Fraunhofer-Institut für Angewandte Informationstechnik FIT

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  • Publication
    Managing artificial intelligence applications in healthcare: Promoting information processing among stakeholders
    ( 2024-04)
    Hofmann, Peter
    ;
    Lämmermann, Luis
    ;
    Urbach, Nils
    AI applications hold great potential for improving healthcare. However, successfully operating AI is a complex endeavor requiring organizations to establish adequate management approaches. Managing AI applications requires functioning information exchange between a diverse set of stakeholders. Lacking information processing among stakeholders increases task uncertainty, hampering the operation of AI applications. Existing research lacks an understanding of holistic AI management approaches. To shed light on AI management in healthcare, we conducted a multi-perspective literature analysis followed by an interview study. Based on the organizational information processing theory, this paper investigates AI management in healthcare from an organizational perspective. As a result, we develop the AI application management model (AIAMA) that illustrates the managerial factors of AI management in healthcare and its interrelations. Furthermore, we provide managerial practices that improve information processing among stakeholders. We contribute to the academic discourse by providing a conceptual framework that increases the theoretical understanding of AI's management factors and understanding of management interrelations. Moreover, we contribute to practice by providing management practices that promote information processing and decrease task uncertainty when managing AI applications in healthcare.
  • Publication
    Consumer-centric electricity markets: Six design principles
    ( 2024-03)
    Michaelis, Anne
    ;
    Hanny, Lisa-Maria
    ;
    Körner, Marc-Fabian
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    Strüker, Jens
    ;
    Weibelzahl, Martin
    Key to the necessary decarbonization of energy systems is the large-scale expansion of renewable energy sources and their integration into the electricity system. This integration is challenging because the feed-in from renewable energy sources is highly intermittent and largely dependent on uncontrollable factors such as weather patterns. To maintain grid stability, which refers to the required balance between demand and supply in the electricity system, flexibility is key. Large flexibility potentials can be found on the electricity demand side. However, current electricity market design in Europe, while providing major flexibility incentives, often neglects small-scale electricity consumers and distributed energy resources. We contribute to shape future electricity markets with consumers at the heart by developing six design principles for a consumer-centric electricity market design. We proceed by conducting a systematic literature review and evaluate the findings by expert interviews. Based on the developed design principles, we define a consumer-centric electricity market design as a set of market rules that align with the rules of other relevant energy markets and allow for the efficient matching of electricity demand and supply, with consumers having nondiscriminatory market access, being exposed to fine-grained price signals, being able to express their preferences, and having sufficient possibilities to protect themselves against unexpected price spikes. By actively incorporating consumers into electricity markets, we contribute to the overarching goal of integrating renewable energy sources while promoting energy justice, i.e., supporting a balanced mix of economic, political, environmental, and social interests.
  • Publication
    Fake it till you make it: Synthetic data for emerging carsharing programs
    ( 2024)
    Albrecht, Tobias
    ;
    Keller, Robert
    ;
    Rebholz, Dominik
    ;
    Röglinger, Maximilian
    Carsharing is an integral part of the transformation toward flexible and sustainable mobility. New carsharing programs are entering the market to challenge large operators by offering innovative services. This study investigates the use of generative machine learning models for creating synthetic data to support carsharing decision–making when data access is limited. To this end, it explores the evaluation, selection, and implementation of leading-edge methods, such as generative adversarial networks (GANs) and variational autoencoders (VAEs), to generate synthetic tabular transaction data of carsharing trips. The study analyzes usage data of an emerging carsharing program that is expanding its services to include free-floating electric vehicles (EVs). The results show that augmenting real training data with synthetic samples improves predictive modeling of upcoming trips by up to 4.63%. These results support carsharing researchers and practitioners in generating and leveraging synthetic mobility data to develop solutions to real-world decision support problems in carsharing.
  • Publication
    Smartphone-Enabled Predictive Maintenance - Development and Implementation of a Reference Architecture and Processes
    ( 2024)
    Jonas, Claudius
    ;
    König, Ulrich
    ;
    Röglinger, Maximilian
    Predictive maintenance (PdM) is a hot topic in the field of manufacturing. However, its industry-wide realization lacks accepted integration concepts. Small and medium-sized enterprises (SMEs), in particular, tend to postpone PdM initiatives, primarily due to the high costs and effort of creating interoperability with established as well as in-use machines. PdM requires machine data to be proactively maintained. Therefore, in-use machines without integrated sensors must be replaced or cost-intensively upgraded. Furthermore, it is not advisable to invest in upgrades of existing machines, as they are cost-intensive, and their remaining lifespan is unknown as well as difficult to predict. One promising approach to applying PdM to these kinds of machines is the use of retail smartphones. With up to 16 sensors onboard, they offer an opportunity to cost-effectively collect required data without being tied to a single machine. Following a design science research approach, we present a reference software architecture consisting of a mobile and server application and reference processes for smartphone-enabled PdM to provide a lightweight approach, especially for SMEs. Together with five manufacturers and a software developer, we demonstrated and evaluated our artifacts using the software prototypes in a real-world setting.
  • Publication
    Vergleich zweier Ansätze zur Bekämpfung der kalten Progression: Tarifverschiebung vs. einkommensteuerpflichtige Kopfpauschale
    ( 2024)
    Broer, Michael
    ;
    Stöwhase, Sven
    Die Bundesregierung hat im Jahr 2022 das Inflationsausgleichsgesetz verabschiedet, das zum Ausgleich der kalten Progression in der Einkommensteuer sowohl den Grundfreibetrag erhöht als auch die übrigen Tarifeckpunkte anpasst. Bei dem in Gesetzentwürfen verpflichtenden Hinweis auf Alternativen steht "keine". Doch es gibt sehr wohl eine Alternative zur Tarifverschiebung, schreiben Michael Broer und Sven Stöwhase. Sie besteht darin, allein den Grundfreibetrag zu erhöhen, was gemäß höchstrichterlicher Rechtsprechung zwingend notwendig ist. Die fiskalischen Einnahmen, die durch den Verzicht auf eine Anpassung der übrigen Tarifeckpunkte zustande kommen, werden dann über eine steuerpflichtige Kopfpauschale an die Steuerpflichtigen ausgeschüttet, ähnlich wie im Fall der Energiepauschale im Jahr 2022. Es zeigt sich beim Vergleich, dass gerade einkommensschwache Steuerzahler, die von der Inflation aktuell besonders belastet werden, von einer Kopfpauschalenlösung profitieren würden.
  • Publication
    Digital Facilitation of Group Work to Gain Predictable Performance
    ( 2024)
    Gimpel, Henner
    ;
    Lahmer, Stefanie
    ;
    Wöhl, Moritz
    ;
    Graf-Drasch, Valerie
    Group work is a commonly used method of working, and the performance of a group can vary depending on the type and structure of the task at hand. Research suggests that groups can exhibit "collective intelligence" - the ability to perform well across tasks - under certain conditions, making group performance somewhat predictable. However, predictability of task performance becomes difficult when a task relies heavily on coordination among group members or is ill-defined. To address this issue, we propose a technical solution in the form of a chatbot providing advice to facilitate group work for more predictable performance. Specifically, we target well-defined, high-coordination tasks. Through experiments with 64 virtual groups performing various tasks and communicating via text-based chat, we found a relationship between the average intelligence of group members and their group performance in such tasks, making performance more predictable. The practical implications of this research are significant, as the assembly of consistently performing groups is an important organizational activity.
  • Publication
    How influencing factors of intention to use smart watches changed in pandemic times in Germany - a comparison
    ( 2024)
    Hall, Kristina
    ;
    Oesterle, Severin
    ;
    Watkowski, Laura
    ;
    Buck, Christoph
    The use of smart wearables, especially smart watches, has increased significantly in recent years. Driven by the COVID-19 pandemic, personal self-Tracking has never been more relevant. However, it is not yet clear which factors, functional or non-functional, influence the pre-Adoption of smart watches and to what extent the COVID-19 pandemic has changed their weighting. To address this research gap, we reviewed the relevant literature and subsequently developed a conceptual model based on existing acceptance models and analysed our online empirical data using structural equation modelling. Our findings reveal significant differences over time, mainly driven by non-functional characteristics (i.e., perceived aesthetics, perceived price, perceived enjoyment). In addition, fashion consciousness seems to influence the relationship between perceived haptics and intention to use during pandemic times. Our findings shed light on the importance of contextual behavioural changes on technology use and provide practical and theoretical implications for manufacturers, users, and society.
  • Publication
    The Twin Transformation Butterfly: Capabilities for an Integrated Digital and Sustainability Transformation
    ( 2024)
    Christmann, Anne-Sophie
    ;
    Crome, Carlotta
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    Graf-Drasch, Valerie
    ;
    Oberländer, Anna Maria
    ;
    Schmidt, Leonie
    Complex digitalization and sustainability challenges shape today’s management agendas. To date, the dedication of Information Systems research to both challenges has not been equal in terms of effort and reward. Building capabilities to leverage the synergetic potential of digital and sustainability transformation may enhance organizational performance and imply new value creation for the common good. To uncover such synergetic potential, this work conceptualizes the “twin transformation” construct as a value-adding reinforcing interplay between digital transformation and sustainability transformation efforts that improve an organization by leveraging digital technologies to enable sustainability and to guide digital progress by leveraging sustainability. The twin transformation conceptualization is complemented with a capability framework for twin transformation drawing from dynamic capability theory. This work contributes to descriptive knowledge of the interplay between digital transformation and sustainability transformation, setting a foundation for further theorizing on twin transformation and enabling organizations to twin transform.
  • Publication
    Exploring decentralized data management: a case study of changing energy suppliers in Germany
    ( 2024)
    Rülicke, Linda
    ;
    Fehrle, Florian
    ;
    Martin, Arne
    ;
    Monti, Antonello
    ;
    Berkhout, Volker
    ;
    Warweg, Oliver
    ;
    Möller, Sven
    This paper presents an innovative approach to decentralized data management in the German energy market, focusing on the use of decentralized data management with the help of Data Spaces to facilitate the automated change of energy suppliers within 24 h. The central focus of this research is the MakoMaker Space, a demonstrator project that employs the Connector from the Eclipse Data Space Components. The MakoMaker project demonstrates the successful automation of energy supplier changes, emphasizing the preservation of customer data sovereignty. It shows an alternative approach to the process, putting the customer into the center. Customers retain control of their data, which is accessible to providers as needed. While the paper discusses the potential for further enhancements, such as the integration of an identity provider and the development of a sustainable business model for service coordination, the primary focus is on the demonstrator’s successful application in a pilot setting.
  • Publication
    Presenting the lighthouse of energy transition "STADTQUARTIER 2050"
    ( 2024)
    Görres, Jürgen
    ;
    Kühl, Simeon
    ;
    Siegl, Melissa
    ;
    Erhorn-Kluttig, Heike
    ;
    Lenz, Katrin
    ;
    Gimpel, Henner
    ;
    Graf-Drasch, Valerie
    ;
    Roser, Annette
    ;
    Schakib-Ekbatan, Karin
    ;
    Ressel, Anneka
    The state capital Stuttgart and the large district city Überlingen on Lake Constance are working together with eleven other partners on the lighthouse project "STADTQUARTIER 2050" on converting two urban residential districts in a socially responsible, climate-neutral way and transferring the concepts to other quarters. In addition to the demonstration districts, the project partners are working on technological issues, on the socio-scientific accompaniment of the implementation and are developing four different tools for application in city districts.