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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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Business plan. Business in the area of cultivation and processing of lavender.
Třešňáková, Karin ; Zadražilová, Dana (advisor) ; Zadražil, Václav (referee)
This thesis is focused on the business plan in the cultivation and processing of lavender. The aim is to determine whether the plan can be implemented profitably. In the first part, I deal with the formal requirements of business plan, its simplified form LEAN CANVAS, SMART method for determining targets. Another chapter is a marketing strategy and marketing mix. Following the financial plan, which is divided into an optimistic and a pessimistic variant. The second part describes the history of growing lavender, its healing powers and possibilities of use. The third part, its own business plan.
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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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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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Differences between men and women in the Czech labour market
Stroukal, Dominik ; Kadeřábková, Božena (advisor) ; Pavelka, Tomáš (referee) ; Němec, Otakar (referee)
This thesis consists of five articles that apply current world research on labor economics at the Czech Republic and confirms the significant differences between men and women in this market. It shows that gender has a significant influence on the preference on the labor market and, consequently, on employment and health. First, the thesis shows that preferences are relevant determinant of career and then we study the difference in preference of salary for men and women. Subsequently it shows that gender plays a significant role in explaining the relationship between homeownership, and unemployment, as well as unemployment and health. The first chapter was able to demonstrate that the preference for a career has a positive influence on the choice of career. The influence of higher education on prioritizing career proved to be positive and significant. Probability of a career choice is reduced by the presence of children, however, is not dependent on their number, which is contrary to the theory of preferences. The second chapter shows that Czech women prefer more non-monetary rewards than men. It has also been shown that people with university education are same in the preferences of non-monetary rewards regardless of the gender of the respondents, however, compared to the world's research, the Czech higher education increases this preference. It turned out that women prefer risk less than men. The third chapter demonstrates that although the housing market undermines labor mobility and employment in the Czech Republic at the regional level, therefore, that in regions with a higher rate of home ownership is higher unemployment, at the individual level, the owners of housing are unemployed are less likely. The estimates are significantly different for men and women. Men living in owner-occupied housing have a higher likelihood of employment than women. At regional level, however, this thesis shows that the high rate of home ownership increases unemployment for both men and women, in the long run only to women. The fourth chapter showed that men transition to homeownership reduces the likelihood of unemployment next year. For women, this relationship has proved to be insignificant. In addition, as insignificant showed the opposite relationship, the transition from unemployment to the newly acquired home ownership. The last chapter shows that the change in the working status to unemployment will increase in the future probability of worse health. Influence in less than two years, however, proved to be significant. An important conclusion is that men have a significantly stronger relationship between health and unemployment than women.
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The impact of South China Sea dispute on trade relations between China and Vietnam
Nguyen Hong, Viet ; Vlčková, Jana (advisor) ; Hasík, Gabriel (referee)
This bachelor thesis investigates the impact of South China Sea dispute on mutual relations between China and Socialist Republic of Vietnam. Thesis lays great emphasis on the analysis of mutual trading relations. The goal of this work is to find out if the dispute over territory has negative influence on mutual relations and to what extent. Therefore, thesis is divided into 3 main chapters. The introductory chapter describes position and development of each country. Second chapter uses findings from the introductory part for the analysis of political and trade relations of both countries. It focuses on the history of mutual relations and mainly it lays emphasis on current mutual relations. Last chapter of the thesis is dedicated to the issues regarding South China Sea. Motives and causes of this dispute are described in this chapter. It provides a view on the course of this territorial dispute, and also impacts on mutual relations are analyzed. The output of all three chapters helps to formulate following conclusion. Dispute over South China Sea has impact on mutual relations. Predominantly, it influences political relations between China and Vietnam, therefore, this dispute is often mentioned in media. However, according to available data this dispute has not had major effect on trading relations. Mutual trading between both countries went off in dispute period without any limitations and barriers.
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Analysis of the company environment
Hladík, Ondřej ; Dvořáček, Jiří (advisor) ; Strouhal, Jiří (referee)
This bachelor thesis deals with methods of analysing the company environment and then using these methods on a company Travel Service, a.s. The primary purpose is to determine main factors affecting the market position of this company. Methods used for analyzing the company environment are introduced in theoretical part of the thesis. For analysing the macroenvironment is used PEST analysis and Porter five force model is used for analysing the critical factors of macroenvironment. The thesis include SWOT analysis and recommendations for the company based on the collected informations.
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Possibilities of Big Data use for Competitive Intelligence
Verníček, Marek ; Molnár, Zdeněk (advisor) ; Šperková, Lucie (referee)
The main purpose of this thesis is to investigate the use of Big Data for the methods and procedures of Competitive Intelligence. Among the goals of the work is a toolkit for small and large businesses which is supposed to support their work with the whole process of Big Data work. Another goal is to design an effective solution of processing Big Data to gain a competitive advantage in business. The theoretical part of the work processes available scientific literature in the Czech Republic and abroad as well as describes the current state of Competitive Intelligence, and Big Data as one of its possible sources. Subsequently, the work deals with the characteristics of Big Data, the differences from working with common data, the need for a thorough preparation and Big Data applicability for the methods of Competitive Intelligence. The practical part is focused on analysis of Big Data tools available in the market with regard to the whole process from data collection to the analysis report preparation and integration of the entire solution into an automated state. The outcome of this part is the Big Data software toolkit for small and large businesses based on their budget. The final part of the work is devoted to the classification of the most promising business areas, which can benefit from the use of Big Data the most in order to gain competitive advantages and proposes the most effective solution of working with Big Data. Among other benefits of this work are expansion of the range of resources for Competitive Intelligence and in-depth analysis of possibilities of Big Data usage, designed to help professionals make use of this hitherto untapped potential to improve market position, gain new customers and strengthen the existing user base.
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