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17th International Conference on Wirtschaftsinformatik, WI 2022

作者： Blaß, Marlene Graf-Drasch, Valerie Schick, Doreen Project Group Business & Information Systems Engineering of the Fraunhofer FIT Germany Digital Management University of Hohenheim Germany FIM Research Center Project Group Business & Information Systems Engineering of the Fraunhofer FIT Germany

Death and grief are going digital. Start-up companies are working on avatars that people feed with personal information while alive so that relatives can communicate with this artificial self after death. This is supposed to make it easier to say goodbye. Considering these digital innovations, the IS community should be the leading discipline for handling grief. However, IS scholars attribute grief to other disciplines, such as psychology. Like any crisis, also grief cannot be merited to one single discipline. We conduct a literature review and synthesis alongside the ‘BAO framework’ [1]. Findings suggest that IS research has so far not grasped the consequences of grief on either individual or organizational and societal levels. To spark future research, we propose 9 clear-cut IS research questions. The provided comprehensive understanding of IS intersecting grief is crucial for different (also practical) stakeholders to leverage the potential of IS in coping with grief. © 2022 17th International Conference on Wirtschaftsinformatik, WI 2022. All rights reserved.

关键词： bereavement grief literature review mourning research agenda

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Improving the Educational Value of Operating systems 23

Improving the Educational Value of Operating Systems

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23rd RoEduNet Conference: Networking in Education and Research, RoEduNet 2024

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

ISBN: (纸本)9798331540388

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. © 2024 IEEE.

关键词： Contrastive Learning

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A Literature Review on the Risks and Potentials of Tracking and Monitoring eHealth Technologies in the Context of Occupational Health Management 17

A Literature Review on the Risks and Potentials of Tracking ...

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17th International Conference on Wirtschaftsinformatik, WI 2022

作者： Hall, Kristina Oesterle, Severin Watkowski, Laura Liebel, Sabrina University of Bayreuth Bayreuth Germany Research Center Finance & Information Management Fraunhofer Project Group Business & Information Systems Engineering Bayreuth Germany

Employee health is increasingly important, as is the use of eHealth technologies in the private and the organizational context. This paper examines which existing eHealth technologies that support monitoring and tracking of health are applied in occupational health management (OHM) and investigates the advantages and disadvantages of their application. To pursue this intention, we analyze the current state of research with a structured literature review and provide a comprehensive overview of relevant works. The results point out advantages and disadvantages that provide the groundwork to discuss success factors for tracking and monitoring eHealth technologies in OHM. The derived success factors aim at operational, technological, operational/technological aspects of eHealth tracking and monitoring usage. Thereby, favorable outcomes such as an increase in employee health can be achieved, and participation in OHM measures can be increased. However, it can also lead to adverse outcomes such as a reduced work-life balance. © 2022 17th International Conference on Wirtschaftsinformatik, WI 2022. All rights reserved.

关键词： Industrial hygiene

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Demystifying Industrial Internet of Things start-ups – A multi-layer taxonomy 17

Demystifying Industrial Internet of Things start-ups – A mu...

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17th International Conference on Wirtschaftsinformatik, WI 2022

作者： Jonas, Claudius M. Oberländer, Anna M. Schmitt, Kevin Wethmar, Simon FIM Research Center University of Bayreuth Germany Project Group Business & Information Systems Engineering of the Fraunhofer FIT Bayreuth Germany University of Bayreuth Germany

Described as a fundamental paradigm shift by researchers, the Industrial Internet of Things (IIoT) is credited with massive potential. In the context of emerging technologies, such as the IIoT, start-ups occupy a crucial role, as new technologies are often first commercialized by start-ups. Because of the rising importance of IIoT start-ups as drivers of industrial innovation, IIoT solutions demand deepened theoretical insights. As existing classification schemes in the industrial context do not sufficiently account for the ever more critical role of IIoT start-ups, we present a multi-layer taxonomy of IIoT start-up solutions. Building on state-of-the-art literature and a sample of 78 real-world IIoT start-up solutions, the taxonomy comprises ten dimensions and related characteristics structured along the three layers solution, data, and business model. The taxonomy contributes to the descriptive knowledge on the IIoT and enables researchers and practitioners to better understand IIoT start-up solutions. © 2022 17th International Conference on Wirtschaftsinformatik, WI 2022. All rights reserved.

关键词： Internet of things

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Combination of Process Mining and Causal Discovery Generated Graph Models for Comprehensive Process Modeling 57

Combination of Process Mining and Causal Discovery Generated...

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18th IFAC Workshop on Time Delay systems, TDS 2024

作者： Hennebold, Christoph Islam, Muhammad M. Krauß, Jonas Huber, Marco F. Fraunhofer Institute for Manufacturing Engineering and Automation IPA Nobelstr. 12 Stuttgart70569 Germany Institute for Industrial Manufacturing and Management IFF University of Stuttgart Allmandring 35 Stuttgart70569 Germany Project Group Process Innovation Fraunhofer Institute for Manufacturing Engineering and Automation IPA Universitätsstraße 9 Bayreuth95447 Germany Fraunhofer Institute for Ceramic Technologies and Systems IKTS Fraunhofer Technology Center for High-Performance Materials THM Am St.-Niclas-Schacht 13 Freiberg09599 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. © 2024 The Authors.

关键词： Knowledge graph

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Beyond the beaten paths of forecasting call center arrivals: on the use of dynamic harmonic regression with predictor variables

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Journal of Business Economics 2022年第4期92卷 675-706页

作者： Rausch, Theresa Maria Albrecht, Tobias Baier, Daniel University of Bayreuth Universitätsstraße 30 Bayreuth 95447 Germany FIM Research Center University of Bayreuth and Project Group Business & Information Systems Engineering of the Fraunhofer FIT Bayreuth Germany

Modern call centers require precise forecasts of call and e-mail arrivals to optimize staffing decisions and to ensure high customer satisfaction through short waiting times and the availability of qualified agents. In the dynamic environment of multi-channel customer contact, organizational decision-makers often rely on robust but simplistic forecasting methods. Although forecasting literature indicates that incorporating additional information into time series predictions adds value by improving model performance, extant research in the call center domain barely considers the potential of sophisticated multivariate models. Hence, with an extended dynamic harmonic regression (DHR) approach, this study proposes a new reliable method for call center arrivals’ forecasting that is able to capture the dynamics of a time series and to include contextual information in form of predictor variables. The study evaluates the predictive potential of the approach on the call and e-mail arrival series of a leading German online retailer comprising 174 weeks of data. The analysis involves time series cross-validation with an expanding rolling window over 52 weeks and comprises established time series as well as machine learning models as benchmarks. The multivariate DHR model outperforms the compared models with regard to forecast accuracy for a broad spectrum of lead times. This study further gives contextual insights into the selection and optimal implementation of marketing-relevant predictor variables such as catalog releases, mail as well as postal reminders, or billing cycles. © 2021, The Author(s).

关键词： Call center arrivals Customer relationship management Dynamic harmonic regression Forecasting Machine learning Time series analysis

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The Human Factor in Blockchain Ecosystems: A Sociotechnical Framework 17

The Human Factor in Blockchain Ecosystems: A Sociotechnical ...

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17th International Conference on Wirtschaftsinformatik, WI 2022

作者： Brennecke, Martin Guggenberger, Tobias Sachs, Alexander Schellinger, Benjamin FIM Research Center Project Group Business & Information Systems Engineering of the Fraunhofer FIT University of Bayreuth Bayreuth Germany Nova School of Business & Economics Lisbon Portugal

As blockchain development continues at an ever-increasing pace, an increasing number of individual actors and organizations throughout entire economies get into contact with the technology. Furthermore, the growing collaboration of companies, customers, suppliers, and other actors is evolving into a multilateral network between the parties engaged with the technology. Therefore, to understand blockchain-based business models and innovations, it is necessary to understand human interactions within blockchain ecosystems. Consequently, this paper offers new insights concerning the role of human actors within blockchain ecosystems. For this purpose, the structure within and around the Ethereum-blockchain is analyzed using existing literature on the Ethereum ecosystem and Sociotechnical systems. The analysis results are then placed in their context and summarized in a framework for comparable ecosystems. © 2022 17th International Conference on Wirtschaftsinformatik, WI 2022. All rights reserved.

关键词： Ecosystems

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Electricity Markets in a Time of Change: A Call to Arms for Business Research

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Schmalenbach Journal of Business Research 2022年第1期74卷 77-102页

作者： Bichler, Martin Buhl, Hans Ulrich Knörr, Johannes Maldonado, Felipe Schott, Paul Waldherr, Stefan Weibelzahl, Martin Department of Informatics Technical University of Munich Boltzmannstr. 3 Garching 85748 Germany FIM Research Center Project Group Business & Information Systems Engineering of the Fraunhofer FIT Alter Postweg 101 Augsburg 86159 Germany FIM Research Center University of Bayreuth Project Group Business & Information Systems Engineering of the Fraunhofer FIT Wittelsbacherring 10 Bayreuth 95444 Germany School of Business and Economics Vrije Universiteit Amsterdam De Boelelaan 1105 Amsterdam 1081 HV Netherlands

Europe’s clean energy transition is imperative to combat climate change and represents an economic opportunity to become independent of fossil fuels. As such, the energy transition has become one of the most important, but also one of the most challenging economic and societal projects today. Electricity systems of the past were characterized by price-inelastic demand and only a small number of large electricity generators. The transition towards intermittent renewable energy sources changes this very paradigm. Future electricity systems will consist of many thousands of electricity generators and consumers that actively participate in markets, offering flexibility to balance variable electricity supply in markets with a high spatial and temporal resolution. These structural changes have ample consequences for market operators, generators, industrial consumers as well as prosumers. While a large body of the literature is devoted to the energy transition in engineering and the natural sciences, it has received relatively little attention in the recent business research literature, even though many of the central challenges for a successful energy transition are at the core of business research. Therefore, we provide an up-to-date overview of key questions in electricity market design and discuss how changes in electricity markets lead to new research challenges in business research disciplines such as accounting, business & information systems engineering, finance, marketing, operations management, operations research, and risk management. © 2021, The Author(s).

关键词： Demand response Electricity market design Energy transition Renewable energy sources

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Life is a Journey in Smart and Sustainable Districts 17

Life is a Journey in Smart and Sustainable Districts

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17th International Conference on Wirtschaftsinformatik, WI 2022

作者： Graf-Drasch, Valerie Meindl, Oliver Voucko-Glockner, Hannes Digital Management University of Hohenheim Stuttgart Germany Project Group Business & Information Systems Engineering of the Fraunhofer FIT Augsburg Germany FIM Research Center University of Augsburg Augsburg Germany

Worldwide, cities grapple with the expectation of putting the brakes on climate change. Before acting, smart districts often serve as a testing bed for strategies towards carbon-neutrality. If effective, scale-up agendas at city-level are formulated. Smart districts are touted for their sustainability lever, as their core rationale is encouraging residents to use ‘smart energy technologies’ which increase efficiency or integrate renewable energy sources. The primary focus of these districts is on technical implementations of available sustainability services instead of orienting their service-portfolio around citizens. The result is a mismatch of supply and demand of sustainability-inducing services. We take in a customer journey perspective when searching for literature and conducting qualitative interviews. Results reveal a framework for mapping service touchpoints into citizen journeys. The framework is meant to benefit district planners to tailor their service selection to meet their citizens’ needs and exploit the district’s sustainability potential at the citizen interface. © 2022 17th International Conference on Wirtschaftsinformatik, WI 2022. All rights reserved.

关键词： Sustainable development

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IoT Ethics - Status Quo and Directions for Further Research 42

IoT Ethics - Status Quo and Directions for Further Research

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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： Bayer, Sarah FIM Research Center University of Augsburg Project Group Business & Information Systems Engineering of the Fraunhofer FIT Germany

ISBN: (纸本)9781713893608

As one of the most disruptive technology, IoT spreads in numerous areas of our lives and its potential is estimated with enormously high digits. Although discussions about ethics of emerging technologies are at the forefront, e.g., for artificial intelligence, IoT specific ethical considerations remain crucial, but scarce. Based on a structured literature review, this research identifies and structures ethical issues of IoT, provides an overview of the current state of research for each aspect, and relates each aspect to IoTs features. Based on these results, concrete options for further research are provided, including suggestions for an examination of the transferability of known ethical issues from other technologies to IoT, identification of further ethical issues based on features and applications of IoT, a thorough examination of know ethical issues, and a positive view on IoT ethics. The results raise awareness for an intense examination of IoT ethics in research and practice. © 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： Internet of things

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