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Ziel der Arbeit ist es, Narrative und diskursive Strategien von politisch rechten Akteuren zu erforschen und aus einer pädagogischen Sicht zu bewerten. Der Fokus der Untersuchung wird hierbei auf Kommunikation innerhalb des Social Web gelegt. Zur Bewältigung des Forschungsvorhabens wird als Methode eine Diskursanalyse angewendet. Die Analyse kommt zu dem Ergebnis, dass sowohl die erzeugten Narrative als auch die verwendeten diskursiven Strategien in allen untersuchten diskursiven Arenen starke Ähnlichkeiten aufweisen – unabhängig davon, ob die Arena vorrangig rechtsextreme, rechtsradikale oder rechtspopulistische Tendenzen besitzt. Dies legt den Verdacht nahe, dass ein Großteil der politisch rechte Akteure immer wiederkehrende Narrative verbreiten und diese mit den stets gleichen diskursiven Strategien untermauern, eine klare diskursive Grenze zwischen Rechtsextremismus, Rechtsradikalismus und Rechtspopulismus scheint es nicht zu geben. Dadurch besteht die Gefahr, dass Rechtsextreme Gedanken zunehmend in die Mitte der Gesellschaft vordringen können.
Fundamental changes in business-to-business (B2B) buying behavior confront B2B supplier firms with unprecedented challenges. On the one hand, a rising share of industrial buyers demands digitalized offerings and processes from suppliers. Consequently, suppliers are urged to implement digital transformations by expanding the range of both digital offerings and processes. On the other hand, B2B buyers increasingly expect suppliers to provide individually tailored solutions to their idiosyncratic needs. Hence, suppliers are also required to implement non-digital transformations by providing offerings and processes that are customized to each customers’ specific requirements.
The rise of these digital and non-digital transformations calls established knowledge into question. Thus, B2B marketing research and practice are urged to create a comprehensive understanding of digital and non-digital transformations by means of novel and empirically grounded insights and derive actionable response strategies. In respond, my dissertation addresses the overall research question of how B2B supplier firms can successfully implement both digital and non-digital transformations in three individual essays.
In Essay 1, I offer a broader perspective on both digital and non-digital transformations by investigating digital service customization (i.e., the tailoring of digital B2B services to customers’ individual needs). Through a systematic literature review and bibliometric analysis, I outline a comprehensive set of factors that favor the application of distinct digital service customization strategies. Essay 2 represents a deep dive into digital transformations of sales processes. By making use of two rich sets of qualitative interview material from supplier and buyer firms, I identify the challenges resulting for B2B salespeople from the introduction of digital sales channels into personal selling. Moreover, I uncover facilitating mechanisms that sales managers can employ to support salespeople in coping with digital sales channels. Finally, Essay 3 constitutes a deep dive into non-digital transformations. Based on qualitative interview material and survey data from matched sales manager–salesperson dyads, the essay explores how configurations of individual salespeople’s personal and procedural competencies facilitate success at selling customer solutions (i.e., highly customized, performance-oriented offerings comprising products and/or services). The essay shows that successfully selling customized offerings like solutions hinges on salespeople’s unique configurations of present and absent competencies.
In a nutshell, these essays provide three major insights on how B2B suppliers can successfully implement digital and non-digital transformations. First, they underscore that a comprehensive understanding of the origins and spillover effects of transformations is a key prerequisite to successfully implementing them. Second, they unveil that digital and non-digital transformations impact on multiple organizational levels. Third, they point out important resources and capabilities that help suppliers to successfully implement transformations, be they digital or non-digital.
With this dissertation, I make substantial contributions to the broader literature on digital and non-digital transformations in B2B contexts. At the same time, my dissertation provides hands-on implications for managers in B2B supplier firms that are facing fundamental transformations in the marketplace—both digital and non-digital in nature.
Job Sequencing and Tool Switching Problems with a Generalisation to Non-Identical Parallel Machines
(2020)
Manufacturing tools have been dominating the manufacturing process since the 1960s. The job sequencing and tool switching problem is an NP-hard combinatorial optimization that has first been introduced in the context of flexible manufacturing systems in the late 1980s. Since then, production systems have undisputedly changed and improved but manufacturing tools still dominate manufacturing processes. Production and system operation processes are continuously adjusted and optimised to changing customer requirements. If the product variety requires an increasing number of tools for processing that exceeds the local tool magazine capacity of the manufacturing system, tool switches become necessary. Although tool changing times within a manufacturing centre or cell may nowadays be very small due to the high degree of automation, tool switching within a dynamic production environment is still a time consuming process that must be avoided. In order to minimize the total tool setup time to enhance productivity, the objectives of the basic job sequencing and tool switching problem are to sequence a set of jobs and simultaneously to determine the best tool loading. Therefore, job sequencing and tool switching problems are gaining considerable attention.
Several solution approaches to the standard problem and related versions of the problem exist. The first part of this dissertation assesses the current state-of-the-art of the job sequencing and tool switching problem and provides a classification scheme for literature on the job sequencing and tool switching problem and its variations. Only few authors consider generalisations of the problem because the level of complexity of extended problems is high. A general approach of the job sequencing and tool switching problem with non-identical parallel machines and sequence-dependent setup times is described in this dissertation. A novel mathematical model based on time periods is presented and analysed which can be adapted to different objective functions. The last part of this dissertation is a quantitative evaluation of fast and effective construction heuristics as well as of an iterated local search algorithm tested on a new set of benchmark instances. As such this dissertation provides a broad basis for future evaluations of solution approaches to the job sequencing and tool switching problem with non-identical parallel machines and sequence-dependent setup times as well as a basis for further generalisations of the problem like for example tool availability constraints or tool-size dependent variations.
Abstract concepts and ideas from Computer Science Education can benefit from immersive visualizations that can be provided in virtual environments. This thesis explores the effects of the key characteristics of virtual environments, immersion and presence, on learning outcomes in Educational Virtual Environments for learning Computer Science.
Immersion is a quantifiable description of the technology to immerse the user into the virtual environment; presence describes the subjective feeling of 'being there'. While technological immersion can be seen as a strong predictor for presence, motivational traits, cognition, and the emotional state of the user also influence presence. A possible localization of these technological and person-specific variables in Helmke's pedagogical supply-use framework is introduced as the Educational Framework for Immersive Learning (EFiL). Presence is emphasized as a central criterion influencing immersive learning processes. The EFiL provides an educational understanding of immersive learning as learning activities initiated by a mediated or medially enriched environment that evokes a sense of presence.
The idea of Computer Science Unplugged is pursued by using Virtual Reality technology in order to provide interactive virtual learning experiences that can be accurately displayed, schematizing, substantiating, or metaphorical. For exploring the effects of virtual environment characteristics on learning, the idea of Computer Science Replugged focuses 'hands-on' activities and combines them with immersive technology. By providing a perception of non-mediation, Computer Science Replugged might enable experiences that can contribute additional possibilities to the real activity or enable new activities for teaching Computer Science.
Three game-based Educational Virtual Environments were developed as treatments: 'Bill's Computer Workshop' introduces the components of a computer; 'Fluxi's Cryptic Potions' uses a metaphor to teach asymmetric encryption; 'Pengu's Treasure Hunt' is an immersive visualization of finite state machines. A first study with 23 middle school students was conducted to test the instruments in terms of selectivity, the devices' induced levels of presence, and adequacy of the selected learning objectives. The second study with 78 middle school students playing the environments on different devices (laptop, Mobile Virtual Reality, or head-mounted-display) assessed motivational, cognitive, and emotional factors, as well as presence and learning outcomes.
An overall analysis showed that pre-test performance, presence, and the previous scholastic performance in Maths and German predict the learning outcomes in the virtual environments. Presence could be predicted by the student's positive emotions and by the technological immersion. The level of immersion had no significant effect on learning outcomes. While a good-fitting path analysis model indicated that the assumed relations deriving from the EFiL are largely correct for 'Bill's Computer Workshop' and 'Fluxi's Cryptic Potions', not all results of the overall path analysis were significant for the analyses of the particular environments.
Presence seems to have a small effect on learning outcomes while being influenced by technological and emotional factors. Even though the level of immersion can be used to predict the level of presence, it is not an appropriate predictor for learning outcomes. For future studies, the questionnaires have to be revised as some of them suffered from poor scale reliabilities. While the second study could provide indications that the localization of presence and immersion in an existing educational supply-use framework seems to be appropriate, many factors had to be blanked out.
The thesis contributes to existing research as it adds factors that are crucial for learning processes to the discussion on immersive learning from an educational perspective and assesses these factors in hands-on activities in Educational Virtual Environments for Computer Science Education.
Im Folgenden wird zunächst beschrieben, auf welcher fachwissenschaftlichen Grundlage das Modell Literarischer Kompetenz nach Schilcher/Pissarek fußt. Davon ausgehend werden anschließend die Potenziale der Literatursemiotik sowohl für die hochschulische Lehre als auch für den Deutschunterricht beleuchtet. In einem weiteren Abschnitt werden die drei im Rahmen der Passauer Kooperation zwischen Literatursemiotik und Literaturdidaktik erprobten Vernetzungsmodelle einander gegenübergestellt. Um diese zu differenzieren, wird zunächst ein Überblick über das jeweilige Veranstaltungskonzept gegeben, woraufhin in einem zweiten Schritt die Art der De-Fragmentierung erläutert wird, was schließlich in eine Skizzierung der Seminargestaltung mündet, um abschließend auf Grundlage zentraler Evaluationsergebnisse ein Gesamtfazit ziehen zu können.
With the frequency and impact of data breaches raising, it has become essential for organizations to automate intrusion detection via machine learning solutions. This generally comes with numerous challenges, among others high class imbalance, changing target concepts and difficulties to conduct sound evaluation. In this thesis, we adopt a user-centered anomaly detection perspective to address selected challenges of intrusion detection, through a real-world use case in the identity and access management (IAM) domain. In addition to the previous challenges, salient properties of this particular problem are high relevance of categorical data, limited feature availability and total absence of ground truth.
First, we ask how to apply anomaly detection to IAM audit logs containing a restricted set of mixed (i.e. numeric and categorical) attributes. Then, we inquire how anomalous user behavior can be separated from normality, and this separation evaluated without ground truth. Finally, we examine how the lack of audit data can be alleviated in two complementary settings. On the one hand, we ask how to cope with users without relevant activity history ("cold start" problem). On the other hand, we seek how to extend audit data collection with heterogeneous attributes (i.e. categorical, graph and text) to improve insider threat detection.
After aggregating IAM audit data into sessions, we introduce and compare general anomaly detection methods for mixed data to a user identification approach, designed to learn the distinction between normal and malicious user behavior. We find that user identification outperforms general anomaly detection and is effective against masquerades. An additional clustering step allows to reduce false positives among similar users. However, user identification is not effective against insider threats. Furthermore, results suggest that the current scope of our audit data collection should be extended.
In order to tackle the "cold start" problem, we adopt a zero-shot learning approach. Focusing on the CERT insider threat use case, we extend an intrusion detection system by integrating user relations to organizational entities (like assignments to projects or teams) in order to better estimate user behavior and improve intrusion detection performance. Results show that this approach is effective in two realistic scenarios.
Finally, to support additional sources of audit data for insider threat detection, we propose a method representing audit events as graph edges with heterogeneous attributes. By performing detection at fine-grained level, this approach advantageously improves anomaly traceability while reducing the need for aggregation and feature engineering. Our results show that this method is effective to find intrusions in authentication and email logs.
Overall, our work suggests that masquerades and insider threats call for different detection methods. For masquerades, user identification is a promising approach. To find malicious insiders, graph features representing user context and relations to other entities can be informative. This opens the door for tighter coupling of intrusion detection with user identities, roles and privileges used in IAM solutions.
In den aktuellen Lehrplänen aller deutschen Bundesländer für die Sekundarstufe im Fach Deutsch ist die Kompetenz im Umgang mit Medien ein integrativer Bestandteil. Wenn sich auch die einzelnen Bundesländer hinsichtlich einer konkreten Definition des Feldes der Medienkompetenz unterscheiden, so ist die grundsätzliche Relevanz einer Medienkompetenz im Sinne eines reflektierten Umgangs mit medialen Produkten deutlich herauszulesen. Dabei darf es allerdings nicht, wie es die meisten Lehrpläne auch explizit herausstellen, bei der Kompetenz im Umgang mit mobilen Endgeräten belassen werden, vielmehr wird häufig der Konstruktionscharakter medialer Produkte benannt, den es zu rekonstruieren und zu hinterfragen gilt. Ziel muss dabei sein, Medienkonsument*innen auf dem Weg zu mündigen Mediennutzer*innen zu begleiten.
In meinem Beitrag geht es um die prinzipielle Leistung und Funktion der Mediensemiotik als einer medienübergreifenden Herangehensweise in der Lehrer*innenbildung, weil es der schulische Umgang mit jeglicher Art von Medien ist, der einen dringenden Handlungsbedarf hervorruft.
Im vorliegenden Beitrag soll es darum gehen, die Grundeigenschaften, die das sprachliche Zeichen definieren, vom Gegenstand eines nur deklarativen Wissens durch die Erzeugung produktiver Irritation auf die Ebene des Verstehens zu heben. Vor einer linguistischen Professionalisierung ist das muttersprachliche Zeichen für Angehörige einer Sprachgemeinschaft nämlich keineswegs "bilateral", stellt sich die Frage seiner "Motiviertheit" nicht, ist seine "Konventionalität" selbstverständlich.
Our subject of study is strong approximation of stochastic differential equations (SDEs) with respect to the supremum and the L_p error criteria, and we seek approximations that are strongly asymptotically optimal in specific classes of approximations. For the supremum error, we prove strong asymptotic optimality for specific tamed Euler schemes relating to certain adaptive and to equidistant time discretizations. For the L_p error, we prove strong asymptotic optimality for specific tamed Milstein schemes relating to certain adaptive and to equidistant time discretizations. To illustrate our findings, we numerically analyze the SDE associated with the Heston–3/2–model originating from mathematical finance.