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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.