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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.
Crowdfunding is considered a promising instrument for transforming existing socio-technical regimes by financing radical innovations of such entrepreneurs. However, this potential has not yet been fully explored. Therefore, this dissertation addresses the overarching research question of how sustainable entrepreneurs can exploit the full potential of investment-based crowdfunding to develop from niche operators to actors in the socio-technical regime. Five journal articles and one book chapter are included in this PhD project, which use a wide range of quantitative methodologies. In the framework paper, the findings are conceptually evaluated on a meta-level by applying the multi-level perspective. The key insights can be assigned to four categories, including the financing and marketing function, the target group, and the project presentation. The analysis shows that investment-based crowdfunding is suitable to equally fund and market the business ideas of environmental entrepreneurs, since the quest for entering the mass market is highest for such ventures. In contrast, purely social entrepreneurs tend to conduct crowdfunding projects on a smaller scale and probably aim to stay in the niche. Nevertheless, profit-oriented social entrepreneurs are still encouraged to use investment-based crowdfunding for funding and marketing purposes. The prominent display of environmental effects (e.g. the amount of compensated greenhouse gases) and financial incentives (e.g. high interest rates) has a high impact on the investment decision of individuals on investment-based crowdfunding platforms. The case of fairafric is used as a best practice example to demonstrate how crowdfunding can be a stepping stone for sustainability-oriented niche actors to enter the mass market. The fair-trade and organic chocolate manufacturer has undergone six crowdfunding campaigns which enabled it to grow and build a strong community of supporters. The outcomes of this dissertation clarify how sustainable entrepreneurs can unleash the potential of investment-based crowdfunding for financing and marketing purposes.
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.
Rangelands are the most widespread land-use systems in drylands, where they often represent the only sustainable form of land-use due to the limited water availability. The intensity of the land-use of such rangeland ecosystems in drylands depends to a large extent on the climatic variability in time and space. Rangeland systems are seriously threatened by climate change, because climate change will alternate the availability of water in time and space. This dissertation therefore deals with the question which role climatic variability plays for the effects of grazing on vegetation in dry rangelands. The relatively intact steppes in central Mongolia were chosen as a model system. They are characterised by low precipitation and high climatic variability in the south (100mm annual precipitation), and comparatively high precipitation and low climatic variability in the north (250mm). The effects of grazing on vegetation on 15 grazing transects were investigated along the climatic gradient. The central elements were the plant species and their abundances on 10m x 10m areas, for which functional characteristics such as height, affiliation of functional groups or leaf nutrients were recorded. The main hypothesis of this dissertation is that grazing has a greater impact on vegetation communities with increasing rainfall. To test this hypothesis, three studies were carried out. In a first study, the research group found that the vegetation communities in the dry area differ strongly along the climatic gradient, while the plant communities in the wetter area differ more strongly along the grazing gradient. The results of the second study suggested that this difference can be explained by a functional environmental filter that becomes weaker from south to north as the niche spectrum increases. The third study has shown that this is likely a function of the higher availability of resources, which at the same time leads to higher grazing pressure, therewith stressing the vegetation especially in years with droughts. In summary, the author concludes that the climate gradient also represents an environmental filter that filters species for certain characteristics, thus having a significant influence on the vegetation. Climatic variability influences the effect of grazing on vegetation, which is particularly problematic where the grazing intensity is high and the species are less adapted to strong climatic fluctuations. Future scenarios predict increasing productivity and therefore increasing livestock density. This may lead to an increase in floristic and functional diversity across the climate gradient, but also to increasing grazing effects and therefore threads for overgrazing. Increasing climatic variability is likely to intensify this thread, especially in the moister regions, whereas the dry rangelands are likely to be more resilient due to the adaptation of the plants to non-equilibrium dynamics.
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.
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.
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.
Human activities have become a major driver of global change, so that global society and economy are facing consequences such as climate change, increasing scarcity of resources, environmental pollution and degradation as well as disturbances of ecosystem functioning and services.In order to meet these main challenges in an appropriate way, adequate starting points and solutions must be pursued at all levels to shift the current socio-economic pathway from an unsustainable to a safe operating and thus sustainable development within the planetary boundaries. One of the application concepts in industrial contexts is Industrial Symbiosis (IS), which deals with the set-up of advanced circular/cascading systems, in which the energy and material flows are prolonged for multiple material and energetic (re-)utilization within industrial systems in order to increase resource productivity and efficiency, while reducing environmental impacts. The overarching goal of the research project was to identify and develop approaches to enable the evolution of Industrial Symbiosis (IS) in Industrial Parks (IPs). IS is a collaborative cross-sectoral approach to connect the resource supply and demand of various industries in order to optimize the resource use through exchange of materials, energy, water and human resources across different companies, while generating ecological, technical, social and economic benefits. Many Information Communication Technology (ICT) tools have been developed to facilitate IS, but they predominantly focus on the as-is analysis of the IS system, and do not consider the development of a common desired target vision or corresponding possible future scenarios as well as conceivable transformation paths from the actual to the defined (sustainability) target state. This gap shall be addressed in this work, presenting the software requirements engineering results for a holistic IT-supported IS tool covering system analysis, transformation simulation and goal-setting. This study also aims to present the conceptual IT-supported IS tool and its corresponding prototype, developed for the identification of IS opportunities in IPs. This IS tool serves as an IS facilitating platform, providing transparency among market players and proposing potential cooperation partners according to selectable criteria (e.g. geographical radius, material properties, material quality, purchase quantity, delivery period). Therefore a quantitative indicator system was compiled and recurring patterns were identified to utilize this knowledge in the comprehensive IT-supported IS tool. So this IS tool builds the technology-enabled environment for the processes of first screening of IS possibilities and initiation for further complex business-driven negotiations and agreements for long-term IS business relationships.
Many dynamics are reshaping the global macroeconomics and finance. This cumulative dissertation empirically examines the impacts of two major global dynamics, the disaster risks and the China's rise, on the global economy. Chapter 1 introduces the motivation and summarizes the dissertation. Chapter 2 investigates how geopolitical risks affect financial stress in the whole financial system and its sub-sectors (banking, stock, foreign exchange, bond) of major emerging economies. Chapter 3 shows how different disaster risks (financial, geopolitical, natural-technological) can explain the returns and risk premiums of stock and housing in advanced economies between 1870 and 2015. Chapter 4 examines how the rise of China is contributing to higher economic growth in emerging economies, especially after the Global financial crisis of 2007-2008. Chapter 5 illustrates how a close trade and investment relation with China has helped African countries to reduce poverty and to improve their income distribution.
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.