The question of electromobility is greatly discussed theme of the present especially in connection with the reduction of greenhouse gas emissions. In order to fulfill decarbonization targets, incentives of many countries lead to the support of electromobility. In this paper we ask to which extend are Visegrád Group countries prepared for the widespread utilization of electric cars and define a new coefficient K called the infrastructural country electromobility coefficient. Its computing is covered by appropriate analysis and calculations done previously. Several indices that keep particular information about the state of preparation for electromobility are defined and debated here, as well. Their product forms the coefficient K. Obtained results include outcomes and discussion regarding the level of infrastructural electromobility preparedness for the chosen states, among which we extra focus on the position of Slovakia compared to the European Union average and European electromobility leaders. Based on the data obtained, we found out that the stage of preparation of Slovakia for electromobility among Visegrad Group countries is rather good, although it is far behind the European Union leaders. We realized that there was a rapid growth of electromobility infrastructure in Slovak Republic in the last five years as its infrastructural country electromobility coefficient grew 334 times.

The paper focuses on the evaluation of some aspects of the spatial organization of economic development of regions in the V4 countries after their accession to the EU. It focuses on the confirmation or confutation of the application of two principles of spatial organization based on the context of polarization theories, namely the polarity between western and eastern regions (i.e. the West–East gradient) and the polarity between the capital and other regions of the country (i.e. the national metropolitan gradient) at national and supranational levels. In the evaluation of the spatial polarity, the remoteness of various regions of the V4 countries from the economic core area (the Blue Banana, respectively the capital of the country) acts as the independent variable, whereby two economic indicators, i.e. the average monthly wage and the unemployment rate were chosen as the dependent variables. The analysis showed that on the supranational scale of the research in the monitored period, the increase of spatial polarisation was recorded. The increasing role of the West–East gradient and declining role of the national metropolitan gradient in the dynamics of spatial polarity has also been confirmed. The analysis has not confirmed the scale shift of polarity according to the West–East gradient to the national level, but at the same time it has pointed out the significant influence of the national metropolitan gradient in Slovakia, the Czech Republic and Hungary at this assessment level.

In the paper we evaluate the quality of life in European Union countries. The introductory database is made up of 19 variables which, in our view, appropriately capture numerous spheres of human life. The reference date for this data, taken from the Eurostat database is April 10, 2021. The Principal Component Analysis that we have used in this paper is not rare in the conditions of multivariate statistics, however, when evaluating the quality of life, it is not much used. Many authors dealing with the topic take advantage of the traditional questionnaire survey and the points-based approach when analysing data. Our objective was to demonstrate that the Principal Component Analysis can be used in evaluating quality of life, especially if it is necessary to evaluate a significant number of variables and select factors with the highest impact. Apart from the main objective-the identification of factors most impacting the quality of life in European Union countries, we also focused on the comparison of countries as per particular main factors and searched for what caused differences between them. Quality of life is also reflected in the subjective perception of responders' happiness. We were concerned to know whether the evaluated data would indicate that the feeling of happiness increases along with prosperity , or does not depend on growing prosperity at a certain stage.

The paper deals with the assessment of the landscape ecological stability on the basis of land cover at the interface of two contrasting units: Vihorlatské vrchy - mountains and Východoslovenská nížina - lowland. The intensity of eco-stabilizing ability of landscape we expressed to the coefficients of ecological stability of the landscape. The coefficient of the ecological stability we calculated with using of two methods. The first one consisted in the evaluation of eco-stabilizing ability of the land cover classes the second one in the evaluation the impact of eco-stabilizing ability of nature protected areas, zone of water protection, land cover classes and natural landscape in the studied territory. The main contribution of the paper is the comparison of two research methods with the different methodological procedures. Another benefit is the possibility of monitoring landscape ecological changes in the chronological development. In the first method we used the regular grid of squares and the second method was based of the loaded maps evaluated structures.

The paper deals with the analysis of the similarity's rate of 81 universities and other schools of university's type in EU all of which have in this consideration the same status. From each state of the European Union, three largest universities according to the number of students criterion were chosen (when such an amount of universities was existing in the considered state) and added to our database. We have used hierarchical clustering methods based on the simple join of several clusters as well as methods of explorative analysis presented by some profile diagrams in order to compare these universities. As the space analysis created in the geographical information system environment is joined here with the methods of mathematical statistics, we consider the paper being important both from the interdisciplinary and the statistical-environment analysis point of view. It points out to the fact that multi-dimensional statistical methods can be used also at interdisciplinary level.