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The doctoral dissertation deals with the problems of the diagnosis of rolling bearings using recurrence analysis. The main topic is the influence of radial internal clearance on the change of dynamics in a self-aligning double-row ball bearing with a tapered bore, in which the axial preload can control this parameter in a wide range. The dissertation began with an analysis of the state of knowledge. In the next part of the dissertation, the thesis was formulated and activities related to its proving were defined. The theoretical part was supplemented with the basics related to vibroacoustic diagnostics of rolling bearings and presented methods that can be used for their diagnostics. The research on proving the thesis was started with the preparation of a mathematical model in which a change in the damping coefficient in the field of radial clearance was adopted, a difference in the clearance value for a given row of balls was proposed, and the influence of shape errors and radial shaft endplay on the dynamics of the tested bearing was taken into account. During the dynamics tests, the radial clearance was adopted as a bifurcation parameter, and on the basis of the bifurcation diagram, it was possible to indicate the characteristic areas of bearing operation due to the radial internal clearance. In order to verify the model, experimental tests were carried out with a series of bearings in which the radial clearance was changed in a wide range possible to be physically realized. Recurrence analysis was used for both the dynamic response obtained from model and experimental studies. Owing to the comparative analysis of the dynamic response, recurrence quantificators were selected that are most susceptible to changes in radial clearance to bearing dynamics. Moreover, as a result of the research, it was possible to select a narrow range of radial clearance, ensuring the smoothest operation of the tested bearing.
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.
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.
Food forests present a promising solution to address multiple sustainability challenges adaptable to local contexts. As biodiverse multi-strata agroforestry systems, they can provide several ecological, socio-cultural and economic services. They sequester carbon, limit soil erosion and regulate the micro-climate; they offer the opportunity for education on healthy diets and ecology, and they produce food and can create livelihood opportunities. However, despite their obvious benefits, food forests are still a niche concept. To date, research has focused on their ecological and social services; we lack an understanding of food forests as a comprehensive sustainability solution, including their economic dimension, and knowledge on how to develop them. Addressing these gaps, this qualitative research used a solution- and process-oriented methodology guided by transformational sustainability research. In a comparative case study approach, it created an inventory of 209 food forests, followed by interviews and site visits of 14 sites to understand their characteristics and assess their sustainability (Article 1). More indepth, it analyzed the implementation path of seven food forest for success factors, barriers and coping strategies (Article 2). Based on these insights, two experimental case studies were initiated to develop sustainable food forests with practice partners, one based in Phoenix, Arizona, U.S. and one in Lüneburg, Germany. Two studies analyzed the cases' outputs and processes highlighting success factors and challenges, including the role of a sustainable entrepreneurial ecosystem (Article 3, Phoenix case) and key features of productive partnerships to understand why one case succeeded and the other failed (Article 4). Findings include key features of existing and sustainable food forests as well as success factors on how to develop them; namely acquiring a complementary skill set that includes specialty farming and entrepreneurial know-how, securing sufficient start-up funds and long-term land access as well as overcoming regulatory restrictions. Supporting institutions are especially needed to integrate and professionalize the planning stage and provide know-how on alternative business practices. Key features of productive partnerships include an entrepreneurial attitude, access to support functions, long-term orientation and commitment to food system sustainability.
Increased international compliance with human rights and democracy standards is a core issue for both human rights and democratizing actors as well as for victims of human rights abuse. International human rights organizations (IHROs) are expected to make positive contributions to this end, even though they possess low levels of authority. This authority has been renegotiated multiple times in various reform processes. An oversimplified expectation would have us assume that democracies would want to strengthen IHROs, and that autocracies would seek to weaken them. As the United Nations Human Rights Council (UNHRC) was reformed in 2006, 2007, 2010, and 2011, some autocracies strived to abolish parts of the UNHRC. Other autocracies aimed "merely" to weaken them. Democracies displayed an even larger variance. The question that drives this research work is how we can explain the broad variety of state preferences for strengthening or weakening IHROs. Previous research has mostly concentrated on democracies, leaving autocracies understudied. It also treated countries as black boxes. To account for such shortcomings, first, the author systematically tests the relationship between the UNHRC and its authoritarian and democratic members by means of inferential statistics. Second, he analyzes a bottom-up process inherent to New Liberalism. It scrutinizes the role of domestic societal actors, domestic institutions, as well as pressures on the international stage. The results reveal that societal actors, along with the interplay of wealth and regime type in the international realm, figure as the most important predictors of delegation preferences voiced by autocracies and democracies during the reform of the monitoring bureaucracy Special Procedures of the UNHRC. Societal actors play a more important role in democracies than in autocracies. Institutionalized domestic oversight mechanisms help societal actors to conduct effective lobbying at the domestic level. Oversight mechanisms are more important than the rule of law and electoral institutions. Regarding international coalition building, authoritarian regimes turn out to be better organized than democracies. The author concludes that supporters of strong IHROs shall 1. empower domestic societal actors; 2. disrupt cohesive delegation preferences of authoritarian regimes; and 3. invest in independent domestic oversight mechanisms.oversight mechanisms.
Design methods for collaborative knowledge production in inter- and transdisciplinary research
(2022)
This dissertation seeks to better understand how design methods facilitate collaborative knowledge production and integration in inter- and transdisciplinary sustainability research. Through five independent papers, this dissertation contributes to addressing the research question on four levels – conceptual-epistemological, empirical, methodological and practical. By exploring the linkages between design research and inter- and transdisciplinary research, a conceptual basis for the targeted use of design methods in collaborative processes of inter- and transdisciplinary research is laid and their spectrum of methods is expanded. This is followed by the development of a transformative epistemology in and for problem-oriented, collaborative forms of research, such as transdisciplinary sustainability research, called problematic designing. Based on a deeper understanding of integration and collaborative knowledge production, as well as its accompanying challenges, empirical research into applying design prototyping as a method in and for situations of collaborative research was conducted. To this end, the findings provide a fundamental basis for the facilitation of inter- and transdisciplinary research processes when dealing with complex problems. With its inherent openness and iterative approach in addressing the unknowns of complex phenomena, design prototyping contributes to the required form of imagination that enables to anticipate possible futures. Furthermore, by including visual-haptic modes of expression, design prototyping reduces the dominance of language and text in scientific negotiation processes and does justice to the diversity of cognitive modes. Finally, the empirical findings of this dissertation emphasise the importance of the visual-haptic dimension for collaborative knowledge production and the communication of knowledge, and provide insights into the visual structuring of human thought processes. The results on material metaphors, collaborative prototyping and material-metaphorical imagery contribute decisively to the basic knowledge of the epistemological quality of design and the importance of the visual and haptic for thought processes in general. The extension and adaptation of existing analysis methods in this dissertation add to the further development of analysis of visual-haptic data. The results are once again reflected in the synthesis of this framework paper as cross-cutting issues.
The choice to continue working until or even beyond retirement is a function of the interplay of factors on micro, meso, and macro levels. Research within this area has grown significantly over the last years. I contribute to this line of research with the studies conducted within the scope of this cumulative habilitation thesis. More specifically, the aim of the research presented here is to add to the literature on later life work with the investigation of individual (micro level) as well as job and organizational (meso level) factors that have the potential to contribute to prolonged working lives. I was guided by the general research interest on how individual, job, and organizational factors contribute to later life work, and more specifically to retirement timing and work-related activities beyond normal retirement age. My research was directed by the following research questions: (1) What is the work activity potential of older people in Germany and what characterizes different types of later life work potential? (2) Which role do individual psychological factors such as personality, values, and beliefs play in the context of later life work? (3) How do specific job characteristics interact or align with individual psychological factors with regard to later life work? (4) What characterizes a holistic organizational approach to later life work that helps the alignment of the work environment to older workers’ (individual) needs and abilities?
Following an introduction, I give an overview on the theoretical framework of my research in Chapter 2 (“Theoretical Background”). I describe the conceptualization of later life work before I go into multilevel antecedents of later life work and present key theoretical approaches to a person-environment fit perspective of later life work. In the following four chapters, I present ten studies corresponding to the ten scientific publications that constitute the basis of the cumulative habilitation thesis.
In Chapter 3 (“Later Life Work: Work Activity Potential”) I present research on the extent as well as different types of later life work potential in Germany to describe the context for most of my research. With the two studies presented here (Büsch, Zohr, Brusch, Deller, Schermuly, Stamov-Roßnagel, & Wöhrmann, 2015; Mergenthaler, Wöhrmann, & Staudinger; 2015), I also intend to provide answers to the research question on the later life work potential in Germany and the characteristics of different later life work potential constellations. In Chapter 4 (“Later Life Work: Individual Psychological Factors”) the role of stable as well as malleable individual psychological factors for later life work is explored in two studies (Fasbender, Wöhrmann, Wang, & Klehe, 2019; Wöhrmann, Fasbender, & Deller, 2016). Thus, with the studies presented in this chapter, I contribute to the research question on the role of individual psychological factors in the context of later life work. In Chapter 5 (“Later Life Work: Job Characteristics Corresponding to Older Workers’ Needs and Abilities”) I present three studies exploring the interplay of individual factors and job characteristics for later life work to address the research question on the interaction or alignment of specific job characteristics with individual psychological factors with regard to later life work (Pundt, Wöhrmann, Deller, & Shultz, 2015; Wöhrmann, Brauner, & Michel, 2020; Wöhrmann, Fasbender, & Deller; 2017). Chapter 6 (“Later Life Work: A Holistic Organizational Approach”) reports the development of the Later Life Workplace Index (LLWI) as a multidimensional tool to holistically assess organizational practices and working conditions targeted at the promotion of later life work through the maintenance and enhancement of older employees’ health, work ability, and motivation (Wilckens, Wöhrmann, Adams, Deller, & Finkelstein, 2020; Wilckens, Wöhrmann, Deller, & Wang, 2020; Wöhrmann, Pundt, & Deller, 2018. With the LLWI, I intend to provide an answer to the research question on the characteristics of a holistic organizational approach to later life work that helps the alignment of the work environment to older workers’ (individual) needs and abilities. Finally, in Chapter 7 (“General Discussion”) I discuss the contributions, implications, and limitations of my research presented here.
This doctoral thesis deals with the topic of organizational misconduct and covers the three salient research streams in this area by addressing its performance outcomes, antecedents, and preventive measures. Specifically, it is concerned with the question of how different forms of misconduct are reflected in the stock performance of related organizations, thereby, covering the three pillars of corporate sustainability environmental, social, and governance (ESG). Furthermore, it aims to conceptualize how individual cognitive biases may lead to misconduct, therefore, potentially representing an antecedent and how existing management control systems can be enhanced to effectively address specific forms of misconduct, respectively. To these ends, the author first reviews the research stream of stock price reactions to environmental pollution events in terms of the underlying research samples, methodological specifications, and theoretical underpinnings. Based on the findings of the systematic literature review (SLR), he performs three stock-based event studies of the Volkswagen diesel emissions scandal (Dieselgate), workplace sexual harassment (#MeToo accusations), and the 2003 blackout in the US to cover the three ESG dimensions, respectively. In line with the SLR, his event studies reveal substantial stock losses to firms involved in misconduct that are eventually even accompanied by a spillover effect to uninvolved bystanders. Then, the author reviews the extant literature conceptually to develop a framework outlining how moral licensing as an individual cognitive bias might lead to a self-attribution of corporate sustainability, a consecutive accumulation of moral credit, and a later exchange of this credit by engaging in misconduct afterward. Finally, he assesses existing workplace sexual harassment management controls, such as awareness training and grievance procedures critically in another conceptual analysis. Based on the shortcomings stemming from management controls' focus on compliance and negligence of moral duties, he introduces five specific nudges firms should consider to enhance their existing management controls and eventually prevent occurrences of workplace sexual harassment. Based on the six distinct articles within this doctoral thesis, the author outlines its limitations and point at directions for future research. These mainly address providing further evidence on the long-term performance effects of organizational misconduct, enriching our knowledge on further cognitive biases eventually leading to misconduct, and conceptualizing nudging beyond the use-case of workplace sexual harassment.
Consisting of three articles and a framework manuscript, this cumulative dissertation deals with sustainable compensation of chief executive officer (CEO) with a focus on climate-related aspects. Against the backdrop of the European action for sustainability and the EU Green Deal, the dissertation pays special attention to the consideration of climate-related aspects of corporate performance in CEO compensation. In this context, sustainable compensation is characterized by the consideration of long-term interests and sustainability of the company as well as by the inclusion of financial and non-financial aspects of environmental, social and governance performance (ESG) in compensation agreements. While this novel instrument of corporate governance aims to incentivize the implementation of sustainability-oriented corporate strategy, it is particularly important to unfold this incentive effect at the individual CEO level in view of their managerial discretion. The framework manuscript discusses the research objectives, the regulatory and theoretical background, the results of the dissertation and their implications in the context of regulation, research, and business practice. The essence of the dissertation are the three articles. The first article examines the current state of empirical research based on 37 articles that were published between 1992 and 2018. Based on a multidimensional research framework, the structured literature review compiles past research findings, identifies contentual and methodological foci in the research area, and derives questions for future research. The second article addresses the topic from a conceptual perspective. Taking the existing work as a starting point, a conceptual framework is derived, which organizes the determinants of carbon-related CEO compensation at societal, organizational, group and individual levels of analysis. On this basis, eight propositions are presented that seek to distinguish between the determinants which support and challenge the implementation of carbon-related CEO compensation. The third article focuses on the use of CO2-oriented performance indicators in CEO compensation. The empirical-qualitative study analyzes corporate disclosure of the 65 largest companies in the EU for the years 2018 and 2019. The study addresses the use of CO2-oriented performance indicators in corporate strategy and CEO compensation. It also examines which compensation components are determined with the help of CO2-oriented performance indicators, which type of performance indicators are used, and whether CO2-intensive and less CO2-intensive companies differ in this regard.
This research report presents a transdisciplinary student research project on the development of climate resilience of communities on the Caribbean Island Dominica.
The research was conducted through a partnership between the Leuphana University Lüneburg and the Sustainable Marine Financing Programme (SMF) of the GIZ.
For the GIZ, the research project aimed at improving the understanding of the socio-ecological resilience framework for tackling problems of Marine Managed Areas and Marine Protected Areas. Also, it enabled new thoughts on how the GIZ and other development agencies can more effectively assists island states to better cope with the challenges of climate change.
The role of the students from the “Global Environmental and Sustainability Sciences” programme of Leuphana University included the design of four transdisciplinary research projects to research aspects of resilience of Caribbean communities.
The developing island states in the Caribbean are extremely vulnerable to more frequent and intense natural hazards while relying on the ecosystem services that are also at risk from extreme weather events, in particular Hurricanes. Low economic stability leads to a dependency of the states on international assistance. To decrease the vulnerability to shocks, counteracting measures that encourage learning and adaptation can increase the resilience against extreme weather events and their consequences.
Concepts that were considered during the design of the transdisciplinary research projects were the adaptation of systems, diversity and stakeholder participation and resilience-focused management systems. Also, the students critically assessed the concept of foreign aid and how it can be successful, mitigating the risk of introducing neo-colonial structures. Flood Management, Biodiversity, Small-Scale Agriculture and Foreign Aid on Dominica were the topics of the transdisciplinary projects. The research methods of a literature review, stakeholder mapping, interviews, scenario development and visioning were used in the projects.
In four scenarios developed in the ‘Flood Management’ project, it became evident that a broad as well as coordinated stakeholder engagement and a variety of measures are required for community resilience. A key finding of the ‘Biodiversity’ project was the identity dimension of community resilience, underlining the importance of the relationship between individuals and nature. The interlinkage of social identity processes and a resilient disaster response was also stressed by the project ‘Foreign Aid’, which highlighted that financial support is similarly important to inclusivity and reflexivity in the process of resource distribution. To recover from extreme weather events, the social memory also plays an important role. The project on ‘Small-scale Agriculture’ concluded, that the memory-making of local communities is as vital to community resilience as formal plans and trainings.
The research project was based on the research approach of transdisciplinarity because of its solution-orientation. It links different academic disciplines and concepts, and non-scientific stakeholders are included to find solutions for societal and related scientific problems. In the four projects, principles of transdisciplinary research were party applied, but some challenges arose due to the geographical distance, time constraints and a strong focus on the scientific part in some phases. Nonetheless, the findings of the projects provide valuable learning lessons to be applied in practice and that can prove useful for future research.