Analysis of regional innovation systems by neural networks and cluster analysis

Authors:
Veronika Hájková;Petr Hájek
Affiliations:
Institute of Public Administration and Law, Faculty of Economics and Administration, University of Pardubice, Pardubice, Czech Republic;Institute of Public Administration and Law, Faculty of Economics and Administration, University of Pardubice, Pardubice, Czech Republic
Venue:
COMATIA'10 Proceedings of the 2010 international conference on Communication and management in technological innovation and academic globalization
Year:
2010

Citing 1
Cited 1

Self-Organizing Maps

Self-Organizing Maps

Using a computer-based model for developing business students' skills: case study on the regional application of the model

MCBANTA'11 Proceedings of the 12th WSEAS international conference on Mathematics and computers in biology, business and acoustics

Quantified Score

Hi-index	0.00

Visualization

Abstract

The paper discusses the importance of regional innovation systems. They are defined as cooperation between companies and institutions in the development and dissemination of knowledge in innovation processes. The input variables are proposed for the analysis of regional innovation systems. They include factors related to economy, R&D and education. Data are analyzed by the model merging neural networks and cluster analysis algorithm with the aim of data dimension reduction and, moreover, the model makes it possible to visualize regional innovation systems in a topological map. The results show on different typologies of regional innovation systems in the European Union.