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Innovation activities in Germany in the context of smart specialisation
Vlčková, Markéta ; Vlčková, Jana (advisor) ; Vošta, Milan (referee)
Economic growth is slowing in many countries. It leads to a discussion on what sources of growth should countries focus. For this purpose, EU created the concept of smart specialization, which puts an emphasis on the most efficient use of public financial resources dedicated to research and development. The aim of this thesis is to find out on what industry Germany as a leader of EU innovation and its individual regions specializes and to identify potential areas for targeting resources to innovation, research and development. This will be determined by using the patent network. The secondary objective is to interconnect findings of patenting and analysis of innovation activities in various regions of Germany with international trade and to determine whether there is a correlation between innovation activity in a particular sector and export of the sector's products abroad.
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Content Marketing for Lead Generation in B2B Educational and Consulting Services
Nykodýmová, Barbora ; Zamazalová, Marcela (advisor) ; Pospíchal, Tomáš (referee)
The aim of this thesis is to acquaint the reader with the issue of content marketing for generating leads and information about potential customers, then to analyze and offer some recommendations for its further use among B2B suppliers of educational and consulting services. The theoretical part discusses three key topics: the specifics of the services and B2B sector; content marketing and the reasons for its inclusion in marketing strategy; and the issue of lead generation as a possible metric of content marketing and sales tool. The practical part of the thesis approaches this topic from the perspective of four representatives of service suppliers, complemented by a point of view of the mediate company IVITERA. This company brings together one of the largest B2B communities in the services sector on the Czech market within its (especially online) media projects. Research was conducted through individual interviews with representatives of all five companies and by an analysis of secondary data, leads and keywords provided by the mediate company.
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Employer branding in Building Industry
Hralová, Lenka ; Bušina, Filip (advisor) ; Havlíček, Karel (referee)
The Master's Thesis is focused on a modern trend in human resource management, employer branding, analysed as a general image of a company as employer, its working conditions and a preference of this company as a stable employer. The main goal is to review the range and relevance of employer branding within Czech building industry based on existing company and comparison with its competition. The first part describes theoretical definitions of employer branding and its instruments. The second part presents the empirical research done in Metrostav a.s., comparison with its competition and a questionnaire between civil engineering students and construction apprentices that was focused on their expectations of future employment in the building industry. In the end of the thesis the research is evaluated and the improvements that would lead to empowerment of employer brand are suggested.
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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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Motivation and evaluation of empolyees
Sinkulová, Anna ; Legnerová, Kateřina (advisor) ; Šmíd, David (referee)
My bachelor thesis is focused on motivation and assessment of employees in the company. The aim of this thesis is to investigate the influence of team building and benefits on employees' motivation. Literature based theoretical part of my thesis describes and investigates the real meaning and purpose of motivation and basic motivational concepts. Furthermore, I outlined the basics behind employee benefits, team building and also stated the current given trends in these areas. The practical part is focused on benefit and workplace research and their impact on the general motivation to work and the relations between the employees of the Czechoslovak Commercial Bank (ČSOB). In order to collect the best results, I used the method of questionnaires. Respondents were asked to answer questions considering their satisfaction with the system of employee benefits and the importance of teamwork. Based on the survey results I propose certain changes that should lead to motivation improvement and better job performance.
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ELECTRON BEAM REMELTING OF PLASMA SPRAYED ALUMINA COATINGS
Matějíček, Jiří ; Veverka, J. ; Čížek, J. ; Kouřil, J.
Plasma sprayed alumina coatings find numerous applications in various fields, where they enhance the properties of the base material. Examples include thermal barriers, wear resistance, electrical insulation, and diffusion and corrosion barriers. A typical structure of plasma sprayed coatings, containing a multitude of voids and imperfectly bonded interfaces, gives them unique properties - particularly low thermal conductivity, high strain tolerance, etc. However, for certain applications such as permeation barriers or wear resistance, these voids may be detrimental.\nThis paper reports on the first experiments with remelting of plasma sprayed alumina coatings by electron beam technology, with the purpose of densifying the coatings and thereby eliminating the voids. Throughout the study, several parameters of the e-beam device were varied - beam current, traverse velocity and number of passes. The treated coatings were observed by light and electron microscopy and the thickness, structure and surface morphology of the remelted layer were determined and correlated with the process parameters. Based on the first series of experiments, the e-beam settings leading to dense and smooth remelted layer of sufficient thickness were obtained. In this layer, a change of phase composition and a marked increase in hardness were observed.\n
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Modelling, parameter estimation, optimisation and control of transport and reaction processes in bioreactors.
ŠTUMBAUER, Václav
With the significant potential of microalgae as a major biofuel source of the future, a considerable scientific attention is attracted towards the field of biotechnology and bioprocess engineering. Nevertheless the current photobioreactor (PBR) design methods are still too empirical. With this work I would like to promote the idea of designing a production system, such as a PBR, completely \emph{in silico}, thus allowing for the in silico optimization and optimal control determination. The thesis deals with the PBR modeling and simulation. It addresses two crucial issues in the current state-of-the-art PBR modeling. The first issue relevant to the deficiency of the currently available models - the incorrect or insufficient treatment of either the transport process modeling, the reaction modeling or the coupling between these two models. A correct treatment of both the transport and the reaction phenomena is proposed in the thesis - in the form of a unified modeling framework consisting of three interconnected parts - (i) the state system, (ii) the fluid-dynamic model and (iii) optimal control determination. The proposed model structure allows prediction of the PBR performance with respect to the modelled PBR size, geometry, operating conditions or a particular microalgae strain. The proposed unified modeling approach is applied to the case of the Couette-Taylor photobioreactor (CTBR) where it is used for the optimal control solution. The PBR represents a complex multiscale problem and especially in the case of the production scale systems, the associated computational costs are paramount. This is the second crucial issue addressed in the thesis. With respect to the computational complexity, the fluid dynamics simulation is the most costly part of the PBR simulation. To model the fluid flow with the classical CFD (Computational Fluid Dynamics) methods inside a production scale PBR leads to an enormous grid size. This usually requires a parallel implementation of the solver but in the parallelization of the classical methods lies another relevant issue - that of the amount of data the individual nodes must interchange with each other. The thesis addresses the performance relevant issues by proposing and evaluation alternative approaches to the fluid flow simulation. These approaches are more suitable to the parallel implementation than the classical methods because of their rather local character in comparison to the classical methods - namely the Lattice Boltzmann Method (LBM) for fluid flow, which is the primary focus of the thesis in this regard and alternatively also the discrete random walk based method (DRW). As the outcome of the thesis I have developed and validated a new Lagrangian general modeling approach to the transport and reaction processes in PBR - a framework based on the Lattice Boltzmann method (LBM) and the model of the Photosynthetic Factory (PSF) that models correctly the transport and reaction processes and their coupling. Further I have implemented a software prototype based on the proposed modeling approach and validated this prototype on the case of the Coutte-Taylor PBR. I have also demonstrated that the modeling approach has a significant potential from the computational costs point of view by implementing and validating the software prototype on the parallel architecture of CUDA (Compute Unified Device Architecture). The current parallel implementation is approximately 20 times faster than the unparallized one and decreases thus significantly the iteration cycle of the PBR design process.
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Global Economy Outlook - December 2016
Česká národní banka
Global Economic Outlook presents the regular monthly overview of recent and expected developments in selected territories, focusing on key economic variables: inflation, GDP growth, leading indicators, interest rates, exchange rates and commodity prices. In this issue, we also focus on a major phenomenon of the day: the migration of people into Europe, and Germany in particular. In this context, we present an analysis of the effect of the increased number of refugees on the German labour market. We show, among other things, that the incoming migrants will be far from enough to cover the demand for labour in Germany and also that they will compete more with workers arriving in search of jobs in Germany from Central and Eastern European countries than with German citizens.
Fulltext:  PDF; PDF
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