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Analysis framework for developing cross-platform mobile applications using HTML technology.
Voldřich, Martin ; Pavlíčková, Jarmila (advisor) ; Hrubý, Jan (referee)
The aim of the master thesis is to assess frameworks that are used for development of multiplatform cell phone applications supported by HTML technology. The theoretical part is focused to current market analysis, mobile access issues and the issue of difficulties in specific cases of their application. Analysis is followed by choice of evaluation criteria for setting the most appropriate architecture. Selected evaluation criteria will be used as a tool for detecting of the optimal technology's possibility, which is the most appropriate possibility for development of basic cell phones applications. The practical part is focused to choosing of new evaluation criteria, which helps to create specific questionnaire research. The confirmation or refuse of the hypothesis set up the level of criteria's severity. Based on criteria there will be selected and analysed six of the most used hybrid frameworks. Two of the frameworks with the highest ratings will be tested by real basic cell phone application. The conclusion of the thesis will be follow up by tested frameworks. The frameworks will be described and measured by the author's development experiences.
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Bayesian statistical modelling
Vilikus, Ondřej ; Hebák, Petr (advisor) ; Berka, Petr (referee) ; Militký, Jiří (referee)
Conjoint analysis is a popular method in consumer preferences research. One of the factors that caused the increasing popularity of this method in recent years is wide use of hierarchical Bayesian models which has been found invaluable in solving the problem of how to obtain reliable estimates of individual preferences without need for overloading respondents with too many conjoint tasks. First goal of my dissertation was to confirm whether the use of Bayesian models is the best choice under all circumstances or whether there are some limitations of this approach. For this purpose I conducted a study based on simulated datasets. Algorithm used enabled generation of datasets that differed in several parameters of interest but which were most comparable in other aspects. Results show that hierarchical models represent choice leading to highest accuracy in predicting respondents' choices in holdout tasks. Use of hierarchical models is most beneficial in the situation of strongly heterogeneous population yet limited amount of available data. In these cases we are able to capture the structure of heterogeneity with significantly lower number of choice task necessary from each respondent. Second goal of the dissertation was to answer the question whether we can increase also the effectiveness of the questioning in conjoint analysis by adding several direct questions. Suggested hybrid choice-based conjoint method (HCBC) combines conjoint analysis tasks with direct questions regarding the preference of levels for each attribute. These are used during the estimation of the model and for increasing the effectiveness if the conjoint analysis tasks design. The HCBC was compared with traditional choice-based conjoint (CBC) and adaptive choice-based conjoint (ACBC) based on practical study involving 421 respondents randomly assigned in one of three test groups. Suggested method has been found as useful alternative that can help with reducing number of choice task needed and as a solution for some situations when diverse importance of the attributes tested does not allow for indirect estimation of preferences with respect to all attributes tested.
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