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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.
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.
Companies develop and implement strategies with the aim to address the needs of their customers. Acquisition is one market expansion strategy that companies can use to acquire new market access, technologies and/or to grow organically. In recent years, Chinese companies have been active in acquiring companies all over the globe to develop their strategic position. This caused certain contra reaction in Europe and as well in the Swiss media against cross-border acquisitions of Swiss companies.
Swiss companies and particularly the Swiss-MEM (Machinery, Electrical and Mechanical) industry is highly export oriented and their value proposition builds on attributes like knowledge, technology, and differentiating products. Among them are many “hidden champions” and niche players who successfully dominate the market segment.
As observed with Chinese companies, Indian companies also started to become more active outside of their domestic markets by increasing their foreign direct investments into Europe, Asia and North America, over the last decades. The lasting and good relationship of India and Switzerland might trigger the wish for Indian companies to acquire Swiss and particularly Swiss-MEM companies for acquisitions.
This Master’s Thesis assesses how often Indian investments into public and privately owned Swiss-MEM companies by acquisition happen, how are the attempts of acquisitions perceived by the stakeholders and what measures Swiss and Swiss-MEM companies can take, to protect themselves from being acquired. To access the research topic, several sub-questions will be analysed with the aid of primary and secondary research to assess the situation.
The research topic is of particular interested to the author since he spent over 20 years working in the Swiss-MEM industry, involved in international affairs and in recent years specifically with India. The observation of Chinese acquisition activities and insight into the size and potential of India were the drivers for researching whether India might follow China’s example.
In conclusion, Indian companies are not explicitly targeting Swiss and Swiss-MEM companies, but there are reasons to believe that it would make sense for Indian companies to look into the acquisition of Swiss and Swiss-MEM companies. The perception of such acquisitions varies, but there are arguments for and against them. Companies must take strategic and organisational measures in order to prevent themselves from becoming the target of an acquisition. However, it is known that the state should not interfere in the market and a discussion at a political level, planning how to deal with cross-border acquisition, is needed.
Further areas for research based on this Master’s Thesis could be the review of how the targeting of Swiss and Swiss-MEM companies by Indian companies would look, and also the topic of the succession planning in Swiss secondary sector in conjunction with Indian targeting for acquisitions. A third area to research might be investigating the political aspects involved in the research questions.
Many test drives are carried out in the automotive environment. During these test drives many signals are recorded. The task of the test engineers is to find certain patterns (e.g. an emergency stop) in these long time series. Finding these interesting patterns is currently done with rule based processing. This procedure is very time consuming and requires a test engineer with expertise. In this thesis it is examined if the emerging field of machine learning can be used to support the engineers in this task. Active Learning, a subarea of machine learning, is used to train a classifier during the labeling process. Thereby it proposes similar windows to the already labeled ones. This saves the annotator time for searching or formulating rules for the problem. A data generator is worked out to replace the missing labeled data for tests. The custom performance measure “proportion of seen samples” is developed to make the success measurable. A modular software architecture is designed. With that, several combinations of Time Series Classification algorithms and query strategies are compared on artificial data. The results are verified on real datasets, which are open source available. The best performing, but computational intensive solution is an adapted RandOm Convolutional KErnel Transform (ROCKET). The custom query strategy “certainty sampling” shows the best results for highly imbalanced datasets.
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.
Throughout history, a variety of influences have changed the way we sell our products. Starting with the Industrial Revolution up to the first saturation phase in the 1970s. The question now arises as to whether the heating industry is currently back on an evolutionary development path with the increasing digitalisation of distribution. How the sales process in the B2B sector will change with increasing digitalisation and what effects this will have on sales personnel is only documented by a few sources which do not allow any conclusions to be drawn about the craft or even the heating industry. This results in a research gap which is to be closed in the context of this thesis. The aim of this research project is to find out the effects of a further digitalisation of the sales process on the sales force in the defined environment of the heating industry in Central Europe. For this purpose the following research questions are asked: Which steps in the sales process in the heating industry in Central Europe should be digitalised? How will the digitalisation of the sales process affect the sales force in the heating industry in Central Europe? A case study, according to Yin was chosen as the research method. The data were collected by means of in-depth interviews and analysed qualitatively, according to Mayring. The increasing digitalisation will have a large effect on the sales force, tasks will disappear, new tasks will be added and new ones will replace conventional working methods. In summary, automation will simply make tasks superfluous, software tools will improve quality and increase efficiency, and personal selling will become a premium skill. Companies will try to automate as many backoffice activities as possible and reduce the number of office staff if necessary.
The present research had compared how Uppsala and Bartlett & Ghoshal (B&G) models explain the internationalization process of the Brazilian pulp producer Fibria.
The Uppsala model describes the developments of capabilities that enable the firm to move towards higher commitments abroad. Despite its sine-qua-non dependence on foreign markets, it is unlikely that Fibria will internationalize its production to another country, given the country-specific advantages that the company has in Brazil. Nevertheless, Fibria set its structure abroad even when the direct exports would suffice to reach the markets without any foreign direct investment.
B&G deals with the aspects of the organizational structure and described the Transnational type as the evolution of the international firm. In their typology, Fibria was a Global and Ethnocentric type, but interestingly, elements of Transnational and Geocentric models were also observed in the company.
Both theories overlap or complement each other in many aspects. However, they could not explain the peculiarities of the internationalization of Fibria. One reason is the lack of country-related elements in these models.
Eventually, comparisons between theories such as those presented enable decision-makers to align the corporate strategy using suitable models, bearing in mind the limitations that each method entails.
Nowadays, the area of customer management strives for omni-channel and state-of-the-art CRM concepts including Artificial Intelligence and the approach of Customer Experience. As a result, modern CRM solutions are essential tools for supporting customer processes in Marketing, Sales and Service. AI-driven CRM accelerates sales cycles, improves lead generation and qualification, and enables highly personalized marketing. The focus of this thesis is to present the basics of Customer Relationship Management, to show the latest Gartner insights about CRM and CX, and to demonstrate an AI Business Framework, which introduces AI use cases that are used as a basis for the expert interviews conducted in an international B2B company. AI will transform CX through a better understanding of customer behavior. The following research questions are answered in this thesis: In which AI use cases can Sales and CRM be improved? How can Customer Experience be improved with AI-driven CRM?
Sustainable distribution
(2020)
This master thesis gives an insight into the topic of sustainability in the banking industry and focuses on distribution. In the first part of the thesis, the terms and concepts of sustainability and sustainable distribution are being explained and existing methods for measuring sustainability are presented on the basis of an extensive literature research.
Subsequently, the banking industry is introduced, the distribution of financial services is explained, and the specifics of sustainable distribution in the banking industry are elaborated.
An empirical study in form of expert interviews was used to show to what extent sustainability currently plays or will play a role in the banking sector. For this purpose, experts from six banks were interviewed.
In the final part of the paper, the hypotheses formulated at the beginning of the paper as well as additional questions are examined or answered and a model for evaluating the effects of selected distribution channels on ecological and social sustainability is being presented.
Graphite substrates underwent two methods of creating doped silicon carbide films via carbothermal reduction; the first method being liquid-phase processing, or dip-coating, and the second gas-phase processing, otherwise referred to as the solid-vapour reaction. The dip-coating procedure resulted in flaky coatings, while the solid-vapour reaction resulted in polycrystalline films with columnar growth that displayed promising morphological and electrical properties. The films were tested on their performance as semiconductor diodes, and proved that carbothermal reduction in the gas phase is a promising technique for creating polycrystalline silicon carbide films for the application of light-emitting diodes.
In recent years, much research has been done on medical laser applications inside the human body, as they are minimally invasive and therefore have fewer side effects and are less expensive than conventional therapies. In order to bring the laser light into the human body, a glass fibre with a diffuser is needed. The goal of this master thesis is the characterization and production of fibre optic diffusers that can be used for the three therapeutic applications: photodynamic therapy, laser-induced thermotherapy and endovenous laser therapy. For this purpose the following goals have to be achieved:
- Optimization of the efficiency and homogeneity of internally structured diffusers
- Examine damage thresholds of the diffusers in the tissue using a crash test
- Achieving a better understanding of the decouple mechanism with a simulation
Using an ultra-short pulse laser, modifications could be introduced into the fibre in this way that the radiation profile is homogeneous and the decoupling efficiency is 68.3 %. It was discovered that the radiation profile depends on the wavelength. Attempts have been made to improve the decoupling efficiency by mirroring the distal end of the fibre. The mirror reflects the remaining light back into the fibre, so that it is also decoupled lateral on the modifications. Vapor-deposited aluminum with physical vapor deposition is a promising approach. However, the adhesion of the coating must be improved or the coating must be protected by a mechanical cover, otherwise it will flake off too quickly.
In a crash test, it was shown that the glass fibre diffusers can withstand 20 W laser power for 300 s without visible change. In an ex vivo test, the coagulation zone in the tissue was examined and it was showed that the diffusers radiate radially homogeneously. Using a ray trace simulation, the course of the light rays in the fibre was examined and the correlation of modification width and length with the decoupling efficiency was investigated. It was discovered that there are helical light rays in the fibre, which cannot be decoupled by modifications in the fibre centre.
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.
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.
Digitalisation poses great challenges for regional tourism management. However, many organisations are currently undergoing a transformation from a marketing to a destination management organisation (DMO), which is why only a few have managed to adopt new digital approaches and to assert themselves as DMOs within the destination and against ever growing global platforms.
The presented master thesis therefore deals with this issue and aims to pave the way for DMOs to develop and use digital business models themselves.
The objective of the thesis is to develop a systematic process for the development of own DMO business models and to evaluate whether the establishment of a multi-sided platform as the recipe for the success of global platform providers is also suitable for DMOs. For this purpose, an extensive literature research was conducted and semi-structured expert interviews were evaluated. In addition, the Anchor Point Canvas was developed as a supporting framework for the modelling of business models for companies with historically grown structures and constraints.
This thesis aims to support the product development process. Therefore, an approach is developed, implemented as a prototype and evaluated, for automated solution space exploration of formally predefined design automation tasks holding the product knowledge of engineers. For this reason, a classification of product development tasks related to the representation of the mathematical model is evaluated based on the parameters defined in this thesis. In a second step, the mathematical model should be solved. A Solver is identified able to handle the given problem class.
Due to the context of this work, System Modelling Language (SysML) is chosen for the product knowledge formalisation. In the next step the given SysML model has to be translated into an object-oriented model. This translation is implemented by extracting information of a ".xml"-file using the XML Metadata Interchanging (XMI) standard. The information contained in the file is structured using the Unified Modelling Language (UML) profile for SysML. Afterwards a mathematical model in MiniZinc language is generated. MiniZinc is a mathematical modelling language interpretable by many different Solvers. The generated mathematical model is classified related to the Variable Type and Linearity of the Constraints and Objective of the generated mathematical model. The output is stored in a ".txt"-file.
To evaluate the functionality of the prototype, time consumption of the different performed procedures is measured. This data shows that models containing Continuous Variables need a longer time to be classified and optimised. Another observation shows that the transformation into an object-oriented model and the translation of this model into a mathematical representation are dependent on the number of SysML model elements. Using MiniZinc resulted in the restriction that models which use non-linear functions and Boolean Expressions cannot be solved. This is because the implementation of non-linear Solvers at MiniZinc is still in the development phase. An investigation of the optimally of the results, provided by the Solvers, was left for further work.
Increasing international competition and accelerated technological change characterize the environment in which companies must maintain and, if possible, expand their competitive advantage. In this context, the new, popular keyword innovation management is often mentioned. Many corporations propagate and use it for marketing purposes. As a result, the companies have to evaluate, develop and launch innovations increasingly faster, which poses great challenges for many and requires a high degree of adaptability.
This master thesis analyzes innovation management (IM) in the automotive industry and in other industries (material manufacturers, service providers, medicine, ...) depending on the number of employees and turnover. In addition, the maturity levels of the IMs and the innovation management systems (IMS) are examined. It also tries to determine which design or "building blocks" are necessary for a successful innovation management. Furthermore, factual and monetary guidelines by the management are evaluated. The thesis also aims to find out how the success of IM is measured. Therefore, guideline-based expert interviews were conducted with responsible people from the innovation departments and then systematically analyzed.
In the literature, expenses for innovations are often wrongly equated with the R&D rate. In this master thesis, it could be shown that this ratio is highest in the automotive industry. However, it does not correlate with the number of employees, turnover, maturity level, success or design of the IM. Furthermore, it could be shown that larger companies have a higher degree of maturity. The reason for this is that more people are usually involved in innovation and that a holistic understanding of innovation is better anchored in large corporations. When designing the IM or the roles of the innovation department, large companies use several different types. While the IM departments in small and medium-sized companies are usually incubators and accelerators, large companies also use corporate venture capital to support start-ups and develop new business models. In this thesis, the success of IM was determined by the number of innovations implemented in customer projects. It was found that, regardless of the size of the company, a higher degree of maturity of the IM and the accelerator role seem to have a positive influence.
Unfortunately, there are rarely concrete goals and targets set by the management although these, along with a holistic understanding of innovation in the company, are without doubt the most important part of a successful innovation management.
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.
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.
A novel calorimetric technique for the analysis of gas-releasing endothermic dissociation reactions
(2020)
The humidification-dehumidification process (HDH) for desalination is a promising technology to address water scarcity issues in rural regions. However, a low humidifier efficiency is a weakness of the process. Bubble column humidifiers (BCH) are promising for HDH, as they provide enhanced heat and mass transfer and have low maintenance requirements. Previous studies of HDH-systems with BCHs draw different conclusions regarding the impact of superficial air velocity and liquid height on the humidification. Furthermore, the impact of flow characteristics has never been investigated systematically at all. In this study, an optimized BCH test setup that allows for optical analysis of the humidifier is used and evaluated. Our test setup is validated, since the influence of water temperature on the humidification, which is exponential, is reproduced. Measurements with seawater show that the normalised system productivity is increased by about 56 % with an increase in superficial air velocity from 0.5 to 5 cm/s. Furthermore, the system productivity is increased by around 29 % with an increase in liquid height from 60 to 378 mm. While the impact of superficial air velocity can be traced back to temperature changes at the humidifier and dehumidifier outlets, the impact of liquid height is shown to be caused by a smaller heat loss surface in the humidifier with an increase in liquid height. For the impact of sieve plate orifice diameter, a clear influence on the humidification is not apparent, this parameter needs to be investigated further. Finally, our new test setup allows for analysing the humidification of air (1) in a systematic way, (2) in relevant measurement ranges and (3) in comparison with optical analyses of the flow characteristics.