scholarly journals Artificial Intelligence for Cluster Analysis: Case Study of Transport Companies in Czech Republic

2021 ◽  
Vol 14 (9) ◽  
pp. 411
Author(s):  
Eva Kalinová
Keyword(s):  
Cluster Analysis ◽  
Czech Republic ◽  
Financial Analysis ◽  
Transport Sector ◽  
Economic Sectors ◽  
Accounting Data ◽  
The Czech Republic ◽  
Kohonen Networks ◽  
Further Development

What is the situation of the transport sector in the Czech Republic and what is its importance for the economy of the Czech Republic? How and to what extent do businesses operating in this sector influence the sector as such, and how many businesses in this sector have such influence? Additionally, what happens if the most important businesses in the transport sector go bankrupt, and which businesses are the most important ones? Searching for the answers to these questions is a subject of this contribution, focusing primarily on the cluster analysis using artificial neural networks (ANN), specifically with Kohonen networks, which represent the main method for processing a large volume of not only accounting data on transport companies. In this research, the dataset consists of the financial statements of transport companies for the years 2015–2018. The research part of the contribution deals mainly with the issue of the transport sector’s development in the years 2015–2018 with the companies operating in this sector and tries to identify the most important companies in terms of their importance for this sector. The results show that the whole transport sector is influenced mainly by the two largest companies, whose potential changes can affect companies themselves but to a great extent also the development of the whole transport sector. For the two companies, financial analysis is carried out using ratios, whose results show that despite the negative values of the important value generators of one of these companies, the company is still able to significantly influence the situation in the transport sector of the CR. This information is a clear guide for experts, development analysts, to determine the further development of the whole sector when focusing on the development of the two specific companies only. A question arises as to how the created model can be applied to other economic sectors, especially in other EU countries.

scholarly journals Using Kohonen networks in the analysis of transport companies in the Czech Republic

2019 ◽  
Vol 61 ◽  
pp. 01010 ◽  
Author(s):  
Tomáš Krulický
Keyword(s):  
Neural Networks ◽  
Cluster Analysis ◽  
Czech Republic ◽  
Financial Statements ◽  
Transport Sector ◽  
The Czech Republic ◽  
Operating Profit ◽  
Kohonen Networks ◽  
Kohonen Map ◽  
Further Development

The transport sector has a significant impact on the performance of the Czech economy. Transport companies, of course, have their own specificities, whether they deal with ecology or the financial and economic situation. It is precisely the economic position of a transport company that needs to be analysed in order to identify the need for change, to predict the further development of such company. For analysis, a variety of methods is used, of which artificial neural networks are a very interesting and effective tool. The aim of this paper is to make a cluster analysis of transport companies operating in the Czech Republic based on this tool. The data of the financial statements of transport companies in the Czech Republic in 2016 are taken into account. Only some items from the financial statements are selected for analysis. The file is then subjected to a cluster analysis, specifically using the Kohonen networks – Statistica software. In accordance with the methodology of the contribution, the data is divided into three sets - training, testing and validation. Companies were divided into clusters in the 10x10 Kohonen Map. Some clusters are significant in terms of number of companies. These clusters are further analysed. Specific conclusions are made: A larger company generates, on average, a higher operating profit, larger companies achieve higher ROE and, in the case of a larger company, the financial leverage acts more positively.

scholarly journals Entrepreneurial subjects in forestry and data mining from accounting data in the Czech Republic

2004 ◽  
Vol 52 (5) ◽  
pp. 131-146
Author(s):  
Zbyněk Šmída
Keyword(s):  
Data Mining ◽  
Czech Republic ◽  
Financial Analysis ◽  
Business Environment ◽  
Financial Statement ◽  
State Enterprise ◽  
Ratio Analysis ◽  
Volume Data ◽  
Accounting Data ◽  
The Czech Republic

Forests owned by the state in the Czech Republic are managed by Forests of the Czech Republic, state enterprise with its headquarters in Hradec Králové. The private companies (established during the economic reform in 1992 and privatization in 1994) carry out silvicultural and logging activities in state forests on the basis of contracts. This study is focused on forest enterprises (contractors); the current situation of business environment in the Czech Republic was studied. There have been found 38 236 forestry entrepreneurs in the Czech Republic, and divided according to legal title, to numbers of employees onto groups on the basis of size and availability of their accounting data in the first part of the article.The second part deals with data mining from accounting by a process known as a Financial statement analysis, which has to make an informed decision for owners or managers of the enterprise. Ratio analysis is regarded as the basic methodical instrument of financial analysis. Ratio analysis effectively summarizes multiple financial statement categories into few relative indices of performance and financial position. It is powerful method for managing with the complexity and volume data presented in financial statements. The relative indices converse financial statement categories into measures and it helps control for differences across companies and across time. This article contains chosen forestry contractors and describes the most useful economic indicators (ratios) and takes into account possible utilization in the sector generally.

scholarly journals Study on a Brain-Controlled Pneumatic Actuator to Assist Emergency Braking of a Vehicle

2021 ◽  
Vol 23 (3) ◽  
pp. F49-F57
Author(s):  
Ryszard Dindorf ◽  
Jakub Takosoglu ◽  
Piotr Wos
Keyword(s):  
Czech Republic ◽  
Legal Framework ◽  
Freight Transport ◽  
Current Situation ◽  
Transport Sector ◽  
The Czech Republic ◽  
The Road ◽  
Emergency Braking ◽  
Road Freight

This article deals with the issue of safety within the road freight transport sector with regards to the securing of cargo on a vehicle. The first part of the article focuses on the legal framework that regulates this issue in the Czech Republic. The second part is based on a case study and survey conducted among drivers of the road freight transport vehicles into their awareness of what they understand is meant by securing and secure cargo. The case study was carried out in a specific transport company and includes an analysis of the current situation and concrete measures for improving safety while securing timber for transport.

scholarly journals The application of Kohonen networks for identification of leaders in the trade sector in Czechia

Equilibrium ◽  
2019 ◽  
Vol 14 (4) ◽  
pp. 739-761 ◽  
Author(s):  
Jaromír Vrbka ◽  
Elvira Nica ◽  
Ivana Podhorská
Keyword(s):  
Neural Networks ◽  
Cluster Analysis ◽  
Czech Republic ◽  
Value Added ◽  
Financial Statements ◽  
Data Set ◽  
The Czech Republic ◽  
Return On Equity ◽  
Kohonen Networks ◽  
Trade Sector

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.

scholarly journals A Case Study into the Safety Compliance within the Road Freight Transport Sector with Regards to Securing Cargo

2021 ◽  
Vol 23 (2) ◽  
pp. F43-F48
Author(s):  
Ján Ližbetin ◽  
Mária Stopková
Keyword(s):  
Czech Republic ◽  
Legal Framework ◽  
Freight Transport ◽  
Current Situation ◽  
Transport Sector ◽  
The Czech Republic ◽  
The Road ◽  
Safety Compliance ◽  
Road Freight

This article deals with the issue of safety within the road freight transport sector with regards to the securing of cargo on a vehicle. The first part of the article focuses on the legal framework that regulates this issue in the Czech Republic. The second part is based on a case study and survey conducted among drivers of the road freight transport vehicles into their awareness of what they understand is meant by securing and secure cargo. The case study was carried out in a specific transport company and includes an analysis of the current situation and concrete measures for improving safety while securing timber for transport.

scholarly journals Strategic Challenges of Human Resources Allocation in Industry 4.0

Information ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 120
Author(s):  
Majid Ziaei Nafchi ◽  
Hana Mohelská
Keyword(s):  
Czech Republic ◽  
Human Resources ◽  
Industry 4.0 ◽  
Industrial Revolution ◽  
High Tech ◽  
Economic Sectors ◽  
The Czech Republic ◽  
Services Sector ◽  
Productivity And Competitiveness ◽  
Near Future

The emergence of the fourth industrial revolution (Industry 4.0, hereinafter I 4.0) has led to an entirely fresh approach to production, helping to enhance the key industrial processes and therefore increase the growth of labor productivity and competitiveness. Simultaneously, I 4.0 compels changes in the organization of work and influences the lives of employees. The paper intends to construct a model for predicting the allocation of human resources in the sectors of the national economy of the Czech Republic in connection with I 4.0. The model used in this research visualizes the shift of labor in the economic sectors of the Czech Republic from the year 2013 to the following years in the near future. The main contribution of this article is to show the growth of employment in the high-tech services sector, which will have an ascending trend.

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