Sborník 2009 díl 2. - Fakulta informatiky a managementu - Univerzita ...

INPUT AND OUTPUT INNOVATION TYPE IN CZECH, POLISH AND
SLOVAK REGIONS AT THE BACKGROUND OF THE EUROPEAN SPACE 1
Małgorzata Markowska
Wrocław University of Economics
malgorzata.markowska@ue.wroc.pl
Key words:
Innovation – positional classification – NUTS 2 level regions
Abstract:
The article presents classification results obtained using positional statistics of the EU
NUTS 2 level regions with regard to innovation level of INPUT and OUTPUT type.
Eurostat database was used with reference to characteristics indicated, within the
framework of the European Innovation Scoreboard, for the description of innovation.
Special attention was devoted to the evaluation of Czech, Polish and Slovak regions’
position in the obtained classification.
Introduction
Notions referring to innovation are usually confined to the description of the due
economic category depending on its scale eg. macro-economy, mezzo-region, or an
enterprise. An internal division of innovation within their scope is emphasised less
frequently, which was very well presented in Eurostat statistics. Methodology of
innovation measurement in the EU statistics distinguishes five groups of indicators
covered by two types of categories: INPUT and OUTPUT. Innovation diversification at
the level of NUTS 2 regions is significant also in the countries of 2004 EU accession.
The study of innovation in regional dimension
European Innovation Scoreboard (EIS) in the domain of innovation collects information
in five groups of topics divided into two areas: INPUT and OUTPUT. Innovation
measure of INPUT type is facilitated by 15 indicators divided into the following
thematic groups [1]:
factors stimulating innovation: tertiary education graduates per 1000 population aged
20-29 – % share of tertiary education graduates (in overall population number aged
25-64), broadband penetration indicators (number of broadband lines per 100
inhabitants), share of population aged 25-64 participating in continuing education,
level of education obtained by young people (% of population aged 20-24 who at
least graduated from post-secondary schools);
knowledge creation: % share of public expenditure spent on R&D in the total value of
GDP, % share of expenditure on R&D in business, in the total GDP value, share of
moderately advanced and highly advanced research and scientific projects (measured
1 The paper was prepared within the framework of N 111011433 grant “Knowledge Based Economy
(KBE) vs. regional development in the European space of NUTS-2 level. Econometric measurement
methods”
54