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The emergence of sustainability as a guiding principle for tourism development came along with needs to introduce instruments that can monitor the actual impacts of tourism. Sustainability assessments in tourism (SAT) have gained popularity in recent years with a range of measurement schemes being introduced for national and subnational tourism destinations. With the help of sustainability indicators these schemes intend to guide decision-makers in making better evidence-informed decisions and to improve the overall sustainability performance of tourism. With this dissertation, the author aims to contribute to a deeper understanding of the implementation and performance of sustainability assessments, by linking transformative needs of tourism with necessary assessment approaches that can serve as effective instruments for a shift towards a more sustainable tourism development. Thus, the research is part of recent efforts to establish profound and effective measurement approaches for sustainable tourism. The author employs a mixed-methods approach combining qualitative, quantitative, set-theoretic, and review methods, with the aim of maximising the validity of results. First, he explores the general progress and current state of research on sustainability assessments in tourism, with the intention to identify patterns, key elements and research gaps within assessment approaches This is followed by subsequent detailed analyses that examine specific environmental and socio-economic sustainability issues with the aim of providing conceptual, methodological and empirical solutions for assessing them in detail. The dissertation highlights that concrete assessment tools are needed for evidence-informed decision-making and the establishment of effective actions in destination management. The findings indicate that assessments will be more successful in terms of serving as tools for decision-making, if they tackle main drivers of change and encourage management or policymakers to take decisions that affect multiple sustainability issues. It also reviews different concepts and accounting principles and rises awareness of a cautious selection of methods and measurement approaches, as this may affect overall results. The thesis empirically evaluates and applies different measurement approaches in specific destinations, with the help of quantitative and qualitative data collection methodologies. In general, my thesis provides further clarification about key environmental and socio-economic measurement methodologies, which supports ongoing debates about sustainability impacts of tourism. Thus, the research contributes to knowledge, frameworks, methodologies and practical application for tourism governance and tourism sustainability science.
Artificial intelligence, most prominently in the form of machine learning, is shaping up to be one of the most transformational technologies of the 21st century. Auditors are among the professions forecasted to be the most affected by artificial intelligence, as the profession encompasses many highly structured and repetitive tasks. Automating such tasks would naturally increase the efficiency of financial statement audits. By allowing auditors to focus on higher value-added tasks, and the capability to analyze large volumes of data at a fracture of the time a human would need, artificial intelligence would also benefit the effectiveness of auditing. Despite these benefits, to this day, the actual adoption of artificial intelligence in the audit domain remains rather limited. The audit profession is highly regulated and has to consider requirements regarding, e.g. the application of professional standards, codes of conduct, and data protection obligations. Hence, the question arises of how audit firms can be supported in their efforts to adopt artificial intelligence and how machine learning systems can be designed to comply with the specific demands of the audit domain. The goal of this dissertation is to better understand the adoption of artificial intelligence in the audit domain and to actively support the adoption of artificial intelligence in auditing based on this understanding. To this end, we employ a mixture of research methods. On the one hand, the research presented here adopts a qualitative approach, examining the adoption of artificial intelligence and other advanced analytical technologies of the audit domain through taxonomy development and grounded theory. The findings of these studies inspire the second stream of work within this dissertation, which adopts a quantitative and design-oriented approach: It focuses on using machine learning to extract information from invoices for tests of details. Tests of details are essential substantive audit procedures used in nearly every audit. This dissertation proposes a new machine learning model architecture for information extraction from invoices, compares different machine learning models, and proposes design principles for machine learning pipelines for an audit application addressing the test of details through action design research.
Since its establishment, the African Union (AU) has assumed an important role in matters of peace and security on the continent. This doctoral dissertation is dedicated to its conflict and crisis interventions and seeks to identify as well as subsequently explain the broader patterns that have emerged. The dissertation posits that neither the AU's regime-serving roots, which emphasize the primacy of incumbents' parochial interests, nor the AU's problem-solving commitment, which emphasizes the pursuit of its declared organizational mission, can convincingly explain these patterns on their own. Instead, we should understand the AU as being driven by two different logics of cooperation at the same time: a problem-solving and a regime-serving logic. Across its three constitutive articles, the dissertation makes empirical as well as theoretical contributions to the existing literature. Empirically, it offers a broad and systematic analysis of AU interventions over time, across different intervention types, and without bias towards high-profile cases. The novel dataset, on which the dissertation builds, constitutes the hitherto most comprehensive effort to capture the AU's responses to crises and conflicts. Theoretically, the dissertation develops a set of testable theory-driven expectations based on the notion of two different logics of cooperation. While identifiable in the literature on the AU and linking to broader existing debates on international cooperation, the dissertation breaks ground by clearly outlining the implications of each logic and bringing them together under a single theoretical framework. Jointly, the articles provided strong evidence that the AU is indeed driven by both a problem-solving and a regime-serving logic of cooperation, and that this serves as the foundation for explaining the AU's broader intervention patterns. This contributes not only to a better understanding of AU interventions but also has a chance to enrich other important debates, including the debates on African regionalism, comparative regionalism, and multilateral interventions.
Environmental governance beyond borders: Governing telecoupled systems towards sustainability
(2023)
This doctoral dissertation analyses the environmental governance of long-distance social-ecological interactions in telecoupled systems in two issue domains: global commodity chains and infrastructure projects as part of China’s Belt and Road Initiative (BRI). Although both domains involve different governance actors, institutions and processes, they both concern the question of how the involved actors develop governance structures and institutional responses to telecoupling. This dissertation aims to contribute to a deeper understanding of how to govern environmental problems that are associated with global flows. Since many multilateral environmental governance initiatives have not yet produced the desired solutions to global problems, particular attention is directed at unilateral state-led governance approaches. This dissertation addresses the questions of (1) how to achieve a spatial fit between the scale of telecoupled systems and the scale of governance institutions, (2) how governance actors exercise agency in governing telecoupled systems, and (3) how state actors can govern the domestic and foreign environmental effects of telecoupled flows. The results show that creating a spatial fit in the governance of global commodity flows is challenging because boundary and resolution mismatches can emerge. Boundary mismatches denote situations where social-ecological problems transcend established jurisdictional boundaries, whereas resolution mismatches refer to governance institutions that have too coarse a spatial resolution to allow them to address the specific aspects of social-ecological problems effectively. No single governance institution is likely to avoid all mismatches, which highlights the need to align multiple governance approaches to effectively govern telecoupled systems.
The Sustainable Development Goals (SDGs) recognize the importance of the inextricable link between social and ecological systems and human quality of life (QoL) and biodiversity. Therefore, understanding the feedback and interactions between biodiversity, nature’s contributions to people (NCP), and QoL plays a central role in advancing toward sustainability. In this context, the social-ecological systems (SES) approach has advanced on the subject, particularly in recent decades; however, much remains to be done to comprehensively understand these relationships and interactions, especially at local decision-making scales. In this thesis, through the lenses of the SES approach, the researcher investigates connections between biodiversity, NCP, and QoL in a tropical dry forest (TDF) on the Western coast of Mexico. This place is one of the best-known Neotropical TDF and has been the focus of SES research in the past 20 years, making it an excellent case study for exploring these connections. First, to approach the need for dialogue among different global and local scales and between global and local frameworks, the thesis identifies five key components of the SES dynamics-(1) ecological supply, (2) co-production of NCP, (3) management, (4) demand, and (5) benefits - and three local decision-making scales of analysis: individual plot, smallholder, and land tenure or governance units. A literature review was performed on the social-ecological indicators for the last 11 years in the Chamela-Cuixmala region to operationalize this framework. Second, this thesis uses social-ecological information to identify social-ecological systems units (SESU) spatially explicitly. A methodology was provided to spatially identify the components of social-ecological systems that environmental conditions and management practices have shaped at three previously stated relevant decision-making scales: plots owned by individuals, plot owners, and governance units. To do so, the research group identified and characterized: (1) ecological clusters (EC), (2) social-management clusters (SC), and (3) SESU in a TDF in western Mexico. The findings suggested that decision-makers (ejidatarios, i.e., type of ownership (related to agrarian reform), that in most cases the land allocated is small-smallholders) are bounded by the topographical characteristics and the public policies that determine communal (or private) governance and the number of resources available to them. Finally, the thesis examines the self-perceived QoL across the different SESU, finding 48 QoL items, which were grouped into six categories: 1) social capital, 2) economic capital, 3) agency, 4) nature, 5) peasant non-work activities, and 6) government and services; and two additional dimensions referred to obstacles and enablers of QoL. The researchers found that the more land cover transformation, the more enablers, and obstacles of QoL are identified; emphasis was put on economic capital to achieve QoL. As management is intensified and governance fosters individualism across SES, the higher the Current Welfare Index, and the lower the self-perceived material and non-material satisfaction.
The ethical apparatus: The material-discursive shaping of ethics, autonomy, and the driverless car
(2023)
This research argues that the emergent driverless car, as a kind of autonomous vehicle, is a Foucault-ian "ethical apparatus", working as an epistemic device to materially embody and enable discursive power by generating notions of "autonomy" and "ethical decision-making". The ethical implications of AI, algorithmic, and autonomous technologies are topics of current regulatory and academic concern. This concern relates to the lack of meaningful oversight of black boxes inside AI systems, liabilities for manufacturers, and inadequate frameworks to hold AI-based socio-technical systems to account. One recent artefact, the driverless car, has taken on these concerns quite literally in the shaping of a niche discourse of the "ethics of autonomous driving". Ambitions to produce a fully autonomous vehicle based on AI technologies are constrained by speculative concerns that its decision-making in unexpected accident situations cannot be assumed to protect humans. "The ethics of autonomous driving" evaluates proposals to build "ethical machines" by examining the relationship between structures of human values and moral decision-making, and how they comport to computational architectures for decision-making. This is the first case this work takes up, chiefly organised around an analysis of a thought experiment, the Trolley Problem, and the online game, Moral Machine, that crowdsourced values to suggest approaches to an "ethics of autonomous driving". Rather than evaluate the feasibility or appropriateness of these two approaches, this work attends to the more critical issue that ethics is being proposed in terms of technologies turning on the logics of risk, speculation, and probabilistic correlations that are fundamental to how machine learning makes decisions. The concern in this work is less a normative framework or approach for a better or more appropriate ethics of autonomous driving. Rather, this work argues that what we understand as "the ethical" is being transformed when architected by, through, and for Artificial Intelligence / autonomous technologies to become their own regulators. Hence the production of autonomous driving necessitates computational infrastructures that are creating a world legible to and for the navigation of a driverless car. The author argues that this is fostering computational governance that has implications for human bodies and social relations, chiefly that conventional approaches to regulation and accountability attend to human values and decision-making rather than computational ones. A second case that this research examines is that of driverless car crashes, to examine how "autonomous" driving requires substantial embodied human knowledge and micro-work. Taken together, these two cases make an argument for how myriad practices of knowledge-production are translating the human world into something legible to the navigational needs of the car, producing changes in the human world through the actions of the car on that basis, and advancing notions of "autonomy". This work concludes with arguments for a critical reconceptualisation of ethics and ethical decision-making in AI / autonomous systems.
Companies are invited to contribute to the United Nations' 17 Sustainable Development Goals (SDGs) and sustainability management accounting (SMA) has an important role to play in achieving them. However, if companies are to address the SDGs and linkages beyond organizational boundaries, SMA needs a broader scope than is conventionally assumed. Therefore, the author advances a multi-level framework that addresses context, action-formation, and transformative contributions (CAT) in the following directions: first, an innovative systematic method that allows screening company-related SDGs and assessing corporate contributions to selected SDGs is introduced; second, management control systems are integrated to support managers in guiding employee behavior to make contributions to the SDGs; and, third, self-reinforcing mechanisms of the path-dependence theory are incorporated to serve as a guide to identifying barriers to individuals and groups becoming involved in SMA. This advanced CAT framework contributes to corporate practice and research by providing a multilevel framework that offers concrete management guidance for SMA to address the SDGs. It also facilitates analysis of both enabling and inhibiting factors at the organizational level. The advanced CAT framework has several implications for SMA: it promotes backcasting from the SDGs for benchmarking purposes, integrates different social, environmental, and economic issues, facilitates future-oriented action and transformation planning, addresses different layers such as the company as well as individuals and groups within it and enables to identify barriers hindering individuals and groups from becoming involved in SMA.
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
Tropical ecosystems are critical for biodiversity conservation and local people’s livelihood sustenance. However, these ecosystems are under high pressure from land-use and land cover (LULC) change, which is further projected to intensify and increase rapidly, thereby affecting biodiversity and the provisioning of vital ecosystem services (ES). It is thus important to understand how LULC might change in the future and how such changes could affect biodiversity and ES provisioning in a given landscape of tropical ecosystems. Scenario planning has become an increasingly popular tool and technique to produce narrative scenarios of the future landscape change. Thus, quantifying changes under different land-use scenarios could be a means to elucidate the synergies and trade-offs within the scenarios. In this dissertation, the author examines the future of biodiversity and ES provisioning for different plausible land-use scenarios in southwestern Ethiopia. First, he translates four future plausible narrative social-ecological land-use scenarios ("Gain over grain", "Coffee and conservation", "Mining green gold" and "Food first") developed for southwestern Ethiopia by participatory scenario planning into spatially explicit LULC scenario maps. Results showed distinct LULC changes under each scenario. Second, the author investigates the impact of these land-use scenarios on biodiversity by specifically modelling woody plant species richness in farmland and forest. Both indicators of human disturbance and environmental conditions were used. Third, he also investigates the effect of these land-use scenarios on woody plant-based ES provisioning by combining woody plant species with household surveys on how woody plants were used by the local community. He models and predicts the current and future availability of woody plant-based ES under the four scenarios of landscape change. Overall, the findings of this dissertation show the importance of integrating future land-use mapping with participatory, narrative-based scenarios to assess the social-ecological outcomes of alternative futures. The spatially explicit maps of LULC change, biodiversity and ES (at different scales) could be used as a valuable input to support stakeholders and decision-makers to weigh the advantages and disadvantages of different development trajectories on ecosystems and human well-being and to avoid or minimize future undesirable consequences. To this end, apart from the benefits of coffee production under "Mining green gold" and crop production under "Food first" scenarios, the findings under these scenarios of large-scale agricultural intensification point to a potentially high loss of biodiversity and ES. These two scenarios could have a negative long-term impact on ecosystems and human well-being. Finally, the "Coffee and conservation" scenario, which involves the creation of a new biosphere reserve, appears to be the most sustainable scenario. This scenario could result in a sustainably managed, diversified landscape which could make major contributions to biodiversity conservation and human well-being in the region and beyond.
This thesis deals with sustainability in African Higher Education Institutions (HEIs) and the influence of language in achieving sustainable development. Several authors highlight the existing imbalance of sustainability research in higher education, with most publications focusing on the so-called Global North. Little is known about sustainability in the so-called Global South, and in African educational institutions in particular. The first article of this thesis investigated existing sustainability activities in African HEIs. Rather than focusing on the shortcomings, the paper took a positive stance, opposing the predominant language of deficits in research on Africa. In the Delphi study conducted, 32 experts from 29 HEIs in 16 African countries described the sustainability activities they are engaging in. Experts provided information about their experiences in their respective HEI, while language and culture emerged as areas in need of further research. The second article therefore focused on the relationship between language and education for sustainable development in African educational institutions, and systematically reviewed scholarly literature regarding this connection. Authors of the reviewed 33 papers approached this connection mainly on a theoretical and philosophical level, focusing on education and Africa as a whole rather than specified forms of education in specific countries. The third article examined the views of Tanzanian higher education students and graduates regarding language and sustainability. Participants explained how they integrate sustainability and the Sustainable Development Goals (SDGs) into their research and how they approach translations in the process. In the ensuing interviews, participants estimated that only a fraction of people outside of academia are aware of sustainability and the SDGs, rendering the achievement of target 4.7 unlikely. This thesis therefore contributes to a better understanding of the current challenges in implementing sustainability and the SDGs in African educational institutions. It highlights the need to integrate (local) African languages in order for sustainability activities as well as the SDGs to be successful.
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.