<abstract xmlns="http://www.w3.org/1999/xhtml"><p>The business environment is reshaped by knowledge economy which has taken both competitiveness and doing business to a whole new level. Because knowledge economy plays a key role in the creation of welfare it has been classified as an important reliable indicator for comparing world’s economies. The present paper highlights the geographic distribution of knowledge economy at the level of the European Union by means of factorial analysis. Factor analysis, a well-known statistical clustering technique, has been applied on the 28 EU countries (seen in our study as random variables) with an a priori fixed number of two factors. On each variable, the realisations are given by the scores (normalized between 0 and 1) registered for year 2012 on 12 key Knowledge Economy (KE) indices. The resulting factor structure is compared to the standard geographical grouping of EU countries (NorthWest-SouthEast) in present KE literature. SPSS software has been used for the statistical analysis. The highest correlations attained were in terms of the Global Competitiveness Index, World Happiness Index, R&amp;D expenses signifying that they could also act as predictors in evaluating the status of the knowledge economy of a particular country, whereas weaker correlations can be spotted for enterprises selling online, electric energy consumption, carbon dioxide emissions and others. In the future, the same relationship can be tested to see whether the influences have changed, in the light of new available data.</p></abstract>

The business environment is reshaped by knowledge economy which has taken both competitiveness and doing business to a whole new level. Because knowledge economy plays a key role in the creation of welfare it has been classified as an important reliable indicator for comparing world’s economies. The present paper highlights the geographic distribution of knowledge economy at the level of the European Union by means of factorial analysis. Factor analysis, a well-known statistical clustering technique, has been applied on the 28 EU countries (seen in our study as random variables) with an a priori fixed number of two factors. On each variable, the realisations are given by the scores (normalized between 0 and 1) registered for year 2012 on 12 key Knowledge Economy (KE) indices. The resulting factor structure is compared to the standard geographical grouping of EU countries (NorthWest-SouthEast) in present KE literature. SPSS software has been used for the statistical analysis. The highest correlations attained were in terms of the Global Competitiveness Index, World Happiness Index, R&D expenses signifying that they could also act as predictors in evaluating the status of the knowledge economy of a particular country, whereas weaker correlations can be spotted for enterprises selling online, electric energy consumption, carbon dioxide emissions and others. In the future, the same relationship can be tested to see whether the influences have changed, in the light of new available data.

The geographic distribution of Knowledge Economy (KE) within the European Union (EU)

The Bucharest University of Economic Studies

Management & Marketing

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

The business environment is reshaped by knowledge economy which has taken both competitiveness and doing business to a whole new level. Because knowledge...

The geographic distribution of Knowledge Economy (KE) within the European Union (EU)

Online veröffentlicht: 29. Okt. 2018

Seitenbereich: 1089 - 1107

DOI: https://doi.org/10.2478/mmcks-2018-0025

Schlüsselwörter
knowledge economy, competitiveness, innovation, competitiveness index, sustainability

© 2018 Shahrazad Hadad, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

The geographic distribution of Knowledge Economy (KE) within the European Union (EU)

Online veröffentlicht: 29. Okt. 2018

Seitenbereich: 1089 - 1107

DOI: https://doi.org/10.2478/mmcks-2018-0025

Schlüsselwörterknowledge economy, competitiveness, innovation, competitiveness index, sustainability

© 2018 Shahrazad Hadad, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Schlüsselwörter
knowledge economy, competitiveness, innovation, competitiveness index, sustainability