The thesis deals with information technologies on different levels of management. The first chapter analyzes a strategy level and a function of strategic documents in the IT management analyzed. The second half of the theoretical part deals with IT governance, its connection to the strategic management, and its chosen tools - decision-rights structure, service-level agreements, and accounting (focused on chargeback). The practical part of the thesis deals with IT management at the University of Economics in Prague. It analyzes and evaluates strategic documents from the IT management point of view. The second half of the practical part evaluates possibility of implementing the chosen tools of IT governance in the university's IT management.

The chargeback process is costly for the merchant. Not only does the merchant lose the revenue from the purchase, but it must also pay handling fees to the bank and risks never getting paid for provided service. The purpose of this study is to examine and investigate how to prognosticate future chargebacks by using machine learning in form of Artificial Neural Network on transaction data. Doing so can be used to minimize and decrease financial costs for the merchant. The study indicates that it’s complex to prognosticate chargebacks, but illuminates that it’s possible under certain circumstances. The created model has been concluded to be more suitable as a compliment, rather than a substitute for the current Rule-Based classification system. The model should be implemented based on economic analysis since it can be used to reduce costs and contribute to profitability over time. Furthermore, the study highlight lessons learned and complementary research areas for future studies. / Återbetalningar medför stora kostnader för handlare i form av förlorade intäkter vid återbetalning av transaktionssumman, samt tillkommande handläggningsavgifter i processen. Syftet med rapporten är att utvärdera och undersöka möjligheten att prognostisera framtida återbetalningar, genom att applicera maskininlärning i form av Artificiellt Neuralt Nätverk på transaktionsdata. På så sätt kan återbetalningar minimeras och reducera finansiella kostnader hos handlaren. Studien påvisar att det är komplext att predicera återbetalningar, men att det är möjligt under särskilda omständigheter. Modellen som skapats har konstaterats mer lämpad som ett komplement till det aktuella regelbaserade klassificeringssystemet än ett substitut. Utifrån en ekonomisk analys klargörs att algoritmen bör implementeras för att reducera kostnader och på sikt bidra till lönsamhet. Studien belyser även lärdomar, samt kompletterande forskningsområden för framtida studier.

This thesis is focused on ICT costs monitoring and controlling among enterprises, whose purpose is to maximize their market value and to achieve a profit by selling products or offering services and simultaneously these enterprises neither do operate in ICT industry nor banking and similar industries. Purpose of this thesis is to help responsible users with better understanding of causes where and why enterprise ICT cost origin. For this purpose there is formed a pattern for ICT costs monitoring and controlling. This pattern comes into use in enterprises in cases when it is necessary to discover true costs of ICT. The pattern is further convenient for costs controlling and budgeting and it could serve as a basis for ICT cost-effectiveness evaluation. Additional asset of this thesis would be an introduction of cost allocation methods, a software costs categorization in view of an acquiring form, and a description of appropriate budgeting methods.