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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. Yet, sustainability assessments have hardly led to changes in organisational or management structures in tourism in the last years.
With this dissertation I aim 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.
I employ a mixed-methods approach combining qualitative, quantitative, set-theoretic, and review methods, with the aim of maximising the validity of results. First, I explore 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.
My 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.
Motivation: 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.
Research Approach: 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.
Contribution: This dissertation presents several contributions to the research on the adoption of artificial intelligence in auditing. To form an initial understanding of the problem environment around the application of artificial intelligence to auditing, we developed a taxonomy. The taxonomy integrates the audit and technology perspective in a structured manner and supports the description of use cases in the audit domain. The dissertation further presents a process theory that illustrates how audit firms adopt artificial intelligence and other advanced data analytics technologies. The study uses a previously unused theoretical perspective, which allows for contextualizing known technology adoption factors in the audit domain. Based on the understanding of the problem environment obtained through the taxonomy and process theory, we engaged in developing artifacts and methods for applying information extraction from invoices. Here, we offer the first contribution by developing a novel graph-based neural network architecture and showing its ability to extract information accurately from invoice data sets with a significant layout variance. The second contribution deepens the understanding of the effects of layout distributions on the generalization ability of neural networks: We compared different model types and disaggregated the evaluation into in-sample and out-of- sample layouts. We show that the gap in accuracy between in- and out-of-sample layouts varies across models. To arrive at these results, we developed an end-to-end machine learning pipeline. As part of the last contribution of this dissertation, we automatically orchestrated this pipeline which serves as a structured approach to evaluate and deploy machine learning models for information extraction from invoices. We designed it such that new models from the continuously flowing stream of research are easily integrated. By reflecting on the genesis of the pipeline and the design choices that guided its emergence, we also propose a set of design principles for information extraction pipelines in audit tools.
Limitations: The results presented in this dissertation must be seen in the light of some limitations. First, we obtained the taxonomy’s dimensions and characteristics to describe use cases from the scientific literature. Use cases only identified in practice might not be characterized in their entirety by the taxonomy. The presented process theory is grounded in data obtained from expert interviews. Hence, the sampling of interview partners can affect its generalizability. For instance, most of our interview partners are located in Germany and take on roles in the upper management of their respective organizations. The results presented in the design-oriented studies are limited by the characteristics of the available data sets. These characteristics include the languages of the documents, which is primarily English, their quantity, and the recurring vendor layouts. Finally, we conducted the action design-oriented research within a large multinational audit firm. Hence, the requirements for the developed artifact and the proposed design principles might not be transferable to smaller firms.
Future Research: Several threads are laid out in the presented body of work that may be picked up in future research endeavors. The taxonomy could be updated to the most recent developments in artificial intelligence, such as generative and conversational systems. In the process theory, the nature of the relationship between the contextual factors and the adoption process could be explored in more detail. Concerning information extraction for the test of details, future research could explore how the extraction results could be parsed into standardized formats or how they could be internally validated. Larger audit firms have clients from a variety of countries, which begs the question of whether language-specific models or multilingual models are better. In this context, the need for labeled training data poses a challenge for adapting models to different languages. Therefore, future inquiries could explore how the utilization of training paradigms such as active learning to reduce the need for labeled training data.
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.
Biodiversity is quickly diminishing across the planet, primarily owing to human pressures. Protected areas are an essential tool for conserving biodiversity in response to increasing human pressures. However, their ecological effectiveness is contested and their capacity to resist human pressures differ. This dissertation aimed to assess the ecological effectiveness of different protection levels (from strict to less strictly protected: national park, game reserve, forest reserve, game-controlled area, and unprotected areas) in biodiversity (both mega diverse butterflies and mammals), maintaining habitat connectivity, and reducing anthropogenic threats at the wider landscape in the Katavi-Rukwa Ecosystem of southwestern Tanzania. To achieve this overarching goal, I employed an interdisciplinary approach.
First, I analyzed butterfly diversity and community composition patterns across protection levels in the Katavi-Rukwa Ecosystem. I found that species richness and abundance were highest in the game reserves and game-controlled areas, intermediate in the forest reserves, national park and unprotected areas. Species composition differed significantly among protection levels. Landscape heterogeneity, forest cover, and primary productivity influenced species composition. Land-use, burned areas, forest cover, and primary productivity explained the richness of species and functional traits. Game reserves hosted most indicator species.
Second, I modelled the spatial distribution of six large mammal target species (buffalo Syncerus caffer, elephant Loxodonta africana, giraffe Giraffa camelopardalis, hartebeest Alcelaphus buselaphus, topi Damaliscus korrigum, and zebra Equus burchellii) across environmental and protection gradients in the Katavi-Rukwa Ecosystem. Based on species-specific density surface models, I found relatively consistent effects of protection level and land-use variables on the spatial distribution of the target mammal species: relative densities were highest in the national park and game reserves, intermediate in forest reserves and game-controlled areas and lowest in un-protected areas. Beyond species-specific environmental predictors for relative densities, our results highlight consistent negative associations between relative densities of the target species and distance to cropland and avoidance of areas in proximity to houses.
Third, I examined temporal changes in land-use, population densities and distribution of six large mammal target species across protection levels between 1991 and 2018. During the surveyed period, cropland increased from 3.4 % to 9.6 % on unprotected land and from ≤0.05 % to <1 % on protected land. Wildlife densities of most, but not all target species declined across the entire landscape, yet the onset of the observed wildlife declines occurred several years before the onset of cropland expansion. Across protection levels, wildlife densities occurred at much greater densities in the national park and game reserves and lowest in the forest reserves, game-controlled areas and unprotected areas. Based on logistic regression models, target species preferred the national park over less strictly protection levels and areas distant to cropland. Because these analyses do not support a direct relationship between the timing of land-use change and wildlife population dynamics, other factors may account for the apparent ecosystem-wide decline in wildlife.
Fourth, I quantified land-use changes, modelled habitat suitability and connectivity of elephant over time across a large protected area network in southwestern Tanzania. Based on analyses of remotely-sensed data, cropland increased from 7% in 2000 to 13% in 2019, with an average expansion of 634 km2 per year. Based on ensemble models, distance from cropland influenced survey-specific habitat suitability for elephant the most. Despite cropland expansion, the locations of the modelled elephant corridors (n=10) remained similar throughout the survey period. According to ecological knowledge, nine of the modelled corridors were active, whereas one modelled corridor had been inactive since the 1970s. Based on circuit theory, I prioritize three corridors for protected area connectivity. Key indicators of corridor quality varied over time, whereas elephant movement through some corridors appears to have increased over time.
Overall, this dissertation underpins differences in ecological effectiveness of protected areas within one ecosystem. It highlights the need to utilize a landscape conservation approach to guide effective conservation across the entire protection gradient. It also suggests the need to enforcing land use plans and having alternative and sustainable forms for generating income from the land without impairing wildlife habitat.
Contemporary society is shaped by the idea that time is, above all, a scarce economic resource that must be used efficiently – “time is money” not to be wasted. Increasingly, however, scientific findings suggest that such a way of perceiving of time seems a major cause of the current global climate and sustainability crisis. So far, this research has often focused on mobility, energy consumption, or the structural conditions of the social organisation of time. Considerably less work has been carried out in relation to the role of individual time-related needs regarding unsustainable consumption behaviour, although consumer research has been addressing needs-oriented approaches to sustainable consumption for a long time. Environmental and Sustainability Education (ESE) is considered an essential strategy to achieve the global sustainability goals of Agenda 2030. Internationally, as well as on a national level, ESE is increasingly mainstreamed in educational curricula and practice, including in Germany. Given the relation between time, needs and sustainability, it appears valuable to inquire into this field from the perspective of ESE – where time as a resource for sustainability has received comparatively little attention so far. The core research interest of this cumulative dissertation is therefore the question of how the connection between time, our needs and sustainability can be conveyed through pedagogical approaches. The inquiry used an exploratory, qualitative research design to address this question. In a first step, the concept of sustainability-related time use competence was developed. This then served as a guiding concept for the understanding of time used in this work and as the overall objective for the educational intervention developed and piloted as part of the research. Next, a content analysis of German curricula was conducted with the aim of determining whether and to what extent these address the relation between time and sustainability. The results show curricula contain only a few starting points that encourage a connection between time and sustainability in school lessons. The study further indicates that an understanding of time as a scarce resource to be used efficiently has prevailed in school contexts so far. Accordingly, pedagogical approaches to time often focus heavily on time management. The next step involved developing and piloting a time use competence curriculum in cooperation with three partner schools, using an Action Research Approach. This intervention followed the pedagogical approach of Self-Inquiry Based Learning (SIBL) seeking to sensitise learners to the relation between individual needs and consumer behaviour. During implementation, which lasted one semester, students logged their time, were encouraged to reflect on their personal needs, and subsequently implement individual change projects related to time use. This was embedded in continuous reflective individual and group exercises. The results strengthen the hypothesis that there is a relation between time use and sustainability. Furthermore, the pedagogical approach of SIBL has proven suitable to enable students to reflect on their time use and to raise their awareness of the role of individual needs. Participants reported that changes in time use did indeed increase their personal well-being. This, according to existing evidence from sustainability science, has been found to potentially lead to more sustainable behaviour. At the same time, previous research found that behavioural changes that lead to an increase in well-being do not automatically lead to more sustainable consumption behaviour. Rather, personal attitudes and motivation regarding sustainability are important. This suggests that future ESE interventions aiming at changes in time use should always also contain sufficient opportunities for reflection of values and motives. A third empirical study was carried out, inquiring into students’ time use during the eriod of COVID-19-induced school closures, using a Grounded Theory Approach. Since the pandemic disrupted young peoples’ routines drastically, the research focused on which kinds of learning experiences students made during this time and which insights can be derived for ESE. The results of the semi-structured interviews with 69 participants show first that the narrative of students’ learning loss, which is predominant in the current educational science, policy, and media discussion, falls short. Instead, a variety of learning experiences are revealed, such as learning one’s own learning and everyday rhythms or creatively adapting consumption habits to the new situation of “lockdown”. Overall, a key finding of this work is that students are currently unable to adequately realise their time-related needs. In view of the findings from research on time and sustainability, one recommendation is therefore that everyday school life could give students more space to organise their time according to their needs. This might be done through pedagogical measures in the classroom, but would also require a stronger institutional anchoring, for example, within the framework of the Whole Institution Approach to Sustainability (WIA), to bring about lasting changes. Furthermore, it would be advisable to give the topic of time in connection with sustainability more space in curricula and in teacher training. This gives rise to future research needs, such as the need to explore how time use competence can be included into everyday pedagogical practice, for instance, by adapting the SIBL approach piloted in a school setting here. It would also call for longitudinal research designs, and it would be of interest to research how time use competence might be incorporated into school development processes. Given the ongoing debate about the impact of the COVID-19 pandemic on schools and education in general, the findings of the research can stimulate both further research and future ESE practice. The experiences during the pandemic have shown that schools and all actors involved including students and teachers, are so far insufficiently prepared to handle crises. Here, the approach to time use competence piloted in this work can offer valuable stimulations for ESE research and practice. This is especially true since it is compatible with existing approaches to key competencies for sustainability by seeking to complement them with a stronger focus on individual, needs-oriented time shaping.
To respond to the challenges of the Anthropocene, scholars from various disciplines increasingly emphasize that a mere outer transformation is insufficient and that we also need an inner transformation that addresses deep leverage points. Yet, the open questions are how the inner and outer dimensions relate to each other
and how inner transformation might lead to outer transformation. How we attempt to answer these questions is determined by our dominant paradigm. Paradigms define how we understand and shape the world, and thus, they define how we conceptualize challenges, such as inner and outer transformation. Various authors argue that the dominant paradigm, which is characterized by reductionism, empiricism, dualism, and determinism, might be a root cause for insufficiently addressing sustainability challenges. As an alternative, many argue for a relational paradigm, which understands complex phenomena in terms of constitutive processes and relations. A relational paradigm might offer possibilities to reconceptualize inner and outer transformation in the Anthropocene and might shed new light on how to integrate both in sustainability science. Yet, it is still being determined how a relational paradigm can contribute to the understanding of inner and outer transformations towards sustainability in the Anthropocene. Therefore, this dissertation's overarching scope is to contribute to systems change towards a more social-ecological future by generating insights into and exploring possibilities of a relational paradigm for inner and outer transformation in the Anthropocene. This thesis is divided into three sub-questions. The first research question aims to contribute to transformation research by increasing the theoretical understanding of a relational paradigm. The second research question aims to contribute to transformative research by developing a transformative educational case study grounded in a relational, justice-oriented approach. The third research question aims to contribute to transformation research by analyzing how a relational paradigm might contribute to policies and practices for sustainable lifestyles. The results indicate that inner and outer transformation in the Anthropocene can be reconceptualized as paradigm-ing relationality in the Ecocene. "Paradigm-ing" as an active verb, reconceptualizes inner and outer transformation into ontologies, epistemologies, ethics, and socialecological realities that are ongoing, nonhierarchical, nonlinear, dynamic, co-creative processes of intra-action. The Ecocene decenters the human and attends to what we might be able to intra-actand become-with. These insights can offer unexplored perspectives to address sustainability challenges and increase our capacities to respond in novel ways.
This dissertation comprises three stand-alone research papers dealing with different aspects of labor market characteristics: bonus payments and the gender pay gap; second job holding; and workers un-covered by collective bargaining. The first paper ``Non-base compensation and the gender pay gap'' investigates whether and how non-base compensation in the form of bonus payments, overtime pay, and shift premia contributes to the gender pay gap.
Unionization along with collective bargaining coverage has been on the decline on recent decades. Using German administrative data, the second paper examines which workers in firms covered by col-lective bargaining agreements still individually benefit from these union agreements, which workers are not covered anymore and what this means for their wages.
The third paper studies the development and persistence of second job holding in Germany after a legislative change in the year 2003 allowed the extensive dispensation of marginal second jobs from taxes and social security contributions. Using data from the German Socio-Economic Panel I document a substantial increase in second job holding in Germany since 2003 and find in a dynamic panel model setting that there is true state dependence in second job holding.
The requirements for the design of information and assistance systems in labour-intensive processes are interdisciplinary and have not yet been sufficiently addressed in research. This dissertation analyses, evaluates and describes possibilities for increasing the effectiveness and efficiency of labour-intensive processes through design-optimised socio-technical systems. The work thus contributes to further developing information and assistance systems for industrial applications and use in healthcare. The central dimensions of people, activity, context and technology are the focus of the scientific investigations following the Design Science Research paradigm. Design principles derived from this, a corresponding taxonomy, and a conceptual reference model for the design of socio-technical systems are the results of this dissertation.
This 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 cumulative dissertation "Corporate Social Responsibility (CSR) Communication: Four empirical studies on the German banking industry" presents how commercial banks in Germany communicate their ambitions and commitment regarding corporate responsibility - i.e., CSR. The results of the first article show that the quality of mandatory non-financial reporting needs to be improved and that certain characteristics (e.g., previous reporting experience, reporting format and standard) have a positive influence on reporting quality. The second article shows that the CSR reporting scope on bank websites also has room for improvement and that various banking characteristics such as size, capital market orientation, media visibility or public ownership have an influence on communication. The third article illustrates that credit institutions in Germany are increasingly using social media for CSR communication, but that CSR communication strategies differ (Facebook vs. Twitter). The fourth article discusses CSR communication using advertisements and shows that the conceptual design of advertisements should be in line with the credit institution's business model and is therefore beneficial.