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The development of private brands on the Czech market, and consumers point of view at this trend
Paskerová, Kateřina ; Postler, Milan (advisor) ; Průša, Přemysl (referee)
Práce přináší ucelený pohled na problematiku privátních značek. Poukazuje na trendy v oblasti maloobchodních značek ve světě a Evropě, podrobně analyzuje nabídku a vývoj privátních značek na českém trhu. Hodnotí tyto značky z hlediska objemu prodejů, výrobkových kategorií, jakostních a cenových pater, strategií obchodníků a prodejních kanálů s důrazem na diskontní prodejny. Je uveden přehled nabídky privátních značek největších maloobchodních společností působících na českém trhu. Dále se práce věnuje spotřebitelskému chování a pohledu českých zákazníků na privátní značky. Na základě průzkumů zákaznického chování jsou popsány současné postoje, zkušenosti, očekávání a celkový přístup zákazníků k vlastním značkám, jsou zkoumány motivy nákupu a frekvence nákupu, názory na kvalitu, cenu, šíři nabídky, obaly vlastních značek, propagaci apod. V poslední části práce jsou vyhodnocena dvě dotazníková šetření zaměřená na privátní značky provedená v letech 2005 a 2008 v řetězcích Ahold a Tesco.
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Analysis of the EU regulations in the field of Information and Telecommunication technologies and their effect on the single market
Hart, Ludvík ; Procházka, Pavel (advisor) ; Strejček, Ivo (referee)
The bachelor thesis describes the EU regulations in the field of information and communication technologies (ICT), particularly the Digital agenda for Europe strategy. These regulations are then tested for their influence on the European single market. The major question answered here is whether the EU regulations in field of ICT have a positive impact on the EUs single market. Answer to this question helps us evaluate the ongoing Digital agenda strategy. The impact of the regulations is analysed by induction of the following indicators, international trade, ratio of population buying online, DESI index and NRI index. With this method it is possible to tackle the wide range of fields the Digital agenda covers. I conclude this work with the statement, that European ICT regulations do have a positive impact on the single market, although are problematic due to the slow legislative process and low efficiency in addressing the regulated issue.
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Risk group of persons with disabilities on the labour market in Prague from 2005 to 2015
Hošková, Laura ; Maule, Petr (advisor) ; Lukášová, Tereza (referee)
The theoretical part of the Bachelor Thesis comprehensively illustrates the status and representation of persons with disabilities (PWD) on the current labour market in the Czech Republic. In a general manner, the Thesis looks at the employment policy as well; especially its legislative basis in the legal framework of the Czech Republic and selected EU countries. Furthermore, the legal obligations of employers of PWD and the possibilities of fulfilling the mandatory share of PWD employment are stated. Findings of two qualitative employment studies are presented showing that PWD enter the labour market equipped with specialized competencies, which they are willing to complete by retraining programmes in case of need. The employers perceive the employment of PWD mainly as a financial profit, granted to them by the state; and the legislative conditions are a sufficient incentive for them. The questionnaire survey pointed out that the weakness in the employment of PWD is the lack of part-time jobs, which are highly demanded among them. Therefore the Thesis presents a solution, which could be the creation of shared work positions.
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On possible approaches to detecting robotic activity of botnets
Prajer, Richard ; Palovský, Radomír (advisor) ; Pavlíček, Luboš (referee)
This thesis explores possible approaches to detecting robotic activity of botnets on network. Initially, the detection based on full packet analysis in consideration of DNS, HTTP and IRC communication, is described. However, this detection is found inapplicable for technical and ethical reasons. Then it focuses on the analysis based on network flow metadata, compiling them to be processable in machine learning. It creates detection models using different machine learning methods, to compare them with each other. Bayes net method is found to be acceptable for detecting robotic activity of botnets. The Bayesian model is only able to identify the botnet that already executes the commands sent by its C&C server. "Sleeping" botnets are not reliably detectable by this model.
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Serverless single page application in JavaScript
Zikmund, Marian ; Pecinovský, Rudolf (advisor) ; Suchan, Vladimír (referee)
The goal of this thesis is to design and develop a framework for building modern single- page application in the JavaScript programming language and describe this approach to development. The work also contains the documentation for a more comfortable use and customization. The content is divided into eight chapters. The introduction is followed by the retrieval of information resources, including the specifics of the JavaScript programming language and explanation of the formation of single-page application. The description of the basic principles of their functioning, motivation and justification, when and why this approach is appropriate is also included. The work is primarily focused on the issue of single-page application, for which the use of the JavaScript programming language is crucial. For this reason, this work provides a whole chapter about this programming language, also including a description of its history and role in the context of others. Below are the common characteristics of single-page applications frameworks, built on top of the library ReactJS, whose formation is engaged in the following chapter. The developed framework also contains the user guide. The practical outcome of this work is an open source framework for creating serverless single-page applications, which is due to its architecture and documentation appropriately adaptable.
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Řízení IS/ICT se zaměřením na sourcing služeb informačního systému
Šebesta, Michal ; Voříšek, Jiří (advisor) ; Havlíček, Zdeněk (referee) ; Příklenk, Oldřich (referee) ; Král, Jaroslav (referee)
Research on outsourcing has been around for several decades, while recent evolution in the information systems discipline towards ICT service commoditization significantly changes the context of decision-making. Services that are available on-demand via the Internet allow organizations implementing functions they demand in a fraction of time. This trend represents a chance for organizations seeking to use advanced ICT services without a need of major investments. Problem is the current lack of guidelines and tools for managing ICT services and their outsourcing. Given the trends on the ICT service market, it is expected that much of the IT management in the future will encompass the ICT services and utilize service-level structures. Methods currently available are either too broad or encompass only small part of the whole problem. Ad-hoc or unsound decisions in this area might cause major complications in terms of quality, usability, integration, and consequently influence total cost of organizational IT. Organizations need to either revise existing models or propose and implement completely new models to manage their IS/ICT. This thesis deals with the management of IS/ICT with focus on the ICT services outsourcing. It discusses available sourcing models in the literature and links them to the various interconnected areas. Based on these areas, it presents an integrated view on IT outsourcing strategies. Most importantly the thesis proposes an original concept for decision-making about outsourcing of ICT services named the SOURCER framework. This approach utilizes the presented outsourcing strategies, and introduces a complex methodology and decision-making criteria that will assist organizations with selection of ICT services in order to maintain and manage a most suitable ICT service portfolio. The decision-making is based on four essential viewpoints: function, costs, time, and quality. These viewpoints are discussed, individually analyzed, and serve as a basis for further research. The whole framework is developed and validated according to Design Science Research Methodology (DSRM). Individual components are evaluated using a survey among a group of selected IT managers. Proof of concept is then established by a case study on framework use in a real organization. This case study covers strategy specification, business--IT alignment, specifying service architecture and its interconnections, outsourcing, and management of the ICT service portfolio.
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Clustering and regression analysis of micro panel data
Sobíšek, Lukáš ; Pecáková, Iva (advisor) ; Komárek, Arnošt (referee) ; Brabec, Marek (referee)
The main purpose of panel studies is to analyze changes in values of studied variables over time. In micro panel research, a large number of elements are periodically observed within the relatively short time period of just a few years. Moreover, the number of repeated measurements is small. This dissertation deals with contemporary approaches to the regression and the clustering analysis of micro panel data. One of the approaches to the micro panel analysis is to use multivariate statistical models originally designed for crosssectional data and modify them in order to take into account the within-subject correlation. The thesis summarizes available tools for the regression analysis of micro panel data. The known and currently used linear mixed effects models for a normally distributed dependent variable are recapitulated. Besides that, new approaches for analysis of a response variable with other than normal distribution are presented. These approaches include the generalized marginal linear model, the generalized linear mixed effects model and the Bayesian modelling approach. In addition to describing the aforementioned models, the paper also includes a brief overview of their implementation in the R software. The difficulty with the regression models adjusted for micro panel data is the ambiguity of their parameters estimation. This thesis proposes a way to improve the estimations through the cluster analysis. For this reason, the thesis also contains a description of methods of the cluster analysis of micro panel data. Because supply of the methods is limited, the main goal of this paper is to devise its own two-step approach for clustering micro panel data. In the first step, the panel data are transformed into a static form using a set of proposed characteristics of dynamics. These characteristics represent different features of time course of the observed variables. In the second step, the elements are clustered by conventional spatial clustering techniques (agglomerative clustering and the C-means partitioning). The clustering is based on a dissimilarity matrix of the values of clustering variables calculated in the first step. Another goal of this paper is to find out whether the suggested procedure leads to an improvement in quality of the regression models for this type of data. By means of a simulation study, the procedure drafted herein is compared to the procedure applied in the kml package of the R software, as well as to the clustering characteristics proposed by Urso (2004). The simulation study demonstrated better results of the proposed combination of clustering variables as compared to the other combinations currently used. A corresponding script written in the R-language represents another benefit of this paper. It is available on the attached CD and it can be used for analyses of readers own micro panel data.
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Míry podobnosti pro nominální data v hierarchickém shlukování
Šulc, Zdeněk ; Řezanková, Hana (advisor) ; Šimůnek, Milan (referee) ; Žambochová, Marta (referee)
This dissertation thesis deals with similarity measures for nominal data in hierarchical clustering, which can cope with variables with more than two categories, and which aspire to replace the simple matching approach standardly used in this area. These similarity measures take into account additional characteristics of a dataset, such as frequency distribution of categories or number of categories of a given variable. The thesis recognizes three main aims. The first one is an examination and clustering performance evaluation of selected similarity measures for nominal data in hierarchical clustering of objects and variables. To achieve this goal, four experiments dealing both with the object and variable clustering were performed. They examine the clustering quality of the examined similarity measures for nominal data in comparison with the commonly used similarity measures using a binary transformation, and moreover, with several alternative methods for nominal data clustering. The comparison and evaluation are performed on real and generated datasets. Outputs of these experiments lead to knowledge, which similarity measures can generally be used, which ones perform well in a particular situation, and which ones are not recommended to use for an object or variable clustering. The second aim is to propose a theory-based similarity measure, evaluate its properties, and compare it with the other examined similarity measures. Based on this aim, two novel similarity measures, Variable Entropy and Variable Mutability are proposed; especially, the former one performs very well in datasets with a lower number of variables. The third aim of this thesis is to provide a convenient software implementation based on the examined similarity measures for nominal data, which covers the whole clustering process from a computation of a proximity matrix to evaluation of resulting clusters. This goal was also achieved by creating the nomclust package for the software R, which covers this issue, and which is freely available.
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Use of Interest Rate Models for Interest Rate Risk Management in the Czech Financial Market Environment
Cíchová Králová, Dana ; Arlt, Josef (advisor) ; Cipra, Tomáš (referee) ; Witzany, Jiří (referee)
The main goal of this thesis is to suggest an appropriate approach to interest rate risk modeling in the Czech financial market environment in various situations. Three distinct periods are analyzed. These periods, which are the period before the global financial crisis, period during the financial crisis and in the aftermath of the global financial crisis and calming subsequent debt crisis in the eurozone, are characterized by different evaluation of liquidity and credit risk, different relationship between financial variables and market participants and different degree of market regulations. Within this goal, an application of the BGM model in the Czech financial market environment is crucial. Use of the BGM model for the purpose of predicting a dynamics of a yield curve is not very common. This is firstly due to the fact that primary use of this model is a valuation of interest rate derivatives while ensuring the absence of arbitrage and secondly its application is relatively difficult. Nevertheless, I apply the BGM model to obtain predictions of the probability distributions of interest rates in the Czech and eurozone market environment, because its complexity, direct modeling of a yield curve based on market rates and especially a possibility of parameter estimation based on current swaptions volatilities quotations may lead to a significant improvement of predictions. This improvement was also confirmed in this thesis. Use of swaptions volatilities market quotations is especially useful in the period of unprecedented mone- tary easing and increased number of central banks and other regulators interventions into financial markets that occur after the financial crisis, because it reflects current market expectations which also include future interventions. As a consequence of underdevelopment of the Czech financial market there are no market quotations of Czech koruna denominated swaptions volatilities. I suggest their approximations based on quotations of euro denominated swaptions volatilities and also using volatilities of koruna and euro forward rates. Use of this approach ensures that predictions of the Czech yield curve dynamics contain current market expectations. To my knowledge, any other author has not presented similar application of the BGM model in the Czech financial market environment. In this thesis I further predict a Czech and Euro area money market yield curve dynamics using the CIR and the GP models as representatives of various types of interest rates models to compare these predictions with BGM predictions. I suggest a comprehensive system of three criteria, based on comparison of predicti- ons with reality, to describe a predictive power of selected models and an appropria- teness of their use in the Czech market environment during different situations in the market. This analysis shows that predictions of the Czech money market yield curve dynamics based on the BGM model demonstrate high predictive power and the best 8 quality in comparison with other models. GP model also produces relatively good qua- lity predictions. Conversely, predictions based on the CIR model as a representative of short rate model family completely failed when describing reality. In a situation when the economy allows negative rates and there is simultaneously a significant likelihood of their implementation, I recommend to obtain predictions of Czech money market yield curve dynamics using GP model which allows existence of negative interest rates. This analysis also contains a statistical test for validating the predictive power of each model and information on other tests. Berkowitz test rejects a hypothesis of accurate predictions for each model. However, this fact is common in real data testing even when using relatively good model. This fact is especially caused by difficult fulfilment of test conditions in real world. To my knowledge, such an analysis of the predictive power of selected interest rate models moreover in the Czech financial market environment has not been published yet. The last goal of this thesis is to suggest an appropriate approach to obtaining pre- dictions of Czech government bonds risk premium dynamics. I define this risk premium as a difference between government bond yields and fixed rate of CZK IRS with the same length. I apply the GP model to describe the dynamics of this indicator of the Czech Republic credit risk. In order to obtain a time series of the risk premium which are necessary for estimation of GP model parameters I firstly estimate yield curves of Czech government bonds using Svensson model for each trading day since 2005. Resulting si- mulations of risk premium show that the GP model predicts the real development of risk premiums of all maturities relatively well. Hence, the proposed approach is suitable for modeling of Czech Republic credit risk based on the use of information extracted from financial markets. I have not registered proposed approach to risk premium modeling moreover in the Czech financial market environment in other publications.
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