Abstract
Research background: The trade sector is considered to be the power of economy, in developing countries in particular. With regard to the Czech Republic, this field of the national economy constitutes the second most significant employer and, at the same time, the second most significant contributor to GNP. Apart from traditional methods of business analyzing and identifying leaders, artificial neural networks are widely used. These networks have become more popular in the field of economy, although their potential has yet to be fully exploited.
 Purpose of the article: The aim of this article is to analyze the trade sector in the Czech Republic using Kohonen networks and to identify the leaders in this field.
 Methods: The data set consists of complete financial statements of 11,604 enterprises that engaged in trade activities in the Czech Republic in 2016. The data set is subjected to cluster analysis using Kohonen networks. Individual clusters are subjected to the analysis of absolute indicators and return on equity which, apart from other, shows a special attraction of individual clusters to potential investors. Average and absolute quantities of individual clusters are also analyzed, which means that the most successful clusters of enterprises in the trade sector are indicated.
 Findings & Value added: The results show that a relatively small group of enter-prises enormously influences the development of the trade sector, including the whole economy. The results of analyzing 319 enterprises showed that it is possible to predict the future development of the trade sector. Nevertheless, it is also evident that the trade sector did not go well in 2016, which means that investments of owners are minimal.
Highlights
The trade sector is a very important area of the national economy in the Czech Republic
Findings & Value added: The results show that a relatively small group of enter-prises enormously influences the development of the trade sector, including the whole economy
The data set will not contain the data of the companies that did not perform their main activities during the entire monitored period. This applies to the companies that were CLOSED during the period, and companies that commenced their activities during the period
Summary
The trade sector is a very important area of the national economy in the Czech Republic. It is important to predict the future development of the sector. A certain group of companies influences the trade sector, and the development of the whole national economy. It is very important to identify sector leaders. Popular neural networks can be used to identify leaders, even if their potential has yet to be fully exploited. They have many advantages over conventional methods — they are flexible to use and capable of quickly and accurately analyzing complex data. Kohonen networks are a specific type of neural networks that can be used for data clustering, which will be crucial to achieving the aim of the article
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