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Institut
- Fakultät Wirtschaftswissenschaften (114) (entfernen)
With this dissertation, I present a human resources approach to entrepreneurship through selection and training of small-business owners in developing countries. Entrepreneurship is an important source of employment, innovation, and general economic prosperity (Autio, 2005; Walter et al., 2005; Reynolds et al., 2005; Kuratko, 2003). In developing countries, job creation through business ownership is especially important because job opportunities are limited (Walter et al., 2005; Mead & Liedholm, 1998). Strengthening the small business sector is one of the best ways to reduce poverty and increase economic growth (Birch, 1987). Thus, this dissertation adds to the scientific literature in taking a human resources approach to entrepreneurship: selecting and training entrepreneurs. Selection has widely been researched on in various scientific fields like human resource management, industrial-, work-, and organizational psychology, but only partly focusing on selection of entrepreneurs. Regarding training, there exists a fair amount of studies that focus on entrepreneurship education, but a lot of them suffer from substantial heterogeneity and methodological flaws (Glaub & Frese (2011); McKenzie & Woodruff (2013)). The dissertation combines the ideas of using selection procedures for entrepreneurs with the idea of teaching entrepreneurial skills.
In this dissertation, advanced nonlinear control strategies and nonlinear minimum-variance observation are combined, in order to improve the estimation and/or tracking quality within control and fault detection tasks, for several types of systems from the fields of electromobility and conventional drivetrain technology that have some potential for sustainability or performance improvements. The application-specific innovations in terms of nonlinear Kalman filter methods are: (1) Improved state of charge estimation for Lithium-ion battery cells, powered by a novel self-adaptive EKF that uses a high-order polynomial curve fit as a decomposition of the uncertain nonlinear output equation with intentionally redundant bases, and with a reduced number of polynomial parameters that are adapted online by the EKF itself. (2) Online estimation of the time delay between two periodic signals of roughly the same shape that have pronounced uncorrelated noise, based on a fractional-order approximation of the transcendent transfer function of the time delay which is used as a model in a novel kind of EKF. (3) Using two (E)KFs (one for the linear subsystem and one for the nonlinear subsystem of a new kind of multi-stage piezo-hydraulic actuator) in a cascaded loop structure in order to reduce the computation load of the estimation, by appropriate 'interfacing' between the two observers (using one shared system model equation, among other aspects). - The innovations in terms of nonlinear control methods are powered by observation, as well: (1) Sliding mode velocity control of a DC drive that is subject to nonlinear friction and unknown load torques, enhanced by an equivalent control law, and with a new intelligent switching gain adaptation scheme (for reduced control chattering and, thus, less energy consumption and actuator wear), which is powered by Taylor-linearized model predictive control, which in turn requires observer-based disturbance compensation (by a KF with a double-integrator disturbance model) for model-matching purposes in order to function correctly. (2) Direct speed control of permanent-magnet three-phase synchronous motors that have a high power-to-volume ratio, based on sliding mode control in a rotating d,q coordinate system, with a new equivalent control method that exploits both system inputs and with a secondary sliding surface to ensure compliance with the current-trajectory of maximum efficiency for the required torque, and which works without measurement of the rotor angle (thanks to a new kind of EKF that estimates all states in the stationary α,β coordinate system, as well as the disturbance/load torque and its derivative). In all instances, improvements (compared to methods existing in the literature) in terms of control and estimation performance have been achieved and confirmed using simulation studies or real experiments.
This dissertation includes an introduction and five empirical papers focusing on the educational and career decision-making process of individuals in Germany. The five papers embrace different determinants of educational and career decisions including school performance, social background, leisure activities as well as professional expectations, and contribute to the existing literature in this research area. Chapter 2 of this dissertation begins by analysing the nexus between students’ time allocation and school performance in terms of grades and satisfaction with their own performance in mathematics, the German language and a first foreign language, as well as overall achievement. This chapter looks at the heterogeneity of three important extracurricular activities: student jobs, sports and participation in music. Moreover, the heterogeneity of each activity is addressed by accounting for different types of the particular activity and differences in the number of years the activity has been pursued. For this purpose, data from the German SOEP, as a representative panel survey of private households and people in Germany, in particular cross-sectional survey data of 3388 students who are about 17 years old and enrolled in a German secondary school, were used. The main findings are that having a job as a student is negatively correlated with school performance, whereas participation in sports and music is positively correlated. However, the results reveal heterogeneity in each activity, especially with respect to intensity. Chapter 3 addresses the concrete post-school decision of school students, in particular whether to study or to enter the German VET system (Vocational Education and Training). It focuses on individual risk preferences and the social background of individuals and how these determinants affect the ultimate decision to enrol in university or to start an apprenticeship given the same level of qualification. For the empirical approach data from the German SOEP were used, in particular information on individuals' educational decisions between 2007 and 2013. The results indicate that (i) individual risk preferences do not have an overall effect on the real transition; (ii) privileged individuals are more likely to take up higher education; and (iii) compared to highly educated parents, parents without an academic background are less likely to guide their children into tertiary education, regardless of how much they support their children with their school work. Chapter 4 deals with the reconsideration of educational decisions in terms of early contract cancellations in VET. In particular, the effects of a second job on the intention to cancel a VET contract early are analysed for apprentices in Germany. For the empirical approach the representative German firm-level study "BIBB Survey Vocational Training from the Trainee's Point of View 2008", conducted by the Federal Institute for Vocational Education and Training (BIBB), is used. The survey contains 5901 apprentices that were interviewed during their second year of apprenticeship (205 schools, 340 classes, and 15 common occupations). Furthermore, it includes the design, procedures, basic conditions, and quality criteria of apprenticeships. The applied probit regressions show a higher intention to quit if apprentices require a secondary job to cover their living costs. In Chapter 5, new data on 191 apprentices from a vocational school, located in a northern German federal state, are used to validate the empirical results of Chapter 4. This chapter presents new insights into secondary-job-related burdens during apprenticeship. Due to limitations in the data, the applied empirical approach in Chapter 4 lacks to analyse how holding multiple jobs increases the intention to leave an apprenticeship early. Therefore, Chapter 5 includes the investigations of burdens related to the second job. The results indicate a lower intention to quit the apprenticeship if an apprentice holds a second job to cover living costs. However, secondary jobs are linked to lower quality of training, which, on the other hand, increases the intention to leave the apprenticeship early. Furthermore, the probability of secondary-job-related burdens increases with the number of working hours. Chapter 6 concludes the thesis by investigating subjective determinants of early contract cancellations in VET. It examines ten questions on what apprentices want to achieve and how unfulfilled expectations affect the intention to leave the apprenticeship early. The findings of this investigation contributes to the existing research on early contract cancellation. The questions considered include information on the performance, personal development, career development and prospects or position in society and their meaning to apprentices. For the research approach, the "BIBB Survey Vocational Training from the Trainee's Point of View 2008" is considered again. The probit and ordered probit regressions applied show significant effects of job characteristics that represent job security. The expectation of being retained after an apprenticeship and the encouragement to consistently train further decrease the intention to leave the apprenticeship early. Furthermore, women appear to be more affected by job security signals than men, but they also sort more often into occupations with lower retention probabilities. Consequently, this result may be an indication of occupational segregation rather than a sign of differences between sexes.
Analysis of User Behavior
(2020)
Online behaviors analysis consists of extracting patterns from server-logs. The works presented here were carried out within the "mBook" project which aimed to develop indicators of the quantity and quality of the learning process of pupils from their usage of an eponymous electronic textbook for History. In this thesis, the research group investigates several models that adopt different points of view on the data. The studied methods are either well established in the field of pattern mining or transferred from other fields of machine learning and data mining. The authors improve the performance of archetypal analysis in large dimensions and apply it to unveil correlations between visibility time of particular objects in the e-textbook and pupils' motivation. They present next two models based on mixtures of Markov chains. The first extracts users' weekly browsing patterns. The second is designed to process essions at a fine resolution, which is sine qua non to reveal the significance of scrolling behaviors. The authors also propose a new paradigm for online behaviors analysis that interprets sessions as trajectories within the page-graph. In this respect, they establish a general framework for the study of similarity measures between spatio-temporal trajectories, for which the study of sessions is a particular case. Finally, they construct two centroid-based clustering methods using neural networks and thus lay the foundations for unsupervised behaviors analysis using neural networks.
Online marketing, especially Paid Search Advertising, has become one of the most important paid media channels for companies to sell their products and services online. Despite being under intensive examination by a number of researchers for several years, this topic still offers interesting opportunities to contribute to the community, particularly because of its large economic impact and practical relevance as well as the detailed and widely unfiltered view of consumer behavior that such marketing offers. To provide answers to some of the important questions from advertisers in this context, the author present four papers in his thesis, in which he extends previous works on optimization topics such as click and conversion prediction. He applies and extends methods from other fields of research to specific problems in Paid Search. After a short introduction, the dissertation starts with a paper in which the authors illustrates a new method that helps advertisers to predict conversion probabilities in Paid Search using sparse keyword-level data. They address one of the central problems in Paid search advertising, which is optimizing own investments in this channel by placing bids in keyword auctions. In many cases, evaluations and decisions are made with extremely sparse data, although anecdotal evidence suggests that online marketing is a typical "Big Data" topic. In the developed algorithm presented in this paper, the authors use information such as the average time that users spend on the advertiser's website and bounce rates for every given keyword. This previously unused data set is shared between all keywords and used as prior knowledge in the proposed model. A modified version of this algorithm is now the core prediction engine in a productive Paid Search Bid Optimization System that calculates and places millions of bids every day for some of the most recognized retailers and service providers in the German market. Next, the author illustrates the development of a non-reactive experimental method for A/B testing of Paid Search Advertising activities. In that paper, the authors provide an answer to the question of whether and under what circumstances it makes economic sense for brand owners to pay for Paid Search ads for their own brand keywords in Google AdWords auctions. Finally, the author presents two consecutive papers with the same theoretical foundation in which he applies Bayesian methods to evaluate the impact of specific text features in Paid Search Advertisements.
Organizational culture is widely acknowledged to be a driver of organizational effectiveness. However, existing empirical research tends to focus on investigating the links between individual, isolated culture dimensions and effectiveness outcomes. This approach is at odds with the theoretical roots of organizational culture and does not do justice to the complex reality that most organizations face. This issue is addressed by this dissertation, which is comprised of four studies. Study 1 investigated the psychometric quality and cultural equivalence of three culture measures in a German context, based on a sample of 172 employees in a bank. The results suggested that the German versions of the Denison Organizational Culture Survey and the Organizational Culture Profile performed satisfactorily, while results regarding the GLOBE survey fell short of expectations. Study 2 reviewed the literature on the link between culture and effectiveness with a focus on studies that treat organizational culture as a holistic phenomenon. The review yielded four kinds of holistic approaches (aggregation-based, agreement-based, moderation- or mediation-based, and configuration-based). Study 3 investigated how a change in organizational culture induced by an M&A project impacts employee commitment. Based on a sample of 180 employees in a German organization, the findings suggest that individuals perceive cultural change differently, that cultural stability is positively related to employee commitment, and that group-level leader-member exchange and individual self-efficacy moderate this relationship. Study 4 introduced a new theoretical perspective (set theory) and a novel methodology (fuzzy set qualitative comparative analysis) to the field of organizational culture. Across two samples (1170 employees in a financial service provider and 998 employees in fashion retailer), results indicated that culture dimensions do not operate in isolation, but jointly work together in achieving different effectiveness outcomes.
Einhergehend mit politischen, naturbezogenen und konjunkturellen Herausforderungen der Tourismusbranche sehen sich Reisebüros auch im Wettbewerb mit neuen Medien. Beratungsqualität im Face-to-Face Vertrieb muss sich in diesem Zusammenhang der Diskussion stellen, womit traditionelle, konzern-eigene Reisebüros ihre Existenzberechtigung behalten. Die Erfassung persönlicher Faktoren im Gespräch, die weichen Erfolgsfaktoren in Bezug zu Beratungsqualität von Reisebüromitarbeitern, stehen im zentralen Forschungsinteresse. Die daraus resultierenden Fragenstellungen lauten unter anderem: Welche Softskills der Reisebüromitarbeiter sind notwendig, um ein gutes Beratungsgespräch zu führen? Lassen sich Softskills von Reisebüromitarbeitern methodisch erfassen? Was unterscheidet umsatzstarke von umsatzschwachen Beratern in der Reisevermittlung? Die Zielsetzung ist ein innovatives und adaptives Konzept zur Steigerung der Beratungsqualität von Reisebüromitarbeitern und damit zur Erfolgsicherung konzerngesteuerter Reisebüros. Zur Konkretisierung wurde die SERVQUAL-Methode ausgewählt, da sie sich durch eine Doppelskala auszeichnet, um die Lücke zwischen erwarteter und wahrgenommener Beratungsqualität zu messen. Dies bedeutete jedoch auch, dass die Probanden zu jeder gestellten Frage zwei unterschiedliche Antworten geben mussten. Eine zur tatsächlich erlebten, wahrgenommenen Qualität, in dieser Arbeit zur Beratungsqualität und eine zu den subjektiven Erwartungen an die eigene Leistung. Die Mitarbeiterbeurteilung der Beratungsqualität erfolgte durch die SERVQUAL Dimensionen Annehmlichkeit des tangiblen Umfeldes, Zuverlässigkeit, Reaktionsfähigkeit, Leistungskompetenz, Einfühlungsvermögen und wurde um die Dimension Kommunikationsfähigkeit ergänzt. Grund hierfür ist, von Reisebüromitarbeiter werden gleichzeitiges kunden- und auch umsatzorientiertes Arbeiten erwartet. Sie haben dabei einen hohen Anspruch zu erfüllen. Neben dem fachlichen Wissen sind Fähigkeiten in der verbalen und nonverbalen Kommunikation ebenso notwendig wie eine nach innen (zum Konzern, dem Büro und den Kollegen) und nach außen (kundenorientierte) gerichtete Kommunikation. Dies ließ eine Erweiterung des SERVQUALS um Kommunikation für nötig erscheinen. Im weiteren Verlauf wurden auch Schulungen der Reisebüromitarbeiter, in Ergänzung zu früheren Voruntersuchungen, mit einbezogen. Das gewählten SERVQAUL-Verfahren wie auch die Faktorenanalyse boten sich für die vorliegenden Fragestellungen zu den Schlüsselfaktoren der Mitarbeiter geradezu an und haben zu umfangreichen Erkenntnissen geführt. Voraussetzung der gewonnenen Erkenntnisse waren einerseits theoretische Analysen zur Beratungsqualität im Vorfeld, Würdigung bisheriger Untersuchungen des Reisebürovertriebes und die dargestellte empirische Forschung. In der Voruntersuchung wurden die unabgesicherten und subjektiv orientierungsweisende Meinungen der Praktiker hinzugezogen. Konkretisierend zeigt das Ergebnis des mehrjährigen Forschungsprojektes eine eher langfristige Entwicklung der Beratungsqualität von Reisebüromitarbeitern auf. Die Bemühung lag darin, Verbindungen zwischen praktischem Knowhow und Idealvorstellungen von Beratungsqualität mit den Theorien der Wirtschaftswissenschaften zwecks Erkenntnisfortschrittes zu finden.
This paper-based dissertation deals with capital structures and tax policies of German family businesses. Family firms as the predominant company form in Germany are mainly characterized by the overlapping of the two spheres family and business, both having different goal systems and preferences. This also has an impact on decision making with regard to corporate finance including the application of tax avoidance policies. In Germany, bank finance is the dominant financing source for family firms but there is a preference for internal finance since it comes along with more external independency. Extant research usually bases its results on samples of publicly listed companies. These studies come up with different results regarding family firms' actual financing preferences and capture their heterogeneity only to a very little extent. In this light, the present dissertation and its three papers examine different research questions in the context of capital structure decisions and tax avoidance in family firms. All the three papers apply a quantitative empirical research design. The first paper is a comparison between capital structures of family firms and non-family firms. The paper examines differences in bank debt and trade credit ratios. Overall, the findings show that family firms have significantly higher overall and long-term debt levels compared to their non-family counterparts. The identity as a family firm, which leads to a leap of faith by banks, can be a possible explanation for these results. The second paper is an in-depth examination of drivers of bank debt levels within the group of family firms. Further, it addresses heterogeneity amongst family firms and combines survey results and corresponding financial information. This represents a first attempt to capture family firm heterogeneity and its link to financial issues. The study shows that the more power in the company is exerted via management or supervisory board by the family, the less bank debt is used. Paper three is an extension of the previous two studies as it sheds light on tax avoidance, a significant instrument to strengthen the internal financing capability of a firm. This also takes up a research gap as there is very little research on taxation in family firms. Contrary to the expectation, the study reveals that private family firms might pay less tax than their non-family peers.
In this dissertation the relation between time headway in car following and the subjective experience of a driver was researched. Three experiments were conducted in a driving simulator. Time headways in a range of 0.5 to 4.0 seconds were investigated at 50km/h, 100km/h, and 150km/h under varied visibility conditions and at differing levels of driver control over the car. The main research questions addressed the possible existence of a threshold effect for the subjective experience of time headways and the influence of vehicle speed, forward visibility, and vehicle control on the position of time headway thresholds. Furthermore, the validity of zero-risk driver behavior models was investigated. Results suggest that a threshold exists for the subjective experience of time headways in car following. This implies that the subjective experience of time headways stays constant for a range of time headways above a critical threshold. The subjective experience of a driver is only influenced by time headway once this critical time headway threshold is passed. Speed does not influence preferred time headway distances in self- and assisted-driving, i.e. time headway thresholds are constant for different speeds. However, in completely automated driving preferred time headways are influenced by vehicle speed. For higher speeds preferred time headways decrease. A reduction of forward visibility leads to a shift in preferred time headways towards larger time headways. Results of this dissertation give credence to zero-risk models of driver behavior.
Die Fragestellung dieses Forschungsvorhabens resultiert aus der Praxis: Was ist ein christliches Hotel? Wie konkretisieren sich die christlichen Wertehaltungen im betrieblichen Alltag eines Hotels in Deutschland? Gibt es in der betrieblichen Praxis Unterschiede zwischen christlichen und nicht christlichen Hotels aus Sicht der Mitarbeiter christlicher Hotels, und wenn ja, welche sind das? Können christliche Hotels ihre Werte im Personalmarketing als Anreize verwenden? Welche Anreize erwarten die Mitarbeiter christlicher Hotels grundsätzlich von ihren Arbeitgebern? Gibt es Unterschiede in den Bewertungen der Wichtigkeit der christlichen Ausrichtung christlicher Hotels je nach Glaubenszugehörigkeit (christlich, andere, ohne) der Mitarbeiter? Da die Anwendung bzw. Konkretion christlicher Werte im betrieblichen Kontext nicht vom kulturellen außerbetrieblichen Umfeld getrennt betrachtet werden kann, beziehen sich die vorliegenden Ausführungen allein auf christliche Hotels in Deutschland. Das Objekt „Christliches Hotel“ wurde bislang in der Forschungsliteratur noch nicht näher beschrieben. Um den Forschungsgegenstand "Christliches Hotel" zunächst näher zu beschreiben, wird das in der Qualitätsdiskussion bekannte EFQM Excellence Modell herangezogen und anhand des Werteinventars unternehmensrelevanter christlicher Werte auf die Hotellerie übertragen. Dieses entwickelte EFQM Excellence Modell - auch EFQM Excellence Modell Hotel "C" genannt - dient einer ersten Konkretion des Forschungsgegenstandes und bildet zum anderen die Basis für die empirische Studie. Hierfür wurden 276 Mitarbeiter christlicher Hotels befragt, wie sie die im Rahmen des EFQM Excellence Modell Hotel "C" konkretisierten Werte im Management ihres Arbeitgeberhotels wahrnehmen und im Vergleich zu nicht christlichen Hotels und zudem bezüglich der Wichtigkeit bewerten. Die Studienergebnisse zeigen, dass die befragten Mitarbeiter christliche Hotels in den EFQM Konstrukten Führung, Strategie, Mitarbeiter und Prozesse, Produkte und Dienstleistungen sowie in den kulturbezogenen Konstrukten Christliche Werte und Ergänzende christliche Werte im Vergleich zu nicht christlichen Hotels als signifikant besser bewerten. Christliche Werte, sofern sie nicht explizit als solche bezeichnet werden, sind den Mitarbeitern christlicher Hotels in Deutschland unabhängig von ihrer Glaubenszugehörigkeit gleich wichtig. Christlich gläubigen Mitarbeitern christlicher Hotels in Deutschland ist - explizit gefragt - die christliche Ausrichtung ihres Arbeitgebers signifikant wichtiger als Mitarbeitern ohne Glaubenszugehörigkeit. Christliche Werte spielen für die Mitarbeiter christlicher Hotels in Deutschland zusammenfassend eine wichtige Rolle. Diese immateriellen Werte sind starke Beitrags- und Bleibeanreize, die christliche Hotels im Personalmarketing verwenden können. Dies gilt umso mehr, wenn die christlichen Werte von den christlichen Hotels in Deutschland nicht nur explizit als solche zusammenfassend genannt, sondern konkret und vor allem realitätsgetreu dargestellt werden.
The wide accessibility of the Internet and web-based programs enable an increased volume of online interventions for mental health treatment. In contrast to traditional face-to-face therapy, online treatment has the potential to overcome some of the barriers such as improved geographical accessibility, individual time planning, and reduced costs. The availability of clients' treatment data fuels research to analyze the collected data to obtain a better understanding of the relationship among symptoms in mental disorders and derive outcome and symptom predictions. This research leads to predictive models that can be integrated into the online treatment process to assist clinicians and clients. This dissertation discusses different aspects of the development of predictive modeling in online treatment: Categorization of predictive models, data analyses for predictive purposes, and model evaluation. Specifically, the categorization of predictive models and barriers against the uptake of mental health treatment are discussed in the first part of this dissertation. Data analysis and predictive modeling are emphasized in the second part by presenting methods for inference and prediction of mood as well as the prediction of treatment outcome and costs. Prediction of future and current mood can be beneficial in many aspects. Inference of users' mood levels based on unobtrusive measures or diary data can provide crucial information for intervention scheduling. Prediction of future mood can be used to assess clients' response to the treatment and expected treatment outcome. Prediction of the expected treatment costs and outcomes for different treatment types allows simultaneous optimization of these objectives and to increase the cost-effectiveness of the treatment. In the third part, a systematic predictive model evaluation incorporating simulation analyses is demonstrated and a method for model parameter estimation for computationally limited devices is presented. This dissertation aims to overcome the current challenges of predictive model development and its use in online treatment. The development of predictive models for varies data collected in online treatment is demonstrated and how these models can be applied in practice. The derived results contribute to computer science and mental health research with client individual data analysis, the development ofpredictive models, and their statistical evaluation.
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.
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.
Das Recht der Freileitung im Spannungsfeld planerischer, technischer und ökologischer Anforderungen
(2019)
Die Energiepolitik in Deutschland hat in den letzten Jahren umfassende Veränderungen erfahren. In den Fokus rücken dabei immer mehr die erneuerbaren Energien. Deren Anteil an der gesamten Energieerzeugung wird in Zukunft weiter ansteigen. Hintergrund ist die Umsetzung der klimapolitischen Ziele der Bundesregierung: Im Energiekonzept für eine umweltschonende, zuverlässige und bezahlbare Energieversorgung von 2010 wird eine Reduktion der Treibhausgasemissionen um 40% bis zum Jahr 2020 und bis zum Jahr 2050 sogar um 80% gegenüber dem Stand von 1990 angestrebt. Neben dem Energiekonzept der Bundesregierung stellen das Reaktorunglück von Fukushima und die damit verbundene Energiewende 2011 eine wesentliche Zäsur für die Energiepolitik in Deutschland dar. Die Folge war ein beschleunigter Ausstieg aus der Kernenergie sowie die sofortige Abschaltung von acht Kernkraftwerken. Neben der Laufzeitverkürzung und Stilllegung von Atomkraftwerken wurde auch das aus mehreren neuen Gesetzen und Gesetzesänderungen bestehende Energiepaket verabschiedet. Dort wurde mit der Einführung der §§ 12a ff. Energiewirtschaftsgesetz erstmalig eine bundesweite Bedarfsplanung für den Bau von Höchstspannungsleitungen festgelegt. Zudem erfolgte mit der Einführung des Netzausbaubeschleunigungsgesetzes Übertragungsnetz (NABEG) erstmalig ein bundesweit gültiges Gesetz für die Planung von Vorhaben auf der Ebene der Höchstspannungsnetze. Die vorliegende Arbeit untersucht vor diesem Hintergrund die Frage, ob durch die neu geschaffenen Regelungen des NABEG für Höchstspannungsleitungen eine Beschleunigung innerhalb des Planungsverfahrens erreicht werden kann und ob die mit dem NABEG verfolgten Ziele umgesetzt worden sind. Dabei wird aufgezeigt, wie sich die Zielsetzungen des NABEG zu denjenigen Zielen der im Rahmen der Abwägung der öffentlichen und privaten Belange zu beachtenden, sonstigen fachspezifischen Gesetzen verhalten. Der Beschleunigungsgedanke darf nicht dazu führen, dass umwelt-, immissionsrechtliche und sonstige fachgesetzliche Aspekte an Gewicht verlieren. Dabei werden auch mögliche Probleme der jetzigen Gesetzeslage beim Freileitungsausbau sowie weitere gesetzliche Möglichkeiten, die Beschleunigung des Netzausbaus zu erreichen, aufgezeigt.
Detecting and Assessing Road Damages for Autonomous Driving Utilizing Conventional Vehicle Sensors
(2021)
Environmental perception is one of the biggest challenges in autonomous driving to move inside complex traffic situations properly. Perceiving the road's condition is necessary to calculate the drivable space; in manual driving, this is realized by the human visual cortex. Enabling the vehicle to detect road conditions is a critical and complex task from many perspectives. The complexity lies on the one hand in the development of tools for detecting damage, ideally using sensors already installed in the vehicle, and on the other hand, in integrating detected damages into the autonomous driving task and thus into the subsystems of autonomous driving. High-Definition Feature Maps, for instance, should be prepared for mapping road damages, which includes online and in-vehicle implementation. Furthermore, the motion planning system should react based on the detected damages to increase driving comfort and safety actively. Road damage detection is essential, especially in areas with poor infrastructure, and should be integrated as early as possible to enable even less developed countries to reap the benefits of autonomous driving systems. Besides the application in autonomous driving, an up-to-date solution on assessing road conditions is likewise desirable for the infrastructure planning of municipalities and federal states to make optimal use of the limited resources available for maintaining infrastructure quality. Addressing the challenges mentioned above, the research approach of this work is pragmatic and problem-solving. In designing technical solutions for road damage detection, the researchers conduct applied research methods in engineering, including modeling, prototyping, and field studies. They utilize design science research to integrate road damages in an end-to-end concept for autonomous driving while drawing on previous knowledge, the application domain requirements, and expert workshops. This thesis provides various contributions to theory and practice. The investigators design two individual solutions to assess road conditions with existing vehicle sensor technology. The first solution is based on calculating the quarter-vehicle model utilizing the vehicle level sensor and an acceleration sensor. The novel model-based calculation measures the road elevation under the tires, enabling common vehicles to assess road conditions with standard hardware. The second solution utilizes images from front-facing vehicle cameras to detect road damages with deep neural networks. Despite other research in this area, the algorithms are designed to be applicable on edge devices in autonomous vehicles with limited computational resources while still delivering cutting-edge performance. In addition, the analyses of deep learning tools and the introduction of new data into training provide valuable opportunities for researchers in other application areas to develop deep learning algorithms to optimize detection performance and runtime. Besides detecting road damages, the authors provide novel algorithms for classifying the severity of road damages to deliver additional information for improved motion planning. Alongside the technical solutions, they address the lack of an end-to-end solution for road damages in autonomous driving by providing a concept that starts from data generation and ends with servicing the vehicle motion planning. This includes solutions for detecting road damages, assessing their severity, aggregating the data in the vehicle and a cloud platform, and making the data available via that platform to other vehicles. Fundamental limitations in this dissertation are due to boundaries in modeling. The pragmatic approach simplifies reality, which always distorts the degree of truth in the result.
The dissertation contains four journal articles which are embedded within a framework manuscript that interconnects the individual articles and provides relevant background information. The dissertation's overall objective is to provide a multilayered and critical in-depth engagement with the timely phenomenon of integrated reporting (IR), a new reporting concept that is envisaged to revolutionize firms' present reporting infrastructure. While extant corporate reports (e.g., annual financial- and CSR report) often are criticized for being disconnected and to suffer from a lack of coherence, IR intends to provide all information that is material to a firm's short-, medium- und long-term value creation within one single, succinct document. To contribute to a set of previously defined relevant research gaps in literature, the dissertation makes use of a combined empirical-quantitative and explorative-qualitative research design. The first article entitled investigates a set of different IR-, corporate governance and financial accounting-specific factors that are expected to determine European and South African firms' materiality disclosure quality. To this purpose, an original, hand-collected materiality disclosure score was developed. The second article explores IR perceptions of SME managers that have not embarked on IR, but are potential candidates to do so in future. Based on a review of extant literature, the article develops a theoretical framework to subsequently discuss motives for and barriers to IR adoption. The critical discussion contributes to the academic debate on incentives for and barriers to voluntary IR adoption. The third article investigates whether voluntary IR adoption among European firms is associated with lower cost of public debt. While earlier studies suggest that IR leads to lower information asymmetries, increases analyst forecasts, and decreases cost of equity, corresponding evidence for the debt market is largely missing. Subsequent analyses test as to whether such an association is even more pronounced by a firm's environmental, social and governance (ESG) performance or its belonging to an environmentally sensitive industry. The fourth article uses an experimental design to investigate nonprofessional investors' reactions to an IR assurance. To this purpose, two separate experiments with two different groups of nonprofessional investors were carried out: one with Masters students and one with managers of large corporations. Results help to answer the question as to whether an IR assurance as well as its determinants, namely the assurance provider and the assurance level, affect nonprofessional investors' financial decision-making. In the second step, subsequent in-depth interviews reveal an IR assurance-critical attitude among managers, who draw upon their practical experience with assurance engagements.
Viele Betriebsgastronomien in Deutschland sehen sich vor die Herausforderung steigender Gästeansprüche, zunehmenden Kostendrucks und oftmals auch konkurrierender Speisenanbieter gestellt. Hinzu kommt in vielen Betrieben die Forderung der Gäste oder des Managements nach einem Angebot gesundheitsfördernder Speisen und Getränke. Dieses kann z. B. durch die Deutsche Gesellschaft für Ernährung e. V. (DGE) zertifiziert werden. Die innerbetriebliche Umsetzung und Kommunikation des erweiterten, gesundheitsfördernden Speisenangebotes muss indes gesteuert werden. Hierfür bietet sich die Erstellung einer Balanced Scorecard nach Kaplan und Norton an. Diese berücksichtigt neben finanzorientierten Kennzahlen auch ausdrücklich qualitative Ziele und stellt deren wechselseitige Einflüsse in Ursache-Wirkungs-Ketten dar. Die vorliegende Bachelorarbeit spezifiziert eine Balanced Scorecard auf die Anforderungen einer Betriebsgastronomie, die ein DGE-zertifiziertes Speisenangebot etablieren möchte. Zu diesem Zweck werden für die vier Perspektiven einer Balanced Scorecard strategische Ziele vorgeschlagen und deren Ursache-Wirkungs-Beziehungen grafisch in einer Strategy Map dargestellt. Die ebenfalls durchgeführte empirische Untersuchung DGE-zertifizierter Betriebe zeigt, dass durch die Einführung eines gesundheitsfördernden Speisenangebotes die Mitarbeiterzufriedenheit und Mitarbeitergesundheit positiv beeinflusst werden kann. Zudem ist eine Steigerung des Umsatzes durch die Gewinnung neuer Gäste und den Zusatzverkauf komplementärer Produkte möglich.
Der Begriff Blockchain tritt zum ersten Mal in Verbindung mit der Kryptowährung Bitcoin im 21. Jahrhundert auf. Das anfänglich beschriebene Protokoll von Bitcoin hat sich mittlerweile zu einem Phänomen entwickelt, dass unter dem Begriff Kryptoökonomie zusammengefasst wird. Mittlerweile ist Bitcoin nicht mehr die einzige Kryptowährung: Innerhalb der letzten sieben Jahre hat sich ein großes, vielseitiges Universum von Kryptowährungs- und Kryptotransaktionssystemen entwickelt. Diese Arbeit vergleicht zwei dieser Kryptowährungssysteme: das erwähnte dezentrale Zahlungssystem Bitcoin sowie Ethereum, eine Entwicklungsplattform für dezentrale Applikationen. Zuerst wird ein allgemeiner und historischer Überblick gegeben. Die beiden Systeme Bitcoin und Ethereum, die Blockchain und Geld und Währungsdefinition werden betrachtet. Anschließend werden für ein besseres Verständnis der Blockchain relevante Aspekte der Kryptografie vorgestellt. Besonderer Fokus liegt dabei auf asymmetrischen Algorithmen und Hash-Funktionen. Daraufhin werden die Bitcoin Blockchain und die Ethereum Blockchain gesondert und detaillierter beleuchtet. In der Folge werden Bitcoin und Ethereum im Allgemeinen und die Blockchains jener im Speziellen miteinander verglichen. Die Vergleichspunkte orientieren sich sowohl an ökonomischen als auch an technischen Gesichtspunkten. Abschließend wird das Ergebnis des Vergleichs präsentiert und ein Fazit gezogen.
Diese Studie untersucht die Wirkung einer verpflichtenden externen Begutachtung von Gründungsvorhaben im Rahmen der Ich-AG-Förderung der Bundesagentur für Arbeit. Unter Verwendung von prozessproduzierten Daten zu den Gründern und ihren Vorhaben wird geprüft, inwieweit sich Unterschiede zwischen Gründern im Arbeitsagenturbezirk Lüneburg, die unter diese Regelung fallen und solchen, die dies nicht tun, ergeben. Die Ergebnisse der Studie deuten darauf hin, dass keine Unterschiede in beobachtbaren Merkmalen zwischen diesen Gründern bestehen, was ein Hinweis auf die Wirkungslosigkeit der externen Begutachtung sein kann.