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Alleviating the curse of dimensionality in minkowski sum approximations of storage flexibility
(2023)
Many real-world applications require the joint optimization of a large number of flexible devices over some time horizon. The flexibility of multiple batteries, thermostatically controlled loads, or electric vehicles, e.g., can be used to support grid operations and to reduce operation costs. Using piecewise constant power values, the flexibility of each device over d time periods can be described as a polytopic subset in power space. The aggregated flexibility is given by the Minkowski sum of these polytopes. As the computation of Minkowski sums is in general demanding, several approximations have been proposed in the literature. Yet, their application potential is often objective-dependent and limited by the curse of dimensionality. In this paper, we show that up to 2d vertices of each polytope can be computed efficiently and that the convex hull of their sums provides a computationally efficient inner approximation of the Minkowski sum. Via an extensive simulation study, we illustrate that our approach outperforms ten state-of-the-art inner approximations in terms of computational complexity and accuracy for different objectives. Moreover, we propose an efficient disaggregation method applicable to any vertex-based approximation. The proposed methods provide an efficient means to aggregate and to disaggregate typical battery storages in quarter-hourly periods over an entire day with reasonable accuracy for aggregated cost and for peak power optimization.
This thesis evaluates the feasibility of conducting visual inspection tests on power industry constructions using object detection techniques. The introduction provides an overview of this field’s state-of-the-art technologies and approaches. For the implementation, a case study is then conducted, which is done in collaboration with the partner company OMICRON Electronics GmbH, focusing on power transformers as an example. The objective is to develop an inspection test using photographs to identify power transformers and their subcomponents and detect existing rust spots and oil leaks within these components. Three object detection models are trained: one for power transformers and sub-components, one for rust detection, and one for oil leak detection. The training process utilizes the implementation of the YOLOv5 algorithm on a Linux-based workstation with an NVIDIA Quadro RTX 4000 GPU. The power transformer model is trained on a dataset provided by the partner company, while open-source datasets are used for rust and oil leak detection. The study highlights the need for a more powerful GPU to enhance training experiments and utilizes an Azure DevOps Pipeline to optimize the workflow. The performance of the power transformer detection model is satisfactory but influenced by image angles and an imbalance of certain sub-components in the dataset. Multi-angle video footage is a proposed solution for the inspection test to address this limitation and increase the size of the dataset, focusing on reducing the imbalance. The models trained on open-source datasets demonstrate the potential for rust and oil leak detection but lack accuracy due to their generic nature. Therefore, the datasets must be adjusted with case-specific data to achieve the desired accuracy for reliable visual inspection tests. The results of the case study have been well-received by the partner company’s management, indicating future development opportunities. This case study will likely be a foundation for implementing visual inspection tests as a product.
The fact that services have emerged a driving force and the fastest growing sector in international trade attracts researchers to follow the changes taking place in the service industry. This study extends the scientific discussion on internationalization of service firms. Unlike previous research that examined factors that influence a single firm’s decision to internationalize, I acknowledge the heterogeneity of services, and based on the results obtained from secondary analysis of primary qualitative data sets, answer the main research question how internationalization motives differ between people-processing services, possession-processing services, and information-based services. This research goes beyond identification of variation in internationalization motives and analyses the service characteristics that might be responsible for the differences. In addition, I assess the key trends in the service sector and predict the possible future internationalization motives that are likely to emerge from the current trends.
Findings of this study reveal two major issues. First, it is evident that reasons for internationalization differ among hotel, retail firms and Higher education institutions representing people-processing services, possession-processing services, and information-based services respectively. Second, a few motives are common across sub-sectors, however the significance of the motives vary from sub-sector to sub-sector. I conclude that the differences in underlying structures of the respective service sub-sectors is the fundamental cause for the variation in internationalization motives among service sub-sectors. Other factors such as distinctive characteristics of service, firm’s competitive strategies, income elasticity of demand, and life-cycle stage of the service sub-sector also contribute to the differences in internationalization motives.
This paper also presents three different factors, which are likely to emerge as significant factors that influence service firm internationalization decision in future. (1) Company’s urge to be socially responsible and the need to contribute towards the environmental well-being (2) The need to sell regional products and services to neighbouring nations and respond to consumers’ demand for sustainable consumerism (3) Decision to penetrate foreign markets facilitated by the low risks and low cost of internationalization.
Although pilot projects are an accepted means of entry into prospects, research on the object of startups selling SaaS and use pilots to enter and to further scale within their prospect’s organization is limited. The reader can expect a collection of key practices of SaaS startups in the field of Decision Support Software. These combine the main sales-oriented elements within pilot projects that are reflected on by Customer Success Management, Change Management as well as cultural dimensions. Explorative interviews, mainly with stakeholders in Decision Support Software startups, were conducted to further gain an understanding of the research object. Results indicate that pilots are strategically used in the sales of such startups to simultaneously deal with their customer’s uncertainties and as a means for the startups to get commitment and increase their value proposition through the additional service that they offer in order to acquire an internal support basis. Customer Success Management as well as Change Management are furthermore advantageous in quickly achieving measurable results that leverage buyers and seller’s justification for further sales.
Offline speech to text engine for delimited context in combination with an offline speech assistant
(2022)
The inatura museum in Dornbirn had planned an interactive speech assistant-like exhibit. The concept was that visitors could ask the exhibit several questions that they would like to ask a flower. Solution requirements regarding the functionalities were formulated, such as the capacity to run offline because of privacy reasons. Due to the similarity of the exhibit, open-source offline Speech To Text (STT) engines and speech assistants were examined. Proprietary cloud-based STT engines associated with the corresponding speech assistants were also researched. The aim behind this was to evaluate the hypothesis of whether an open-source offline STT engine can compete with a proprietary cloud-based STT engine. Additionally, a suitable STT engine or speech assistant would need to be evaluated. Furthermore, analysis regarding the adaption possibilities of the STT models took place. After the technical analysis, the decision in favour of the STT engines called "Vosk" was made. This analysis was followed by attempts to adapt the model of Vosk. Vosk was compared to proprietary cloud-based Google Cloud Speech to Text to evaluate the hypothesis. The comparison resulted in not much of a significant difference between Vosk and Google Cloud Speech to Text. Due to this result, a recommendation to use Vosk for the exhibit was given. Due to the lack of intent parsing functionality, two algorithms called "text matching algorithm" and "text and keyword matching algorithm" were implemented and tested. This test proved that the text and keyword matching algorithm performed better, with an average success rate of 83.93 %. Consequently, this algorithm was recommended for the intent parsing of the exhibit. In the end, potential adaption possibilities for the algorithms were given, such as using a different string matching library. Some improvements regarding the exhibit were also presented.
Cultural Due Diligence
(2020)
Much research has been conducted in recent years to discover the reasons for the high failure rate of M&As, whereas one frequently cited reason is the incompatibility of the corporate cultures. In order to minimize this risk and to be able to react to these differences already at an early stage, Cultural Due Diligence offers itself as part of the due diligence process. Unlike existing, more general research, I emphasize the cultural challenges companies face when investing transnationally with this thesis. Using the results of a single case study with inductive character, I answer the question how to conduct Cultural Due Diligence in cross-border M&As and propose an appropriate model. The findings reveal that especially in cross-border M&As, cultural incompatibility poses a risk for failure. I was able to find out that companies that seek to grow internationally with M&As deal with similar issues in terms of corporate culture as pointed out in existing Cultural Due Diligence methods. The present study, however, shows that national culture has a great influence on corporate culture, which is why it is essential to include it in the cultural assessment in cross-border acquisitions. This provides information about why there are differences, besides the fact that they exist. Only this understanding puts a company in the appropriate starting position to recognize differences, understand them, assess whether these differ-ences are acceptable, as well as to develop appropriate strategies to address them in the integration phase.
Purpose: In this thesis the viable system model (VSM) is used as a framework to develop a model for the management of a business alliance that contains the necessary and sufficient conditions for maintaining synergy of its constituent organisations and for adapting to a changing environment so that it can remain a long-term viable alliance. In addition, a model is developed that makes explicit the inherent link between the VSM and the core elements of knowledge management theory. Based then on the alliance management model and the link established between the VSM and knowledge management, an application framework is developed to guide practitioners in defining necessary alliance management functions and relationships, the knowledge required by that management to fulfill those functions, and the processes that need to be in place to manage that knowledge. Design/strategy: The research has been divided into four phases: theoretical construction, refinement with practitioners, real-world application, and evaluation of test case and toolset. The researcher has worked closely with practitioners actively involved in the formation of a new international alliance to develop a VSM model and application framework for the alliance management. Formally, the research strategy has been defined as an action research and the research philosophy as one of pragmatism. Findings/limitations: The developed application framework, has been successfully used to identify absent and incomplete roles, actions, and interactions within the management of the specific alliance test case. This has helped to demonstrate how the application framework and VSM model can be used to diagnose and, most importantly, to articulate and visualise management deficiencies to facilitate clear and unambiguous discussions. The timing of this cross-sectional research did not allow the application framework to be utilised from the outset of the alliance formation as an organisational planning tool and also not to its full extent to support the development of knowledge processes for the alliance management. However, the step-by-step approach used in developing the toolset and then explaining its application will allow the reader to judge its credability and generalisability for other practical applications. Practical implications: The developed toolset consists of a VSM for an alliance management, job descriptions for that management (responsibilities, interfaces, and core competencies), a visual model illustrating the link between the VSM and knowledge management, and an application framework to guide the filling of the alliance management job descriptions in phases of recruitment, onboarding, and development (of interfaces and activities processes). Overall, one could say that the conditions prescribed by the VSM are rather obvious and yet, as seen by the specific alliance test case, many of these conditions have been completely overlooked by a management that was more than capable, willing, and empowered to enact those conditions. This gives a good indication that the toolset which has been compiled in a visual and tabular systematic fashion may well be useful to practitioners for the organisational planning of an alliance management. The visual representation of a management role in the VSM as a set of knowledge episodes put forward by this research is significant. It forces the express recognition that knowledge management is an integral part of every interaction that takes place and every action performed that, according to the VSM, are necessary and altogether are sufficient for viability. It means that knowledge management cannot be considered as some abstract topic or unnecessary overhead or afterthought – it is entirely necessary, practical and forms a natural course of events during design of action/interaction processes. In other words, if an organisation is viable then, by definition, it does knowledge management whether or not it is formally recognised as such. The VSM, by defining necessary and sufficient actions and interactions for its roles, therefore provides a focus for relevant knowledge and serves as a tool for structured knowledge management. Originality/value: This research addresses a general academic call for hands-on insights of VSM applications by sharing real-world insights, artifacts and reflections generated by a practical and relevant organisational management application. It also addresses the potential, recognised by academics, for VSM as a framework for knowledge management by developing an intuitive model linking those theories and then using that model as part of a framework to guide its application. The introduction to aspects of knowledge management theory relevant to the model developed as well as the meticulousness and comprehensive explanation of the VSM provides a solid theoretical foundation for practitioners. The developed toolset is based on existing theories from multiple fields of research that have been logically linked and extended in an original and novel manner with a strong focus on practical application. This researcher’s hope is that this will stimulate interest for future research and practical application from academics and practitioners alike.
The research focused on the wood pellet market for private consumers in Germany and has the objective to understand the factors affecting the purchase decisions of wood pellets buy-ers. The aims of the research were achieved by applying the Engel, Kollat, Blackwell model of consumer behaviour, by conducting in-depth interviews and deriving the grounded theory. The application of EKB model revealed that the following groups of factors may influence the con-sumers: cultural (culture and social class), social (family influence), personal (age and lifecycle stage), psychological (believes, motives, attitudes) and unexpected circumstances. In-depth interviews with the buyers of wood pellets helped specify the influencing factors to finally an-swer the research question. The analysis showed that the buyers of wood pellets are influ-enced by family, personal believes and attitudes, and the unexpected circumstances. The most important factors for the buyers are the quality of the pellets and reliability of the supplier. If they are satisfied with the quality of product and service, they will be reluctant to look for an alternative. And on the opposite side, in case the quality of the product or the service is unsat-isfactory this is a limiting factor and will stop the buyer from purchasing this product. Price is an important factor for the buyers of pellets in bags. However, in the situation of volatile mar-ket and exploding prices, the price factor will play a bigger role. Thus, the strategic factors for marketing of pellets is to concentrate on quality and price communication, and to focus on the quality of pellet delivery service.
The number of electric vehicles will increase rapidly in the coming years. Studies suggest that most owners prefer to charge their electric vehicle at home, which will fuel the need for charging stations in residential complexes where vehicles can be charged overnight. Currently, there already are over 100 such residential complexes, with another 70 added every year in Vorarlberg alone. In most existing residential complexes, however, the grid connections are not sufficient to charge all vehicles at the same time with maximum power. In addition, it is also desirable for grid operators and electricity producers that the power demand be as smooth and predictable as possible. To achieve this, ways to manage flexible loads need to be found, which can operate within the technical constraints. Therefore, the most common scenarios how the load can be made grid-friendly with the help of optional battery storage and/or photovoltaics using optimization methods of linear and stochastic programming were examined. At the same time, the needs of the vehicle owners for charging comfort - namely to find their vehicles reliably charged at the time of their respective departure - were addressed by combining both objectives using suitable weights. The algorithms determined were verified in practice on an existing Vlotte prototype installation. For this purpose, the necessary programs were implemented in Python, so that the data obtained during the test operation, which lasted one month, could be subjected to a well-founded analysis. In addition, simulation studies helped to further reveal the influence of PV and BESS sizing on the achievable optimums and confirm that advanced optimization algorithms such as the ones discussed are a vital contribution in reducing the charging stations’ peak load while at the same time maintaining high satisfaction levels.
Projects, in which software products, services, systems and solutions are developed, all rely on the right requirements to be established. Software requirements are the expression of user wants or needs that have to be addressed, business objectives that have to be met, as well as capabilities and functionality that has to be developed. Meanwhile, practice shows that very often incorrect, unclear or incomplete requirements are established, which causes major problems for such projects. It could lead to budget overruns, missed deadlines and overall failure in worst-case scenarios.
The field of requirements engineering emerged as an answer to these shortcomings, aiming to systematize and streamline the process that
establishes requirements. Requirements elicitation is a key component of this process, and one of its starting points. The current thesis attempts to outline best practices in requirements elicitation, as well as what issues, obstacles and challenges are currently faced, and then present this through the lens of national culture. In this way its effects on the practice, if any, could be highlighted and studied further. The way this was achieved was by interviewing practitioners from two nations, which are shown to be
culturally different, and then comparing and contrasting the findings.
Meanwhile, the validity of those findings was enhanced by comparisons with existing literature.
Even though the findings were not compelling enough to form generalizations or concrete conclusions about the effects of national culture on requirements elicitation, these findings revealed patterns that could be worth exploring further. When it comes to requirements elicitation itself, it was observed to benefit from a structured and systematic approach, and be
most effective with one-on-one, instead of group interactions. The main pain points of the process stem from the complexity of communication, but are not always obvious. Practitioners are also advised to carefully plan the gathering of requirements, as the source may not have them readily available, and could even be unclear about what exactly is needed. Overall, this thesis research could be considered successful in its goal to shed a modicum of light on the issue at hand from a different, underexplored angle. By following a systematic and methodical approach, this research has also been made easier to expand or replicate.
The purpose of an energy model is to predict the energy consumption of a real system and to use this information to address challenges such as rising energy costs, emission reduction or variable energy availability. Industrial robots account for an important share of electrical energy consumption in production, which makes the creating of energy models for industrial robots desirable. Currently, energy modeling methods for industrial robots are often based on physical modeling methods. However, due to the increased availability of data and improved computing capabilities, data-driven modeling methods are also increasingly used in areas such as modeling and system identification of dynamic systems. This work investigates the use of current data-driven modeling methods for the creation of energy models focusing on the energy consumption of industrial robots.
For this purpose, a robotic system is excited with various trajectories to obtain meaningful data about the system behavior. This data is used to train different artificial neural network (ANN) structures, where the structures used can be categorized into (i) Long Short Term Memory Neural Network (LSTM) with manual feature engineering, where meaningful features are extracted using deeper insights into the system under consideration, and (ii) LSTM with Convolutional layers for automatic feature extraction. The results show that models with automatic feature extraction are competitive with those using manually extracted features. In addition to the performance comparison, the learned filter kernels were further investigated, whereby similarities between the manually and automatically extracted features could be observed. Finally, to determine the usefulness of the derived models, the best-performing model was selected for demonstrating its performance on a real use case.
This study deals with the energy situation in Ny-Ålesund, an Arctic research station on the archipelago Svalbard, and aims at analysing the technical feasability of a transition to renewable energies by taking into consideration both the environmental and climatic impediments.
The analysis is based on a 27 year long collection of authentic meteorological data with all its strong fluctuations, seasonal as well as yearly. Great emphasis was put on the discussion of tried-and-tested renewable technologies that were compared to a new wind-based energy device that has yet to be tested for its reliability in the harsh environment of notably the Arctic winter. Meticulous calculations lead to the result that bifacial solar modules are an efficient means even in months when the sun stands low and their combination with wind-based devices prove to generate a maximum output. Geothermal energy seems to be promising in the region, but could not be evaluated due to a crucial lack of relevant data.
The study comes to the conclusion that the research station of Ny-Ålesund could well rely on a combination of renewable energy devices to cover its energy load, but needs to keep a back-up system of diesel run generators to bridge short periods of possible dysfunctions or standstills due to meteorological circumstances. Battery storage could only contribute to solve the problem of an unfortunate interruption of the energy supply, but it cannot serve as the entire back-up system since, at present, the need would go beyond all possible dimensions.
Zeros can cause many issues in data analysis and dealing with them requires specialized procedures. We differentiate between rounded zeros, structural zeros and missing values. Rounded zeros occur when the true value of a variable is hidden because of a detection limit in whatever mechanism was used to acquire the data. Structural zeros are values which are truly zero, often coming about due to a hidden mechanism separate from the one which generates values greater than 0. Missing values are values that are completely missing for unknown or known reasons. This thesis outlines various methods for dealing with different kinds of zeros in different contexts. Many of these methods are very specific in their ideal usecase. They are separated based on which kind of zero they are intended for and if they are better suited for compositional or for standard data.
For rounded zeros we impute the zeros with an estimated value below the detection limit. The author describes multiplicative replacement, a simple procedure that imputes values at a fixed fraction of the detection limit. As a more advanced technique, the author describes Kaplan Meier smoothing spline replacement, which interpolates a spline on a Kaplan Meier curve and uses the spline below the detection limit to impute values in a more natural distribution. Rounded zeros cannot be imputed with the same techniques that would be used for regular missing values, since there is more information available on the true value of a rounded zero than there would be for a regular missing value.
Structural zeros cannot be imputed since they are a true zero. Imputing them would falsify their values and produce a value where there should be none. Because of this, we apply modelling techniques that can work around structural zeros and incorporate them. For standard data, the zero inflated Poisson model is presented. This model utilizes a mixture of a logistic and a Poisson distribution to accurately model data with a large amount of structural zeros. While the Poisson distribution is only applicable to count data, the zero inflation concept can be applied to different kinds of distributions. For compositional data, the zero adjusted Dirichlet model is introduced. This model mixes Dirichlet distributions for every pattern of zeros found within the data. Non-algorithmic techniques to reduce the amount of structural zeros present are also shown. These techniques being amalgamation, which combines columns with structural zeros into more broad descriptors and classification, which changes columns into categorical values based on a structural zero being present or not.
Missing values are values that are completely missing for various known or unknown reasons. Different imputation techniques are introduced. For standard data, MissForest imputation is introduced, which utilizes a RandomForest regression to impute mixed type missing values. Another imputation technique shown utilizes both a genetic algorithm and a neural network to impute values based on the genetic algorithm minimizing the error of an autoencoder neural network. In the case of compositional data, knn imputation is presented, which utilizes the knn concept also found in knn clustering to impute the values based on the closest samples with a value available.
All of these methods are explained and demonstrated to give readers a guide to finding the suitable methods to use in different scenarios.
The thesis also provides a general guide on dealing with zeros in data, with decision flowcharts and more detailed descriptions for both compositional and standard data being presented. General tips on getting better results when zeros are involved are also given and explained. This general guide was then applied to a dataset to show it in action.
Packaging has important functions, such as the marketing function or protecting the product from spoilage. However, the supply in the supermarket must be viewed critically, as the majority of packaging is designed for single use. The question of how producers and retailers can increase customer acceptance of sustainable packaging in supermarkets has particular relevance in terms of the environmental impact of packaging waste. Although more and more customers are interested in the topic of sustainability, a gap between their attitude and behavior is apparent. This is addressed in more detail on the basis of two product categories. Expert interviews with international producers and retailers as well as a consumer survey allow the views of these three decision-makers to be taken into account. At the end, concrete recommendations for action are presented. These show that, among other things, information and transparency are essential in order to be able to influence consumers' purchasing decisions. In addition, the responsibility of all decision-makers is seen as the key to success.
Although workplace climate has been already extensively studied, the research has not led to firm conclusions regarding leadership trainings referring to the awareness of psychological safety in a company and its influence on existing teams and the general work climate. The author used the already existing model of Carr, Schmidt, Ford, & DeShon (2003) and adjusted it with psychological safety as 4th climate item to develop hypothesen which can also be seen as a path analytic model. The model posied that climate affects individual level outcomes through its impact on cognitive and affective states. Therefore, the author wants to show the correlation between the 4 higher order facets of climate affect the individual levels of job performance, psychological well-being and withdrawal through their impact on orangizational commitment and job saitsfaction (Carr, Schmidt, Ford, & DeShon, 2003).
This thesis focuses on implementing and testing communication over a private 5G standalone network in an industrial environment, with a specific emphasis on communication between two articulated robots. The main objective is to examine machine-to-machine communication behavior in various test scenarios. Initially, the 5G core and radio access network components are described, along with their associated interfaces, to establish foundational knowledge. Subsequently, a use case involving two articulated robots is implemented, and essential metrics are defined for testing, including round-trip time, packet and inter-packet delay, and packet error rate. The tests investigate the impact of 5G quality of service, packet size, and transmission interval on communication between the robots, focusing on the effects of network traffic. The results highlight the significance of prioritizing network resources based on the assigned quality of service identifier (5QI), demonstrate the influence of packet sizes on communication performance, and underscore the importance of transmission intervals for automation purposes. Additionally, the study examines how network disturbances influence the movements of a robot controlled via 5G, establishing a direct relationship between network metrics and the resulting deviations in the robot’s trajectory. The work concludes that while machine-to-machine communication can be successfully implemented with 5G SA, tradeoffs must be carefully considered, especially concerning packet error rate, and emphasizes the importance of understanding the required resources before implementation to ensure feasibility. Future research directions include investigating network slicing, secure remote control of robots, and exploring the use of higher frequency bands. The study highlights the significance of aligning theoretical standards with practical implementation options in the evolving landscape of 5G Networks.
In recent years, numerous studies around the world have examined the environmental potential of biochar to determine whether it can help address climate challenges. Several of these studies have used the Life Cycle Assessment (LCA) method to evaluate the environmental impacts of biochar systems. However, studies focus mainly on biochar obtained from pyrolysis, while the number of studies on biochar from gasification is small.
To contribute to the current state of LCA research on biochar from gasification, LCA was performed for biochar, electricity, and heat from a wood gasification plant in Vorarlberg, Austria. Woodchips from local woods are used as biomass feedstock to produce energy, i.e., electricity and heat. Thereby, biochar is obtained as a side product from gasification. The production of syngas and biochar takes place in a floating fixed-bed gasifier. Eventually, the syngas is converted to electricity in a gas engine and fed to the power grid. Throughout different stages within the gasification process, heat is obtained and fed into local heat grid to be delivered to customers. The biochar produced complies with the European Biochar Industry (EBI) guidelines and is used on a nearby farm for manure treatment and eventually for soil application. Thereby, the effect of biochar used for manure treatment is considered to reduce emissions occurring from manure, i.e., nitrogen monoxide (N2O). Further, the CO2 sequestration potential of biochar, i.e., removal of CO2 from the atmosphere and long-term storage, is considered. Several constructions, such as the construction of the gasification system and the heating grid, are included in the evaluation.
As input related reference flow, 1 kg of woodchips with water content of 40 % is used. Three functionals units are eventually obtained, i.e., 0.17 kg of biochar applied to soil, 4.47 MJ of heat and 2.82 MJ of electricity, each per reference flow. The results for Global Warming Potential (GWP) for biochar is – 274.7*10 - 3 kg CO2eq per functional unit, which corresponds to – 1.6 kg CO2eq per 1 kg biochar applied to soil. The GWP for heat results in 17.1*10 - 3 CO2eq per functional unit, which corresponds to 3.6*10 - 3 kg CO2eq per 1 MJ. For electricity, a GWP of 38.1*10 - 3 kg CO2eq per functional unit is obtained, which is equivalent to 13.5*10 - 3 kg CO2eq per 1 MJ.
The calculation was performed using SimaPro Version 9.1 and the ReCiPe method with hierarchist perspective.
In this paper, the design of three-dimensional configuration of Y-branch splitter is compared with Multimode Interference splitter. Both splitters use the IP-Dip polymer as a standard material for 3D laser lithography. The optical properties of the splitters for both approaches are discussed and compared.
Effective lead management
(2023)
In the last few years the global interest on lead management has increased. This classic topic for marketing and sales departments is aimed at converting potential customers into sales. The following thesis identifies the challenges and solutions for marketing and sales departments in order to process effective lead management. Using data from a literature review and qualitative empirical research, conducted with representatives of marketing and sales departments, the results showed overall and task specific challenges and solutions. The research indicates that overall challenges and solutions regarding the gap between marketing and sales, new processes and data management including data quality, software and silos emerge. In addition task specific challenges and solutions concerning lead generation including purchased leads, lead qualification, lead nurturing and sales specific challenges and solutions conclusively the focus on existing customers, time famine and lead routing were identified. This thesis provides a framework for further studies regarding the challenges and solutions for marketing and sales departments processing lead management.
The presented master thesis of the study subject International Marketing and Sales at the Fachhochschule Vorarlberg in Dornbirn deals with the influence of emotions on the attitude toward hydrogen cars and their purchase intention. For this purpose, an empirical analysis with a correlation analysis was conducted in order to be able to determine the correlations of the individual parameters.
At the beginning of the thesis the hydrogen technology was presented in more detail and by means of suitable criteria it was shown that the hydrogen car represents a certain potential, however, in comparison to the combustion cars and electric cars, the hydrogen car is currently in third place. The relatively long range, the fast-refueling and the sustainability were identified as advantages, while the current high price and the poorly developed refueling station network are currently the biggest ob-stacles to a hydrogen car. It can be seen that research and development of hydrogen cars is being driven forward in many countries around the world, including by the gov-ernment side through the provision of various subsidies. For this reason, the future development of the driving technology remains exciting and simultaneously uncertain.
In the second step of the work, emotions were examined in more detail. The aim was to find out which emotions exist and which of them are predominant when buying a car, and then to find out what influence emotions have on the cognitive process, the attitude, and the purchase intention. It turned out that the majority of the population is highly involved in the purchase of a car and therefore tries to make rational decisions, which makes the influence of emotions more difficult, but not impossible.
By presenting suitable marketing tools for measuring emotions, it was shown that measuring emotions is a difficult undertaking. Measurement is often difficult or expen-sive and involves a great deal of effort. For this reason, beside the presentation of marketing tools, the strategic approach for a marketing campaign was also presented.
Based on the conducted empirical analysis, the influence of emotions on attitude and purchase intention could not be significantly confirmed but it could be proven that the knowledge about hydrogen cars is currently low. One inside is that an increase in awareness increases the purchase intention of hydrogen cars. Furthermore, a signifi-cant correlation between the sustainable attitude and the purchase intention could be proven. In addition, people who like to follow new trends are more likely to buy a hy-drogen car than others. This paper concludes with a brief summary of the findings and an outlook on the potential for improvement of the hydrogen car market.
Keywords: Hydrogen Cars, Sustainability, Emotions in Marketing, Purchase Inten-tion, Attitude, Marketing Tool
This master thesis investigates a Computational Intelligence-based method for solving PDEs. The proposed strategy formulates the residual of a PDE as a fitness function. The solution is approximated by a finite sum of Gauss kernels. An appropriate optimisation technique, in this case JADE, is deployed that searches for the best fitting parameters for these kernels. This field is fairly young, a comprehensive literature research reveals several past papers that investigate similar techniques.
To evaluate the performance of the solver, a comprehensive testbed is defined. It consists of 11 different Poisson equations. The solving time, the memory consumption and the approximation quality are compared to the state of the art open-source Finite Element solver NGSolve. The first experiment tests a serial JADE. The results are not as good as comparable work in the literature. Further, a strange behaviour is observed, where the fitness and the quality do not match. The second experiment implements a parallel JADE, which allows to make use of parallel hardware. This significantly speeds up the solving time. The third experiment implements a parallel JADE with adaptive kernels. It starts with one kernel and introduce more kernels along the solving process. A significant improvement is observed on one PDE, that is purposely built to be solvable. On all other testbed PDEs the quality-difference is not conclusive. The last experiment investigates the discrepancy between the fitness and the quality. Therefore, a new kernel is defined. This kernel inherits all features of the Gauss kernel and extends it with a sine function. As a result, the observed inconsistency between fitness and quality is mitigated.
The thesis closes with a proposal for further investigations. The concepts here should be reconsidered by using better performing optimisation algorithms from the literature, like CMA-ES. Beyond that, an adaptive scheme for the collocation points could be tested. Finally, the fitness function should be further examined.
The classification of waste with neural networks is already a topic in some scientific papers. An application in the embedded systems area with current AI processors to accelerate the inference has not yet been discussed. In this master work a prototype is created which classifies waste objects and automatically opens the appropriate container for the object. The area of application is in the public space.
For the classification a dataset with 25,681 images and 11 classes is created to re-train the Convolution Neuronal Networks EfficientNet-B0, MobileNet-v2 and NASNet-mobile. These Convolution Neuronal Networks run on the current Edge \acrshort{ai} processors from Google, Intel and Nvidia and are compared for performance, consumption and accuracy.
The master thesis evaluates the result of these comparisons and shows the advantages and disadvantages of the respective processors and the CNNs. For the prototype, the most suitable combination of hardware and AI architecture is used and exhibited at the university fair KasetFair2020. An opinion survey on the application of the machine is conducted.
This paper analyses an electrical test tower of the OMCIRON electronics GmbH and evaluates whether a Predictive Maintenance (PdM) strategy can be implemented for the test towers. The company OMICRON electronics GmbH performs unit tests for its devices on test towers. Those tests consist of a multitude of subtests which all return a measurement value. Those results are tracked and stored in a database. The goal is to analyze the data of the test towers subtests and evaluate the possibility of implementing a predictive maintenance system in order to be able to predict the RUL and quantify the degradation of the test tower.
By assuming that the main degradation source are the relays of the test tower, a reliability modelling is performed which is the model-driven approach. The data-driven modelling process of the test tower consists of multiple steps. Firstly, the data is cleaned and compromised by removing redundances and optimizing for the best subtests where a subtest is rated as good if the trendability and monotonicity metric values are above a specific threshold. In a second step, the trend behaviours of the subtests are analyzed and ranked which illustrates that none of the subtests contained usable trend behaviour thus making an implementation of a PdM system impossible.
By using the ranking, the data-driven model is compared with the reliability model which shows that the assumption of the relays being the main error source is inaccurate.
An analysis of a possible anomaly detection model for a PdM is evaluated which shows that an anomaly detection is not possible for the test towers as well. The implementability of PdM for test towers and other OMICRON devices is discussed and followed up with proposals for future PdM implementations as well as additional analytical analyses that can be performed for the test towers.
Strain-induced dynamic control over the population of quantum emitters in two-dimensional materials
(2023)
The discovery of quantum emitters in two-dimensional materials has triggered a surge of research to assess their suitability for quantum photonics. While their microscopic origin is still the subject of intense studies, ordered arrays of quantum emitters are routinely fabricated using static strain-gradients, which are used to drive excitons toward localized regions of the 2D crystals where quantum-light-emission takes place. However, the possibility of using strain in a dynamic fashion to control the appearance of individual quantum emitters has never been explored so far. In this work, we tackle this challenge by introducing a novel hybrid semiconductor-piezoelectric device in which WSe2 monolayers are integrated onto piezoelectric pillars delivering both static and dynamic strains. Static strains are first used to induce the formation of quantum emitters, whose emission shows photon anti-bunching. Their excitonic population and emission energy are then reversibly controlled via the application of a voltage to the piezoelectric pillar. Numerical simulations combined with drift-diffusion equations show that these effects are due to a strain-induced modification of the confining-potential landscape, which in turn leads to a net redistribution of excitons among the different quantum emitters. Our work provides relevant insights into the role of strain in the formation of quantum emitters in 2D materials and suggests a method to switch them on and off on demand.
The impact of organizational citizenship behavior for the environment on corporate sustainability
(2022)
Today, many businesses increasingly engage in pro-environmental activities to face environmental challenges such as pollution or climate change. In addition to formal management practices, employees are impacting environmental advances with voluntary pro-environmental activities, also known as Organizational Citizenship Behavior for the Environment. The purpose of this master thesis is to explore factors that could influence employees’ engagement in Organizational Citizenship Behavior for the Environment. For this aim, five semi-structured interviews were carried out with multinational corporations from the DACHL region. The results show that certain leadership styles, corporate culture, a sustainability-driven mindset, environmental concern, communication and motivation can influence employees’ engagement in Organizational Citizenship Behavior for the Environment. In addition, the cumulative effect of small initiatives seems to considerably impact environmental sustainability. In contrast to past research on this topic, this study takes a qualitative approach to explore different influencing factors of Organizational Citizenship Behavior for the Environment. In addition, the study focuses on businesses located in the DACHL region.
Systems are constantly increasing in complexity. This poses challenges to managing and using system knowledge. The Systems Modeling Language (SysML) is a modeling language specifically for systems, while Machine Learning (ML) is a tool to tackle complex problems. Currently, no bridge between systems modelled in SysML and ML regarding said systems has been proposed in literature. This thesis presents an approach that uses Model-driven Software Engineering (MDSE) and Template-based Code Generation (TBCG) to generate a ML IPython Notebook (IPYNB) from a SysML model. A mapping configuration using JavaScript Object Notation (JSON) allows the definition of mappings between SysML elements and template variables, enabling configuration and user-supplied templates. To test the approach, a SysML model describing ML to predict the weather based on data is created. Python ML templates are supplied and template variables mapped with the JSON mapping configuration are proposed in the thesis. The outcome is an executable IPYNB that contains all information from the SysML model and follows the modelled workflow. The findings of the work show that model-driven ML using SysML as a modeling language is beneficial due to the representation of ML knowledge in a general-purpose modeling language and the reusability of SysML model elements. It further shows that TBCG and a mapping configuration allow for more flexible code generation without changing the source implementation.
A quantum-light source that delivers photons with a high brightness and a high degree of entanglement is fundamental for the development of efficient entanglement-based quantum-key distribution systems. Among all possible candidates, epitaxial quantum dots are currently emerging as one of the brightest sources of highly entangled photons. However, the optimization of both brightness and entanglement currently requires different technologies that are difficult to combine in a scalable manner. In this work, we overcome this challenge by developing a novel device consisting of a quantum dot embedded in a circular Bragg resonator, in turn, integrated onto a micromachined piezoelectric actuator. The resonator engineers the light-matter interaction to empower extraction efficiencies up to 0.69(4). Simultaneously, the actuator manipulates strain fields that tune the quantum dot for the generation of entangled photons with fidelities up to 0.96(1). This hybrid technology has the potential to overcome the limitations of the key rates that plague current approaches to entanglement-based quantum key distribution and entanglement-based quantum networks. Introduction
The advent of autonomous and self-driving cranes represents a significant advancement in industrial automation. One critical prerequisites for achieving this long-term goal is the accurate and reliable detection of tools guided by ropes in real-world environments. Since the tool is suspended by ropes, the tool pose cannot be controlled directly. This master’s thesis addresses the challenges of pose estimation for rope-guided tools using point cloud measurements. The proposed algorithm utilizes constraints imposed by the crane kinematics and information extracted during the segmentation process to efficiently infer the pose of the hook, therefore enabling the use of the pose for decision making in real-time critical applications. RANSAC (Random Sample and Consensus) is deployed in the segmentation process to extract geometric primitives from the point cloud which represent the ropes and distinctive parts of the tool. Since the point cloud is often to sparse for feature matching a bounding box is used to estimate the initial position of the tool. Two different methods are presented to improve the initial pose. A computationally expensive method with a high level of confidence, integrating the ICP (Iterative Closest Point) algorithm is used as a benchmark. A linear Kalman filter is used in the second method which is real-time capable. The benchmark is then used to evaluate the real-time capable approach. The core contributions of this research lie in the innovative utilization of bounding boxes for pose estimation. The findings and methodologies presented herein constitute an advancement towards the realization of autonomous and self-driving cranes.
With green cosmetics becoming widely used in Germany, this research would like to fill a research gap and investigate the impact of transatlantic transportation on the willingness of German customers to purchasing the product. With growing environmental awareness this information might be decisive for companies willing to expand internationally. They can take it into consideration when creating their international expansion strategy and deciding for the mode of entry.
Current research also explores the option of targeting the customers with marketing messages to share information about the low environmental impact of the transatlantic transport. It tests different marketing messages and analyses their impact on green purchase intention.
The research activity described in this master thesis focus on global leadership in team sport. Football head coaches working or who have worked in the globalised Big Five leagues of England, France, Germany, Spain and Italy are investigated. These leagues are host to players, staff, executives, fandoms and head coaches from around the globe. Sport in general is posed as a valid platform to investigate global leadership. Elite and globalised clubs in association football are further posed the archetype of global sport. Head coaches at the helm of the on-field and off-field teams are hypothesised as global leaders, due to their squad, staff and networks of global nature and the span of their influence on individuals around the globe.
It is proposed that investigations of the leadership in this setting can usefully contribute to insights on global leadership. The research activity follow an exploratory purpose resulting from a gap found in the literature review. The research design framework is a first sequential loop of Ground Theory methodology with the aim to identify useful hypotheses for future theoretical sampling. Secondary data was gathered and analysed qualitatively. The data stems from the public domain and statements from interviews, commentaries, biographies, and conferences on or by the head coaches. The theoretical framework of the presented re-search covers the personal traits and attributes of the investigated individuals.
Findings both overlap and contrast with findings from other global leadership research activities. The differences were identified in properties of the global sport business such as constant public attention. Based on the findings from the purposive sampling and acknowledging applicable limitations on the findings, hypotheses for theoretical sampling are proposed. Theoretical sampling is the next step in the workflow of the Grounded Theory methodology used for this study.
Companies worldwide and, therefore, companies from Vorarlberg face a common problem: the lack of skilled workers that led to the so-called “war for talents” in the last decades. This problem encouraged scientists to investigate the importance of many different monetary incentives and non-cash benefits to win this war for talents. This master’s thesis aims to examine if and how companies in Vorarlberg already use non-cash benefits. Furthermore, the most important benefits and their influence on the attractiveness of job advertisements are identified.
For this purpose, interviews with three HR managers from companies in Vorarlberg are carried out. Subsequently, in a quantitative survey, 21 different monetary incentives and non-cash benefits, intangible non-cash benefits, and corporate culture are evaluated by 316 participants. Furthermore, the participants ranked five different job advertisements to conceive results on the research questions.
The results clearly show that non-cash benefits are far more critical for future employees than classical monetary incentives. Although the number of international participants was lower than the number of Austrian and German participants (41 to 81 to 194), it is still obvious that independent of nationality, non-cash benefits can lead to a competitive advantage for companies in Vorarlberg. The interviews show that companies already work with such benefits in their daily business but do not strategically communicate on the topic.
To summarize, it can be concluded that a variety of non-cash benefits should be implemented within a company and also should be mentioned in job advertisements as they can help to attract more applicants not only from Austria but also from abroad and, therefore, help to win the war for talents.
Power cables play an important role in power grids. Insulation faults in cables can have adverse effects on the operating behaviour. These effects can be assessed through an AC withstand test by using a very-low frequency high voltage generator. This generator produces a sinusoidal voltage waveform at 0.1Hz with high voltage levels up to 65kV peak. During the quality assessment, the power cable is repeatedly charged and discharged. The discharging process is done by a discharging circuit where the energy is dissipated thermally. But to reuse the dissipated energy a novel extension in form of an energy storage system is presented. This thesis, therefore, describes the design process of an energy storage system that allows the temporary storage of the discharge energy. The developed system is composed of a bidirectional DC/DC converter and an aluminium electrolytic capacitor as storage type. Based on the maximum VLF system ratings the energy storage unit is dimensioned and sized. The effective power flow control between the storage system and the available discharge energy is done by a synchronous buck-boost converter. This bidirectional converter works in continuous conduction mode over the complete charging phase. Together with a theoretical analysis of the underlying problem and the use of converter analysis methods the selected synchronous buck-boost converter is dimensioned and sized. In addition, a state space AC modeling of the converter with its electrical uncertainties is conducted. With the converters AC model, the controller is designed. A closed-loop input converter current control scheme based on a proportional-integral controller is implemented. The system assessment is done by a model-based hardware implementation in Matlab Simulink and Plecs Blockset. The system is rated to store discharge energies up to 4.3kJ in a short charging period of 2.5s. The maximum peak power during the charging phase is 2.7kW. The digital proportional-integral controller is implemented through an emulation process of the designed analog controller. Based on a C-code implementation of the digital controller the gap between the real hardware is reduced. During the design process theoretical calculations are made and reveal that designing a capacitor storage unit has a direct impact on the peak system currents and also impose also limitations on permissible DC voltage ranges on electrical components. The developed energy storage system and its power flow control strategy were investigated through simulation studies. The results show proper charging of the energy storage medium. In addition, also a statement of the final technical feasibility is made. In total, this work summarizes a detailed design process of the energy storage system. This proof of concept is intended to further advance the system integration.
The rapidly evolving nature of Industry 4.0 has confronted corporates with the challenge of being able to react rapidly and nimbly (Van Solingen, 2020). Hence, many corporates need to embark on a journey of adaptation toward becoming agile organisations (Schmitz, 2018). However, this adaptation can only be achieved if employees fully commit to changing to an agile posture, and the required commitment is simply not forthcoming without proper corporate initiatives (Neves & Caetano, 2009). As there is no holistic summary of corporate initiatives required to boost employees' commitment to change when approaching an agile transformation, this study supplements the current research. The initiatives are derived from the existing literature and from unique insights given into a European automotive supplier that is currently managing a global agile transformation. Employees’ perceptions of the transformation in Austria and China were recorded and conclusions regarding what drives employees’ commitment to change and what led to job terminations were determined.
Development of a low pressure syringe pump for detecting cannabinoids through liquid chromatography
(2022)
The following thesis covers the miniaturization and characterization of a pneumatic syringe pump, which is used for applications in low-pressure liquid chromatography. For this purpose, the components of the prototype are dealt with in the first section. These include the membrane pump and the cylinder for pressure and force generation, the syringe used for sample preparation and the construction of the test column. Furthermore, the pressure preparation on the cylinder, the friction losses of the syringe and then the behavior of the syringe in various application scenarios are considered. In the second section, the focus is on the different behaviors when using water and ethanol as a solvent. Tests in normal applications, as well as with air pockets or leaking seals, show the different behavior and the resulting deviations in the test pressure of the column. In addition, the maximum forces that can be applied to the syringe are worked out in several tests and the different maximum pressures, which depend on the solvent contained, are evaluated. These different maximum pressures, which are due to the different sealing behavior in connection with the surface tension of the liquid, will be discussed in conclusion. An outlook follows, up to which test pressures the system can be used and how these can be achieved.
How people perceive stigmatization at work in connection with mental health problems and what role this stigmatization fulfils in the DACH-Region, means Germany-Austria-Switzerland, has so far received no greater attention from scientists. Although the stigma of mental illness has been extensively researched among the general population, little is known about its consequences of the stigma of mental health in the workplace.
This study seeks to bridge the gap in this area. As the purpose of this thesis is to illustrate the dynamics of stigmatization rather than to explain its mere quantitative relevance, I have chosen to investigate how the complex systemic interdependencies according to Forrester (1968) manifest in the reflection of the subjects.
On the background of socio-cultural aspects in the DACH-Region regarding mental health problems and forms and natures of stigma while following the question what role stigmatization plays in this German-speaking area DACH, I conducted a qualitative social research study with affected persons (employees from various German companies) to investigate this issue. Hereby I focus on people working in the industry sector.
The present thesis begins by exploring the question of intercultural and sociocultural differences in the DACH region according to Hofstede’s Dimensions, as well as their possible relevance for answering the research question. Definitions and theoretical interpretations regarding the backgrounds about mental health, mental health problems and their appearance will be mentioned. Based on Goffman’s (1963) research on stigma, I investigate why mental health issues have the potential to stigmatize especially at the workplace. Goffman’s ideas on stigma illustrate how by providing important insights into understanding the situation of affected persons. The connection between stereotypes, stigmatization, and discriminatory behaviour according to Major & O’Brien (2005) is hereby necessary to be noticed.
Through personal interviews I explore how, what way, people at work perceive stigmatization surrounding mental health problems and how stigmas interact. The findings conducted in this study give a cue towards the systemic approach of stigmatization. That is why a new hypothesis on the ways of stigmatization in German-speaking countries is drawn up. Stigmatization is under investigation as a systemic instrument for maintaining management and group power to affect single employees and restore group identity, consciously or unconsciously. I discuss the theoretical and practical implications of these findings for management behaviour and leadership development in organizations.
This master’s thesis provides an overview of a more efficient, future-oriented living concept in Dornbirn, Austria. The use of a combined heat and power unit (CHP), in combination with a thermal storage, as a heating system is specifically investigated. In order to make this heating system more attractive for the consumer, the sale of the generated electricity from the CHP is considered. The more efficient use of energy for heating increases the attractiveness by a minimisation of the living space. This master’s thesis aims to draw attention to the issue and to achieve a rethinking in the planning of future living space. For the research and elaboration of this thesis, statistics and trustworthy literature were used, and physical modelling was applied. This Master’s thesis can be assigned to the fields of energy technology, mechatronics, architecture and civil engineering. It contributes for students, researchers, and other interested person in these sectors.
Supply shortages faced in products and resources from semiconductors to natural gas in recent years have had impact massive on global economy, but such challenges are not new for supply chain professionals. Many major events in the past have disrupted supply chains: 9/11 attack in New York, Tsunami in Japan to name a few, but COVID19 have had the biggest and widespread impact in the modern times. Even though supply chain resilience being a term coined in early 2000’s, its usage and importance has increased since then. With the curiosity of assessing the current state of sup-ply chain resilience literature and finding a resilience measurement method which is a one-fit for all supply chains in the manufacturing industry of Vorarlberg, the following research project was undertaken. Research is carried out with mixed methods, using a systematic literature review followed by expert interviews. In the conclusion of the research the author argues that there is a significant difference in the understanding of the term resilience within industry, there is a lack on the need for a meas-ure for resilience. The ways in which the structure of an organization impacts the level of resilience, foreseen benefits of digitalization and technologies for resilience are also dis-cussed. A comparative analysis on the SCR measurement methods discovered in literature, resulted in recommending Resilience index for on-time delivery proposed by Carvalho et al for the mentioned industry.
In the context of this master thesis, general tensions within the relationship between headquarters and their subsidiaries are examined using the practical example of a Swiss company with its subsid-iary in Kenya. Thereby, the influence of cultural aspects and the associated different expectations on management and leadership are emphasized. In doing so, two countries are compared which have not yet been considered in the same context. The objective of this master thesis is to develop a framework that enables the headquarter in the German speaking area of Switzerland and the sub-sidiary in the Bantu speaking area of Kenya to overcome cultural barriers and to increase mutual understanding in the business context. This will facilitate the identification of potentially dysfunc-tional aspects in the working relationship and provide a basis for optimizing the existing business relationship between the Swiss headquarter and the Kenyan subsidiary.
This thesis addresses the overarching question of what the two business entities need to know about each other in terms of cultural characteristics and emerging differences in business practices (in terms of management/leadership) in order to improve the overall cooperation and working rela-tionship between the headquarter and its subsidiary. Thus, the following topics are emphasized with-in this thesis: tensions within the headquarter/subsidiary relationship, concise country profiles of Switzerland and Kenya including a cultural overview of both countries, cultural concepts including organizational culture, common leadership theories related to the situational leadership approach, and finally, an evaluation of the current status quo in the working relationship between the Swiss headquarter and the Kenyan subsidiary based on interviews.
This research seeks to explore the cultural impact in the development of a new product, and if operational CRM (CRM technologies) can bring these two concepts together. As an industrial designer, the researcher finds it fascinating to explore how the abilities that a designer uses can help to solve users' problems could be implemented into structural or strategic decision-making of a company. Therefore, the researcher believes that the results might bring value to the head of international teams in charge of Product Development, by bringing some ideas for what is essential to consider in these processes and how CRM could become a relevant tool to satisfy customers and users.
This research generates value to international management and leadership studies because it brings the management of new product development from an organizational point of view within an international context to the forefront. It also builds an understanding of what to consider when the value chain is decentralized and involves international collaboration in product development processes. And positive elements and/or problems that may arise concerning culture and the role of the CRM within this process.
In an oversaturated market, companies are required to use innovative and, above all, creative advertising methods to capture their customers’ attention, and thus differentiate themselves from rival businesses. To this end, companies have been increasingly relying on the use of humor, a phenomenon that remains highly subjective and is perceived differently by each individual. This master’s thesis, which was completed as part of the International Marketing and Sales program at the FH Vorarlberg, focuses on this phenomenon of humor as well as its impact on advertising perception. With the aid of three different theories, the term “humor” is defined. Furthermore, this study explains and researches the so-called vampire effect, wherein various factors (in this case humor) draw attention away from the actual advertising message. In addition, this thesis takes a closer look at involvement, as a person’s involvement or interest in a brand or product can influence brand and product recall and recognition. An online survey was conducted to determine whether the vampire effect caused by humor is able to influence brand and product recall. In other words, this concerns whether the viewer can still remember the brand and product afterward or whether the humor employed triggers the vampire effect. Furthermore, this thesis explored whether the vampire effect caused by humor is able to influence brand and product recognition. Recall is the retrieval of information from memory without direct cues, whereas recognition refers to the recognition of information when it is presented again. Furthermore, within this context, it was discovered that brand and product recall varies with low and high involvement viewers of the advertisement. In other words, this means that the strength of the vampire effect caused by humor changes depending on the strength of the viewer’s involvement. During the course of this research, it was further observed that the humor employed significantly affects the perception of the advertising message, thus confirming the existence of the vampire effect. This effect also influences both brand as well as product recall and recognition. In both cases, participants in the survey were less able to remember the product and brand in the humorous advertising. Furthermore, it was proven that people with low involvement in the advertised product group are more heavily affected by the vampire effect. As such, they are more likely to not remember the product or brand after seeing the advertisement.
Marketing automation
(2021)
In the residential construction industry, the focus on energy efficiency and cost effectiveness has been gaining importance. In order to achieve these contradicting objectives, a shift towards a reduced complexity in building practices can be observed.
Within the HVAC sector, the Tempering method for space heating has received particular attention as an alternative way to heat museums and buildings worthy of preservation.
In spite of the simplified design, this space heating system is claimed to offer significant advantages in its present field of application.
This study evaluates the implementation of Tempering in the residential context. So far, there is no scientific research on the implementation of Tempering in energy efficient-dwellings.
This master thesis provides initial results on achievable heat flux values, the impact on heat generation efficiency, the inherent installation costs as well as the particular
consequences in terms of end energy consumption of the building as a whole. The findings are compared to the individual performances of well-established heat emission approaches.
By means of a numerical analysis and a case study on a real-case single-family home, it is found that the heat flux values of Tempering systems suffice for the implementation within buildings, which comply with the low-energy building standard. Comparing radiant walls, radiant floors and radiators, the inherent installation costs are lowest for Tempering and radiant floors. The impact on the end energy consumption depends largely on the utilised heat generation system. With a gas-condensing boiler, Tempering performs equal to the radiant systems. When a ground source heat pump system is installed, however, Tempering performs poorly and accounts for a significantly increased energy consumption. Radiator systems are found to be the most energy-efficient method for space heating in both cases.
The demand for managing data across multiple domains for product creation is steadily increasing. Model-Driven Systems Engineering (MDSE) is a solution for this problem. With MDSE, domain-specific data is formalized inside a model with a custom language, for example, the Unified Modelling Language (UML). These models can be created with custom editors, and specialized domains can be integrated with extensions to UML, e.g., the Systems Modeling Language (SysML). The most dominant editor in the open-source sector is Eclipse Papyrus SysML 1.6 (Papyrus), an editor to create SysML diagrams for MDSE.
In the pursuit of creating a model and diagrams, the editor does not support the user appropriately or even hinders them. Therefore, paradigms from the diagram modelling and Human Computer Interaction (HCI) domains, as well as perceptual and design theory, are applied to create an editor prototype from scratch. The changes fall into the categories of hierarchy, aid in the diagram composition, and navigation. The prototype is compared with Papyrus in a user test to determine if the changes have the effect of improving usability.
The study involved 10 participants with different knowledge levels of UML, ranging from beginners to experts. Each participant was tested on a navigation and modelling task in both the newly created editor, named Modelling Studio, and Papyrus. The study was evaluated through a questionnaire and analysis of the diagrams produced by the tasks.
The findings are that Modelling Studio’s changes to the hierarchical elements improved their rating. Furthermore, aid for diagram composition could be reinforced by changes to the alignment helper tool and adjustments to the default arrow behaviour of a diagram. Lastly, model navigation adjustments improve a link’s visibility and rating of a specialized link (best practice). The introduction of breadcrumbs had limited success in bettering navigation usability. The prototype deployed a broad spectrum of changes that found improvement already, which can, however, be further improved and tested more thoroughly.
The purpose of this work is to explore implicit schemes underlying the market segmentation analysis process. Boosting transparency for and in the new discipline of healthcare marketing, the work offers a toolbox of both primary and secondary methods to identify the accurate target market. This is crucial, since resource allocation in B2C segmentation and targeting is still often misleading. An Austrian, internationally present niche player serves as a research object to turn theoretical insights into practical verification. Data for the thesis are collected through company-internal data analysis and desk research, grounded in a multi-method approach with primary and secondary research. On the one hand, the work assesses the most effective segmentation and attractiveness/knock-out criteria according to scientific sources. Delving into the topic of a priori and a posteriori segmentation, an overview of suitable techniques is going to be offered. On the other hand, the thesis illustrates how the accurate target segment in the healthcare industry can be evaluated and determined through companyinternal consumer and market data.
Primary research on demographics (age, gender), psychographics (preferred channels), behavioral criteria (new/existing, CLC) and product categories is found to be particularly meaningful for the healthcare player. Results vary between countries, which is why an international-marketing strategy instead of a domestic-marketing approach is advisable.
Secondary research shows that socio-demographic and behavioral criteria are most used as a priori criteria, whereas a posteriori segmentation is promising to reveal psychographic clusters. One of the author’s recommendations is to niche down accurate market segments such as LOHAS or “best agers” by refining psychographics/socio-demographics with behavioral segmentation through “occasions” (e.g. back pain, depression, injuries). Novel approaches such as outcome-based segmentation or emphasizing “promoters” are discussed too.
The findings pave marketing managers the way for identifying the accurate target segments in the B2C health industry, selecting accurate methods grounded in profound scientific research and with concepts suitable for SMEs. The thesis proves that marketing segmentation is no longer a “nice-to-have” but a “must” in the health(care) industry.
Moving from one country to another, from one cultural context to a different one comes with many challenges and problems. The expatriate adjustment process, in general, has been evaluated extensively in the literature. Little is known if the knowledge in the literature is also valid for the situation of expatriates in rural Vorarlberg. In this paper was examined, which are the most common problems for highly skilled immigrants that are moving to Vorarlberg. In a mixed-method approach, information was gathered with an online questionnaire whose results served as a basis for a series of semi-structured interviews. In addition, an expert talk with a local relocation consultant was conducted. It was found that by far, the most severe difficulty is based on the domestic language situation. An expatriate needs to talk and understand German, but the local language is an Alemannic subsection of the German language that is not easy to understand. Additional difficulties that cause culture shock are limited opening hours, mobility troubles, and several others. The awareness about the composing of these problems might help to find the appropriate measures to support expatriates to come in the future.
In recent years, more and more companies have become aware that a brand also has a social dimension, and with the advent of social media platforms, brand communities have experienced a shift from a traditional offline to more of an online presence. Brands of innovative consumer durables have also recognized social media brand communities as a very significant marketing strategy. It is therefore important to understand the influence of these communities on members' purchase intentions.
This master’s thesis has the goal of demonstrating to enterprises what aspects of a social media brand community will influence the purchase intention of its members and what should be considered in order to enhance it. This will ultimately lead to the following research question: How do social media brand communities influence the diffusion process of innovative consumer durables in the DACH region?
To answer this, a quantitative study has been conducted that has targeted people who are participating in a social media brand community of innovative consumer durables in the DACH region. This involved testing various criteria of a social media brand community and their impact on the diffusion process (purchase intention).
The findings of the study revealed that increased positive electronic word-of-mouth leads to enhanced purchase intention of members. Furthermore, the research has shown that higher identification with a social media brand community, greater engagement, increased entertainment value, faster corporate responsiveness, and reduced occurrence of social spam, do not have a positive effect on the diffusion process of innovative consumer durables.
Influencer Marketing has been discussed by various marketing experts for years and is already a fixed component of the marketing strategy in many companies. These are mainly companies from the B2C sector. Recently, more and more companies are asking themselves about possible areas of application within the B2B structure. This phenomenon is influenced by the increase in digitalization and the ever-higher hurdles in reaching target groups using traditional marketing tools.
The topic of this master’s thesis was the result of professional and personal development. Various modules attended during the study inspired a deeper interest in the subject. Furthermore, the topic was always a point of discussion in the professional environment, resulting in the realisation that there is currently very little knowledge in B2B companies regarding Influencer Marketing.
The aim of the research was to discover how to systematically find end users for the use of Influencer Marketing in B2B companies in the tool and hardware industry. Furthermore, the success factors for a long-term cooperation between influencers and companies from this industry will be identified and presented.
Research questions were created in order to realise the above-mentioned objectives. Therefore, the primary research question and three sub-research questions were created for both the theoretical and empirical part of the work. To answer these questions, eight experts from B2B companies in the tool and hardware industry were interviewed. The evaluation was based on the qualitative content analysis according to Mayring.
From the research results, a possible selection procedure could be identified, which would enable companies to systematically select influencers for marketing purposes. Furthermore, success criteria for a long-term cooperation between influencers and companies were also identified.