O32 - Management of Technological Innovation and R&DNávrat zpět

Practical analysis of the policies implemented by countries successful in the field of science and technology is crucial, especially in the context of optimal policy selection for countries needing technological development. In this context, ranking the world's countries in terms of technological development is important for increasing the effectiveness of the policies to be implemented in this field. This study ranks 28 OECD countries on seven key science and technology indicators in 2022 using multi-criteria decision making (MCDM) methods. In the analysis, first, the importance of the variables was ranked based on the entropy method. Then, a ranking was made among the selected countries in terms of technological performance using the weighted aggregated sum product assessment (WASPAS) method. The findings obtained with the WASPAS method were confirmed with the additive ratio assessment (ARAS) method. Among the identified variables, the export market (share of computer, electronics and optics sector) parameter was selected as the most dominant criterion. Korea, Germany, Japan, France and the Netherlands were determined to be the best performing in terms of basic science and technology indicators. On the other hand, it can be said that Chile, Latvia, Luxembourg and Lithuania need more effective policies in terms of technology and innovation indicators. In this context, it can be suggested that the policies implemented by countries at the forefront in technological development should be a guide for other countries.

The aim of the paper is to identify differences in innovation efficiency of national innovation systems of Slovakia and selected countries of the European Union (Austria, Belgium, Bulgaria, the Czech Republic, Estonia, Germany, Romania and Sweden) in the period 2006-2015. The relative efficiency model applied uses a non-parametric method known as data envelopment analysis (DEA) in a super-efficiency version with a constant-returns-to-scale technology and input orientation. The data selection is based on innovation indicators and methodological aspects of the model. The authors discovered that Austria and Germany achieved an efficient score for technological efficiency, Belgium, Estonia, Romania and Slovakia for economic efficiency, and only Austria for overall efficiency. The research identifies peers for Slovakia among all the EU countries at all levels of efficiency, provides several recommendations for improvement and also confirms the existence of small countries' resulting bias.

The paper deals with an analysis of economic impacts of ICT implementation within the public administration, which is called e-Government. The current situation in the Czech Republic is discussed using data about particular implemented tools, such as the contact points of public administration, data mailboxes or basic registries of public administration and more. In the paper there are evaluated impacts of these projects not only on public administration and public sector, but on the overall economic environment of the state including discussion of the rate of bureaucratic burden, transparency of the legal system or cyberspace security. In spite of the fact that a number of significant e-Government projects has been already implemented in the Czech Republic, there is still unused potential of other projects, whose adaptation could have positive economic impacts.

The paper evaluates innovative performance in terms of theoretical and methodological concept of learning economy applied to the EU countries. Implications of this assessment for quality-based competitiveness are also discussed, and the positions of EU countries are compared as to different sources of competitiveness (cost vs. knowledge-based advantage) and technology knowledge (internal innovative capacity vs. technology transfer). The theoretical and methodological concept of learning economy has so far not been applied to the new EU members. The paper starts with the introductory description of the key theoretical and methodological concepts and clarification of the applied terms and methods. The exploited data set is described and major results of the analysis of organisational models presented. The structural aspect includes classification according to industries, occupations and countries. The impact of national differences on organisational models is evaluated. The typology of organiyational models is subsequently compared against the typology of innovators and sources of competitiveness.

Slovakia ranked to the poorest innovation performers in the EU 25 area in early 2000s. While the country's economics was booming due to high influx of foreign investment, there was real danger that Slovakia would convert to the "greatest assembly line" in Europe, with little own innovation efforts employed in production. Poor innovation performance of Slovakia was given by an ineffective national innovation system and inadequate innovation policies. Substantial increases in R&D spending and structural changes in allocation of public resources (towards applied research and new technologies) were the basic preconditions for establishing a knowledge-based economy.