional economic transformation, required an examination of the impact of knowledge on regional economic transformation of each cluster and also of the entire sample of post-transition EU regions. The panel regression analysis applied for this purpose confirmed the positive influence ofknowledge on regional economic transformation and that the statistically significant positive influence of knowledge is most pronounced in the third cluster. This results in the most important guideline for economic policy subjects, how important it is to continuously promote the improvement of knowledge: It is necessary to further promote the development of a highly skilled workforce by investing in education at all levels and to ensure equal access to education and information for all regions in order to reduce regional inequalities, as well as to promote cooperation between different sectors, institutions and companies.