Evaluation of the Benelux Innovativeness in the Years 2003-2011

Authors

  • Andrzej Kobryń Politechnika Białostocka
  • Joanna Prystrom Uniwersytet w Białymstoku

DOI:

https://doi.org/10.18559/SOEP.2018.1.6

Keywords:

Social economic development, Innovative character, Regional innovation, Innovation economy, Economy, Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS)

Abstract

Due to the importance of innovation in boosting the socio-economic development of individual countries, this article presents an assessment of the innovation level in the Benelux countries (Belgium, the Netherlands and Luxembourg), which are considered to be some of the most innovative and best developed countries in the world. The level of innovation is affected by various factors, which influence the innovation of individual economies and thus far has not yet been thoroughly investigated. For this reason, using a quantitative - TOPSIS method - it was taken up to try to rank the Benelux countries' economies in terms of the level of innovation, in the light of chosen determinants of innovative capacity. The analysis showed that the highest level of innovativeness characterizes the economy of Luxembourg, followed by the economy of the Netherlands and Belgium. It was also found that the indicators of innovativeness for Luxembourg and the Netherlands generally decrease, while in the case of Belgium is shown to be slow but stable with a growing trend.

Downloads

Download data is not yet available.

References

Behzadian, M., Khanmohammadi, O. S., Yazdani, M. i Ignatius, J. (2012). A state of the art survey of TOPSIS applications. Expert Systems with Applications, 39(17).

Brzeziński, M. (2001). Zarządzanie innowacjami technicznymi i organizacyjnymi. Warszawa: Difin.

European Commission. (2001). European Innovation Scoreboard 2001. Innovation/ SMEs Programme. Luxembourg: CORDIS.

European Commission. (2002). European Innovation Scoreboard 2002. European Trend Chart on Innovation, Luxembourg: CORDIS.

European Commission. (2003). European Innovation Scoreboard 2003. European Trend Chart on Innovation. Luxembourg: CORDIS.

European Commission. (2004). European Innovation Scoreboard 2004. Comparative Analysis of Innovation Performance. Luxembourg: CORDIS.

European Commission. (2005). European Innovation Scoreboard 2005. Comparative Analysis of Innovation Performance. Luxembourg: CORDIS.

European Commission. (2006). European Innovation Scoreboard 2006. Comparative Analysis of Innovation Performance. Maastricht: MERIT.

European Commission. (2008). European Innovation Scoreboard 2007. Comparative Analysis of Innovation Performance. Maastricht: UNU-MERIT.

European Commission. (2009). European Innovation Scoreboard 2008. Comparative Analysis of Innovation Performance. Maastricht: UNU-MERIT.

European Commission. (2010). European Innovation Scoreboard 2009. Comparative Analysis of Innovation Performance. Maastricht: UNU-MERIT.

European Commission. (2011). Innovation Union Scoreboard 2010. The Innovation Union's Performance Scoreboard for Research and Innovation, Maastricht: UNU- -MERIT.

European Union. (2012). Innovation Union Scoreboard 2011. Research and Innovation Union scoreboard. Maastricht: UNU-MERIT.

European Union. (2013). Innovation Union Scoreboard 2013. Enterprise and Industry. Maastricht: UNU-MERIT.

European Union. (2014). Innovation Union Scoreboard 2014. Enterprise and Industry, Maastricht: UNU-MERIT.

European Union. (2015). Innovation Union Scoreboard 2015. Internal Market, Industry, Entrepreneurship and SMEs. Maastricht: UNU-MERIT.

European Union. (2016). European Innovation Scoreboard 2016. Internal Market, Industry, Entrepreneurship and SMEs. Maastricht: UNU-MERIT.

Hwang, C.L. i Yoon, K. (1981). Multiple attribute decision making: Methods and applications. Berlin: Springer Verlag.

Ishizaka, A. i Nemery, P., (2013). Multi-criteria decision analysis. Methods and software. Chichester: John Wiley & Sons.

Kobryń, A. (2014). Wielokryterialne wspomaganie decyzji w gospodarowaniu przestrzenią. Warszawa: Difin.

San Cristóbal Mateo, J. R. (2012). Multi-criteria analysis in the renewable energy industry. London: Springer Verlag.

Trzaskalik, T. (2014). Wielokryterialne wspomaganie decyzji. Metody i zastosowania. Warszawa: Polskie Wydawnictwo Ekonomiczne.

Tzeng, G. H. i Huang, J. J. (2011). Multiple attribute decision making. Methods and applications, Boca Raton: CRC Press.

OECD.StatExtracts.(2014). Pobrane 16 grudnia 2014 z http://stats.oecd.org/ Powierzchnia, ludność i stolice wybranych krajów. (2014). Pobrane 16 grudnia 2014 z stat.gov.pl/cps/rde/xbcr/gus/1.1_pow_lud_stolice_kr_r.xls.

Downloads

Published

31-01-2018

Issue

Section

Articles

How to Cite

Kobryń, Andrzej, and Joanna Prystrom. 2018. “Evaluation of the Benelux Innovativeness in the Years 2003-2011”. DEMO 6 (1): 91-114. https://doi.org/10.18559/SOEP.2018.1.6.

Share

Similar Articles

51-60 of 75

You may also start an advanced similarity search for this article.