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The present work introduces four theoretical papers, which primarily focus on R&D, interindustrial linkages, and their policy implications. All in all, three issues basically motivated conception and realization: At first, previous NEG models do not incorporate endogenous R&D activities of firms. Existing models include R&D only in a growth context, which increases the formal complexity and departs from the simple core-periphery formulation. Second, vertical linkages are extensively considered in the class of international models. In face of its formal simplicity, the majority of publications refer to the standard model of Krugman and Venables (1995) utilizing intra-industry trade in which the manufacturing sector produces its own intermediates. However, the results are similar to the core-periphery model, but the implications of vertical linkages, especially in terms of specialization, cannot be reproduced. In contrast, the more challenging version of Venables (1996), which considers an inter-industry framework of an explicit upstream and downstream sector, is often cited (143 citations according to IDEAS/RePEc), but only few papers were directly built on it: Puga and Venables (1996), Amiti (2005), Alonso-Villar (2005). The third issue concerns the calibration of real economies. Although, hundreds of numerical simulations have been done in order to display the modeling outcomes, an application to particular industries in terms of their spatial formation and evolution is still a neglected field of research. Against this background, the present work aims to make a contribution to these topics. For a summary, all four papers are briefly to be summarized at this point. The first paper, entitled 'Too Much R&D? – Vertical Differentiation and Monopolistic Competition,' discusses whether product R&D in developed economies tends to be too high compared with the socially desired level. In this context, a model of vertical and horizontal product differentiation within the Dixit-Stiglitz (1977) framework of monopolistic competition is set up where firms compete in horizontal attributes of their products, and also in quality that can be controlled by R&D investments. The paper reveals that in monopolistic-competitive industries, R&D intensity is positively correlated with market concentration. Furthermore, welfare and policy analysis demonstrate an overinvestment in R&D with the result that vertical differentiation is too high and horizontal differentiation is too low. The only effective policy instrument in order to contain welfare losses turns out to be a price control of R&D services. The main contribution of this closed economy model in the course of the present work is a modeling framework, which can easily be adapted to the New Economic Geography. This has been approached in the second paper: ‘R&D and the Agglomeration of Industries' in which the seminal core-periphery model of Krugman (1991) is extended by endogenous research activities. Beyond the common ‘anonymous' consideration of R&D expenditures within fixed costs, this model introduces vertical product differentiation, which requires services provided by an additional R&D sector. In the context of international factor mobility, the destabilizing effects of a mobile scientific workforce are analyzed. In combination with a welfare analysis and a consideration of R&D promoting policy instruments and their spatial implications, this paper also makes a contribution to the brain-drain debate. In contrast to this migration based approach, the third paper 'Agglomeration, Vertical Specialization, and the Strength of Industrial Linkages' focuses on vertical linkages in their capacity as an additional agglomeration force. The paper picks up the seminal model of Venables (1996) and provides a quantifying concept for the sectoral coherence in vertical-linkage models of the New Economic Geography. Based upon an alternative approach to solve the model and to determine critical trade cost values, this paper focuses on the interdependencies between agglomeration, specialization and the strength of vertical linkages. A central concern is the idea of an 'industrial base,' which is attracting linked industries but is persistent to relocation. As a main finding, the intermediate cost share and substitution elasticity basically determine the strength of linkages. Thus, these parameters affect how strong the industrial base responds to changes in trade costs, relative wages and market size. The fourth paper 'The Spatial Dynamics of the European Biotech Industry' presents a simulation study of the R&D intensive biotech industry using the standard Venables model. Thus, it connects all three preceding papers and puts them into the real economic context of the European integration. The paper reviews the potential development of the European biotech industry with respect to its spatial structure. On the first stage, the present industrial situation as object of investigation is described and evaluated with respect to a further model implementation. In this context, the article introduces the findings of an online survey concerning international trade, conducted with German biotech firms in 2006. On the second stage, the results are completed by the outcomes of a numerical simulation within the New Economic Geography (NEG), considering vertical linkages between the biotech and pharmaceutical industries as an agglomerative force. The analysis reveals only a slight relocation tendency to the European periphery, constrained by market size, infrastructure and factor supply. In the final conclusions, central results of all four papers are summarized with respect to economic policy. Against the background of general legitimization and the impact of political intervention, Chapter 6 draws the main conclusions for location and innovation policies. In this regard, the industrial-base concept as well as the mobility of R&D play a central role during this discussion.
This cumulative dissertation deals with the association between corporate governance, corporate finance and corporate tax avoidance in four scientific articles. The aim of this dissertation is to explain corporate tax avoidance by (a) focusing on corporate governance institutions as determinants of tax avoidance and (b) focusing on financial consequences of tax avoidance. Due to the close association between corporate governance and the concept of corporate social responsibility (CSR), the relationship between CSR and tax avoidance is also addressed. The first article using structured literature review methodology, analyzes extant research on the association between corporate governance and tax avoidance based on stakeholder-agency theory. However, also classical principal-agent theory is taken into account as its classical foundation. The first article identifies a number of open research questions and thereby serves as a theoretical basis for the subsequent articles. The second article also using structured literature review methodology, analyzes extant research on the association between CSR and tax avoidance. This article is also based on stakeholder-agency theory and identifies open research questions. The third article based on results of the first article, investigates tax avoidance by German private family firms as a specific variant of corporate governance, using an empirical quantitative approach. The article finds that (a) German private family firms avoid more tax than non-family firms, that (b) tax avoidance is positively associated with the capital stake of the family and that (c) tax avoidance is positively associated with the number of shareholders in both family and non-family firms. Results reinforce that corporate tax avoidance is associated to conflicts among the shareholders of private firms. The fourth article investigates the cost of debt of German public firms as a function of tax avoidance and tax risk. The article finds that (a) tax avoidance is negatively associated to the cost of debt, that (b) tax risk is positively associated to the cost of debt and that (c) the association between tax avoidance and the cost of debt becomes negative when a high level of tax risk is present.
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.
Corporate Social Responsibility (CSR) has been established in recent years as an essential component of the economic system, demanded and promoted by a wide variety of stakeholder groups. The present dissertation shows that organizations face major communicative challenges with regard to CSR. CSR is not only determined by organizations themselves, but rather arises in the interplay with economic and social discourses. It is assumed that boundarys of organizational action are under constant change, so that CSR actors inevitably initiate constitutive communication processes. The resulting polyphony requires an understanding of the underlying communication processes. Hence, the performative character of CSR communication is taken up by this dissertation and thus the constitution of both the communicating actors and their relationships in the network is illustrated. The presented scientific papers are united by the overarching assumption that communication does not accompany and describe organizational action, but unfolds its own power.
To be prepared for one´s own career is a major task during career development. However, existing research has primarily focused on adolescence in the transition from school to work while research on career preparation among university students, that are challenged by successfully transiting from university to work, are lacking so far. Thus, this cumulative dissertation studies career preparation in terms of career decidedness, planning, confidence, and career engagement using large samples of German university students and alumni as well as a variety of quantitative methods like latent state-trait analysis, cross-lagged analysis, and mediation analysis with multiple mediators. In the first paper, the stable component of career indecision is investigated with longitudinal data stemming from two samples with different time lags (Sample 1: N = 363, 7 weeks; Sample 2: N = 591, 6 months). Furthermore, the combined and unique effects of career indecisiveness and generalized indecisiveness on life satisfaction are examined using a sample consisting of 469 university students. Results indicate that career indecision is determined by a stable component (i.e., trait career indecisiveness) that is associated with lower core self-evaluations, lower occupational self-efficacy, and higher perception of career barriers. Additionally, results indicate that the stable career indecision component explains 5% of the variance in student life satisfaction beyond self-evaluated generalized indecisiveness. The second paper deals with the relationships of vocational interest characteristics - interest congruence, interest differentiation, and general interest level (elevation) - with several indicators of career preparedness (i.e., career planning, occupational self-efficacy beliefs, career decidedness, and career engagement) among a sample of 239 university students. Controlling for sociodemographic variables, multiple regression analyses revealed that differentiation is positively associated with career decidedness and career engagement and elevation is positively related to occupational self-efficacy beliefs and career engagement. The third paper investigates how protean career orientation (PCO) is related to vocational identity clarity and occupational self-efficacy. Study 1 reports a 1-year, three-wave cross-lagged study among 563 university students and established that PCO preceded changes in identity and self-efficacy - but not the other way around. Based on a 6-month longitudinal study of 202 employees, Study 2 shows that identity clarity and self-efficacy mediated the effects of PCO on career satisfaction and proactive career behaviors. PCO only possessed incremental predictive validity regarding proactive career behaviors. However, specific direct or mediated effects of PCO on job satisfaction could not be confirmed. The fourth paper explores the relationships between narcissism and two indicators of career success (i.e., salary and career satisfaction) among a group of young professionals (N = 314). A model proposing that the effect of narcissism on career success is mediated by increased occupational self-efficacy beliefs and career engagement was assessed. While correlations between narcissism and the two indicators of career success were minimal, the results show a significant indirect effect on salary via occupational self-efficacy and indirect effects on career satisfaction via self-efficacy and career engagement. Overall, the different studies corroborate the crucial role of career preparation for a successful start into working life. In sum, this dissertation contributes to literature on vocational psychology by providing novel insights in terms of facilitators and outcomes of career preparation among university students and graduates. Theoretical and practical implications are discussed, and promising directions for future research are identified.
Employee health is an important factor for individual and organizational performance. In particular the healthcare sector is characterized by high physical and mental demands that result in poor employee health and high levels of sick leave. One way to support employee health at the workplace is through leadership. By creating a healthy work environment and climate, leadership can promote employee health and well-being, in particular health-specific leadership. However, there has been scant insights into contextual factors that are relevant for health-specific leadership. This dissertation aims to investigate the relevance of contextual factors for health-specific leadership and its relationship with employee health. Three studies were conducted to identify relevant individual and work-related characteristics for health-specific leadership as well as to investigate the influence of specific individual and organizational factors. The first study is a questionnaire-based survey with 861 healthcare employees. Its findings show a positive relationship between health-specific leadership and employee health in the healthcare sector. Social demands and social resources are analysed as mediating factors. Furthermore, the affective commitment of employees is considered as an additional outcome of health-specific leadership. The second study identifies drivers and barriers for health-specific leadership in an explorative design based on 51 interviews with healthcare managers and collates these factors with the theoretical background. The findings show various influencing factors relating to leadership, employees, and the organization. The third study investigates the influence of individual factors on health-specific leadership and is based on a questionnaire survey among 525 healthcare employees. Managers personal initiative and employee self-care influence the relationship between health-specific leadership and employee burnout in different ways. In summary, this dissertation contributes to the literature by putting health-specific leadership into context and providing insights into influencing factors. The findings broaden the understanding of how health-specific leadership can influence employee health. The implications for theory and practice are discussed and directions for future research are outlined.
The concept of empowerment has gained considerable attention in the field of international development. Institutions such as the World Bank and the United Nations invest considerable funds and efforts trying to facilitate empowerment in developing countries. Thus, empowerment becomes important when people need to take action and be innovative in overcoming scarcity and fighting against poverty. Research shows the positive effects of empowerment on entrepreneurship-related behavior and outcomes such as proactive behavior, goal achievement, and innovation. Yet, there is a dearth of research addressing the phenomenon of empowerment in entrepreneurship. This dissertation aims to contribute to the understanding of the role of empowerment in entrepreneurship and its effects. Particularly, this dissertation targets the interplay between empowerment and entrepreneurship in the context of developing countries. Chapter 1 provides a general overview of the different topics of this dissertation. Chapter 2, introduces the construct of psychological empowerment at work as the theoretical foundation to advocate for the importance of empowerment in entrepreneurship. The chapter takes initial steps in drawing the rationale and identifying empirical evidence for the relationship between empowerment and entrepreneurial behavior and outcomes. Specifically, the chapter links the components of psychological empowerment to concrete action characteristics in entrepreneurship such as effectuation and experimentation. Chapter 3 establishes a first empirical link between empowerment and entrepreneurship. The chapter provides the construct of entrepreneurial empowerment and develops a multidimensional measure to measure its dimensions. By means of a nomological network, the chapter reveals the relations of entrepreneurial empowerment with relevant constructs and outcomes derived from entrepreneurship and empowerment research such as innovation, self-reliance, and decision-making. Chapter 4 posits entrepreneurship training, particularly personal initiative training and business literacy training, as effective means to facilitate entrepreneurial empowerment and its effect on business performance. The chapter uncovers the mechanisms accounting for the relationship between entrepreneurship training and entrepreneurial empowerment. Chapter 5 provides general theoretical and practical contributions and finishes with a general conclusion.
Intelligent Product Design
(2012)
The aim of this thesis is to generate reality-based hypotheses about the opportunities and obstacles that create the implementation of Cradle to Cradle for the companies Jules Clarysse NV and Steelcase Inc. It discusses further which marketing-mix is appropriate for Cradle to Cradle products. Therefore exploratory expert interviews have been conducted with both companies. The empirical part is introduced by a literature study. From marketing perspective, the Cradle to Cradle approach for product design is investigated while taking into account that academic literature categorizes the concept on the one hand as consistent sustainability strategy, on the other hand as sustainable design. Moreover, the broad use of the expression design, within the literature of the Cradle to Cradle founders, is analyzed. Here, Cradle to Cradle design is holding out the prospect of Triple Top Line growth, rather than meeting only the economic bottom line. In regard of aesthetics, Cradle to Cradle aspires diversity in contrast to prevailing principles of Functionalism and universal design solutions. The ‘hidden‘ design assignment of Cradle to Cradle, service design, is highlighted as sphere that should be progressed. All these considerations form the interview guideline. The interviews serve as reality check whether there result Triple Top Lines and new service models for the companies and explore how aesthetics and tools of the marketing-mix are handled in Cradle to Cradle practice.
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.
Since 2000, data generation has been growing rapidly from various sources, such as Internet usage, mobile devices and industrial sensors in manufacturing. As of 2011, these sources were responsible for a 1.4-fold annual data growth. This development influences practice and science equally and led to different notations, one of the most popular one is Big Data. Besides organization with a business model based solely on Big Data, companies have started to implement new technologies, methodologies and processes in order to deal with the influx of data from different sources and structures and benefit the most of it. As the progress of the implementation and the degree of professionalism regarding data analysis differs amongst industries and companies, latter ones are faced with a lack of orientation regarding their own stage of development and existing relevant capabilities in order to deal with the influx of data as only a few best practices exist. Therefore, this research project develops a maturity model for the assessment of companies capabilities in the field of data analysis with a focus on Big Data. Basis for the model development is a construction model, developed along the criteria of Design Science Research. The developed model contains the different levels of maturity and related measurements for the evaluation of a companies Big Data capabilities with a focus on topics along the dimensions data and organization. The developed model has been evaluated based an application to different companies in order to ensure the practical relevance. The structure of the thesis is the following: In a first step, a structured literature review is carried out, focussing on existing maturity models in the field of Big Data and nearby fields as Business Intelligence and Performance Management Systems. Based on the identified white spots, a design science research oriented construction model for the maturity model development is designed. This model is applied subsequently.