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Transformative learning is increasingly set to become an essential component in sustainability transformation. Despite, little has been done to systematically explore the contribution to sustainability transformation. This learning theory developed decades ago independently of sustainability discourses; however, it provides an analytical framework for understanding the learning processes, outcomes and conditions in individual and social learning towards sustainability transformation. Against this background, the following research question arises: To which extent can transformative learning lead to sustainability transformation? This doctoral work aims to explore transformative learning processes, outcomes, and conditions occurring and advancing towards sustainability transformation of the textile-fashion industry in Mexico. Taking an exploratory approach, the methods employed were literature reviews to untangle concepts and to construct theoretical pillars to support the empirical research design and data analysis. For data collection, snowball-sampling techniques were used to explore the practice field of the textile-fashion industry in Mexico. Qualitative interviews were employed to gather data about the learning experiences of actors. Qualitative and quantitative methods were required to perform the respective data analysis, the qualitative codification of interviewees' responses. Analysis of social media content was also utilised to understand the communication and business practices of projects involved in the transformation of the textile-fashion sector. As a result, this work comprises three articles, one a systematic literature review and two empirical research articles, investigating the transformative learning processes of entrepreneurs in the development of sustainability niches. As for the findings of this doctoral work, the use of transformative learning in sustainability transformation requires a careful study of the theory and its conceptual elements. Regarding the case study, transformative learning is inherent in forming and developing sustainability niches as entrepreneurs venture into them: It is individual prior learning, expectations and actions that initiate the path of sustainability transformation while disorienting dilemmas, critical reflection, and discourse accelerate them. Through these stages, it is when individual learning turns into social learning. On the other hand, based on the multi-level perspective, the interplay between the niche, regime and landscape levels generates a space for sustainability transformation and transformative learning.
The global coffee market is connected to many sustainability issues like the persisting poverty of coffee farmers, and degrading ecosystems. Many interventions, from state-led regulation to industry-led certification processes, exist, that try to change global value chains to shift societies back on more sustainable trajectories. To this date, it is still under debate if these interventions are an effective means to change global value chains. With climate change and persisting issues of social justice as strong accelerators, calls are increasingly made for a radical transformation of global production and consumption patterns. Many frameworks try to inform research and real-world policies for a transformation of global value chains. In this dissertation, the author uses the framework of the practical, political and personal sphere proposed by O'Brien and Sygna (2013) highlighting that the interactions between these three spheres bare the greatest potential for a transformation towards sustainability. However, in this dissertation, the author argues that it is exactly at the nexus between the three spheres of transformation where barriers towards a fundamental shift of systems occur. He, therefore, uses three perspectives to bring empirical nuance to the problems that arise on the interplay between the different spheres of transformation. (1) The scientific perspective: using a systematic review of alternative trade arrangements; (2) the producer perspective: facilitating a participatory network analysis of social-ecological challenges of Ugandan coffee farmers and their adaptive management practices; (3) the consumer perspective: through the use of a German consumer survey and a structural equation model to investigate into the Knowledge-Doing-Gap end-consumers are facing. Through the results from the scientific perspective, the author is able to show that most of the research is investigating the certified market and that the effectiveness of labels rarely exceeding the practical sphere. His empirical research on the producer perspective highlights that Ugandan coffee farmers facilitate a variety of on-farm crop management (practical sphere) but their support structures rarely exceed informal exchange with neighboring communities (political sphere). Exchange with governmental actors and global traders is happening but has been assessed as not sufficient to cope with the social-ecological challenges the producers are facing. Through the results of the consumer perspective, the author is able to highlight that even though end-consumers have pro-sustainable attitudes (personal sphere) they are facing situational constraints (political sphere) that create a gap between their attitudes and the respective behavior. Using these empirical insights about drivers and barriers for a transformation he proposes that frameworks, aiming to inform research and policies, need to include two aspects: (1) the notion of a forced transformation; and (2) the translational capacity of the frameworks to create meaningful interdisciplinary discourses in different contexts. The author, therefore, propose two approaches:(1) a fourth sphere, called the "planetary force" to include the notion of a forced transformation that is already happening in different contexts, highlighted by the producer perspective in this dissertation; and (2) the consequent use of methods that create interdisciplinary exchange and rigorous testing.
The transition of our energy system towards a generation by renewables, and the corresponding developments of wind power technology enlarge the requirements that must be met by a wind turbine control scheme. Within this thesis, the role of modern, model-based control approaches in providing an answer to present and future challenges faced by wind energy conversion systems is discussed. While many different control loops shape the power system in general, and the energy conversion process from the wind to the electrical grid specifically, this work addresses the problem of power output regulation of an individual turbine. To this end, the considered control task focuses on the operation of the turbine on the nonlinear power conversion curve, which is dictated by the aerodynamic interaction of the wind turbine structure and the current inflow. To enable a power tracking functionality, and thereby account for requirements of the electrical grid instead of operating the turbine at maximum efficiency constantly, an extended operational range is explicitly considered in the implemented control scheme. This allows for an adjustment of the produced power depending on the current state of the electrical grid and is one component in constructing a reliable and stable power system based on renewable generation. To account for the nonlinear dynamics involved, a linear matrix inequalities approach to control based on Takagi-Sugeno modeling is investigated. This structure is capable of integrating several degrees of freedom into an automated control design, where, additionally to stability, performance constraints are integrated into the design to account for the sensitive dynamical behavior of turbines in operation and the loading experienced by the turbine components. For this purpose, a disturbance observer is designed that provides an estimate of the current effective wind speed from the evolution of the measurements. This information is used to adjust the control scheme to the varying operating points and dynamics. Using this controller, a detailed simulation study is performed that illustrates the experienced loading of the turbine structure due to a dynamic variation of the power output. It is found that a dedicated controller allows wind turbines to provide such functionality. Additionally to the conducted simulations, the control scheme is validated experimentally. For this purpose, a fully controllable wind turbine is operated in a wind tunnel setup that is capable of generating reproducible wind conditions, including turbulence, in a wide operational range. This allows for an assessment of the power tracking performance enforced by the controller and analysis of the wind speed estimation error with the uncertainties present in the physical application. The controller showed to operate the turbine smoothly in all considered operating scenarios, while the implementation in the real-time environment revealed no limitations in the application of the approach within the experiments. Hence, the high flexibility in adjusting the turbine operating trajectories and structural design characteristics within the model-based design allows for efficient controller synthesis for wind turbines with increasing functionality and complexity.
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.
Die institutionelle Bildung, Erziehung und Betreuung für Kinder im Alter von 0-3 Jahren erfährt seit Beginn der Diskussionen um einen quantitativen Ausbau der institutionellen Betreuungsplätze für diese Altersgruppe, einen intensiven Wandel. Die vorliegende Dissertation eröffnet eine Metaperspektive auf das Feld der Aus-, Fort- und Weiterbildungen im Bereich der Frühpädagogik (Kinder von 0 bis 3 Jahren) und leistet einen Beitrag zur (didaktischen) Weiterentwicklung und Reflexion dieser vielfältigen Lehr-/Lernsettings. Den Kern der Dissertationsstudie bilden qualitative leitfadengestützte (Experten-) Interviews. Das forschungsleitende Interesse ist auf Lehrende im oben genannten Bereich gerichtet, die zum Zeitpunkt der Erhebungen bereits langjährig in diesem Feld tätig sind. Ausgewählte Ebenen und Dimensionen einer Professionalisierung des Feldes werden daher primär aus der Perspektive der dort lehrend tätigen Akteure transparent gemacht. Integriert wird hierbei u.a. die Offenlegung der Anforderungen an die Fachkräfte (die Lernenden) und ihre Aus-, Fort- und Weiterbildner (die Lehrenden) im Kontext der zu gestaltenden (lebenslangen) Lehr-/Lernprozesse. Es werden zentrale Zusammenhänge und Abhängigkeiten aufgezeigt, um eine weitere Systematisierung des Feldes der Aus-, Fort- und Weiterbildungen im Bereich der institutionellen Bildung, Erziehung und Betreuung für Kinder von null bis drei Jahren zu unterstützen. Es wird gezeigt, dass Lehrende aus diesem Bereich Perspektiven, Strategien und Ansätze entwickelt haben, um mit der vorhandenen Komplexität, den Anforderungen und Strukturen des Feldes, bei der Planung sowie Realisierung von Lehr-/Lernprozessen zukunftsorientiert umzugehen. Für die Erarbeitung einer Aus- oder Fort- und Weiterbildung müssen schwerpunktspezifisch, grundlegende, feldbezogene Implikationen und Zusammenhänge aufgearbeitet und den Lernenden transparent gemacht werden. Für die Erarbeitung eines Themas/einer Theorie werden von Lehrenden Reflexionsfolien zur Kontextualisierung dieser sowie Fokussierung und Individualisierung der Lehr-Lernprozesse eingesetzt. Es wird deutlich, dass die am/im Lehr-/Lernprozess beteiligten/wirkenden Ebenen, Akteure und Anforderungen/Konstruktionen sich dabei in wechselseitigen Prozessen der Gestaltung und Aushandlung befinden. Durch ihre vielfältigen Tätigkeitsfelder und Impulse leisten die Lehrenden selbst einen elementaren Beitrag zur Weiterentwicklung des Feldes.
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.
Mit der vorliegenden Arbeit werden die bis Ende 2020 entstandenen gesetzlichen Strukturen und Instrumente zum Ausbau erneuerbarer Energien aus rechtswissenschaftlicher Perspektive eingeordnet, um der Frage nachzugehen, mit welchen Ansätzen und in welchem Umfang der Rechtsrahmen die verschiedenen Entwicklungen zur Erreichung der Ausbauziele für die erneuerbaren Energien einerseits und damit deren Beitrag zur Erreichung der Klimaschutzziele steuern kann. Darüber hinaus wird beleuchtet, welche Reformperspektiven aus den bisherigen Entwicklungen abgeleitet werden können oder sollten. Dazu werden die Strukturen und Elemente des Erneuerbare-Energien-Rechts sowie dessen Entwicklungslinien herausgearbeitet und bewertet. Dieser Schritt erfolgt durch die Analyse einzelner, für das Recht der erneuerbaren Energien prägender Strukturen und Entwicklungsschritte, etwa der Schaffung neuer Instrumente wie der Nutzungspflicht erneuerbarer Energien, der Beschreibung der prägenden Strukturelemente und Wirkungszusammenhänge in dem sich im Laufe von 30 Jahren herausgebildeten Recht der Erneuerbaren Energien im Stromsektor oder anhand der Einordnung von tiefgreifenden gesetzgeberischen Veränderungen wie der Umstellung auf Ausschreibungen im Erneuerbare-Energien-Gesetz. Diese Einzelbeobachtungen werden dann in Beziehung zueinander gesetzt, Gemeinsamkeiten und Unterschiede der hinter den Entwicklungen erkennbaren Gründe herausgearbeitet und in einen übergeordneten Gesamtkontext. Die Arbeit gliedert sich in vier Schritte, die sich einer kurzen einleitenden Problemskizze in Teil 1 anschließen: die grundlegende Analyse zu Recht und Klimaschutz sowie zur Rolle des Rechts bei der Transformation (Teil 2), eine umfassende Bestandsaufnahme zu den Bausteinen des Erneuerbare-Energien-Rechts, den Entwicklungslinien und deren Einordnung (Teil 3), ein Zwischenfazit, das die Gründe für die beobachteten Entwicklungslinien und Strukturen zusammenfasst und eine Einordnung des Rechts der erneuerbaren Energien in den größeren Kontext des Umweltenergierechts (Teil 4) sowie abschließend ein auf einer Einordnung des Rechts der erneuerbaren Energien in den Kontext der neu entstehenden Klimaschutzgovernance beruhenden Ausblick auf mögliche Themenfelder der weiteren Rechtsfortbildung (Teil 5).
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.
Urban areas are prone to climate change impacts. Simultaneously the world's population increasingly resides in cities. In this light, there is a growing need to equip urban decision makers with evidence-based climate information tailored to their specific context to adequately adapt to and prepare for future climate change. To construct climate information high-resolution regional climate models and their projections are pivotal. There is a need to move beyond commonly investigated variables, such as temperature and precipitation, to cover a wider breath of possible climate impacts. In this light, the research presented in this thesis is centered around enhancing the understanding about regional-to-local climate change in Berlin and its surroundings, with a focus on humidity. More specifically, following a regional climate modelling and data analysis approach, this research aims to understand the potential of regional climate models, and the possible added value of convection-permitting simulations, to support the development of high-quality climate information for urban regions, to support knowledge-based decision-making. The first part of the thesis investigates what can already be understood with available regional climate model simulations about future climate change in Berlin and its surroundings, particularly with respect to humidity and related variables. Ten EURO-CORDEX model combinations are analyzed, for the RCP8.5 emission scenario during the time period 1970-2100, for the Berlin region. The results are the first to show an urban-rural humidity contrast under a changing climate, simulated by the EURO-CORDEX ensemble, of around 6% relative humidity, and a robust enlarging urban drying effect, of approximately 2-4% relative humidity, in Berlin compared to its surroundings throughout the 21st century. The second part explores how crossing spatial scales from 12.5km to 3km model grid size affects unprecedented humidity extremes and related variables under future climate conditions for Berlin and its surroundings. Based on the unique HAPPI regional climate model dataset, two unprecedented humidity extremes are identified happening under 1.5°C and 2°C global mean warming, respectively SH>0.02 kg/kg and RH<30%. Employing a double-nesting approach, specifically designed for this study, the two humidity extremes are downscaled to the 12.5km grid resolution with the regional climate model REMO, and thereafter to the 3km with the convection-permitting model version of REMO (REMO NH). The findings indicate that the convection-permitting scale mitigates the SH>0.02kg/kg moist extreme and intensifies the RH<30% dry extreme. The multi-variate process analysis shows that the more profound urban drying effect on the convection-permitting resolution is mainly due to better resolving the physical processes related to the land surface scheme and land-atmosphere interactions on the 3km compared to the 12.5km grid resolution. The results demonstrate the added value of the convection-permitting resolution to simulate future humidity extremes in the urban-rural context. The third part of the research investigates the added value of convection-permitting models to simulate humidity related meteorological conditions driving specific climate change impacts, for the Berlin region. Three novel humidity related impact cases are defined for this research: influenza spread and survival; ragweed pollen dispersion; and in-door mold growth. Simulations by the regional climate model REMO are analyzed for the near future (2041-2050) under emission scenario RCP8.5, on the 12.5km and 3km grid resolution. The findings show that the change signal reverses on the convection-permitting resolution for the impact cases pollen, and mold (positive and negative). For influenza, the convection-permitting resolution intensifies the decrease of influenza days under climate change. Longer periods of consecutive influenza and mold days are projected under near-term climate change. The results show the potential of convection-permitting simulations to generate improved information about climate change impacts in urban regions to support decision makers. Generally, all results show an urban drying effect in Berlin compared to its surroundings for relative and specific humidity under climate change, respectively for the urban-rural contrast throughout the 21st century, for the downscaled future extreme conditions, and for the three humidity related impact cases. Added value for the convection-permitting resolution is found to simulate humidity extremes and the meteorological conditions driving the three impacts cases.
Destination websites, which are maintained by destination marketing/management organisations (DMOs), are a key source of information for tourists in the pre-trip phase. DMOs are increasingly applying experiential marketing on their websites to support positive pre-travel online destination experiences (ODEs) and make the vision of the holiday as vivid as possible. However, research into technology-driven travel experiences is still in its infancy. In particular, a theoretical understanding of the nature of ODEs arising from destination websites is still lacking. Therefore, this dissertation is dedicated to an extensive investigation of ODEs on destination websites in the pre-travel phase. The aims were to analyse the influences of experiential design on ODEs, explore the ODE dimensions, and develop and validate a measurement tool for assessing the ODE values of destination websites. In the first qualitative multi-method study (eye-tracking, retrospective think-aloud protocols, semi-structured interviews, and video observations), the objective was to gain an in-depth understanding of the ODE facets in the travel inspiration phase. It was found that the experience dimensions adopted in previous research regarding the product-brand context (sensory, affective, intellectual, social, and behavioural dimensions) also occurred in the ODE context but exhibited some particularities, such as a future-oriented affective component (affective forecasting). Moreover, a supplementary spatio-temporal experience dimension was identified. An online field experiment was subsequently conducted and aimed at assessing the effects of applying experiential marketing on destination websites on ODEs in the travel inspiration phase. Based on the findings of Study 1, an initial attempt at developing an ODE measurement instrument was made and the ODE dimensionality tested. The results showed the theoretically relevant experience dimensions to be less differentiated compared to the product-brand context; instead, they merged into a holistic ODE encompassing several experience facets. Furthermore, it was shown that the application of experiential design enhanced ODEs; however, considering the subjectivity of experiences, the effect was rather small. Accordingly, complex multi-media elements do not automatically increase the experiential effect. In the third study, a quasi-online field experiment was conducted, simulating the travel information phase (higher involvement than Study 2) to re-assess the ODE dimensions and develop and validate a measurement instrument. The results showed the overall ODE to be reflected by two interrelated dimensions that aligned with the dual process theory: hedonic and utilitarian experiences. The facets identified in the first study were largely reflected in these two overarching components. Moreover, a reliable, valid, and parsimonious second-order measure for assessing ODEs was proposed. Overall, the results yielded by this dissertation enhance the scientific understanding of the technology-empowered tourist experience in the currently under-researched pre-travel experience phase. In addition, by proposing a new scale for the measurement of ODEs, this dissertation provides useful methodological advancements that can pave the way for further research in this field.