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EN
Innovations play the key role in the today's globalized world economy. This is a fact which also the European Union is aware of. Therefore, it is concerned with the innovation support. And individual national economies focus on the characteristics that influence their innovation potential. Several various methods are used for the evaluation of the innovation efficiency, for example the Summary Innovation Index (SII), by the means of which the individual countries are assessed through 25 indicators. This contribution aims to find out which of the indicators involved in the method are available, so that this method could be used for the evaluation of the innovation efficiency of the individual regions at the level of NUTS3. For this purpose, the Regional Innovation Index (RII) has been defined and it uses 16 indicators, the same as or similar to the original methodology, to compare the regions of the Czech Republic. RII maintains the original weight ratio of innovation input and output dimensions. RII is used as a base for the creation of regional typology, which divides the regions into those considerably above average, those above average, the average ones, those below average and those considerably below average. Moreover, the results are compared with the conclusions of another study, which used a simpler methodology. This makes us able to draw final conclusions and also to define bases for further research.
EN
The paper concentrates on the new European Union member states, i.e. the states of central and eastern Europe which entered the Union in 2004 (Czech Republic, Slovakia, Poland, Hungary, Lithuania, Latvia, Estonia and Slovenia) and 2007 (Bulgaria and Romania). The basis of the paper is the evaluation of the cohesion policy in the countries in question, which are then analysed at the level of NUTS 2 regions (cohesion regions). The aim of the socioeconomic analysis is to assess the economic level of the regions and to use the results to form their typology. Ten characteristic indicators were chosen so that the study was as complex as possible. For each indicator in the examined countries the average was calculated, which allowed for a considerable increase of the information relevance of the study conclusions. For the cartographic representation of the regional differentiation intervals based on this average and the standard deviation were used. The final part of the study presents a concluding synthesis together with the above-mentioned typology of the regions. The results are interpreted in the context of the optimal strategy selection for the regional policy determined by the EU cohesion policy.
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