TY - JOUR A1 - Bleyer, Bernhard A1 - Braun, Irene A1 - Ebner, Richard A1 - Plank, Maria A1 - Riecke, Ramona T1 - Ein Projekt zur Qualifikation von Besuchsdiensten in stationären Altenhilfeeinrichtungen: Begegnungen gegen die Einsamkeit JF - Informationsdienst Altersfragen N2 - Das Bildungskonzept „Ins Altenheim gehen – eine lohnende Sache! Fortbildung für ehrenamtliche Besuchsdienste im Alten- und Pflegeheim“ verpflichtet sich, die Idee der Teilhabe sowohl für Ehrenamtliche als auch für hilfebedürftige Menschen im Alter in die Tat umzusetzen. Das aus fünf Modulen bestehende Curriculum, das als Kooperationsverbund zwischen Kirche, Wohlfahrtsverband, Universität, Altenhilfeeinrichtung und Ehrenamt in diesem Zuschnitt ein Pilotprojekt darstellte, befähigt Ehrenamtliche mit speziellen Themen der stationären Versorgungsform (z.B. Symptome der Demenz, Versicherungsfragen bei Ausflügen, praktischer Umgang mit Pflegebetten und Hilfsgeräten) umgehen zu lernen, damit den hilfebedürftigen Menschen ein Mehr an gesellschaftlichem Leben ermöglicht wird. N2 - The educational concept “Going into a retirement home - a worthwhile endeavour! Further training for volunteer visiting services in retirement and nursing homes” is committed to putting the idea of participation into practice for both volunteers and people in need of help in old age. The five-module curriculum, which is a pilot project involving a cooperation between the church, charitable organisation, university, elderly care facility and volunteers, enables volunteers to learn how to deal with special topics relating to inpatient care (e.g. symptoms of dementia, insurance issues for excursions, practical handling of care beds and assistive devices) so that people in need of help can enjoy a more active social life. KW - Einsamkeit KW - Altenhilfeeinrichtung KW - Altenpflege KW - Besuchsdienst KW - Ehrenamt Y1 - 2014 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-14321 VL - 41 (2014) IS - 1 SP - 21 EP - 24 PB - Deutsches Zentrum für Altersfragen CY - Berlin ER - TY - JOUR A1 - Bleyer, Bernhard T1 - Besuchen will gelernt sein JF - neue caritas 114/10 N2 - „Ins Altenheim gehen – eine lohnende Sache!“: Ein Regensburger Projekt von Diözese, Universität und Caritasverband entwirft ein Konzept für ehrenamtliche Besuchsdienste im Alten- und Pflegeheim. KW - Altenheim KW - Altenhilfe KW - Pflege KW - Besuchsdienst KW - Ehrenamt Y1 - 2013 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-14478 VL - 114 (2013) IS - 10 SP - 15 EP - 17 ER - TY - THES A1 - Still, Enid T1 - Affective Roots: Memory, emotions and viscerality within organic agri-food networks in Tamil Nadu, India N2 - For activists I met in Chennai, the capital city of Tamil Nadu in India, organic food and farming was a ‘way of life’. Stemming from my curiosity about this statement and what it meant for different actors in the regional organic agri-food networks, this research explores the interconnected lives and livelihoods of organic farmers and activists in Tamil Nadu. To engage with the social dynamics of these agri-food networks, the research focuses in on the role of the affective, feeling body. The emphasis on affect emerged in the form of memories, emotions and visceral experience, from empirical data collected between 2020 and 2022. And as the thesis demonstrates, affective dimensions, or what moves people, are important because, unlike economic, statistical or structural perspectives, they make visible the ways different actors feel socio-ecological change. Adopting the lens of Feminist Political Ecology and drawing on the fields of historical anthropology and feminist ethics, this thesis highlights: (1) the enduring nature of epistemic injustice within agri-food relations, (2) how social boundaries are built, maintained and remade through affective encounters, circumscribing what I call the ‘affective roots’ of socio-ecological change and (3) how ambiguous affective relations co-constitute organic agri-food networks, shaping anxious environmental subjectivities, that stem from socially mediated encounters with agro-chemicals, the market, the landscape and the other. Deepening our understanding of socio-ecological and agrarian change through empirical inquiry into how people feel matters, I argue, because it sheds light on injustices that are often concealed beneath the clouds of crisis. KW - Affect KW - Organic Agriculture KW - Tamil Nadu KW - Feminist Political Ecology KW - Epistemic injustice Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-15838 ER - TY - THES A1 - Julka, Sahib T1 - Towards Data Efficiency and Controllable Representations for Deep Learning in Resource-Constrained Domains N2 - The deployment of artificial intelligence (AI) in specialised domains such as planetary science and healthcare, as well as in low-resource NLP settings, faces two fundamental challenges: label scarcity and data scarcity. Label scarcity stems from the high cost of expert annotation, the scarcity of domain experts, and the infeasibility of crowdsourcing, particularly in complex tasks requiring specialised knowledge. In parallel, data scarcity stems from the inherent difficulty of acquiring sufficient raw data, whether due to limited observational opportunities, environmental and technical barriers, or stringent privacy constraints. Together, these limitations impede the broader adoption of AI in these fields. Many existing approaches to label efficiency, such as active learning, rely on problem-specific heuristics and often, as a design choice, employ naive uncertainty estimations—typically at the instance level. However, such methods can lead to redundant or suboptimal sample selection by ignoring structural data properties and failing to account for representational diversity. In practice, they often perform no better than random sampling. For data synthesis, generative models face their own set of challenges. Despite their promise for synthetic data generation, these models frequently lack mechanisms to disentangle generative factors at the representation level, limiting their controllability. Additionally, standardised evaluation metrics to assess the quality of disentanglement remain underdeveloped, limiting their practical utility. These limitations highlight the need for advancements in data-efficient machine learning and controllable generative modelling, focusing on domain-specific validity and rigorous evaluation. This thesis contributes to addressing these challenges by proposing tailored solutions in two key directions. First, for data-efficient learning, a deep active learning (DAL) framework is introduced to enhance label efficiency by prioritising the most informative samples for annotation. Unlike traditional per-sample approaches, this framework aggregates uncertainty across larger data segments—such as orbital intervals in planetary science—allowing it to capture contextual variations. This method reduces labelled data requirements by up to 90% in the case of boundary crossing detection at Mercury’s magnetosphere. To further improve sampling diversity, a GAN-based concept drift detection method is integrated into the DAL framework, leveraging uncertainty and diversity together to offer a sampling method that outperforms random sampling. Additionally, foundation models such as the Segment Anything Model (SAM) are employed for zero-shot annotation to generate high-quality pseudo-labels, which are subsequently used to train a domain-specific model via knowledge distillation. This approach significantly enhances data efficiency, reducing the need for annotated samples several times over in the tested scenario of image segmentation for geological mapping. Furthermore, large language models (LLMs) are explored as active annotators for linguistic tasks in low-resource languages, achieving near-baseline performance while reducing annotation costs by up to 40x. Second, the thesis investigates methods to induce controllability in generative models, enabling the production of high-fidelity, controllable synthetic data. Conditional generative adversarial networks (CGANs) and disentangled representation learning techniques (DRL) are explored, particularly in the context of pedestrian trajectory prediction in the mobility domain, where controlled synthesis of diverse motion patterns is critical. Additionally, the work examines existing metrics for evaluating disentanglement and identifies critical limitations in them. A novel metric, the Exclusivity Disentanglement Index (EDI), is proposed as an improved standardised measure. Based on the principle of exclusivity in factor-code relationships, this metric offers advantages over existing alternatives in terms of efficiency and robustness. By advancing data-efficient learning and controllable generation strategies, this thesis aims to bridge the gap between AI’s vast potential and its practical adoption in resource-constrained environments. These contributions pave the way for transformative applications in planetary science, healthcare, and beyond, where label and data scarcity have long been barriers to progress. KW - artificial intelligence KW - deep active learning KW - label scarcity KW - data scarcity Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-16030 ER - TY - THES A1 - Wilhelm, Sebastian T1 - Emergency Detection in Private Households Utilizing Existing Data Sources for Human Activity Event Recognition N2 - In an aging society, the need for efficient emergency detection systems in smart homes is becoming increasingly important. Over 30% of those aged 65 and older experience at least one fall per year, often resulting in the inability to rise without assistance, leading to ‘long lies’ lasting hours or even days. Systems for detecting such emergency events usually rely on wearable sensors or specific installations of ambient sensors, which can be intrusive and complex, hindering acceptance. This thesis proposes a novel approach that utilizes existing digital data sources within the residential infrastructure to detect human activities and identify potential emergencies. A survey identifies 44 potential data sources in private households for recognizing human activity. However, extracting activity information often requires complex preprocessing. In this thesis, methodologies are developed for three of these data sources to highlight practical applications: Smart Power Meters, Smart Water Meters, and Home Weather Stations. It is shown that detecting human activities using these sources is feasible in a practical environment, although accuracy and reliability vary. Notably, Smart Water Meters demonstrate high reliability, with a precision of 0.86 and a recall of 1.00, making them particularly suitable for emergency detection. Existing emergency detection methods are not designed to handle uncertain activity data. This thesis introduces a novel approach based on probabilistic activity information, employing an Inactivity Score that provides a probabilistic weighting of inactivity periods based on the reliability of sensor measurements. By analyzing historical Inactivity Scores, anomalies that potentially represent an emergency can be identified. Evaluations across seven datasets show this approach outperforms existing methods, achieving a mean time to detect emergencies of approximately 05:23:28 hours and producing 0.09 false positives per day under noise-free conditions. Moreover, unlike related approaches, the proposed method remains effective with noisy data. This thesis demonstrates that emergencies in private households can be detected using existing data sources from the home infrastructure, offering a cost-effective and non-intrusive solution to enhance the safety and autonomy of the elderly at home. Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-15992 ER - TY - THES A1 - Stoffels, Dominik T1 - Advancing Pattern Detection, Theory Development and Decision Making with Explainable AI N2 - The application of explainable artificial intelligence (XAI) methods in data-driven decision-making and computationally intensive theory development (CTD) is a subject of ongoing debate, particularly concerning how and whether these methods can be effectively employed, and how the reliability of their explanations can be ensured. This dissertation addresses these issues by systematically analyzing the usability of XAI for pattern detection, CTD, and decision-making, drawing on various real-world and synthetic datasets and employing different empirical methods and perspectives. The dissertation consists of four studies, each addressing distinct issues in the field of XAI application. KW - Explainable Artificial Intelligence KW - Machine Learning KW - Computationally Intensive Theory Development Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-15975 ER - TY - THES A1 - Hasenpflug, Mareike T1 - Slice sampling on Riemannian manifolds N2 - This thesis is concerned with hybrid slice samplers for approximate sampling of distributions on Riemannian manifolds. First for distributions on the Euclidean unit sphere, and then for distributions on general Riemannian manifolds we introduce a geodesic-based hybrid slice sampler, called geodesic slice sampler. Under mild regularity assumptions, we establish reversibility with respect to the target distribution for this sampler and positive semi-definiteness of the corresponding operator. Moreover, on compact Riemannian manifolds we show uniform ergodicity with explicit constants for the geodesic slice sampler if the target distribution has a bounded density with respect to the Riemannian measure. As an important building block of this sampler, we provide an explicit expression for the shrinkage procedure proposed in (Neal, 2003) in terms of a Markov kernel. We establish that this kernel is reversible with respect to the uniform distribution on the target set and that its corresponding operator is positive semi-definite. Beyond the geodesic slice sampler, we apply these results also to elliptical slice sampling (Murray, Adams, MacKay, 2010) to obtain a proof for its reversibility with respect to the target distribution and positive semi-definiteness of the corresponding operator. KW - Markov chain Monte Carlo KW - Slice sampling KW - Riemannian manifolds Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-15903 ER - TY - THES A1 - Baak, Werner T1 - Advanced Ordered Weighted Averaging Methods in Robust Optimization N2 - In decision-making under uncertainty, robust optimization is a critical tool across various fields, providing solutions that perform effectively across a range of scenarios where precise probabilities are unavailable or unreliable. Traditional approaches, such as min-max and min-max regret, focus on minimizing the worst-case outcomes and worst-case regret, respectively, often resulting in highly conservative solutions. To address this limitation, this dissertation investigates the Ordered Weighted Averaging (OWA) operator, which offers a flexible framework for aggregating outcomes according to varying risk preferences, from risk-averse to risk-neutral, encompassing traditional robust approaches as special cases. This work is organized around three primary contributions that expand the application and understanding of OWA in robust optimization. The first contribution develops a preference elicitation framework for OWA weights, enabling decision-makers to derive weighting schemes based on observed historical decisions, thereby aligning aggregation strategies with specific risk attitudes. The second contribution introduces a novel variant of OWA for robust optimization, integrating OWA into a regret minimization framework to generalize both robust min-max and min-max regret approaches. This model is complemented by new complexity results, including insights into the inapproximability and approximability of OWA regret, providing stronger approximation bounds that asymptotically improve on previously established results for classic OWA models. These advancements position the OWA regret model as a powerful alternative to min-max regret, offering a more adaptable approach to risk-sensitive decision-making. The third contribution addresses interval uncertainty, extending the OWA framework to scenarios where outcomes are represented as bounded intervals instead of discrete points. This interval-based OWA model accommodates real-world decision-making needs, where scenario data are uncertain or costly to specify. By using Value-at-Risk (VaR) in our definition, we provide a natural way to handle continuous ranges of uncertainty while maintaining computational tractability for large-scale problems. Together, these contributions advance both the theoretical and practical applications of OWA in decision making, establishing OWA-based methods as versatile tools for addressing complex uncertainties across a variety of decision-making environments. KW - decision-making KW - uncertainty KW - risk Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-15879 ER - TY - CHAP A1 - Meißner, Annekatrin ED - Henkel, Anna T1 - Wirtschaftsethik : Globale Mitverantwortung für ungerechte Folgen des Marktsystems am Beispiel der Umweltverschmutzung der Lagune Mar Menor (Spanien) T2 - 10 Minuten Soziologie : Verantwortung N2 - "Aus Perspektive der Wirtschaftethik wird deutlich, dass ein reines Verursacherverständnis und darauf basierendes Haftbarkeitsmodell angesichts globaler Wirtschaftsprozesse eine Weiterverschiebung von Verantwortung für Umweltschäden mit sich bringt. Dem gegenüber ist das Konzept globaler Mitverantwortung geeignet, Verantwortungsfragen umfassend zu analysieren und solchen Defiziten zu begegnen. Am Fall der Lagune Mar Menor wird gezeigt, wie globale Mitverantwortung im Kontext globaler Machtstrukturen Handlungsoptionen eröffnet." (Aus der Einleitung zu Henkel, Anna; 10 Minuten Soziologie : Verantwortung; transcipt Bielefeld 2021, S. 151, doi.org/10.1515/9783839451120-001) KW - Verantwortungsverschiebung KW - Verursacherverständnis KW - soziale Verbundenheit KW - Haftbarkeit KW - kollektive Handlung Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-15887 SP - 137 EP - 150 PB - transcipt CY - Bielefeld ER - TY - BOOK ED - Benkel, Thorsten ED - Meitzler, Matthias T1 - Mythenjagd : Soziologie mit Norbert Elias N2 - Der vorliegende Band rückt verschiedene Aspekte und Diskurse rund um Elias’ Schaffen in den Vor­der­grund und kontex­tua­­lisiert die generelle soziologische Relevanz seines Schaffens. Er liefert einen Überblick über die ak­tuel­le Elias-Forschung und verdeutlicht den Stellenwert und die Anschlussfähigkeit des Elias’schen Werks für so­zialwissenschaftliche bzw. sozialtheo­re­tische Debatten, insbesondere hinsichtlich zeit­ge­nös­si­scher ge­sellschaftlicher Ent­wick­lungen. Dabei zeigt sich: Die Wis­sen­schaft selbst, so Elias, läuft Gefahr, sich in Mythen zu verfangen, während sie die Mythen der Wirk­lich­keit unter die Lupe nimmt. Somit ist Mythenjagd nicht nur ein Schlagwort, sondern auch eine Devise, unter die sich Elias’ Gesamtwerk stellen lässt. Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-14002 SN - 978-3-7489-1579-9 PB - Velbrück Wissenschaft CY - Weilerswist ER - TY - THES A1 - Hering, Robin T1 - Protection of Civilians in Armed Conflict: Safe Areas and the Silencing of Mass Atrocities N2 - This publication-based thesis approaches the topic of the protection of civilians in armed conflict by ‘zooming in‘ on two specific sub-topics: safe areas as well as the silencing of mass atrocities. The thesis consists of five publications (four of them published in double-blind peer reviewed journals) and of an introductory chapter that presents the overall argument and contextualises the publications. Two publications argue that mass atrocities are silenced, or at least not politicised, in the discourses and debates of Germany as an exemplary UN member state. It is argued that ‘silencing’ is a structural feature of an ‘identity-mismatch’ with the domestic ideational structure that inhibits debates and freezes the possibility space for foreign policy. Empirically, the first publication assesses the rhetoric of the German chancellor, foreign ministers and parliamentary group leaders vis-à-vis the mass atrocities committed in Yemen, Myanmar and South Sudan. The second publication widens the scope and looks at German political, media and societal debates in twelve cases of mass atrocities between 1992 and 2019. The remaining three publications focus on the topic of safe areas. The first publication systematically collects and assesses the existing conceptual literature on safe areas. The second publication presents a comprehensive definition, a four-fold typology based on a distinction by size and the logic of protection as well as an extensive empirical dataset of safe areas. By analysing case studies from Iraq and South Sudan, the third publication argues that safe areas have a very limited potential to provide an alternative to flight, especially from the perspective of the protection-seeking civilians themselves. KW - Protection of Civilians KW - Mass Atrocities KW - Foreign Policy Analysis KW - Safe Areas KW - Silencing KW - Zivilbevölkerung KW - Schutzzone KW - Außenpolitik KW - Schweigen KW - Völkermord Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-15765 ER - TY - THES A1 - Lorenz, Catherine T1 - Studies on optimization problems with dynamically arriving information N2 - In today’s fast-paced world, transportation planning, e-commerce, smart manufacturing, emergency services, and financial markets operate in real-time environments where dynamically arriving information must be integrated on-the-fly into decision-making. Research produced online algorithms ranging from myopic reoptimization (Reopt) to learning-based anticipation methods. However, given the complexity of real-world problems, optimal decision policies remain unknown, and effectiveness is often assessed through simulations against simple benchmarks, leaving improvement potential and robustness uncertain. This dissertation proposes effective online policies using classical and innovative analytical and computational evaluation methods, establishing performance bounds and comparisons to optimal solutions. It designs algorithmic frameworks for two dynamic optimization problems: the Online Order Batching, Sequencing, and picker Routing Problem (OOBSRP) in warehousing and the Traveling Salesman Problem with a Truck and a Drone under Incomplete Information (TSP-DI), for disaster relief. Given the importance of automation in real-time environments, a strong emphasis is placed on robotic solutions. For the OOBSRP with manual and robotic carts, we prove that Reopt is asymptotically optimal with probability one under broad stochastic conditions. From a worst-case perspective, no policy can improve Reopt by more than 50%, as it is shown to be asymptotically two-competitive. A computational study confirms that Reopt’s gaps to the complete-information optimum are small, e.g. averaging less than 5% for a cost-minimization objective. A pattern analysis of Complete-Information Optimal Solutions (CIOSs), generated with dynamic programming algorithms, identifies simple algorithmic enhancements – like eliminating waiting, intervention, or strategic relocation – that further reduce costs and delivery times. These findings suggest limited benefits of anticipatory (including AI-based) algorithms in OOBSRP. Conversely, for TSP-DI, where road blockages reveal dynamically, Reopt performs poorly in the worst case, as we reveal its exponentially growing competitive ratio. We show that policies delaying deliveries for drone surveillance are significantly superior in competitive ratio. A proposed hybrid policy achieves best average and worst-case results in experiments. Using battery-limited drones introduces a challenging static subproblem within these policies, classified as Drone Routing Problems with Energy Replenishment (DRP-E). We develop a Very Large-Scale Neighborhood Search (VLNS) and an exact method for generic DRP-Es. VLNS searches an exponential-sized neighborhood of a promising solution entirely in polynomial runtime, making it ideal for real-time policies or intensification in metaheuristics. This dissertation underscores the importance of analytical guarantees and comparisons to the optimum in online algorithm design, as policy effectiveness often diverges from intuition and varies significantly across problems. KW - Dynamic optimization KW - Online algorithms KW - Competitive analysis KW - Probabilistic performance guarantees KW - Very large-scale neighborhood search Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-15649 N1 - According to § 11 FPromO, Abs. 1, Satz 5 of the Promotionsordnung and with the agreement of the Chair of the Board of Examiners for Doctoral Awards, the following minor revisions have been made for the publication of the dissertation compared to the version submitted for grading. These changes result from comments and requests by the external reviewer, Prof. Dr. Stefan Irnich, as well as the author’s own observations during the revision process: - Corrected minor typos in grammar and mathematical notation. - Implemented wording improvements. - Reorganized and updated the list of abbreviations alphabetically. - Updated the publication status of the list of papers to the submission date and added the affiliation of the University of Bologna. - Page 13: Corrected the reduction of the average observed gap to CIOS of Reopt (16.6 percentage points) and provided clarification. - Pages 23 and 58: Added an inequality of indices k and l in definitions of a partition of batches in an optimal solution. - Page 24, "because the cart- and picker equipment is order-specific for each batch" changed to "because of pick-lists that are printed out " - Page 55: Added and corrected a statement (one sentence) regarding the reference Wahlen and Geschwind (2023). - Page 71: Added the statement: "Note that an increase in batching capacity significantly impacts the runtime of the DP approaches for both objectives." - Page 80: Replaced and corrected Figure 3.8 (statement remains unchanged). - Page 79: Corrected column names in Table 3.12. - Standardized the abbreviation "VLNS" instead of "VLSN" throughout Chapter 5. - Unified the written-out problem names of OOBSRP and OBSRP-R throughout the dissertation ER - TY - JOUR A1 - Komander, Verena A1 - König, Andreas T1 - Organizations on stage: organizational research and the performing arts JF - Management Review Quarterly N2 - Management and organization scholars have long been intrigued by the performing arts—music, theater, and dance—as a rich context for studying organizational phenomena. Indeed, a plethora of studies suggest that the performing arts are more than an interesting sideline for authors, as they offer unique theoretical and empirical lenses for organization studies. However, this stream of literature spreads across multiple research areas, varies with regard to its underlying theories and methods, and fails to pay sufficient attention to the contextuality of the findings. We address the resulting limitations by identifying and reviewing 89 articles on management and organization related to the performing arts published in 15 top-tier journals between 1976 and 2022. We find that research in the performing arts advances organizational theory and the understanding of organizational phenomena in four key ways, namely by studying (1) organizational phenomena in performing-arts contexts; (2) performing-arts phenomena in organizational contexts; (3) organizational phenomena through the prism of performing-arts theories; and (4) organizational phenomena through the prism of performing-arts practices. We also find that, in contrast to other settings, the performing arts are uniquely suited for immersive participant-observer research and for generating genuine insights into fundamental organizational structures and processes that are generic conditions of the performing arts and management alike, such as leadership, innovation, and the management of uncertainty. Finally, based on our consolidation of the research gaps and limitations of the reviewed studies, we develop a comprehensive agenda for future research. KW - Performing arts KW - Music KW - Dance KW - Jazz KW - Theatre KW - Organization KW - Management KW - Leadership Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:101:1-2023010321004612876788 VL - 2024 IS - 74 SP - 303 EP - 352 PB - Springer Nature CY - Berlin ER - TY - JOUR A1 - Schweikl, Stefan A1 - Obermaier, Robert T1 - Lost in translation: IT business value research and resource complementarity : an integrative framework, shortcomings and future research directions JF - Management Review Quarterly N2 - Despite longstanding research efforts, there is still ambiguity surrounding the business value created by IT. To approach this conundrum, research focus has progressed from an isolated investigation of IT to the assessment of complementarity between IT and different non-IT resources such as work practices or decision structures. However, incoherence around the characteristics and scope of these complementary non-IT resources has created a fragmented body of research, preventing a sustainable knowledge creation. Thus, in this paper we synthesize the dispersed research efforts, identify shortcomings in the extant literature, and derive opportunities for future research. Specifically, we present a converging definition of complementary non-IT resources and specify their role in the value creation process from IT by viewing it through three distinct lenses: microeconomic theory, resource-based view, and contingency theory. We structure current research efforts by organizing complementary non-IT resources into distinct categories, namely strategy, structure, practices, processes, and culture (organizational resources), top management support, internal relations, and external relations (relational resources), worker skill (non-IT human resources), non-IT physical resources, as well as internal funds and external funds (financial resources). Finally, we highlight five important shortcomings in the current literature, such as the predominant use of reductionist approaches or monolithic IT measures, and make actionable recommendations to resolve them. KW - Literature review KW - Classification KW - IT value KW - Complementarity KW - Resource system KW - Configurations Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:101:1-2022093021520340946532 VL - 2022 IS - 73 SP - 1713 EP - 1749 PB - Springer Nature CY - Berlin ER - TY - JOUR A1 - Reiter, Florence T1 - Die Rolle der Europawahl 2019 in der Online-Medienberichterstattung. Eine Blended Reading Analyse am Beispiel von Spiegel-Online JF - Zeitschrift für Politikwissenschaft N2 - Die quasi unbegrenzte Anzahl an frei verfügbaren Daten im Internet birgt für die politikwissenschaftliche Forschung große Chancen, aber auch methodische Herausforderungen. Letztere zeigen sich vor allem in der Erhebung,Speicherung und Verarbeitung von webbasierten Daten wie beispielsweise Medienwebsites, die wissenschaftlichen Standards entsprechen. Insbesondere intersubjektive Nachvollziehbarkeit und Reliabilität sollten im Umgang mit internetbasierten Daten gewährleistet werden können. Dabei ist es beispielsweise nicht ausreichend zur intersubjektiv nachvollziehbaren Erhebung die URL einer Webseite abzuspeichern. Die hohe Fluidität dieser Art von Daten kann dazu führen, dass die Webseite bereits wenige Minuten nach der Speicherung der URL nicht mehr dem Bild entspricht, das die Forscher*in zum Speicherzeitpunkt hatte. Webarchivierung zur Datenerhebung und -speicherung sowie der Blended Reading Ansatz zur Analyse dieser Datenmengen bieten vielversprechende Möglichkeiten für Forschende, mit diesen Herausforderungen umzugehen. Daher führt der vorliegende Beitrag eine exemplarische Analyse durch: Auf Basis von via Event-Crawl erhobenen Daten soll mit einem Blended Reading Ansatz analysiert werden, welche Rolle der Europawahl 2019 in der Online-Medienberichterstattung am Beispiel von Spiegel-Online zugeschrieben wird. Dabei geht es darum, an einem bewusst begrenzt gehaltenen Datensatz exemplarisch aufzuzeigen, über welches Potenzial die Durchführung dieser Methodenkombination verfügen und wie sie Forschung und Lehre bereichern kann. KW - Webarchivierung KW - Event-Crawl KW - Blended Reading KW - Europawahlen KW - Wahlkampfforschung Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:101:1-2022081622245924254625 VL - 2022 IS - 32 SP - 839 EP - 864 PB - Springer Nature CY - Berlin ER - TY - JOUR A1 - Grimm, Michael A1 - Luck, Nathalie A1 - Steinhübel, Franziska T1 - Consumers' willingness to pay for organic rice: Insights from a non‐hypothetical experiment in Indonesia JF - Australian Journal of Agricultural and Resource Economics N2 - As in many high‐income countries, there is increasing awareness towards organic farming in many low‐ and middle‐income countries. Sustained local demand is an essential requirement for further adoption of organic farming by smallholders, who typically have only limited access to export markets. Until now, only few studies have explored the local willingness to pay (WTP) for organic products in low‐ and middle‐income countries in real purchase situations. This paper analyses the consumers' WTP for organic rice in urban and suburban Indonesia using an incentive‐compatible auction based on the Becker–DeGroot–Marschak (BDM) approach. We further study the effect of income and a randomised information treatment about the benefits of organic food on respondents' WTP. Estimates suggest that respondents are willing to pay an average price premium of 20% compared with what they paid for conventional rice outside our experiment. However, our results also indicate that raising consumers' WTP further is complex. Showing participants a video about health or, alternatively, environmental benefits of organic food was not effective in further raising WTP. The results can be used as a basis for the design of alternative awareness measures to increase knowledge, interest and demand for organic food. KW - BDM KW - Indonesia KW - organic food KW - rice KW - willingness to pay Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-12412 VL - 67 IS - 1 SP - 83 EP - 103 PB - Wiley CY - Hoboken ER - TY - INPR A1 - Pantaleón Osuna, Álvaro T1 - Climate change as a driver of migration? A comparative case study in eastern and northern Ghana N2 - Academic studies and media reports have pointed to climate change as a dominant factor responsible for future mass migrations from and within the Global South. In response to the deterministic nature of their estimates and predictions, this research explores the link that migrants establish between the environmental changes they experience and migration as a climate adaptation strategy. Furthermore, the overlaps between the profile and migratory behavior of those who manifest a greater presence of climate change in their migratory processes and their counterparts are analysed to identify potential unique climate migration patterns and practices. The quantitative analysis of data gathered in the context of the Mitra|WA project in Ghana's Eastern and Northern Regions in 2022 reveals that, while migration is not predominantly propelled by climate change climate, it does not constitute a new form of mobility demarcated from existing migration patterns and practices. This paper provides an opportunity to redirect future research towards the factors that determine the agency of individuals in response to climate hazards and to explore the role of climate change in a set of drivers of migration in a West African setting. T3 - Migration, translocality and development in times of climate change. Mitra|WA Working Paper Series - 1 KW - Environmental change KW - Adaption strategies KW - Climate-induced migration KW - Drivers of migration KW - Translocality Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-14585 IS - 1 CY - Passau ER - TY - THES A1 - Schwind, Mara T1 - „Insgesamt sah ich wirklich die Wellen an mir vorbeirauschen, mich darin befindend“ - Die Folgen negativer Reaktionen gegen Wissenschaftler*innen in den sozialen Medien N2 - Wissenschaftler*innen werden immer häufiger zum Ziel von Kritik, Anfeindungen und Ähnlichem in den sozialen Medien. Die Studie nimmt die reziproken Effekte dieser negativen Reaktionen in den Blick. Konkret wird untersucht, mit welchen Arten negativer Reaktionen Wissenschaftler*innen konfrontiert werden, welche mentalen Verarbeitungs- und Bewertungsprozesse in diesem Kontext relevant sind und wie die Betroffenen mit den negativen Reaktionen anschließend umgehen, um die entstandene Belastungssituation zu bewältigen. Neben der theoretischen Aufarbeitung der Thematik wird dafür auf qualitative Leitfadeninterviews mit betroffenen Wissenschaftler*innen zurückgegriffen. Die Erkenntnisse der Studie werden in einem „Modell der Konfrontation mit negativen Reaktionen in den sozialen Medien“ zusammengeführt. Das Modell ermöglicht zum einen die strukturierte Beschreibung entsprechender Vorfälle und kann zum anderen als theoretisch-konzeptionelle Grundlage für weitere empirische Untersuchungen dienen. KW - qualitative Leitfadeninterviews KW - Hate Speech KW - Wissenschaftler*innen in den sozialen Medien KW - Kritik, Anfeindungen und Hass gegenüber Wissenschaftler*innen Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-15627 ER - TY - THES A1 - Faltermaier, Stefan T1 - A Sociotechnical Perspective on Digital Transformation of Work in Organizations, on Platforms, and in Academia N2 - The findings of this dissertation reveal that digital transformation in the workplace accelerates ongoing changes in work practices, leading to transformations in organizations on both social and technological levels (study one). A key challenge identified in our case from study one is that highly virtual and digital work environments can undermine the integration of new employees and weaken organizational cohesion, resulting in more isolated work that tends to occur either individually or in small groups. In completely detached work settings (study two), our findings emphasize the prevalence of negative work experiences - frustration in our case – and the central role of both social and technical antecedents. Work settings devoid of any organizational framework, such as microtask crowd work, show an even greater detachment from shared values and structures compared to study one, posing significant challenges for the workers involved. These challenging conditions for individuals and organizations highlight the necessity for further research and the development of innovative theories to better comprehend these dynamics, and to devise strategies to manage these challenges effectively. Studies three and four build on this premise. In these studies, within the context of the digital transformation of academic work, we demonstrated how ML combined with XAI applications can be employed in theory development. KW - Digital Transformation of Work KW - Hybrid Work KW - Online Labor Platforms KW - Artificial Intelligence KW - Explainable Artificial Intelligence Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-15233 ER - TY - THES A1 - Sawhney, Udit T1 - Incentivizing Sustainable Agriculture in Indonesia: Empirical Essays on the Role of Social Norms and Information Provision N2 - The Green Revolution (GR) was one of the most transformative events in modern agricultural history. It was characterized by the widespread adoption of high-yield crop varieties, synthetic fertilizers and pesticides, and advanced irrigation systems. By significantly increasing agricultural productivity, the GR responded to global food shortages and hence played a crucial role in educing hunger, particularly in developing economies. However, while the GR alleviated food insecurity and stimulated economic development, it also brought about several unintended consequences like environmental degradation, as well as, widening socio-economic inequalities. Farmers, particularly in South and Southeast Asia, indulged heavily in fertilizer overapplication, which led to declining soil health and long-term sustainability concerns. Recognizing these challenges, the United Nations’ Sustainable Development Goals (SDGs) placed significant emphasis on sustainable agriculture, particularly through SDG - 2, which seeks to end hunger and promote sustainable food production. In line with these efforts, there has been a growing movement by several countries and international organizations towards promoting sustainable agricultural practices that balances agricultural productivity with environmental conservation. This dissertation contributes to this discourse on sustainable agriculture by examining key socio-economic factors that influence the adoption of sustainable farming practices among smallholder farmers in Indonesia. Indonesia’s agricultural landscape, particularly its rice farming sector, has been shaped by decades of Green Revolution policies, with Java serving as a focal point for agricultural intensification. While these policies led to impressive yield increases and national self-sufficiency in rice production by the mid-1980s, they also resulted in several environmental and economic challenges, including excessive use of chemical fertilizers, soil nutrient imbalances, and long-term land degradation. In response, the Indonesian government introduced several sustainability-focused policies, including Integrated Pest Management (IPM), Farmer Field Schools (FFS), and the “Go Organic 2010” initiative. Despite these efforts, adoption of sustainable farming practices remains limited, raising critical questions about the barriers that prevent smallholder farmers from transitioning away from intensive chemical input use. The dissertation focuses on three interrelated research questions that explore the role of social networks, information provision, and economic incentives in shaping farmers’ decisions regarding sustainable agriculture. These questions are addressed through a combination of mixed-methods research and randomized controlled trials (RCTs) conducted in Java, specifically in the regions of Yogyakarta and Tasikmalaya. The first research question investigates whether and how social networks and peer effects influence farmers’ input decisions, particularly regarding fertilizer application. This study builds on existing literature on social networks in agriculture and examines the extent to which perceptions of farming norms - the visible greenness levels of rice plants - affect farmers’ willingness to adopt more sustainable practices. Using a mixed-methods approach, including survey experiments and social network analysis, the study finds that personal opinions about the importance of plant greenness significantly influence farmers’ input decisions. However, second-order perceptions - farmers’ beliefs about how others in their farming network think about their farming choices - do not play a decisive role in shaping actual adoption behaviour. This finding contrasts with previous studies that emphasize the role of social pressure in agricultural decision-making, suggesting that while social learning plays an important role, it does not always operate through peer-effect mechanisms. The results highlight the complexity of social influences in agricultural adoption decisions and the need for more nuanced approaches to integrating behavioural insights into policy interventions. The second research question investigates the role of information provision, particularly about site-specific nutrition, in promoting sustainable soil management practices among smallholder farmers. A large-scale RCT was conducted in 69 villages to assess whether targeted agricultural extension trainings, along with soil testing services, can drive farmers’ adoption of sustainable soil management practices. Villages were randomly assigned to - a treatment group (T1) that received one-day training on soil health management, a second treatment group that received both training and soil tests (T2), and a control group. The study reveals that while training sessions increased awareness and adoption of simple sustainable practices - such as the use of the Leaf Colour Chart (LCC) - there was limited impact on broader behavioural changes, such as the adoption of organic fertilizers or precision fertilizer application. However, the additional provision of soil testing led to measurable reductions in nitrogen fertilizer use while simultaneously increasing yields, demonstrating the potential for personalized, site-specific soil nutrient recommendations to improve both economic and environmental outcomes. A cost-benefit analysis reveals that additional day of soil testing training resulted in an average economic gain of USD 15.71 per farmer and also reduced CO2 emissions by approximately 2 kg per farmer. These findings highlight the potential for scalable, information-based interventions as well as the need for sustained follow-up support to reinforce behavioural changes among farmers. The third research question explores farmers’ willingness to pay (WTP) for soil testing services and compares two different market-dissemination models - a private service model (where farmers purchase individual soil tests) and a collective (club good) model (where farmer groups collectively purchase a soil testing kit). Using an incentive-compatible auction based on the Becker- eGroot-Marschak (BDM) method, the study finds that farmers are willing to pay approximately 43% of the actual cost of soil tests, indicating strong demand for personalized soil fertility information. Furthermore, there is no significant difference in WTP between the private and club good models, suggesting minimal free-riding behaviour within farmer groups. The qualitative data further suggests that group-based models foster a sense of joint responsibility and knowledge-sharing, making them a viable alternative to individual service provision. A deeper analysis reveals that while private service models are more effective in low-subsidy environments, club good models become preferable when subsidies are higher, offering valuable insights into cost-sharing mechanisms for agricultural policy design. Taken together, the findings of this dissertation have important implications for policymakers seeking to promote sustainable agricultural practices in developing economies. First, the dissertation highlights the nuanced role of social networks in shaping farmers’ adoption decisions, suggesting that interventions targeting social learning should account for the complexity of social networks and peer influence mechanisms. Second, the dissertation underscores the importance of integrating soil testing and personalized information into agricultural extension programs, as site-specific soil nutrient recommendations can enhance both farming productivity as well as environmental sustainability. Third, the study provides empirical evidence on cost-effective ways to scale up soil testing services, demonstrating that well- esigned market-dissemination strategies can increase farmers’ access to sustainability-enhancing technologies while maintaining financial viability. Beyond its immediate policy relevance, this dissertation also contributes to broader theoretical debates in development economics, agricultural economics, and environmental sustainability. By integrating experimental research methods, the dissertation advances understanding of how farmers make technology adoption decisions under conditions of uncertainty and social influence. Additionally, the study provides a methodological contribution by demonstrating the effectiveness of combining RCTs with qualitative approaches to capture the complexities of real-world decision-making. Despite its contributions, the dissertation also identifies several avenues for future research. One key limitation is that the analysis focuses primarily on short - to medium-term impacts, leaving open questions about the long-term sustainability of behaviour change. Future studies should explore whether farmers continue to adopt sustainable practices once external support is removed. Additionally, further research is needed to examine the role of digital agricultural advisory services, mobile-based soil testing platforms, and remote sensing technologies in complementing traditional extension services. Finally, more work is needed to explore the broader policy ecosystem surrounding agricultural sustainability, including the role of subsidies, market linkages, and certification schemes in incentivizing long-term adoption. In conclusion, this dissertation provides a comprehensive analysis of the social, informational, and economic factors that drive sustainable agricultural transitions in Indonesia. By offering evidence-based insights into the design of more effective extension programs, market dissemination strategies, and cost- haring mechanisms, it contributes to ongoing efforts to create more resilient and environmentally sustainable food systems. The findings are not only relevant for Indonesia but also offer valuable lessons for other developing economies that are facing the challenge of balancing agricultural productivity with sustainability. KW - Economics KW - Development Economics KW - Agricultural Economics KW - Randomized Controlled Trials Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-16095 ER - TY - JOUR A1 - Lukasczyk, Stephan A1 - Kroiß, Florian A1 - Fraser, Gordon T1 - An empirical study of automated unit test generation for Python JF - Empirical Software Engineering N2 - Various mature automated test generation tools exist for statically typed programming languages such as Java. Automatically generating unit tests for dynamically typed programming languages such as Python, however, is substantially more difficult due to the dynamic nature of these languages as well as the lack of type information. Our P YNGUIN framework provides automated unit test generation for Python. In this paper, we extend our previous work on P YNGUIN to support more aspects of the Python language, and by studying a larger variety of well-established state of the art test-generation algorithms, namely DynaMOSA, MIO, and MOSA. Furthermore, we improved our P YNGUIN tool to generate regression assertions, whose quality we also evaluate. Our experiments confirm that evolutionary algorithms can outperform random test generation also in the context of Python, and similar to the Java world, DynaMOSA yields the highest coverage results. However, our results also demonstrate that there are still fundamental remaining issues, such as inferring type information for code without this information, currently limiting the effectiveness of test generation for Python. KW - Dynamic typing KW - Python KW - Automated Test Generation Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:101:1-2023081721042349746457 VL - 28 IS - 1 SP - 1 EP - 46 PB - Springer Nature CY - Berlin ER -