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Patent Value Determinants
Štefánková, Stanislava ; Korytárová, Jana (referee) ; Němec, Daniel (referee) ; Polednáková, Anna (referee) ; Režňáková, Mária (advisor)
The dissertation extends the line of research in the field of patent valuation by interconnecting two main strands, the evaluation of quality of patent rights based on their characteristics on one hand, and monetary valuation of patents as assets on the other hand. Moreover, the dissertation proposes and verifies the idea that the value of a patent is driven also by the ability of its owner to use the competitive advantage gained. The aim is to identify characteristics of Czech corporate patents and their owners that affect their value and to propose a way to implement this knowledge in monetary patent valuation. The effect of several ex ante and ex post indicators on patent's life was analysed employing survival analysis methods. Factors that significantly affect the lifespan of patents of Czech companies were identified using the Cox proportional hazard model. The company’s ability to benefit from competitive advantage was measured by its return on assets and return on equity, which were described by a linear mixed model. Finally, the combined effect of patent characteristics and the firm’s ability to materialize the competitive advantage on patent renewal was analysed employing the joint model for longitudinal and censored data. The results revealed positive effect on the chance of patent renewal of patent backward citation, and the concordance level between patents' technological-class codes and those of their antecedent, i.e., documents it refers to. Conversely, the size of the patent portfolio and the number of inventors have a negative effect on the chance of patent renewal. Small and medium businesses’ patents are less likely to be renewed. The effect of the patent family size, the age of the company and the patent pendency time is time-dependent, it initially lowers the chance of renewal, but its strength gradually weakens. The economic life of patents was predicted based on the results of the joint model using Monte Carlo simulation, furthermore, the implications for monetary patent and business valuation were discussed regarding its investment value.
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Introduction to Linear Mixed Models
Šaroch, Vojtěch ; Kulich, Michal (advisor) ; Komárek, Arnošt (referee)
of the bachelor thesis Title: Introduction to Linear Mixed Models Author: Vojtěch Šaroch Department: Department of Probability and Mathematical Statistics, MFF UK Supervisor: doc. Mgr. Michal Kulich Ph.D. Abstract: The thesis describes general procedures of estimation and hypothesis testing for linear statistical models. The models compare groups of observation due to dependent variable. Analysis of variance and linar mixed models are commonly used in the major science like pharmacology, biochemistry, economy and others. The thesis is appropriate for general public, because no advanced knowledge of probability and statistics are required. Particular methods are introduced gently and contain some practical examples for easier understanding of theory. Keywords: Analysis of variance (ANOVA), fixed and random effect, linear mixed model 1
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Introduction to Linear Mixed Models
Šaroch, Vojtěch ; Kulich, Michal (advisor) ; Komárek, Arnošt (referee)
of the bachelor thesis Title: Introduction to Linear Mixed Models Author: Vojtěch Šaroch Department: Department of Probability and Mathematical Statistics, MFF UK Supervisor: doc. Mgr. Michal Kulich Ph.D. Abstract: The thesis describes general procedures of estimation and hypothesis testing for linear statistical models. The models compare groups of observation due to dependent variable. Analysis of variance and linar mixed models are commonly used in the major science like pharmacology, biochemistry, economy and others. The thesis is appropriate for general public, because no advanced knowledge of probability and statistics are required. Particular methods are introduced gently and contain some practical examples for easier understanding of theory. Keywords: Analysis of variance (ANOVA), fixed and random effect, linear mixed model 1
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