Multidimensional comparative analysis of the competitive capacity of the European Union countries and geographical regions

Research background: The basic question we ask is whether is it possible to talk in today?s globalizing world about the uniform of the competitiveness of the economies? Posing such questions is particularly important in the case of political and economic structures such as the European Union. The competitiveness of the economies is now one of the most frequently discussed topics. In this work, due to the context of the conducted research (international comparisons of the EU countries? economies) the competitiveness of international economies will be considered in terms of international competitive capacity. In addition to the problems associated with defining this concept, there are also important dilemmas concerned with the measurement of the competitiveness. In the performed comparative analyses of European economies the research results presented within reports of ?Global Competitiveness Index? will be used.

Purpose of the article: The main purpose of the paper is to conduct a multidimensional comparative analysis of the competitive capacity of the European Union countries and geo-graphical regions of Europe.

Methods: In the paper, to study the spatial differentiation of the EU countries and geograph-ical regions of Europe in the context of their competitive capacity, the taxonomic measure of development based on median vector Weber was used.

Findings & Value added: As a result, the classification and the typological groups of EU countries and geographical regions of Europe calculated on the basis of the features describing their competitive capacity arises. The value added of these research is the analysis of competitive capacity conducted not only for EU countries, but also for geographical regions of Europe. In the paper, the verification of criteria using by World Economic Forum to assess the competitive capacity of EU economies was also conducted. In this area of the research, because of high level of correlation, many features from initial database were deleted.