Search

The paper deals with an application of Data Envelopment Analysis (DEA) method to multicriteria performance evaluation of the Visegrad Four countries (V4) in comparison with selected advanced European Union’s (EU) countries – Austria and Germany. The aim of the paper is to analyse a degree of efficiency achieved in individual countries which is perceived as a reflection of the level of competitive potential in three reference years 2000, 2005 and 2010. The theoretical part of the paper is shortly devoted to the fundamental bases of competitiveness in the context of performance/productivity theory and the methodology of factor and cluster analysis (FA, CA) and DEA method. The multivariate methods, CA and FA, have been used to DEA modelling. The empirical part is aimed at measuring the degree of productivity and level of efficiency changes of evaluated countries by the specialized DEA approach – the Malmquist (Productivity)Index (MI/MPI) measuring the change of technical efficiency and the movement of the frontier in terms of evaluated countries. The final part of the paper offers a comprehensive comparison of results obtained by calculating the MI/MPI.

Measurement and evaluation of regional differences (disparities) is associated with the lack of integrated approach and methodology at national or regional level. The paper aims to introduce two selected multivariate statistical methods (factor analysis, cluster analysis) as a possible and convenient tool for regional differences analysis and evaluation. The main goal of the paper is to evaluate and compare regional differences at NUTS 2 level in the Visegrad Four countries on the basis of selected regional indicators in the case of the year 2010 using factor analysis and cluster analysis. Theoretical part of the paper defines, at first, the concept of regional disparities in the context of European Union's approach and deals with quantitative methods used for regional disparities evaluation. Subsequently, in the empirical part, the paper uses the factor analysis for identification of main factors of regional differences. The final evaluation and comparison of different socio-economic position between Visegrad Four NUTS 2 regions in the year 2010, results from cluster analysis that classifies the regions to homogeneous units (clusters) according to the factor similarity. [ABSTRACT FROM AUTHOR]