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Institut
- Fakultät Wirtschaftswissenschaften (66) (entfernen)
On 25 October 2016, the European Commission presented a proposal for a directive on a Common Corporate Tax Base (CCTB Proposal), which contains a comprehensive concept for the harmonisation of profit calculation regulations within the EU. Against this current background, the objective of the present work is to contribute to the implementation of the CCTB by identifying ambiguities and conceptual weaknesses in the design of the profit determination system of the CCTB Proposal and developing concrete recommendations for action for adjustments in the course of the further legislative procedure. In the first article, selected profit calculation rules of the CCTB Proposal will be analysed in detail and compared with the provisions on profit calculation under German commercial and tax law and the International Financial Reporting Standards (IFRS) recognised across member states. Based on the legal comparison, questions of interpretation and inadequacies of the profit calculation system will be considered and proposals for adjustments to various regulatory areas will be submitted. Furthermore, in the second article, within the framework of a holistic study, expert interviews will be used as an empirical-qualitative research design to generate reliable assessments on the part of the various stakeholder groups affected by the implementation of the future directive or involved in its elaboration. The results show the extent to which the profit determination rules of the CCTB Proposal in their current form are suitable for national and EU-wide implementation and in which areas the various expert groups still see concrete need for adaptation. Based on these expert assessments, the third article finally develops a proposal to reduce the threat of legal uncertainty in interpretation issues criticised by the experts. Based on economic maxims developed by the European Commission and existing accounting principles of the current CCTB Proposal, the EU Accounting Directive and IFRS, a system of specific European tax principles will be developed which could be implemented within the framework of the CCTB Proposal.
The dissertation analyzes the role of large banks in the context of financial (in)stability. Based on the underlying "too big to fail"-problem (TBTF), the three included papers investigate the reasons for the instability of banking systems on a national and international level. Already in advance, but at least since the years 2007/2008 with the escalation of the financial crisis, especially large banks are under critical supervision of regulators and the society. There exist numerous aspects that should to be taken into account when addressing TBTF which complicates the finding of a solution to the problem. In particular, the thesis investigates three major issues in this context: (1) The contribution of the size of a bank to the development of financial crises or the exposure of large banks to systematic risk and contagious spillovers. (2) The spillover effects from one banking system to another and the importance of banks' foreign asset holdings for the transmission of sovereign risk on foreign banks. (3) The impact of the degree of competition in the German banking market on the stability of the banking system.
Micro- and small enterprises are of great importance for the economic growth in developing countries, as they contribute to employment creation and innovation. In light of their economic relevance, several approaches to support micro- and small enterprises have emerged, including building human capital through business trainings. However, the effects of existing business trainings on entrepreneurial success have so far been limited. One promising alternative training approach that has emerged in the last years is personal initiative training, which teaches self-starting, future-oriented, and persistent entrepreneurial behavior. This dissertation helps to improve the understanding of personal initiative training by shedding light on the mechanisms through which it affects business success, on supporting factors, and on its long-term impacts. Chapter 1 provides an overview on the topic of personal initiative training for entrepreneurs in developing countries. Chapter 2 introduces personal initiative training and other proactive behavior trainings in various contexts of work, including entrepreneurship. The chapter presents action regulation theory and the theory on personal initiative as the theoretical foundation of the training. In addition, the chapter provides insights into training and evaluation methods and makes recommendations for the successful implementation of personal initiative training. Chapter 3 offers a first answer to the question how personal initiative after training can be maintained over time. The chapter introduces training participants' need for cognition as beneficial factor for post-training personal initiative maintenance. Chapter 4 explains how action regulation trainings like personal initiative training contribute to poverty reduction in developing countries by supporting entrepreneurial success. Chapter 5 enlarges upon the topic of personal initiative training for entrepreneurial success in developing countries. The chapter focuses on how personal initiative training supports female entrepreneurs in developing countries by helping them to overcome the uncertainty involved in entrepreneurial actions. Chapter 6 summarizes the overall findings and illustrates the theoretical and practical implications that result from this dissertation. In sum, this dissertation makes a contribution to the better understanding of personal initiative training and its effects on entrepreneurship in developing countries and thereby helps to create effective interventions to combat poverty in developing countries.
When Libet and colleagues published their results on the temporal order of movement preparation and the reported time of conscious will to move in 1983, they shed some doubt on the existence of free will. This marked the beginning of a controversial and still ongoing debate, not only about the existence of free will, but also about the appropriateness of methods and validity of results from research on free will. Belief in free will was also discovered as psychological research topic. Literature on belief in free will shows some evidence that most laypersons across different cultural backgrounds believe that they have free will and that a person's belief in free will might have an impact on cognition and behavior, tending to positive outcomes with a greater belief in free will. Empirical findings from the German-speaking area are sparse, probably due to a lack of validated measurements assessing belief in free will available in the German language. The aim of this dissertation is to critically examine some aspects in psychological research on free will and the belief in free will. Two studies are reported that aim to generalize the Libet paradigm for a free and voluntary decision with consequences for the acting person, as this was never reported to have been researched in literature before, and to test the critical objection that the measurement of reporting the conscious intention to move has a direct effect on the result in the Libet paradigm. Furthermore, the construction of the first inventory measuring belief in free will in the German language is described. This inventory was also created with the aim of overcoming some methodological problems in the existing instruments in English language. Furthermore, studies on the experimental manipulability of the belief in free will are reported. These findings provide implications in view of the current state of research on free will and belief in free will and its reliability.
This thesis analyses how European merger control law is applied to the energy sector and to which extent its application may facilitate the liberalisation of the electricity, natural gas and petroleum industries so that only these concentrations will be cleared that honour the principles of the liberalisation directives. After having discussed the complex micro- and macro-economic considerations which accompany any concentration of business activities, this thesis discusses the merger control regime of the European Community (EC) so as to establish whether the merger control under either Art. 66 Treaty Establishing the European Coal and Steal Community (ECSCT), the case law under Art. 101 and 102 Treaty on the functioning of the European Union (TFEU) and (Art. 81 and Art. 82 Treaty Establishing the European Economic Community (ECT), as it was introduced by the Commission and reviewed by the CJEU, the original Merger Regulation (MR1989) or the amended Merger Regulation of 1997 (MR1997) or the amended Merger Regulation of 2004 (MR2004) facilitate the liberalisation of European electricity and gas markets. Said liberalisation was introduced by the Internal Electricity Market Directive (IEMD), the Hydrocarbons Licensing Directive and the Internal Gas Market Directive (IGMD). The paper focuses on the contestable idea that regulatory amendments - especially the introduction of third party access by means of the directives - only form a first necessary condition for attaining economic alterations whereas pro-active conduct of the marketers is the second and decisive one in order to increase the competitive performance of the European energy supply industries. The analysis is supported by a second argument which relates closely to the ambivalent nature of concentrations: A concentration may be used to increase the process of market opening and the expansion into new markets by pooling of scarce resources. It may also be used as a retro -active means so as to create national champions, increase barriers to market entry of new competitors, enable cross-subsidisation so as to expand dominant positions on heretofore competitive up- and downstream markets.
Technological development made it possible to store and process data on a scale not imaginable decades ago — a development that also includes network data. A particular characteristic of network data is that, unlike standard data, the objects of interest, called nodes, have relationships to (possibly all) other objects in the network. Collecting empirical data is often complicated and cumbersome, hence, the observed data are typically incomplete and might also contain other types of errors. Because of the interdependent structure of network data, these errors have a severe impact on network analysis methods. This cumulative dissertation is about the impact of erroneous network data on centrality measures, which are methods to assess the position of an object, for example a person, with respect to all other objects in a network. Existing studies have shown that even small errors can substantially alter these positions. The impact of errors on centrality measures is typically quantified using a concept called robustness. The articles included in this dissertation contribute to a better understanding of the robustness of centrality measures in several aspects. It is argued why the robustness needs to be estimated and a new method is proposed. This method allows researchers to estimate the robustness of a centrality measure in a specific network and can be used as a basis for decision making. The relationship between network properties and the robustness of centrality measures is analyzed. Experimental and analytical approaches show that centrality measures are often more robust in networks with a larger average degree. The study of the impact of non-random errors on the robustness suggests that centrality measures are often more robust if missing nodes are more likely to belong to the same community compared to missingness completely at random. For the development of imputation procedures based on machine learning techniques, a process for the evaluation of node embedding methods is proposed.
Extracting meaningful representations of data is a fundamental problem in machine learning. Those representations can be viewed from two different perspectives. First, there is the representation of data in terms of the number of data points. Representative subsets that compactly summarize the data without superfluous redundancies help to reduce the data size. Those subsets allow for scaling existing learning algorithms up without approximating their solution. Second, there is the representation of every individual data point in terms of its dimensions. Often, not all dimensions carry meaningful information for the learning task, or the information is implicitly embedded in a low-dimensional subspace. A change of representation can also simplify important learning tasks such as density estimation and data generation. This thesis deals with the aforementioned views on data representation and contributes to them. The authors first focus on computing representative subsets for a matrix factorization technique called archetypal analysis and the setting of optimal experimental design. For these problems, they motivate and investigate the usability of the data boundary as a representative subset. The authors also present novel methods to efficiently compute the data boundary, even in kernel-induced feature spaces. Based on the coreset principle, they derive another representative subset for archetypal analysis, which provides additional theoretical guarantees on the approximation error. Empirical results confirm that all compact representations of data derived in this thesis perform significantly better than uniform subsets of data. In the second part of the thesis, the research group is concerned with efficient data representations for density estimation. The researchers analyze spatio-temporal problems, which arise, for example, in sports analytics, and demonstrate how to learn (contextual) probabilistic movement models of objects using trajectory data. Furthermore, they highlight issues of interpolating data in normalizing flows, a technique that changes the representation of data to follow a specific distribution. The authors show how to solve this issue and obtain more natural transitions on the example of image data.
Research on motivational and cognitive processes in entrepreneurship has commonly relied on a static approach, investigating entrepreneurs' motivation and cognition at only one point in time. However, entrepreneurs' motivation and cognition are dynamic processes that considerably change over time. The goal of this dissertation is thus to adopt a dynamic perspective on motivational and cognitive processes in entrepreneurship. In three different chapters, the work examines dynamic changes in the level and impact of three different processes, i.e., creativity, entrepreneurial passion, and opportunity identification. In Chapter 2, the thesis develops a theoretical model on the alternating role of creativity in the course of the entrepreneurial process. The model emphasizes that the effects of two components underlying creativity, i.e., divergent and convergent thinking, considerably change both in magnitude and in direction throughout the entrepreneurial process. In Chapter 3, the author establishs and empirically tests a theoretical model on entrepreneurial passion. The theoretical analysis and empirical results show that the relationships between feelings of entrepreneurial passion, entrepreneurial self-efficacy, and entrepreneurial success are dynamic and reciprocal rather than static and unidirectional. In Chapter 4, the author develops and tests a theoretical model on the effect of entrepreneurship training on opportunity identification over time. The theoretical and empirical investigation indicates that entrepreneurship training effects systematically decay over time and that action planning and entrepreneurial action sustain the effects in the long term.
Corporate irresponsibility is often the result of intentionally irresponsible strategies, decisions, or actions, which negatively affect an identifiable stakeholder or environment. For instance, these range from the violation of the human rights and labor standards to environmental damages. Organizations enacting irresponsible practices rely on different factors upon multiple levels (field, organizational, individual) and its interrelations as well as processes evolving within the organization leading to such behavior. However, reasons for the occurrence of and explanations for corporate irresponsibility so far have been limited, leaving a fragmented understanding of this phenomenon. This dissertation helps to improve the understanding and explanation of corporate irresponsibility by identifying driving patterns of corporate irresponsibility and showing how the interactions across multiple levels add to this phenomenon. Chapter 1 provides an overview of the topic of corporate irresponsibility, the theoretical approaches of this dissertation and an introduction to the chapters. The second chapter offers a review and analysis of the corporate irresponsibility literature. The chapter presents a variance model outlining the concept, antecedents, moderators and outcomes of recent corporate irresponsibility literature as well as the different factors across levels (field, organizational, individual). Chapter 2 offers a critical analysis of what we know by referring to current literature and offers insights on what we don't know by deriving main implications for future research on corporate irresponsibility. Chapter 3 enlarges the understanding of corporate irresponsibility introducing a process approach to explain how corporate irresponsibility evolves over time and under which conditions. Based on a qualitative meta-analysis findings converge around two distinct process paths of corporate irresponsibility, the opportunistic-proactive, and, the emerging-reactive, subdivided into three phases. Chapter 3 sheds different lights upon the phases of corporate irresponsibility and its underlying mechanisms. The final chapter 4 focuses on different underlying mechanisms driving the final downfall or demise of organizations, organizational failure. Chapter 4 offers an alternative explanation to the competing extremism and inertia mechanisms driving organizational failure in recent studies by suggesting that these explanations are rather complementary. In addition, chapter 4 enlarges the explanation of organizational failure identifying the role of conflict mechanisms and its interplay with rigidity mechanisms. In sum, this dissertation contributes to a better understanding of what causes and increases corporate irresponsibility, and a better explanation of how and why corporate irresponsibility and organizational failure emerges, develops, grows or terminates over time.
Decoding the psychological dimensions of human odor perception has long been a central issue of olfactory research. As odor percepts could not be linked to a few measurable physicochemical features of odorous compounds or physiological characteristics of the olfactory system, odor qualities have often been assessed by perception–based ratings. Although these approaches have been promising, none of the proposed system has sustained empirical validation. In a review of 28 studies, the authors assessed how basic characteristics of study design have been biasing perception–based classification systems: (1) interindividual differences in perceptual and verbal abilities of subjects, (2) stimuli characteristics, (3) approaches of data collection, and (4) methods of data analysis. Remarkably, many of the difficulties in establishing these systems have been rooted in one underlying issue: the puzzling relationship between language and olfaction in general. While the reference from odors to language is weak, the reverse impact of verbal processing on olfaction seems powerful. Odor perception is biased by verbal–semantic processes when cues of an odor's source are readily available from the context. At the same time, olfaction has been characterized as basically sensation driven when this information is absent. The authors examined whether language effects occur when verbal cues are absent and how expectations about an odor's identity shape odor evaluations. Subjects were asked to rate 20 unlabeled odor samples on perceptual dimensions as well as quality attributes and to eventually provide an odor source name. In a subsequent session, they performed the same rating tasks on a set of written odor labels that was compiled individually for each participant. It included both the 20 correct odor names (true labels) and – in any case of incorrect odor naming in the first session – the self–generated labels (identified labels). The authors compared odor ratings to ratings of both types of labels and found higher consistencies between the evaluation of an odor and its identified label than between the description of an odor and its true (yet not associated) label. These results indicate that basic perceptual as well as quality ratings are affected by semantic information about an odor's source – even in absence of source cues. That is, odor sensation may activate a semantic mental representation of an odorous object that affects odor processing and may in turn relate to further multimodal properties. That means, associations between odors and stimuli from other sensory modalities should not only be stable, but these mappings should be mediated by an odor’s identity. The authors asked subjects to visualize their odor associations on a drawing tablet, freely deciding on color and shape. Additionally, they provided a verbal label for each sample. Color mappings were odor-specific, they reflected the imagery of a natural source and seemed to change with assumed odor identity. Shape mappings changed with odor identifications as well, as drawings frequently displayed concrete objects that reflected visual features of an odor's source. The influence of verbal identity codes on quality ratings or crossmodal mappings is rooted in the very same problem that perception–based classification systems have tried to solve – a terminology that relates to abstract mental categories. The less specific we communicate, the more we need to resort to source–related analogies – in scientific endeavors and everyday life alike.