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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.
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.
Considering the historical relationship of subordination from the Global South countries to the Global North countries, this research aims to understand how culture is instrumentalized in the Peruvian political arena looking to achieve Western development standards. By focusing on the Commission of Culture and Heritage of the Congress of Peru, period 2016-2017, as its case study, it will do a discourse analysis to try to find the spheres in which developmental ideology is produced and reproduced. Those findings will be later discussed under decolonial thought and dependency theories.
In past digital health interventions, an issue has been that participants drop out over time which is referred to as the "law of attrition" (Eysenbach, 2005). Based on this, the study proposes that though initially, participants respond to the intervention, there is a hypothesized second diminishing effect of an intervention. However, the study suggests that on top, there is a third effect. Independent of the individual notification or nudge, people could build the knowledge, skills and practice needed to independently engage in the behavior themselves (schraefel and Hekler, 2020). Using behavioral theory and inspired by prior animal computational models of behavior, the thesis proposes a dynamical computational model to allow for a separation of intervention and internalization. It is targeted towards the specific case of the HeartSteps intervention that could not explain a diminishing immediate effect of the intervention, second hypothesized effect, while a person’s overall steps remained constant, third effect (Klasnja et al., 2019). The study incorporates a habituation mechanism from learning theory that can account for the immediate diminishing effect. At the same time, a reinforcement mechanism allows participants to internalize the message and engage in behavior independently. The simulation shows the importance of a participant’s responsiveness to the intervention and a sufficient recovery period after each notification. To estimate the model, the study uses data from the HeartSteps intervention (Klasnja et al., 2019; Liao et al., 2020), a just-in-time adaptive intervention that sent two to five walking suggestions per day. The study runs a Bayesian estimation with Stan in R. Additional validation tests are needed to estimate the accuracy of the model for different individuals. It could however serve as a template for future just-intime adaptive interventions due to its generic structure. In addition, this model is of high practical relevance as its derived dynamics can be used to improve future walking suggestions and ultimately optimize notification-based digital health interventions.
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.
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.
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.
This study examines the perspective of German venture capitalists on the success factors of digital startups and follows an explorative three-dimensional research approach that integrates the micro perspective on the entrepreneurial personality, the macro perspective on the entrepreneurial context, and the meso perspective on the business model. Thus, the study operates in a very young field of entrepreneurship research. One of the purposes of this research project is to work out the significance of particular characteristics at each research level for the economic success of a digital start-up from the perspective of German venture capitalists. Furthermore, the study sheds light on the view of this group of experts on the relevance of an entire group of characteristics. To answer the central research questions, qualitative research methods and a mixed-methods approach are pursued, with quantitative and qualitative primary data being collected by means of theory-driven semi-structured expert interviews. As a result, a total of four articles have been produced: three articles that focus on presenting the results of qualitative research from only one of the three aforementioned research perspectives each, and a fourth article that combines methods from qualitative and quantitative research and derives an integrated, evidence-based working model of the economic success of digital startups from the perspective of German venture capital (VC) investors.
This dissertation contributes to research on generating actionable knowledge for coastal governance to enhance the resilience of coastal social-ecological systems (SES) to climate change. It does this by providing theoretical, methodological and empirical insights on three research questions (RQs). These are: (1) what is a more actionable concept for applying the concept of resilience in coastal governance?; (2) what methods and approaches are suitable to generate actionable knowledge for coastal governance?; (3) what obstacles to knowledge co-production exist for early-career researchers (ECRs) and how can they be overcome? The RQs are addressed in five publications. For answering RQ1, the dissertation applies a research synthesis to bring together common themes and challenges documented in resilience, climate change and environmental governance literature. For answering RQ2, different methods and approaches for generating actionable knowledge are proposed and tested using a case-study in the SES of Algoa Bay, South Africa. These include (i) the analysis of stakeholder agency; (ii) the application of a stakeholder analysis; and (iii) the combination of a capital approach framework, and fuzzy cognitive mapping. Finally, for answering RQ3, the thesis provides a perspective on the obstacles that especially ECRs face, and actions that are needed to create the conditions under which knowledge co-production processes can be successful. This is done by applying a multi-method approach combining an online survey and workshop targeted at ECRs in the marine sciences. Key findings suggest that system and transformative knowledge are particularly important when applying the concept of resilience in coastal governance to generate actionable knowledge. The different methods and approaches that are proposed and tested contribute to generating both system and transformative knowledge. Firstly, they provide an overview of the capacities of different stakeholders to act, shed light on current collaboration and knowledge exchange, and enable the identification of different governance processes for coastal governance and climate change adaptation (system knowledge). Secondly, results have implications for how to improve knowledge exchange and identify leverage points that can enhance overall governance performance, thus providing recommendations on actions and processes that can enhance climate resilience in the case-study area (transformative knowledge). It is also highlighted how knowledge co-production can contribute to generating system and transformative knowledge together with stakeholders, and what actions are needed to build the capacities to translate knowledge into action. Additionally, the findings of this dissertation put forward actions that are needed at different organisational levels of the academic system to facilitate knowledge co-production processes with stakeholders involved in coastal governance. The results of this dissertation have implications for stakeholders and decision-making in the case-study area, as well as for environmental governance, climate change adaptation and broader sustainability research. Implications for stakeholders include recommendations for implementing formal commitments to share climate information across levels and sectors, establishing the role of information providers in the municipality, and reinforcing human capital within the local municipality in Algoa Bay. Findings also suggest the need for a more integrated approach to climate change adaptation in coastal planning and management frameworks. It also suggests that the conservation of environmental assets presents an important bottleneck for resilience management and needs to be further prioritised within decision-making. Implications for research include the applicability of methods beyond the context of this dissertation; a more actionable concept for approaching resilience in (coastal) governance systems; and a more critical reflection on how transformative research is conducted, and what academic foundation is needed so that it can fulfil its societal goal.
The significance of selecting suitable talent
A company’s success is significantly influenced by the professionalism and quality of decision-making, especially selecting decisions to hire suitable talent. The term “talent” can be taken to mean as someone who has talent (talent as the sum of one’s abilities) and someone who is a talent. Leadership talent makes a difference in organizational success, has the potential to succeed as a leader, and thus will
hold corresponding pivotal positions. In this book, we focus on the selection and acquisition of leadership talent, since such talent is more difficult to find in the market and, at the same time, more challenging to select. Selecting these talented individuals is one of the most critical components of effective organizations. Hardly any other corporate decision has such significant effects on corporate success as talent selection. Recruiting and personnel selection are also the first steps in promoting capability building and creating successful teams. For example, Warren Buffet, renowned for his investing prowess, says, “I have only two jobs. One is to attract and keep outstanding managers to run our various operations”. This highlights the need for an effective and efficient personnel selection process and to improve the diagnostic performance of such procedures. In addition, the increasing diversity of applicants, global competitiveness, and the lack of qualified personnel in specific labor and job markets also increase the importance of high-quality personnel selection processes.