This article deals with the deployment of an Internet of Things (IoT) technology within the energy industry (energy distribution) in the Czech Republic. The first part of the article is devoted to an assessment of the perspectives for developing IoT applications and implementing them within the economy, and then examines how the principles of multi-criteria decision-making are used to select IoT technologies for deployment in the energy industry. The selection of technology is also followed by the selection of the specific application with the highest potential benefit for the company using such a method to select the technology. The selection solution is demonstrated and further discussed from the technological and financial standpoints and illustrated via the example of choosing among two alternatives for a real-world application, very high voltage (VHV) frosting (in electric power transmission engineering, which is usually considered as any voltage between 52,000 and 300,000 V). The application solution is analyzed by how it relates to the direct vs indirect measurement of glaze ice. The result of this technical and financial analysis was that the direct glaze ice measurement variant is clearly the more advantageous one. The direct-measurement variant has a three-year payoff period, compared to six years for indirect measurement. Further, the benefits from the direct-measurement variant are 2.25 times larger than the other variant, and the five-year net profit value amounts to a profit for the direct-measurement variant while it results in a financial loss for the indirect-measurement variant. The recommended variant is to measure the icing of VHV lines directly.

This article describes and discusses research into the perspectives for deploying the IoT (Internet of Things) within the Czech energy industry. Our conclusions are based on empirical research performed among 50 energy-industry experts in 2016 and 2017. This was two-stage research in which we held interviews with these experts in order to select the set of the most acceptable IoT technologies for deployment in the energy industry, and then used the TOPSIS method to select the most suitable technologies among them for deployment in the Czech environment. For use in determining the most suitable technologies, we also defined—with the help of the mentioned experts—individual selection parameters and weightings for them, enabling us to apply the TOPSIS method to the selected set of technologies. Our result was the selection of the SIGFOX IoT technology.

This paper is devoted to issues connected with processes that can be used for the management of economic efficiency of business informatics with the support in the area of Business Intelligence. We analyze the processes of the management of business informatics economics. We propose new model that takes into account requirements on the management of economic efficiency necessitated by accounting, managers of companies, differences in the method of accounting of business informatics cost and profits etc. Our model provides information that helps to define prices and costs for services provided by business informatics to other in-house units, provides information for cost analysis of each employee, total cost of each IS/ICT section, identifying the total costs of business informatics etc.

Background and purpose: The purpose of the article is to analyse results of entrance exams and of regularly exams for foreign students in the Czech language undergraduate study programs at four faculties of University of Economics, Prague (UEP) with the intention to investigate the dependency between the results of Entrance exams from English and mathematics and (1) results of regularly exams during the study and between (2) completion rate of the study. Design/Methodology/Approach: We have analysed 4.381 records for applicants from foreign countries who applied for studies between years 2009 and 2015. We used standard statistics methods and the method of logistic regression in the form of logit model. Results: We identified weak statistical correlation between entrance exam results from mathematics and results of regular exams. The correlation coefficient varies between 0.078 – 0.283 for investigated faculties of UEP. The same indicator for English language exams presents better values and it varies between 0.218 – 0.312. If an entrance exam result is higher by one point, the probability of successful completion of studies is multiplied by values between 1.017 - 1.042 for individual faculty per one additional point. Conclusion: The results of the research in mathematics and English language show that excellent results in entrance exam cannot not guarantee successful regularly exams. Conclusion for the probability of completing studies is that the acceptable level of points for admission foreign students is between 150 and 170 points, depending on the faculty.