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This dissertation includes an introduction and five empirical papers focusing on the educational and career decision-making process of individuals in Germany. The five papers embrace different determinants of educational and career decisions including school performance, social background, leisure activities as well as professional expectations, and contribute to the existing literature in this research area. Chapter 2 of this dissertation begins by analysing the nexus between students’ time allocation and school performance in terms of grades and satisfaction with their own performance in mathematics, the German language and a first foreign language, as well as overall achievement. This chapter looks at the heterogeneity of three important extracurricular activities: student jobs, sports and participation in music. Moreover, the heterogeneity of each activity is addressed by accounting for different types of the particular activity and differences in the number of years the activity has been pursued. For this purpose, data from the German SOEP, as a representative panel survey of private households and people in Germany, in particular cross-sectional survey data of 3388 students who are about 17 years old and enrolled in a German secondary school, were used. The main findings are that having a job as a student is negatively correlated with school performance, whereas participation in sports and music is positively correlated. However, the results reveal heterogeneity in each activity, especially with respect to intensity. Chapter 3 addresses the concrete post-school decision of school students, in particular whether to study or to enter the German VET system (Vocational Education and Training). It focuses on individual risk preferences and the social background of individuals and how these determinants affect the ultimate decision to enrol in university or to start an apprenticeship given the same level of qualification. For the empirical approach data from the German SOEP were used, in particular information on individuals' educational decisions between 2007 and 2013. The results indicate that (i) individual risk preferences do not have an overall effect on the real transition; (ii) privileged individuals are more likely to take up higher education; and (iii) compared to highly educated parents, parents without an academic background are less likely to guide their children into tertiary education, regardless of how much they support their children with their school work. Chapter 4 deals with the reconsideration of educational decisions in terms of early contract cancellations in VET. In particular, the effects of a second job on the intention to cancel a VET contract early are analysed for apprentices in Germany. For the empirical approach the representative German firm-level study "BIBB Survey Vocational Training from the Trainee's Point of View 2008", conducted by the Federal Institute for Vocational Education and Training (BIBB), is used. The survey contains 5901 apprentices that were interviewed during their second year of apprenticeship (205 schools, 340 classes, and 15 common occupations). Furthermore, it includes the design, procedures, basic conditions, and quality criteria of apprenticeships. The applied probit regressions show a higher intention to quit if apprentices require a secondary job to cover their living costs. In Chapter 5, new data on 191 apprentices from a vocational school, located in a northern German federal state, are used to validate the empirical results of Chapter 4. This chapter presents new insights into secondary-job-related burdens during apprenticeship. Due to limitations in the data, the applied empirical approach in Chapter 4 lacks to analyse how holding multiple jobs increases the intention to leave an apprenticeship early. Therefore, Chapter 5 includes the investigations of burdens related to the second job. The results indicate a lower intention to quit the apprenticeship if an apprentice holds a second job to cover living costs. However, secondary jobs are linked to lower quality of training, which, on the other hand, increases the intention to leave the apprenticeship early. Furthermore, the probability of secondary-job-related burdens increases with the number of working hours. Chapter 6 concludes the thesis by investigating subjective determinants of early contract cancellations in VET. It examines ten questions on what apprentices want to achieve and how unfulfilled expectations affect the intention to leave the apprenticeship early. The findings of this investigation contributes to the existing research on early contract cancellation. The questions considered include information on the performance, personal development, career development and prospects or position in society and their meaning to apprentices. For the research approach, the "BIBB Survey Vocational Training from the Trainee's Point of View 2008" is considered again. The probit and ordered probit regressions applied show significant effects of job characteristics that represent job security. The expectation of being retained after an apprenticeship and the encouragement to consistently train further decrease the intention to leave the apprenticeship early. Furthermore, women appear to be more affected by job security signals than men, but they also sort more often into occupations with lower retention probabilities. Consequently, this result may be an indication of occupational segregation rather than a sign of differences between sexes.
Excessive fertilizer use leads to nutrient imbalances and losses of these to the environment through leaching, runoff and gaseous emissions. Nutrient use efficiency (NUE) in agriculture is often low and improving it could increase the sustainability of agricultural systems. The main aims of this thesis were to gain a better understanding of plant-soil-microbe interactions in order to improve agricultural NUEs. The studies included experimentally tested how crops respond to addition of high carbon amendments, fertilizer application rates and timing, and crop rotations. Furthermore, methods for measurement of roots were compared and a protocol for measurement of roots was developed. The first experiment simulated an agricultural field using mesocosms. In this setting, the researchers tested the effect of 4 previous crops (precrops), which either had or did not have a symbiosis with arbuscular mycorrhizal fungi (AMF)/rhizobia, on the focal crop (winter barley). They also tested the addition of high carbon amendments (wheat straw/sawdust) for immobilization of residual soil nitrogen (N) at harvest of the previous crop. Overall, the findings were that non-AMF precrops had a positive effect on winter barley yield compared to AMF precrops. Wheat straw reduced N leaching, whereas sawdust addition had a negative effect on the yield of winter barley. The second experiment tested the effect of different fertilizer (N/phosphorus (P)) application timings on plant traits grown in rhizoboxes. Overall, delaying N application had a more detrimental effect on plant biomass than delaying P application. The root system increased its root length initially due to N-deficiency, but was quickly thus N-limited that root length was relatively lower than the control group. Because of the many root related measurements in the second experiment, a step-by-step method for measuring root traits under controlled and field conditions was developed and included in this thesis. This method paper describes precisely how root traits of interest can be measured, and helps with deciding which approach should be taken depending on the experimental design. Additionally, the authors compared the bias and accuracy of several popular root measurement methods. Overall, these results highlight the importance of crop choice in crop rotations and the plasticity of root systems in relation to nutrient application. The results show high carbon amendments could reduce nitrate leaching after the harvest of crops, especially those with high risk of nitrate leaching, although they had only small impacts on yield.
This doctoral dissertation aims to contribute to clarification of the potential of learning for water governance. The goal is to trace and understand the environmental impacts of learning through participation (research aim 1) and adaptive management (research aim 2), and the effect of learning on participation as a governance mode (research aim 3). For this goal, the researcher engages in a predominantly qualitative research design following the case study method. For every specific research aim cases are selected and analysed qualitatively according to conceptual categories and mechanisms which are defined beforehand. Quantitative studies are used to corroborate the results for research aim 1 and 2 in a mixed-method approach to enhance the validity of results. The empirical research context is European water governance, the implementation of the EU Water Framework and EU Floods Directive (WFD, FD) specifically. Eight cases of participatory decision-making across three European countries and five cases of adaptive management in Northern Germany for WFD implementation are examined to identify whether learning in these processes enhanced environmental outcomes. To detect whether governance learning by public officials occurred, the design of participatory processes for FD implementation in ten German federal states is assessed. The findings of research aim 1, understanding learning through participation and its effects on water governance, reveal that participatory planning led to learning through improved understandings at an individual and group level. Learning did, however, hardly shape effective outcomes. In the AM cases (research aim 2) managers and participants of implementing networks improved their knowledge as well as capacities, and spread the results. Nonetheless, environmental improvement was not necessarily linked to ecological learning. Regarding learning about participation as a governance mode (research aim 3) all interviewed public officials in German federal states reported some degree of governance learning, which emerged not systematically but primarily drawing on own experiences and intuition. These findings are condensed into three overarching lessons for learning in water governance: (1) Interactive communication seems to form the overall frame for participant and group learning. Framing of learning experiences turned out to play an important and potentially distorting role, for which professional facilitation and structured knowledge aggregation methods might be an im-portant counterbalance. (2) Learning did not automatically enhance environmental outcomes. It may thus not be an explanatory variable for policy outcomes, but a conditioning or intervening variable related to collective action, motivation for participation, and situating the issue at hand at wider societal levels. (3) The concepts of puzzling and powering might help understand learning as a source for effectiveness in the long-term when complemented with interest-based debates for creat-ing sufficient political agency of policy issues. Learning seen as puzzling processes might instruct acceptance and legitimization for new powering efforts. The perpetuation of learning in systematic ways and structures appears to characterize an alternative to this reflexive and strategic interplay, for which the water-related EU directives provide the basis.
One of the Colombian strategies to diversify and decarbonize the energy sector is encouraging the use of non-conventional renewable resources (NCRR). This thesis measures the environmental rebound effect (ERE) when increasing the shares of wind power into the Colombian power grid in the residential (household) sector. For doing so, a process-based Life Cycle Assessment (P-LCA), an environmental extended input output (EEIO) model and re-spending models (almost ideal demand system AIDS) were applied. Direct rebound effect was measured thought the elasticity price of the electricity demand; furthermore, the environmental savings for increasing the shares of wind power into the grid were calculated via P-LCA. For doing so, a P-LCA for a wind farm in Colombia was performed, whereas the information for other energy resources (Hydro, Coal, Gas, Solar and Thermal) where collected from Ecoinvent 3.4 database. To calculate the environmental indirect rebound effect the monetary savings obtained for the environmental efficiency were calculated. For doing so, an AIDS was applied to obtain the marginal budget shares (MBS). Combining the MBS obtained with the EEIO model the monetary savings were translated into environmental indicators. The ERE is presented for ten impact categories (climate change (CC), acidification (A), ecotoxicity (E), marine eutrophication (MEUT), terrestrial eutrophication (TEUT), carcinogenic effects (CE), non-carcinogenic effects (NCE), ozone layer depletion (OD), photochemical ozone creation (POC), and respiratory effects, inorganics (RES)). Moreover, a sensitive analysis was conducted to measure the variability of the ERE to different values of the direct rebound effect and different percentages of price efficiency. The results show that the inclusion of the environmental rebound effect has generally a non-negligible impact on the overall environmental indicators across all studied years. Such impacts ranging across impact categories from 5% (eutrophication) and 6,109% (photochemical oxidant creation) for the combined model, whereas for the single model the values fall on the ranges of 1% (eutrophication) and 9,277% (photochemical oxidant creation). Further, a sensitivity analysis of the elasticity price of the electricity and the price of the electricity reveals that the ERE varies in different ways, specifically, changes in these parameters could vary the impacts, respectively, by up to about <1% and 38%. Backfire effects are present for 8 of the 10 environmental impacts studied in different magnitudes across the years, depending meanly of the savings available to re-invest.
Transforming the International Food Supply – Sustainable Practices in Small Intermediary Businesses
(2021)
The global food system faces many complex challenges, and there is general agreement that a transformation is needed. While localizing food has been proposed as a means to this end, changing global food supply chains may also lead to sustainable food systems. Because most food systems today have an international dimension and are likely to remain connected, on one way or another, to other ones across the globe, it is necessary to find solutions to problems such as exploitation or environmental degradation. Addressing this challenge and the related gap in the literature, this study examines the emerging practices of small intermediary food businesses, which act between agricultural producers and consumers, and may have the potential to advance sustainability in international food supply. Including a systematic review of the literature on food systems change (Study#1), this dissertation adopts a transformational sustainability research methodology, which is solution-oriented, aims to integrate system, target and transformation knowledge, and is characterized by a transdisciplinary research practice. It conceptualizes challenges of international food supply and empirically investigates entrepreneurial solution approaches to address these challenges (Study#2). Two transdisciplinary research projects with small coffee businesses located in Germany, Mexico, and the U.S. were conducted to examine how these approaches could be implemented (Study#3, Study#4, Workshop reports 1+2). Overall, this study shows that challenges in international food supply chains can be conceptualized as negative effects of large geographical and relational distances. It also identifies five entrepreneurial solution approaches specified by twelve sustainability-oriented design principles to address these negative effects. Creating relational proximity between supply chain actors, that is, strong relationships based on knowledge and care, seems to be a key factor to advance sustainability in international food supply.The results also suggest that by building such strong relationships and changing the fundamental principles of international food trade, small intermediary businesses could be important agents in food system transformations.
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.
The dissertation consists of three scientific papers and a synopsis. The synopsis addresses the relevance of the dissertation and lists the key factors for the sustainability transition in the electricity system as a common denominator of the three papers. The relevance of the dissertation results, on the one hand, from the urgency of the sustainability transition in the electricity system and an insufficient transition willingness of the eastern European Member States. On the other hand, the Multi-Level-Perspective as one of the most important scientific frameworks to grasp transitions does not provide a sufficient explanation of its mechanisms. Moreover, Demand Response aggregators as new enterprises on the European electricity market and potential reform initiators are still under researched. The following key factors for the sustainability transition of the electricity system have been identified: supply security concerns, Europeanisation, policy making and the dominance of short-term oriented economic evaluation. Paper#1 sheds light on the roots of this problem in the context of Poland. It suggests that unfavorable regulation is symptomatic of the real, underlying barriers. In Poland, these barriers are coal dependence and political influence on energy enterprises. As main drivers, supply security concerns, EU regulatory pressure, and a positive cost-benefit profile of DR in comparison to alternatives, are revealed. A conceptual model of DR uptake in electricity systems is proposed. Applying a social mechanisms approach to the Multi-Level Perspective, paper#2 conceptualizes mechanisms of socio-technical transitions and of gaining legitimacy for transitions as co-evolutionary drivers and outcomes. Situational, action-formational, and transformational mechanisms that operate as drivers of change in a socio-technical transition require corresponding framing and framing contests to achieve legitimacy for that transition. The study illustrates the conceptual insight with the case of the coal dependent Polish electricity system. Paper #3, a qualitative study reveals Demand Response (DR) aggregators as institutional entrepreneurs that struggle to reform the still largely supply-oriented European electricity market. Unfavourable regulation, low value of flexibility, resource constraints, complexity, and customer acquisition are the key challenges DR aggregators face. To overcome them they apply a combination of strategies: lobbying, market education, technological proficiency, and upscaling the business. The study highlights DR aggregation as an architectural innovation that alters the interplay between key actors of the electricity system and provides policy recommendations including the necessity to assess the real value of DR in comparison to other flexibility sources by taking all externalities into account, a technology-neutral approach to market design and the need for simplification of DR programmes, and common standards to reduce complexity and uncertainty for DR providers.
Assessment of forest functionality and the effectiveness of forest management and certification
(2021)
Forest ecosystems are complex systems that develop inherent structures and processes relevant for their functioning and the provisioning of ecosystem services that contribute to human wellbeing. With increasing climate change impacts, especially regulating ecosystem services such as microclimate regulation are ever more relevant to maintain forest functions and services. A key question is how forest management supports or undermines the ecosystems’ capacity to maintain those functions and services. The main objective of this thesis is the development of a concept to assess the functionality of forests and to evaluate the effectiveness of forest ecosystem management including certification. An ecosystem-based and participatory methodology, named ECOSEFFECT, was developed. The method comprises a theoretical and an empirical plausibility analysis. It was applied to the Russian National FSC Standard in the Arkhangelsk Region of the Russian Federation - where boreal forests are exploited to meet Europe's demand for timber. In addition, the influence of forestry interventions on temperature regulation in Scots pine and European beech forests in Germany was assessed during two extreme hot and dry years in 2018 and 2019. Microclimate regulation is a suitable proxy for forest functionality and can be applied easily to evaluate the effectiveness of forest management in safeguarding regulating forest functions relevant under climate change. Thus, the assessment of forest microclimate regulation serves as convenient tool to illustrate forest functionality. In the boreal and temperate forests studied in the frame of this thesis, timber harvesting reduced the capacity to self-regulate forests’ microclimate and thus impair a crucial part of ecosystem functionality. Changes in structural forest characteristics influenced by forest management and silviculture significantly affect microclimatic conditions and therefore forest ecosystems' vulnerability to climate change. Canopy coverage and the number of cut trees were most relevant for cooling maximum summer temperature in pine and beech forests in northern Germany. The Russian FSC standard has the potential to improve forest management and ecological outcomes, but there are shortcomings in the precision of targeting actual problems and ecological commitment. It is theoretically plausible that FSC prevents logging in high conservation value forests and intact forest landscapes, reduces the size and number of clearcuts, and prevents hydrological changes in the landscape. However, the standard was not sufficiently explicit and compulsory to generate a strong and positive influence on the identified problems and their drivers. Moreover, spatial data revealed, that the typical regular clearcut patterns of conventional timber harvesting continue to progress into the FSC-certified boreal forests, also if declared as "Intact Forest Landscape". This results in the need to verify the assumptions and postulates on the ground as it remains unclear and questionable if functions and services of boreal forests are maintained when FSC-certified clearcutting continues.The analysis of satellite-based data on tree cover loss showed that clearcutting causes secondary dieback in the surrounding of the cleared area. FSC-certification does not prevent the various negative impacts of clearcutting and thus fails to safeguard ecosystem functions. The postulated success in reducing identified environmental threats and stresses, e. g. through a smaller size of clearcuts, could not be verified on site. The empirical assessment does not support the hypothesis of effective improvements in the ecosystem. In practice, FSC-certification did not contribute to change clearcutting practices sufficiently to effectively improve the ecological performance. Sustainability standards that are unable to translate principles into effective outcomes fail in meeting the intended objectives of safeguarding ecosystem functioning. Clearcuts that carry sustainability labels are ecologically problematic and ineffective for the intended purpose of ecological sustainability.The overexploitation of provisioning services, i.e. timber extraction, diminishes the ecosystems' capacity to maintain other services of global significance. It also impairs ecosystem functions relevant to cope with and adapt to other stresses and disturbances that are rapidly increasing under climate change.
This cumulative dissertation investigates food policy councils (FPCs) as potential levers for sustainability transformation. The four research papers included here on this recent phenomenon in Germany present new insights regarding the process of FPCs' emergence (Emergence paper), the legal conditions which affect their establishment (Legal paper), the different roles of FPCs in policy-making processes (Roles paper) and FPCs' potential to democratise the food system (Food democracy paper). Drawing on and contextualizing the results of the four individual studies, the framework paper uses the leverage points concept originally developed by Meadows (1999) and adopted by Abson et al. (2016) as a lens to discuss FPCs’ potential as levers for sustainability transformation. This conceptual background includes three so-called realms of leverage, which are considered to be of particular importance in transformational, solution-oriented sustainability science: first, the change, stability and learning in institutions (re-structure), second, the interactions between people and nature (re-connect) and third, the ways in which knowledge is produced and used (re-think). Framing the findings of the four research papers in terms of these three realms, the framework paper shows that FPCs could serve as cross realm levers, i.e. as interventions that simultaneously address knowledge production, institutional reform and human-nature interactions.
Maximizing the value from data has become a key challenge for companies as it helps improve operations and decision making, enhances products and services, and, ultimately, leads to new business models. While enterprise architecture (EA) management and modeling have proven their value for IT-related projects, the support of enterprise architecture for data-driven business models (DDBMs) is a rather new and unexplored field. The research group argues that the current understanding of the intersection of data-driven business model innovation and enterprise architecture is incomplete because of five challenges that have not been addressed in existing research: (1) lack of knowledge of how companies design and realize data-driven business models from a process perspective, (2) lack of knowledge on the implementation phase of data-driven business models, (3) lack of knowledge on the potential support enterprise architecture modeling and management can provide to data-driven business model endeavors, (4) lack of knowledge on how enterprise architecture modeling and management support data-driven business model design and realization in practice, (5) lack of knowledge on how to deploy data-driven business models. The researchers address these challenges by examining how enterprise architecture modeling and management can benefit data-driven business model innovation. The mixed-method approach of this thesis draws on a systematic literature review, qualitative empirical research as well as the design science research paradigm. The investigators conducted a systematic literature search on data-driven business models and enterprise architecture. Considering the novelty of data-driven business models for academia and practice, they conducted explorative qualitative research to explain "why" and "how" companies embark on realizing data-driven business models. Throughout these studies, the primary data source was semi-structured interviews. In order to provide an artifact for DDBM innovation, the researchers developed a theory for design and action. The data-driven business model innovation artifact was inductively developed in two design iterations based on the design science paradigm and the design science research framework.