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17th International Conference on Wirtschaftsinformatik, WI 2022

作者： Fridgen, Gilbert Halbrügge, Stephanie Körner, Marc-Fabian Michaelis, Anne Weibelzahl, Martin SnT - Interdisciplinary Center for Security Reliability and Trust University of Luxembourg Luxembourg FIM Research Center University of Augsburg Germany Project Group Business & Information Systems Engineering of the Fraunhofer FIT Germany FIM Research Center University of Bayreuth Germany

The ongoing energy transition increases the share of renewable energy sources. To combat inherent intermittency of RES, increasing system flexibility forms a major opportunity. One way to provide flexibility is demand response (DR). Research already reflects several approaches of artificial intelligence (AI) for DR. However, these approaches often lack considerations concerning their applicability, i.e., necessary input data. To help putting these algorithms into practice, the objective of this paper is to analyze, how input data requirements of AI approaches in the field of DR can be systematized from a practice-oriented information systems perspective. Therefore, we develop a taxonomy consisting of eight dimensions encompassing 30 characteristics. Our taxonomy contributes to research by illustrating how future AI approaches in the field of DR should represent their input data requirements. For practitioners, our developed taxonomy adds value as a structuring tool, e.g., to verify applicability with respect to input data requirements. © 2022 17th International Conference on Wirtschaftsinformatik, WI 2022. All rights reserved.

关键词： Taxonomies

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A Means to an End of the Other - Research Avenues at the Intersection of Organizational Digital Transformation and Digital Business Ecosystems 42

A Means to an End of the Other - Research Avenues at the Int...

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42nd International Conference on Information systems: Building Sustainability and Resilience with IS: A Call for Action, ICIS 2021 TREOs

作者： Karnebogen, Philip Oberländer, Anna Maria Rövekamp, Patrick FIM Research Center University of Augsburg Project Group Business & Information Systems Engineering of the Fraunhofer FIT Augsburg Germany

ISBN: (纸本)9781713893608

Digital technologies pose challenges and opportunities to individual and ecosystems of organizations. To date, two mostly isolated research streams study these related phenomena: Organizational digital transformation (ODT), focusing on the digital improvement process of individual incumbents and digital business ecosystems (DBEs), focusing on digitally-enabled value co-creation among organizations. Joining the forces of both research streams, our work aims to assess what empirical evidence and theory exist at their intersection. After conducting an assessing review, a theorizing review, and extracting assumptions in isolation, we derive four convergent assumptions for building future theory at their intersection along four topic areas: resources, coopetition, evolution, and control. We propose that ODT and DBEs can be a means to an end of the other connected in a cyclical relationship to meet digitally induced challenges. By presenting avenues for further research, our work builds a foundation for future theory at the intersection of ODT and DBEs. © 2021 42nd International Conference on Information systems, ICIS 2021 TREOs: "Building Sustainability and Resilience with IS: A Call for Action". All Rights Reserved.

关键词： Ecosystems

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How Sustainable is Machine Learning in Energy Applications? – The Sustainable Machine Learning Balance Sheet 17

How Sustainable is Machine Learning in Energy Applications? ...

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17th International Conference on Wirtschaftsinformatik, WI 2022

作者： Wenninger, Simon Kaymakci, Can Wiethe, Christian Römmelt, Jörg Baur, Lukas Häckel, Björn Sauer, Alexander Project Group Business & Information Systems Engineering of the Fraunhofer FIT Augsburg Germany FIM Research Center University of Applied Sciences Augsburg Augsburg Germany Fraunhofer Institute for Manufacturing Engineering and Automation IPA Stuttgart Germany Institute for Energy Efficiency in Production EEP University of Stuttgart Stuttgart Germany

Information systems play a central role in the energy sector for achieving climate targets. With increasing digitization and data availability in the energy sector, data-driven machine learning (ML) approaches emerged, showing high potential. So far, research has focused on optimizing ML approaches’ prediction performance. However, this is a one-sided perspective. ML approaches require large computation times and capacities leading to high energy consumption. With the goal of sustainable energy systems, research on ML approaches should be extended to include the application’s energy consumption. ML solutions must be designed in such a way that the resulting savings in energy (and emissions) are greater than the energy consumption caused using the ML solution. To address this need, we develop the Sustainable Machine Learning Balance Sheet as a framework allowing to holistically evaluate and develop sustainable ML solutions which we validated in a case study and through expert interviews. © 2022 17th International Conference on Wirtschaftsinformatik, WI 2022. All rights reserved.

关键词： Machine learning

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Artificial Intelligence in Radiology – A Qualitative Study on Medical Imaging Specialists’ Perspectives 42

Artificial Intelligence in Radiology – A Qualitative Study ...

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42nd International Conference on Information systems: Building Sustainability and Resilience with IS: A Call for Action, ICIS 2021 TREOs

作者： Buck, Christoph Hennrich, Jasmin Kauffmann, Anna Lina Centre for Future Enterprise Queensland University of Technology Brisbane Australia Project Group Business & Information Systems Engineering of the Fraunhofer FIT Bayreuth Germany FIM Research Center University of Bayreuth Project Group Business & Information Systems Engineering of the Fraunhofer FIT Bayreuth Germany

ISBN: (纸本)9781713893608

Artificial intelligence (AI) applications are particularly promising in the field of medical imaging. Especially in radiology, research presents various AI uses cases, highlighting AI applications' potential to improve the quality and efficiency of healthcare. Further, despite numerous research projects of AI applications, an investigation from the real-world, practice-based point of view regarding AI applications is lacking. Consequently, little is known about medical imaging specialists’ perspective on AI applications. Following the Grounded Theory Methodology, we conducted 15 semi-structured interviews with medical imaging specialists. We derived four opportunities and five concerns representing medical imaging specialists’ perspective on AI applications. © 2021 42nd International Conference on Information systems, ICIS 2021 TREOs: "Building Sustainability and Resilience with IS: A Call for Action". All Rights Reserved.

关键词： Medical imaging

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Automated process (re-)design

Automated process (re-)design

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2021 International Workshop on BPM Problems to Solve Before We Die, PROBLEMS 2021

作者： Röglinger, Maximilian Van Dun, Christopher Fehrer, Tobias Fischer, Dominik A. Moder, Linda Kratsch, Wolfgang Fim Research Center Universities of Augsburg and Bayreuth Germany Project Group Business and Information Systems Engineering Fraunhofer Fit Bayreuth Germany

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Alexa – Welcome to the Family! IT Identity's Mediating Role on Social Presence and Deep Use of In-Home Voice Assistants 42

Alexa – Welcome to the Family! IT Identity's Mediating Role...

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42nd International Conference on Information systems: Building Sustainability and Resilience with IS: A Call for Action, ICIS 2021 TREOs

作者： Diel, Sören Höger, Carolin Schick, Doreen FIM Research Center University of Bayreuth Project Group Business & Information Systems Engineering of the Fraunhofer FIT Bayreuth Germany University of Bayreuth Bayreuth Germany

ISBN: (纸本)9781713893608

Driven by artificial intelligence (AI), in-home voice assistants (VA) emerge as an integral part of an individual's everyday life. As social structures and processes expand into a digital society, information system (IS) research started to examine this intertwinement and identified information technology (IT) identity as a concept to grasp IT use behavior. However, research on IT identity in connection with VAs is rare. To close this gap, we developed and empirically tested a conceptual model (n = 322 VA users). Our results show that symbolic value and hedonic motivation strengthen IT identity, while privacy concerns relate negatively. Moreover, IT identity enhances deep use and social presence and mediates the relationship between symbolic value/hedonic motivation and deep use/social presence. Our study provides critical theoretical and practical implications regarding use behavior and social presence of in-home VAs. Moreover, we contribute to a deeper understanding of IT identity. © 2021 42nd International Conference on Information systems, ICIS 2021 TREOs: "Building Sustainability and Resilience with IS: A Call for Action". All Rights Reserved.

关键词： Information use

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The Digital ‘War for Talents’ – a Conceptual Framework of Technology-Driven Factors in Digital Personnel Selection systems 42

The Digital ‘War for Talents’ – a Conceptual Framework of...

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42nd International Conference on Information systems: Building Sustainability and Resilience with IS: A Call for Action, ICIS 2021 TREOs

作者： Berger, Stephan Niesel, Oliver Häckel, Björn Stahl, Bastian FIM Research Center University of Augsburg Germany FIM Research Center University of Applied Sciences Augsburg Project Group Business & Information Systems Engineering of the Fraunhofer FIT Germany

ISBN: (纸本)9781713893608

Driven by digitalization and accelerated by the COVID-19 pandemic, the ‘war for talents’ is increasingly shifting towards the digital world, transforming traditional personnel selection systems into information systems. While these digital personnel selection systems (DPSSs) make use of video interviews or gamified assessments to realize benefits in terms of cost-efficiency and sustainability, the use of digital technologies has a significant impact on user behaviors and selection outcomes. Against this backdrop, we present a common, interdisciplinary conceptualization of DPSSs in terms of a framework for technology-driven factors, which we inferred from a systematic literature review. Our interview-based evaluation showed that such an overview is urgently needed in research and practice. Our findings represent a theory for analyzing and add to the descriptive knowledge by providing an information systems lens on personnel selection. With this understanding of technology-driven factors, we provide a profound basis for developing user-centric DPSSs. © 2021 42nd International Conference on Information systems, ICIS 2021 TREOs: "Building Sustainability and Resilience with IS: A Call for Action". All Rights Reserved.

关键词： Information use

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Improving the Educational Value of Operating systems

Improving the Educational Value of Operating Systems

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Roedunet International Conference (RoEduNet)

作者： Cezar Sava Răzvan Deaconescu Martin Kröning Antonello Monti Dinu Turcanu Computer Science and Engineering Department POLITEHNICA of Bucharest Bucharest Romania Institute for Automation of Complex Power Systems RWTH Aachen University Aachen Germany Fraunhofer Center Digital Energy Fraunhofer FIT Aachen Germany Department of Software Engineering and Automatics Technical University of Moldova Chişinău Moldova

ISBN: (数字)9798331540388

ISBN: (纸本)9798331540395

Educational operating systems are crucial for facilitating learning in the digital age, as they exist at the intersection of technology and education. While their technical role is well understood, improving their educational value requires enhancing traditional approaches. This paper explores ways to enrich educational operating systems not just through technological advancement, but also by integrating pedagogical principles. In an ever-changing world, the need for an adaptive and responsive educational operating system to meet diverse student needs is crucial. Through case studies, we analyze how design, interactivity, and accessibility can transform these systems into effective and appealing learning environments. We propose a series of recommendations for the future development of educational operating systems, focusing on enhancing the learning experience and promoting student autonomy, thereby offering a fresh perspective on how technology and education can blend harmoniously and efficiently.

关键词： Adaptive systems Operating systems Education Focusing Transforms Information age

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Combination of Process Mining and Causal Discovery Generated Graph Models for Comprehensive Process Modeling

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Procedia CIRP 2024年 130卷 1296-1302页

作者： Christoph Hennebold Muhammad M. Islam Jonas Krauß Marco F. Huber Fraunhofer Institute for Manufacturing Engineering and Automation IPA Nobelstr. 12 70569 Stuttgart Germany Fraunhofer Institute for Ceramic Technologies and Systems IKTS Fraunhofer Technology Center for High-Performance Materials THM Am St.-Niclas-Schacht 13 09599 Freiberg Germany Project Group Process Innovation Fraunhofer Institute for Manufacturing Engineering and Automation IPA Universitätsstraße 9 95447 Bayreuth Germany Institute for Industrial Manufacturing and Management IFF University of Stuttgart Allmandring 35 70569 Stuttgart Germany

The extraction of process knowledge and its use for modeling and subsequent analysis is a very valuable approach to optimizing processes. Process Mining (PM) methods are widely used knowledge extraction techniques based on process knowledge recorded in event logs. One shortcoming is that PM approaches cannot easily access data in non-event log format, and secondly, that models are generated using directly-follows relations, which in the case of processes with concurrent activities means that process transitions may not be modeled correctly, and the resulting models do not correspond to reality as well as being unnecessarily complex. In addition, increasing digitization in manufacturing enables an ever greater collection of various data sources throughout the process with varying levels of information. Besides PM, in recent years great progress has been made in learning causal structures via causal discovery (CD) as well as in explicitly using additional expert knowledge. We argue that CD and expert knowledge are valuable additions to existing PM based approaches, as they allow knowledge extraction and modeling on different process levels. To combine these levels of information, this paper uses a manufacturing use case to show heterogeneous data sources and expert knowledge are used to create hybrid models. The results show that the combination of data-driven modeling methods with expert knowledge help to compensate for the weaknesses of the individual methods and achieve better overall results.

关键词： Process Mining Causal Discovery Domain Knowledge Hybrid Modeling

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Pushing the frontiers of service research - A taxonomy of proactive services

Pushing the frontiers of service research - A taxonomy of pr...

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2020 International Conference on Information systems - Making Digital Inclusive: Blending the Local and the Global, ICIS 2020

作者： Rau, Daniel Röglinger, Maximilian Perlitt, Luise-Henriette Wenninger, Annette FIM Research Center University of Augsburg Augsburg Germany Project Group Business and Information Systems Engineering Fraunhofer FIT Bayreuth Germany FIM Research Center University of Bayreuth Bayreuth Germany

ISBN: (纸本)9781733632553

Rapid advancements in digital technologies and data analysis led to a new service type. With their push-rationale, proactive services (PAS) are pushing the frontiers of traditional and even digital or smart services. Such PAS anticipate consumer needs and address them proactively. For instance, a smart fridge replenishes groceries in line with the consumer's preferences, based on anticipated demand, and without the consumer's intervention. In this paper, we contribute to a better understanding of the PAS phenomenon. Therefore, we propose a literature-backed and empirically validated multilayer taxonomy of PAS along the layers consumer, data, and interaction. Further, we compile a list of 45 PAS examples, demonstrate our taxonomy with three illustrative scenarios, and evaluate their understandability and applicability in seven interviews with domain and method experts. Based on gained insights on this rapidly emerging and important phenomenon, we highlight implications for both researchers and practitioners, and suggest future research directions. © ICIS 2020. All rights reserved.

关键词： Taxonomies

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