The usage of language models for human assistance in production failure root cause analysis

Downtimes (outages) are unfavorable and costly events in production. Although approaches exist, they have to be implemented mainly manually and with a huge effort. Language models could be useful to support the production root cause failure analysis and help to get production up and running again more quickly. However, sparse research focused on this point so far. Therefore, it is still unclear how the usage of language models for human assistance in production failure root case analysis should be implemented. A qualitative expert study was conducted to reveal the potentials of such an approach and to find suitable use cases for language models. Based on the insights triggering factors, use cases as well as benefits and risks were identified and summarized within a model

Virtual influencers in B2B marketing : future perspectives

This study explores the potential role of virtual influencers in future B2B marketing. Combining expert interviews and a literature review, the findings reveal the growing popularity of virtual influencers due to Web 3.0 and Metaverse advancements. The study suggests that virtual influencers may revolutionize brand-customer interactions in the digital space, with implications for B2B marketing strategies

Projektorientierte Hochschullehre im Labor „Financial and Actuarial Data Science“ am Beispiel eines „Robo Advisor“- Projekts

Egal ob es um frühere Studieninhalte geht, um unsere Aktuarausbildung oder aber um Weiterbildungen: Alle von uns haben sicher schon mal die Erfahrung gemacht, dass es schwerfallen kann, das gelernte im Alltag konkret umzusetzen. Unabhängig davon, wie interessant das Thema und die Lehrveranstaltung im Moment des Besuchs auch waren. Monate später trifft man in einem anderen Kontext wieder auf die Lerninhalte, und es drängt sich der Gedanke auf „das habe ich schon mal gehört“, ohne aber jemals selbst einen praxisrelevanten Anwendungsbezug hergestellt zu haben. Aus Sicht der Lehre stellt sich die Frage, wie diese gestaltet werden kann, sodass nicht überwiegend solches „träges Wissen“ (vgl. z. B. (Seibert, et al., 2019)) entsteht, sondern vielmehr konkret anwendbares Wissen, das direkt zur Problemlösung eingesetzt werden kann und eingesetzt wird

Leadership in scholarship: editors' appointments and scientific narrative

Academic journals disseminate new knowledge and therefore can influence the direction and composition of ongoing research by choosing what to publish. We study the change in the topic structure of papers published in the American Economic Review (AER) after the appointments of editors and coeditors of the AER between 1985 and 2011 using a textual analysis of accepted publications. The change due to the appointment of new AER editors, we find, is not an indicator of editors' personal taste in topics, but rather indicates the desire of those who appoint editors to premediate trends in other Top 5 journals

Controlling fibrinogen adsorption on polyelectrolyte multilayer films by modifying self-assembly conditions

This study investigates the relationship between fibrinogen adsorption on polyelectrolyte multilayer (PEM) films and their surface properties. The films were constructed using weak polyelectrolytes, poly(acrylic acid) (PAA), and poly(allylamine hydrochloride) (PAH), with polyethyleneimine (PEI) as a precursor layer. Different deposition conditions, such as pH levels (3.5 and 7.0) and the type of outermost layer (PAA or PAH), were used to create films with tunable hydrophilicity and surface charge. The thickness of these films was measured using ellipsometry, and surface wettability was assessed via the contact angle method. Fibrinogen adsorption was quantified using quartz crystal microbalance with dissipation monitoring (QCM-D) and enzyme immunoassay (EIA) method, focusing on its D-domain exposure concerning surface thrombogenicity. Results indicated that PEM films are generally hydrophilic. Among them, PAH, the outermost layer, is the least hydrophilic and, therefore, has the lowest surface energy. Film thickness varied with the pH of the solutions, creating a mechanism to control layer parameters. Fibrinogen adsorption was more pronounced on less hydrophilic surfaces, which were thinner, viscoelastic, more hydrated, and preferentially positively charged. These findings suggest that by controlling surface properties, one can enhance hemocompatibility by influencing fibrinogen adsorption and subsequent platelet adhesion and activation

Towards generating measurable artifact models from standards in regulated domains

Software and systems development projects in regulated domains need to provide evidence on their compliance to standards. Such standards often come as comprehensive documentation, i.e., documents, which need to be tailored to and interpreted for a particular project. Utilizing such documentations, it is desirable for companies working in regulated domains to provide tool support with regard to measurement systems that, eventually, help determine the product’s quality and to support the compliance analysis. In this paper, we present an AI-supported approach to use a standard’s documentation for generating artifact models. Such models are generated in a machine-readable format and, therefore, help companies create measurable items to be included in their metrication and measurement systems. Using selected ECSS standards from the European Space Agency as cases, we present our approach, the prompt engineering for the extraction of artifacts, and we illustrate the opportunities to generate comprehensive artifact models. Our findings show that, given sufficient information is available, the generation of artifact models is possible to a large degree with an average completeness of 99.64% and an average precision of 67.52% thus laying the foundation for building more efficient measurement systems

Enhancing transparency in space metrics use : insights from an initial study

Software has become a key component in spacecraft development. Due to the size and complexity of spacecraft development projects, multiple project stakeholders need to coordinate and exchange development data that must be integrated to provide a big picture. In this context, metrics as for instance defined in the standards such as the European Cooperation for Space Standardization (ECSS) are important. To provide benefits, transparency and clear information regarding the selection and use of software metrics is critical. A lack of transparency and comprehensibility of the process for selecting and collecting key figures by the actors can lead to risks, e.g., important data is not collected or is collected incorrectly. In this paper, to support the streamlined AENEAS measurement tool chain, we developed a tool that helps manage and configure measurement packages that include agreed metrics to be collected in spacecraft development projects. To evaluate the tool, we populated it with 43 metrics from the ECSS-Q-HB-80-04A standard and used it in a case study within a student project. The case study revealed that while the tool facilitated the selection and definition of project metrics, its overall usefulness and clarity received mixed reviews, indicating the need for further improvements

Elicitation and documentation of explainability requirements in a medical information systems context

Ongoing research indicates the importance of explainabilty as it provides the rationale for results and decision of information systems to users. Explainability must be considered and implemented in software at the early stage in requirements engineering (RE). For the completeness of software requirements specifications, the elicitation and documentation of explainability requirements is essential. Although there are existing studies on explainability in RE, it is not clear yet, how to elicit and document such requirements in detail. Current software development projects miss a clear guidance, how explainability requirements should be specified. Through a review of literature, existing works for elicitation and documentation of explainability requirements are analyzed. Based on these findings, a template and additional guiding for capturing explainability requirements is developed. Following a design science approach, the template is applied and improved in a research project of the medical information domain. The overview of related work presents the current state of research for the documentation of explainability requirements. The template and additional guiding can be used in other information system context for RE elicitation and documentation. The application of the template and the elicitation guidance in a real world case show the refinement and an improved completeness of existing requirements

Handbuch behavioral finance : mit Wissens-Check

Die Autoren schlagen zunächst den Bogen von der neoklassischen Sicht der Finanzmärkte zur Behavioral Finance. Anschließend werden spekulative Blasen als Anzeichen für begrenzte Rationalität ausführlich vorgestellt. Die Anlageentscheidungen an Wertpapiermärkten werden entsprechend ihrer Risiko-/Renditeschädlichkeit eingeordnet. Abschließend werden Beispiele aus dem Wealth Management und Corporate Governance diskutiert sowie ein Blick auf aktuelle Entwicklungen der Neuro-Finance und Emotional Finance geworfen. Zur Neuauflage: Das Grundkonzept des Buches bleibt unverändert. Es richtet sich nach wie vor sowohl an Studierende als auch an Interessierte aus der Praxis. Die Autoren haben aktuelle Informationen hinzugefügt und die Lesbarkeit weiter erhöht. Dies gilt insbesondere für Kapitel 5 zu historischen und jüngsten Spekulationsblasen und für Kapitel 13 zu den neuesten Entwicklungen. Zahlreiche Grafiken, Merksätze und Zusammenfassungen nach jedem Kapitel helfen beim Verständnis

Generative artificial intelligence in business planning and financial budgeting

Corporate planning and financial budgeting are essential for companies to achieve their long-term objectives. While the application of other technologies such as Robotic Process Automation (RPA) in planning and budgeting is already a well-established practice, the potential advantages of incorporating generative artificial intelligence (GenAI), specifically Large Language Models (LLMs) in the domain of planning and budgeting remain rather unclear. Hence, the aim of this research has been to identify potential use cases and review the current state of the discussion. A Multivocal Literature Review (MLR) was conducted to analyze and evaluate both academic and non-academic sources. The literature highlights the transformative potential of GenAI in enhancing business planning and financial budgeting through natural language interfaces, enabling users to access, analyze, and interpret data more effectively. However, the findings also show a gap in the existing academic literature and indicate that some grey literature sources may have to be interpreted with caution. Therefore, further research is required to fully understand and leverage the benefits of GenAI in corporate planning and budgeting