Analysis of Transportation Companies in the Czech Republic by the Kohonen Networks – Identification of Industry Leaders

https://doi.org/10.26552/com.C.2021.1.A32-A43

  • Jakub Horák
  • Petr Šuleř
  • Jaromír Vrbka
Keywords: Kohonen networks, artificial intelligence, industry leaders, transportation, cluster analysis

Abstract

Computational models of artificial neural networks are currently used in different areas. Accuracy of results exceeds the performance of traditional statistical techniques. Artificial neural networks as the Kohonen map may be used e.g. to identify industry leaders, thus replacing the traditional cluster analysis and other methods. The aim of this contribution is to analyse the transportation industry in the Czech Republic by the Kohonen networks and identify industry leaders. The data file contains results - division of companies into a total of 100 clusters. Each cluster is subjected to analysis of absolute indicators and several parameters, average, as well as absolute, are examined. In total, 88 firms may be considered as industry leaders. Consequently, a fairly small group of companies has a strong influence on development of the whole transportation industry in the Czech Republic.

Author Biographies

Jakub Horák

School of Expertness and Valuation, Institute of Technology and Business in Ceske Budejovice, Ceske Budejovice, Czech Republic

Petr Šuleř

School of Expertness and Valuation, Institute of Technology and Business in Ceske Budejovice, Ceske Budejovice, Czech Republic

Jaromír Vrbka

School of Expertness and Valuation, Institute of Technology and Business in Ceske Budejovice, Ceske Budejovice, Czech Republic

Published
2021-01-04
How to Cite
Jakub Horák, Petr Šuleř, & Jaromír Vrbka. (2021). Analysis of Transportation Companies in the Czech Republic by the Kohonen Networks – Identification of Industry Leaders. Communications - Scientific Letters of the University of Zilina, 23(1), A32-A43. https://doi.org/10.26552/com.C.2021.1.A32-A43
Section
Operation and Economics in Transport