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Despite warnings from scientists and from society starting in the 1970s, we have long overshot our planetary boundaries – eroding biodiversity, changing our landscapes, and polluting our soil and atmosphere. Yes, efforts to change the unsustainable trajectories of our Earth system have increased through, for example, the Millennium Goals, the Sustainable Development Goals, or the Aichi Targets, but to no avail. The interventions to increase sustainability are conflicting on local, national and global levels, and often prioritise quick-fixes and short-term solutions instead of tackling the root causes of the “sustainability gap”. We, hence, need to find “places to intervene in complex systems that bring about transformative change” (Meadows 1999) – a premise and concept that Donella Meadows calls “leverage points”. Based on her seminal work, a team from the Leuphana University has identified three “realms of leverage” in which changes may lead to system transformation (Abson et al. 2017). One of these realms is the reconnection of humans to nature. In this habilitation, I focus on this realm of leverage and aim to (1) enhance the understanding of the influence of landscape change on human-nature relations through empirical, place-based research and comparisons across landscapes in different countries and continents; (2) identify and clarify the new concepts of relational values and leverage points; and (3) highlight empirical evidence on leverage points to foster human-nature relations for sustainability transformation, building mainly on empirical work done in six landscapes in Transylvania, Romania and Lower Saxony, Germany, but also including case studies from Ethiopia and India, systematic literature reviews and conceptual pieces. This thesis showed that cultural landscapes are changing with astonishingly comparable trajectories toward unsustainable futures. Our earth’s current environmental and climate crisis will continue to erode the fundaments of sustainability, hence, re-connecting humans to nature is of outstanding significance for transformative change. Identifying leverage points and implementing an intervention to strengthen human–nature relations will be a great challenge in the coming years. One possible leverage point can be strengthening experiential and emotional dimensions, as they specifically shape the connections people have with cultural landscapes. Further, this thesis highlighted the importance of the interlinkages between shallow and deep leverage points. Our results show that structurally complex landscapes and structurally rich social relations mediated by nature are interlinked and strengthening one, may strengthen the other. Moreover, strengthening sense of place and a sense of agency may enable self- and re-organization of cultural landscapes by opening the possibility to renegotiate people’s values for values and the goals of the social-ecological system, which, in turn, may enhance the structural diversity of landscapes and small-scale agriculture. Our results presented in this thesis also lay the ground for the hypothesis that degrading landscapes might also degrade social relations, which, in turn, can lead to contrasts and conflicts between actors and social groups. Although much work is still necessary to foster transformative change, this thesis offers innovative approaches. This thesis created and popularised the “Leverage points perspective”, including “chains of leverage”, as well as producing novel insights on human-nature relations – such as the distinction of human-nature connectedness and relational values, classifying relational value groups and empirically assessing dimensions of human-nature connectedness and relational values concerning landscape change and landscape features. These novel contributions can have wide-ranging impacts on the scientific discussions and societal implementation of interventions for sustainability.
Leverage points to foster human-nature relations for sustainability transformation
The requirements for the design of information and assistance systems in labour-intensive processes are interdisciplinary and have not yet been sufficiently addressed in research. This dissertation analyses, evaluates and describes possibilities for increasing the effectiveness and efficiency of labour-intensive processes through design-optimised socio-technical systems. The work thus contributes to further developing information and assistance systems for industrial applications and use in healthcare. The central dimensions of people, activity, context and technology are the focus of the scientific investigations following the Design Science Research paradigm. Design principles derived from this, a corresponding taxonomy, and a conceptual reference model for the design of socio-technical systems are the results of this dissertation.
This dissertation comprises three stand-alone research papers dealing with different aspects of labor market characteristics: bonus payments and the gender pay gap; second job holding; and workers un-covered by collective bargaining. The first paper investigates whether and how non-base compensation in the form of bonus payments, overtime pay, and shift premia contributes to the gender pay gap. Unionization along with collective bargaining coverage has been on the decline on recent decades. Using German administrative data, the second paper examines which workers in firms covered by col-lective bargaining agreements still individually benefit from these union agreements, which workers are not covered anymore and what this means for their wages. The third paper studies the development and persistence of second job holding in Germany after a legislative change in the year 2003 allowed the extensive dispensation of marginal second jobs from taxes and social security contributions. Using data from the German Socio-Economic Panel, the author documents a substantial increase in second job holding in Germany since 2003 and finds in a dynamic panel model setting that there is true state dependence in second job holding.
The research described in this dissertation focuses on developing a process to remove oligomers and suppress their formation by intercepting the aging procedure's precursors using adsorbents when biodiesel and its blends are used as fuel. So far, there has been no attempt to cause the stabilization of biodiesel and its blends using adsorbents from open literature. This investigation is one of the first studies on the use of adsorbents to mitigate biodiesel and diesel fuel's stability behavior–biodiesel blends and the removal of oligomers or suppressing the formation of high molecular mass species in aging oil. This study's primary aim has been achieved by several experimental measurements that provided results on adsorbents' effecton fuel oxidative stability, especially ester-based fuel like biodiesel and its blends. The chemical composition and some critical rheological analyses of the samples have been measured to understand their role in the oxidation of the sample by comparing the presence and absence of the adsorbents during the aging process. Furthermore, it aims to use adsorbents to suppress oligomers' formation and remove them in aging oil due to the influence of biodiesel and its blends. The research project also seeks to stabilize fuel, especially ester-based fuel like biodiesel, and its blends using the adsorbents. The adsorbents' application will enhance biodiesel's oxidative stability and its blends during long-term storage or application, focusing on its use in plug-in hybrid vehicles, emergency power plants,and generators. The combustion engine only starts in plug-in hybrid vehicles if the battery cannot supply energy on longer journeys. As a result, the fuel remains longer in plug-in hybrid vehicles. Fuels that are exposed to heat and oxygen over anextendedperiod can form aging products. These aging products lead to the formation of deposits, especially in the case of diesel fuels mixed with biodiesel content,and can, therefore, endanger the operational safety of the vehicle in critical components such as injectors or filter units.
The computational analysis and the optimization of transport and mixing processes in fluid flows are of ongoing scientific interest. Transfer operator methods are powerful tools for the study of these processes in dynamical systems. The focus in this context has been mostly on closed dynamical systems and the main applications have been geophysical flows. In this thesis, the authors consider transport and mixing in closed flow systems and in open flow systems that mimic technical mixing devices. Via transfer operator methods, They study the coherent behavior in closed example systems including a turbulent Rayleigh-Bénard convection flow and consider the finite-time mixing of two fluids. They extend the transfer operator framework to specific open flows. In particular, they study time-periodic open flow systems with constant inflow and outflow of fluid particles and consider several example systems. In this case, the transfer operator is represented by a transition matrix of a time-homogeneous absorbing Markov chain restricted to finite transient states. The chaotic saddle and its stable and unstable manifolds organize the transport processes in open systems. The authors extract these structures directly from leading eigenvectors of the transition matrix. For a constant source of two fluids in different colors, the mass distribution in the mixer and its outlet region converges to an invariant mixing pattern. In parameter studies, they quantify the degree of mixing of the resulting patterns by several mixing measures. More recently, network-based methods that construct graphs on trajectories of fluid particles have been developed to study coherent behavior in fluid flow. They use a method based on diffusion maps to extract organizing structures in open example systems directly from trajectories of fluid particles and extend this method to describe the mixing of two types of fluids.
In the study, predictive models for predicting therapy outcome are created using the dataset from E-COMPARED project, which belongs to the so-called type 3 models that use data from the intervention and preintervention phases to predict treatment outcomes, which can help to adapt intervention to maximize treatment. The predictive models aim to classify patients into two groups, improved and nonimproved. Since it is important to determine whether the models contribute to improvement of treatment, research questions that can contribute to the usage of type 3 models are established. The study focuses on the following three questions: (1) How accurately can the therapy outcome be predicted by various machine learning algorithms? Answering this question can let the people concerned obtain information about the reliability of contemporary predictive models. In addition, if the predictive power of the models is good, it is more likely to be used to assist therapists’ decisions. (2) Which kind of data is more important in predicting the therapy outcome? The answer to this question can show which dataset should be considered first to make better predictive models. Therefore, it can be helpful for researchers who want to make predictive models in the future and eventually help to facilitate personalized therapy. (3) What are the features with strong predictive power? The answer to this question can affect the people concerned, especially therapists. Therapists can use the most influential features revealed to adjust and improve future treatments.
The food and land use system is one of the most important global economic sectors. At the same time, today's resource-intensive agricultural practices and the profit orientation in the food value chain lead to a loss of biological diversity and ecosystem services, high emissions, and social inequality - so-called negative externalities. From a scientific perspective, there is a broad consensus on the need to transform the current food system. This paper investigates the suitability of True Cost Accounting (TCA) as an approach to inte-grating positive and negative externalities into business decisions in the food and land use system, focusing on the retail sector due to its high market power and resulting influence on externalities along the entire food value chain. For this purpose, a qualitative study was con-ducted with sustainability managers of leading European food retail companies in terms of their annual turnover, sustainable finance experts, and political actors related to environmental and social policy. A sample of N=11 participants was interviewed about the emergence and meas-urement of externalities along the food value chain, the current and future relevance of knowing about externalities for food retail companies, and the market and policy framework necessary for the application of TCA. The data collected was evaluated using the method of qualitative content analysis according to Mayring. Findings show that TCA is a suitable method for capturing positive and negative external ef-fects along the food value chain and thus also for meeting the growing social, political, and financial demands for its sustainable orientation. At the same time, there are still some chal-lenges in the application of TCA, both from a theoretical and a practical point of view. The main challenges at present are the lack of a standardised methodology, data availability, and key performance indicators. Due to the focus on prices, margins and competitors, food retail groups, in particular, emphasise the risk of revenue and profit losses as well as customer churn when applying TCA. Hence, the introduction of TCA in the food and land use system requires the development of measures that are socially acceptable, backed by legal frameworks and promote the scientific development of the methodology. This offers the opportunity to create a level playing field, apply the polluter-pays principle to the entire value chain and support science in developing appropriate indicators as well as a TCA database. Food retail companies can benefit from addressing TCA at an early stage by analysing their value chain to initiate change processes early, identify risk raw materials and products, reduce negative externalities through targeted measures, sensitise customers to the issue and thus differentiate themselves from competitors.
This thesis aims to contribute to a better understanding of the actual implementation of transdisciplinary research in sustainability science. Following three aims, this work likes to (1) contribute to the measurability of transdisciplinary research processes as well as their societal and academic outputs and impacts, to (2) demarcate transdisciplinary research from other modes of research in sustainability science and to (3) identify and examine the determinants that shape the contribution of transdisciplinary research to societal action for sustainable development and to scientific knowledge production. To serve these aims a mixed methods approach is applied that combines strong quantitative elements with in-depth qualitative analyses that integrate the perspectives of practitioners. This thesis provides a broad set of indicators to describe and assess transdisciplinary research that translate theoretical concepts form transdisciplinarity theory into observable variables. The indicators offer a holistic perspective on transdisciplinary research by representing research mode characteristics, societal as well as scientific outcomes of research projects and their specific context. To theoretically demarcate transdisciplinary research from other forms of research, a narrative literature review first elaborates the differences between "normal science", political use of scientific knowledge and transdisciplinarity in their underlying logics of problem definition, knowledge production and research utilization. Subsequently, these concepts were compared with perspectives and expectations of practitioners in the forest sector on integrative research settings. Moreover, a cluster analysis of data from 59 research projects identified five research modes that empirically demarcate ideal-typical transdisciplinary research from other research modes within sustainability science: (1) purely academic research, (2) practice consultation, (3) selective practitioner involvement, (4) ideal-typical transdisciplinary research and (5) practice-oriented research. Based on this finding, transdisciplinary research can be characterized as an intensive, but balanced involvement of practitioners. It incorporates not only the needs and goals of the practitioners but also their norms and values. Ideal-typical transdisciplinary research goes beyond mere consultatory research approaches and must be distinguished from what is conceptualized as applied research. Regression analysis of 81 research projects and statistical group comparisons of the five research mode clusters show that societal and academic outputs and impacts vary with specific project characteristics and combinations of project characteristics defined as research modes. The findings indicate that more interactive research modes reach more societal impacts. In particular, the involvement of practitioners in early project phases and the targeted dissemination of the research results positively affect societal impacts. This finding also aligns with practitioner expectations on integrative research and research utilization, provided by qualitative analysis. Moreover, the quantitative results show that scientific outputs and impacts decrease with the intensity of interactions, indicating a trade-off between societal and scientific outcomes and impacts. Overall, the empirical results of this thesis support the claimed effectiveness of transdisciplinary research in providing societally relevant, applicable knowledge and encourage further funding of transdisciplinary research by funding agencies.
This dissertation deals with the increasingly recognized role of incumbent firms in advancing sustainability-oriented industry transitions. Incumbent firms are understood as firms-in-industries, which are embedded in established market structures and thereby contrast new entrant firms. The purpose of this research is twofold. First, to provide empirical evidence of barriers to and success factors of incumbent-driven industry transitions. Second, to unify hitherto dispersed descriptions of transition-related firm behaviour in a new understanding of incumbent firms in industry transitions. To this end, theoretical concepts are discussed and extended on the basis of different empirical studies in the German meat industry. The meat industry serves as suitable research setting due to its diverse sustainability challenges, ranging from climate change and pollution to animal welfare and public health, as well as its current developments towards sustainable protein alternatives. The meat context also offers opportunities to delve into individual-level processes influencing transition-related behaviour. The main contribution of this dissertation is a Multi Embeddedness Framework (MEF) that details processes and outcomes of integrated incumbent firm behaviour, including passive, reactive and proactive behaviors. The framework acknowledges the diversity in incumbent firm behaviors within industries and firms and provides new insights into transition-related behaviors at firm and individual level. With regard to the latter, the potential of learning about and from innovative start-up firms as well as shared sensemaking processes are discussed. The contents of this dissertation provide valuable contributions to the transition literature as well as important management implications with regard to the stimulation and promotion of proactive behaviors
In this chapter, we aim to present how shame, vulnerability, self-care and community care interrelate to one another and how they help build the necessary foundation for mutual care in interdependent communities, and thus for community-supported projects (CSX). Furthermore, we argue that by looking at the role of shame and vulnerability within our personal life, as we simultaneously learn to take care of ourselves, we then lay a solid foundation for learning how to support others. We then suggest that at the birthplace between healthy sustainable self-care and community care, people and communities are able to shift from a hyper-individualized lifestyle (isolation, disconnection) to a more collective community-centered approach (belonging and connection) that finally creates the perfect recipe for the creation of CSX Projects and a more inclusive and kinder economy for all.