Fuzzy real option analysis in patent related decision making and patent valuation

The shift towards a knowledge-based economy has inevitably prompted the evolution of patent exploitation. Nowadays, patent is more than just a prevention tool for a company to block its competitors from developing rival technologies, but lies at the very heart of its strategy for value creation and is therefore strategically exploited for economic pro t and competitive advantage. Along with the evolution of patent exploitation, the demand for reliable and systematic patent valuation has also reached an unprecedented level. However, most of the quantitative approaches in use to assess patent could arguably fall into four categories and they are based solely on the conventional discounted cash flow analysis, whose usability and reliability in the context of patent valuation are greatly limited by five practical issues: the market illiquidity, the poor data availability, discriminatory cash-flow estimations, and its incapability to account for changing risk and managerial flexibility. This dissertation attempts to overcome these impeding barriers by rationalizing the use of two techniques, namely fuzzy set theory (aiming at the first three issues) and real option analysis (aiming at the last two). It commences with an investigation into the nature of the uncertainties inherent in patent cash flow estimation and claims that two levels of uncertainties must be properly accounted for. Further investigation reveals that both levels of uncertainties fall under the categorization of subjective uncertainty, which differs from objective uncertainty originating from inherent randomness in that uncertainties labelled as subjective are highly related to the behavioural aspects of decision making and are usually witnessed whenever human judgement, evaluation or reasoning is crucial to the system under consideration and there exists a lack of complete knowledge on its variables. Having clarified their nature, the application of fuzzy set theory in modelling patent-related uncertain quantities is effortlessly justified. The application of real option analysis to patent valuation is prompted by the fact that both patent application process and the subsequent patent exploitation (or commercialization) are subject to a wide range of decisions at multiple successive stages. In other words, both patent applicants and patentees are faced with a large variety of courses of action as to how their patent applications and granted patents can be managed. Since they have the right to run their projects actively, this flexibility has value and thus must be properly accounted for. Accordingly, an explicit identification of the types of managerial flexibility inherent in patent-related decision making problems and in patent valuation, and a discussion on how they could be interpreted in terms of real options are provided in this dissertation. Additionally, the use of the proposed techniques in practical applications is demonstrated by three fuzzy real option analysis based models. In particular, the pay-of method and the extended fuzzy Black-Scholes model are employed to investigate the profitability of a patent application project for a new process for the preparation of a gypsum-fibre composite and to justify the subsequent patent commercialization decision, respectively; a fuzzy binomial model is designed to reveal the economic potential of a patent licensing opportunity.

New methods for controlling twin configurations and characterizing twin boundaries in 5M Ni-Mn-Ga for the development of applications

Traditional methods for studying the magnetic shape memory (MSM) alloys Ni-Mn-Ga include subjecting the entire sample to a uniform magnetic field or completely actuating the sample mechanically. These methods have produced significant results in characterizing the MSM effect, the properties of Ni-Mn-Ga and have pioneered the development of applications from this material. Twin boundaries and their configuration within a Ni-Mn-Ga sample are a key component in the magnetic shape memory effect. Applications that are developed require an understanding of twin boundary characteristics and, more importantly, the ability to predictably control them. Twins have such a critical role that the twinning stress of a Ni-Mn-Ga crystal is the defining characteristic that indicates its quality and significant research has been conducted to minimize this property. This dissertation reports a decrease in the twinning stress, predictably controlling the twin configuration and characterizing the dynamics of twin boundaries. A reduction of the twinning stress is demonstrated by the discovery of Type II twins within Ni-Mn-Ga which have as little as 10% of the twinning stress of traditional Type I twins. Furthermore, new methods of actuating a Ni-Mn-Ga element using localized unidirectional or bidirectional magnetic fields were developed that can predictably control the twin configuration in a localized area of a Ni-Mn-Ga element. This method of controlling the local twin configuration was used in the characterization of twin boundary dynamics. Using a localized magnetic pulse, the velocity and acceleration of a single twin boundary were measured to be 82.5 m/s and 2.9 × 107 m/s2, and the time needed for the twin boundary to nucleate and begin moving was less than 2.8 μs. Using a bidirectional magnetic field from a diametrically magnetized cylindrical magnet, a highly reproducible and controllable local twin configuration was created in a Ni-Mn-Ga element which is the fundamental pumping mechanism in the MSM micropump that has been co-invented and extensively characterized by the author.

A Bayesian Approach for Forecasting Heat Load in a District Heating System

The growing population in cities increases the energy demand and affects the environment by increasing carbon emissions. Information and communications technology solutions which enable energy optimization are needed to address this growing energy demand in cities and to reduce carbon emissions. District heating systems optimize the energy production by reusing waste energy with combined heat and power plants. Forecasting the heat load demand in residential buildings assists in optimizing energy production and consumption in a district heating system. However, the presence of a large number of factors such as weather forecast, district heating operational parameters and user behavioural parameters, make heat load forecasting a challenging task. This thesis proposes a probabilistic machine learning model using a Naive Bayes classifier, to forecast the hourly heat load demand for three residential buildings in the city of Skellefteå, Sweden over a period of winter and spring seasons. The district heating data collected from the sensors equipped at the residential buildings in Skellefteå, is utilized to build the Bayesian network to forecast the heat load demand for horizons of 1, 2, 3, 6 and 24 hours. The proposed model is validated by using four cases to study the influence of various parameters on the heat load forecast by carrying out trace driven analysis in Weka and GeNIe. Results show that current heat load consumption and outdoor temperature forecast are the two parameters with most influence on the heat load forecast. The proposed model achieves average accuracies of 81.23 % and 76.74 % for a forecast horizon of 1 hour in the three buildings for winter and spring seasons respectively. The model also achieves an average accuracy of 77.97 % for three buildings across both seasons for the forecast horizon of 1 hour by utilizing only 10 % of the training data. The results indicate that even a simple model like Naive Bayes classifier can forecast the heat load demand by utilizing less training data.

Brand Protection Perspectives

The main focus of this qualitative study is to explore and understand the boundaries of a brand protection program by assessing risks caused directly or indirectly by counterfeiting and finding remedies for treating those risks. 12 of 20 brand protection managers, anti-counterfeiting experts and marketing professors completed anonymously an internet-mediated questionnaire. During this study, a pattern of risk tolerance level within the sample was identified. The empirical results suggest that this pattern influences participants’ risk perception of and attitude towards counterfeiting; these also imply that, in risk treatment, this pattern influences decision- making as well as selection of countermeasures. Further, the results propose that brand equity and reputation are compared to other brand variables more vulnerable to the impact of counterfeiting. In addition, the results obtained in the question whether companies should employ public announcements of counterfeit seizures as an additional brand protection tool were contradictory. Companies were more apprehensive towards this solution than marketing professors. Thus, further investigation on this subject is recommended. This study concludes that as long as the impact of counterfeiting cannot be measured properly, the true damage on a brand or company and their reputation cannot be determined.

Organization of the marketing communication activities after fusion - the integration and the decision making processes

This master’s thesis was made in order to gain answers to the question of how the integration of the marketing communications and the decision making related to it in a geographically dispersed service organization could be improved in a situation where an organization has gone through a merger. The effects of the organizational design dimensions towards the integration of the marketing communications and the decision making related to it was the main focus. A case study as a research strategy offered a perfect frames for an exploratory study and the data collection was conducted by semi-structured interviews and observing. The main finding proved that from the chosen design dimensions, decentralization, coordination and power, could be found specific factors that in a geographically dispersed organization are affecting the integration of the marketing communications negatively. The effects can be seen mostly in the decision making processes, roles and in the division of responsibility, which are affecting the other dimensions and by this, the integration. In a post-merger situation, the coordination dimension and especially the information asymmetry and the information flow seem to have a largest affect towards the integration of the marketing communications. An asymmetric information distribution with the lack of business and marketing education resulted in low self-assurance and at the end in fragmented management and to the inability to set targets and make independent decisions. As conclusions it can be stated, that with the organizational design dimensions can the effects of a merger towards the integration process of the marketing communications to be evaluated.

Guava Jam packaging determinant attributes in consumer buying decision

Using packaging and labels to lure consumers and to communicate product benefits directly on the shelf is a competitive advantage factor in the food industry sector. The label is especially effective since besides supplying basic details, such as weight, ingredients, and instructions in compliance with governmental regulations, it attracts consumers' attention and the desire to buy and which often becomes synonymous to the brand name. The objective of this study was to obtain detailed information on consumers' attitudes, opinions, behavior, and concepts regarding guava jam packaging using the focus group technique. The results showed that label color and design, packaging type and information, and brand name and price are determinant attributes in the consumers' decision to buy guava jam.