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40th International Conference on Information systems, ICIS 2019

作者： Guggenmos, Florian Hofmann, Peter Fridgen, Gilbert Project Group Business and Information Systems Engineering of the Fraunhofer FIT University Bayreuth Wittelsbacherring 10 Bayreuth95444 Germany FIM Research Center University of Bayreuth Project Group Business and Information Systems Engineering of the Fraunhofer FIT Wittelsbacherring 10 Bayreuth95444 Germany

ISBN: (纸本)9780996683197

IT project portfolios, consisting of IT projects, also interact with the entire IT landscape. In case of a failure of only one element, existing dependencies can lead to a cascade failure, which can cause high losses. Despite the present effects of systemic risk, research into IT portfolio management lacks suitable methods to quantitatively assess systemic risk. We follow the design science research paradigm to develop and evaluate our 'on track' or 'in difficulty' (TD) method by applying the SI model, representing a recognized network diffusion model in epidemiology, in an IT portfolio context. We evaluate our method using a real-world dataset. We introduce a criticality measure for diffusion models in IT portfolios and compare the TD method's results and the alpha centrality to human judgment as a benchmark. From our evaluation, we conclude that the TD method outperforms alpha centrality and is a suitable risk measure in IT portfolio management. © 40th International Conference on Information systems, ICIS 2019. All rights reserved.

关键词： Epidemiology

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A contingency lens on cloud provider management processes

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Business Research 2020年第3期13卷 1451-1489页

作者： Oesterle, Severin Jöhnk, Jan Keller, Robert Urbach, Nils Yu, Xin FIM Research Center University of Bayreuth Bayreuth Germany Project Group Business & Information Systems Engineering of the Fraunhofer FIT Bayreuth Germany Faculty of Tourism Management University of Applied Sciences Kempten Kempten Germany Faculty of Business and Law Frankfurt University of Applied Sciences Frankfurt Germany University of Bayreuth Bayreuth Germany

Traditional ways of managing information technology (IT) service providers are no longer applicable as companies use more and more services provisioned in the cloud. Therefore, organizations are looking for new ways to manage their relationship with cloud providers. The shift from IT-as-a-product to IT-as-a-service puts clients in a continued dependency on cloud service providers (CSPs), making provider management a critical factor for companies’ success. In this paper, we (1) identify cloud-specific challenges in managing CSPs, (2) develop a corresponding process framework for CSP management, and (3) discuss and extend this framework. Our final cloud management framework comprises ten processes for effective CSP management based on a literature study and twelve expert interviews. Furthermore, we unpack three major contingency factors, i.e., client–provider ratio, specificity, and service delivery model, which influence the reasonability and configuration of the cloud management processes. Drawing on two specific cases from our interview study, we explicate the contingency factors’ influence. Thus, our paper contributes to cloud sourcing research by deepening the understanding of client–provider relationships and by introducing a viable CSP management instrument contingent on three salient factors of cloud service provisioning. © 2020, The Author(s).

关键词： Cloud computing Cloud sourcing Contingency theory Interview study IT sourcing Provider management

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Development of Cfd Model for Cryogenic Liquid Rocket Injectors and Validation with Experiments

SSRN

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SSRN 2022年

作者： Sujithkumar, Raghavan Pillai Chenthil Kumar, K. Anil Kumar, K.R. Jayachnadran, T. Bodi, Kowsik Vikram Sarabhai Space Center Kerala Thiruvananthapuram695022 India Limited HSR Layout Bengaluru560102 India Indian Institute of Technology Madras IIT P.O. Chennai600036 India Indian Institute of Technology Bombay Mumbai400076 India Propulsion Systems Space Transportation Systems United States Nozzle and Combustor Study Project Aeronautics Entity Ventil Software Development Multiphysics Solver Development Department of Aerospace Engineering

In this work we present the computational and experimental study of combustors with GH2 and *** experimental setup is established to test the cryogenic liquid rocket combustors. It is used to study the subcritical injection, evaporation, mixing and burning of liquid oxygen and gaseous hydrogen, using a shear coaxial injector. A computational fluid dynamics (CFD) model for two phase flow with phase change and combustion is developed using both the Eulerian-Lagrangian and Eulerian-Eulerian frameworks to simulate these combustors. Multiple evaporation models were used to simulate LO2 evaporation while Modified Eddy Dissipation Concept is used to model combustion. The model is first validated against the earlier published measurements for validating both single phase and two phase flow combustion and then it is used to simulate the experiments conducted as a part of the present work. Comparison of the results shows that both the frameworks can produce similar results for the operating conditions considered. © 2022, The Authors. All rights reserved.

关键词： Combustion

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Decision-making with artificial intelligence: Towards a novel conceptualization of patterns 24

Decision-making with artificial intelligence: Towards a nove...

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24th Pacific Asia Conference on Information systems: Information systems (IS) for the Future, PACIS 2020

作者： Leyer, Michael Dootson, Paula Oberländer, Anna Maria Kowalkiewicz, Marek University of Rostock Ulmenstraße 69 Rostock18057 Germany Queensland University of Technology 2 George St BrisbaneQLD4000 Australia FIM Research Center University of Bayreuth Project Group Business and Information Systems Engineering Fraunhofer FIT Wittelsbacherring 10 Bayreuth95444 Germany

The rapidly increasing amount of data available in society and business drives the development of Artificial Intelligence (AI). As the number of AI-based services is increasing, customers delegate intimate and relevant decisions to AI. However, current literature lacks understanding of what patterns of decision-making processes with AI involved exist, and it remains unclear how to structure and classify AI-based services accordingly. Therefore, we present and evaluate a set of seven patterns of decision-making processes with AI involved. Building on decision-making theory as justificatory knowledge, we focus on the business-to-customer context to provide a novel perspective on the interactions of customers with AI. We apply the patterns to real-world examples of companies offering AI-based services. Our work contributes to the descriptive knowledge of AI and decision-making theory providing a foundation for future research and supporting practitioners in designing AI-based services. © Proceedings of the 24th Pacific Asia Conference on Information systems: Information systems (IS) for the Future, PACIS 2020. All rights reserved.

关键词： Artificial intelligence

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Bank customers’ decision-making process in choosing between ethical and conventional banking: a survey-based examination

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Journal of Business Economics 2019年第6期89卷 655-697页

作者： Bayer, Sarah Gimpel, Henner Sarikaya, Serkan Research Center Finance and Information Management University of Augsburg Augsburg 86159 Germany Project Group Business and Information Systems Engineering Fraunhofer FIT Augsburg 86159 Germany

Although the banking industry is increasingly focused on the issue of sustainability, the market share held by ethical banks remains small. This study applies models of ethical decision-making to investigate the reasons why customers choose conventional rather than ethical banks, and vice versa. Firstly, a model of bank customers’ ethical decision-making process in choosing between ethical and conventional banks is developed, based on multiple established models from the extant literature. Secondly, this theoretical model is evaluated using data from an online-survey and ‘partial least squares structural equation modelling’. This reveals that the primary factors discouraging potential customers from selecting an ethical rather than conventional bank are a lack of information, limited pressure of the social context, weak moral intensity, and a perception that ethical banks are economically disadvantageous. However, the good reputation of ethical banks, a high concern for the topic, and low levels of skepticism, all indicate a positive general opinion of ethical banks. These results suggest that more factual information and emotional charging of the topic of ethical banking would strengthen demand. In terms of theory, our analysis shows how general models of ethical decision-making can be tailored for use in specific contexts and suggests that the integration of multiple established ethical decision-making models is sensible. Furthermore, we suggest that reputation and economic benefit—which we include here as domain-specific extensions of established ethical decision-making models—are concepts to consider for a general context-independent extension of ethical decision-making models. © 2019, Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Bank selection criteria Customer behavior Ethical banking Ethical decision-making Sustainable banking

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Getting Ready for the European Health Data Space (Ehds): The Iderha's Plan to Align with the Ehds Requirements for the Secondary Use of Health Data

SSRN

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SSRN 2024年

作者： Hussein, Rada Balaur, Irina Burmann, Anja Ćwiek-Kupczyńska, Hanna Gadiya, Yojana Ghosh, Soumyabrata Jayathissa, Prabath Katsch, Florian Kremer, Andreas Lähteenmäki, Jaakko Meng, Zhaoling Morasek, Kathrin Rancourt, Rebecca C. Satagopam, Venkata Sauermann, Stefan Scheider, Simon Stamm, Tanja A. Muehlendyck, Christian Gribbon, Philip Ludwig Boltzmann Institute for Digital Health and Prevention Salzburg Austria Luxembourg Centre for Systems Biology University of Luxembourg Luxembourg Fraunhofer Institute for Software and Systems Engineering Dortmund Germany Discovery Research Screening Port Hamburg Germany Theodor Stern Kai 7 Frankfurt60590 Germany Bonn-Aachen International Center for Information Technology University of Bonn Bonn Germany Center for Medical Data Science Medical University of Vienna Vienna Austria ITTM S.A. Luxembourg VTT Technical Research Centre of Finland Ltd Espoo Finland Clinical Modeling and Evidence Integration Sanofi CambridgeMA United States Institute of Outcomes Research Center for Medical Data Science Medical University of Vienna Austria Ludwig Boltzmann Institute for Arthritis and Rehabilitation Vienna Austria Medical School Berlin Berlin Germany Faculty Life Science Engineering FH Technikum Wien Vienna Austria TU Dortmund Dortmund Germany Johnson & Johnson Medical GmbH Norderstedt Germany

Objective: The European Health Data Space (EHDS) shapes the digital transformation of healthcare in Europe. The EHDS regulations will also accelerate the use of health data for research, innovation, policy-making, and regulatory activities for secondary use of data (known as EHDS2). The Integration of heterogeneous Data and Evidence towards Regulatory and HTA Acceptance (IDERHA) project builds one of the first pan-European health data spaces in alignment with the EHDS2 requirements, addressing lung cancer as a *** and Methods: In this study, we conducted a comprehensive review of the EHDS regulations and technical requirements for EHDS2. Mainly utilizing the results of the Joint Action Towards the European Health Data Space (TEHDAS) project to identify the framework of IDERHA’s alignment with EHDS. We also conducted an internal webinar and an external workshop with EHDS experts to share expertise on the EHDS requirements and ***: We identified the minimum-set of requirements for aligning IDERHA infrastructure with the planned EHDS regulations, including user journey, concepts, terminologies, and standards. The future IDERHA framework (i.e., platform architecture, standardization approaches, documentation, etc.) will be developed ***: The IDERHA's alignment plan with EHDS2 necessitates the implementation of three categories of standardization for: data discoverability (DCAT-AP), enabling semantics interoperability (OMOP), and health data exchange (DICOM and FHIR). The main challenge is that some standards are still being refined, e.g., the extension of the DCAT-AP (HealthDCAT-AP). Additionally, extensions to the OHDSI OMOP CMD for representing the Patient-Generated Health Data are still needed. Finally, proper mapping between standards (FHIR/OMOP) is a prerequisite for proper data ***: Collaboration, sharing lessons learned, and creating synergy among the current EHDS initiatives and projects are critical

关键词： Electronic data interchange

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Shedding Light on Blind Spots - Developing a Reference Architecture to Leverage Video Data for Process Mining

arXiv

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arXiv 2020年

作者： Kratsch, Wolfgang K¨nig, Fabian R¨glinger, Maximilian Fim Research Center University of Applied Sciences Augsburg Germany Fim Research Center University of Bayreuth Germany Project Group Business & Information Systems Engineering of the Fraunhofer Fit Germany

Process mining is one of the most active research streams in business process management. In recent years, numerous methods have been proposed for analyzing structured process data. In many cases, however, only the digitized parts of processes are directly captured by process-aware information sys-tems, whereas manual activities often leave blind spots in the process analysis. While video data can contain valuable process-related information that is not captured in information systems, a standardized approach to extracting event logs from unstructured video data remains lacking. To solve this problem and facilitate the systematic usage of video data in process mining, we have designed the ViProMiRA, a reference architecture that bridges the gap between computer vision and process mining. The various evaluation activities in our design science research process ensure that the proposed ViProMiRA allows flexible, use case-driven, and context-specific instantiations. Our results also show that a prototypical implementation of the ViProMiRA is capable of automatically extracting more than 70% of the process-relevant events from a real-world video dataset in a supervised learning scenario. Copyright © 2020, The Authors. All rights reserved.

关键词： Data mining

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Why do business processes deviate? Results from a Delphi study

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Business Research 2019年第2期12卷 425-453页

作者： König, Ulrich Matthias Linhart, Alexander Röglinger, Maximilian Research Center Finance and Information Management Project Group Business and Information Systems Engineering of the Fraunhofer FIT University of Augsburg Universitätsstraße12 Augsburg 86159 Germany Research Center Finance and Information Management University of Augsburg Universitätsstraße12 Augsburg 86159 Germany Research Center Finance and Information Management Project Group Business and Information Systems Engineering of the Fraunhofer FIT University of Bayreuth Wittelsbacherring 10 Bayreuth 95444 Germany

Despite substantial investments in business process management (BPM), every organization experiences deviant processes, i.e., processes that show different behavior than intended. Thus, process deviance is an essential topic of BPM research and practice. Today, research on process deviance is mainly driven from a computer science perspective. IT-based methods and tools (e.g., deviance mining and prediction or compliance checking) detect process deviance by comparing log data from past process instances with normative process models or execution traces of currently running instances. However, requiring process models and event logs as input, existing approaches are expensive and limited to processes executed in automated workflow environments. Further, they can only detect process deviance, not explain why it occurs. Thus, knowledge about reasons for process deviance is immature. What is missing is a systematic exploration of reasons for process deviance. Against this backdrop, we compiled and structured reasons for process deviance based on a rating-type Delphi study with more than 30 experts from industry and academia. Thereby, we chose a process manager’s perspective as analytical lens, as process managers are familiar with and responsible for business processes end-to-end. We also analyzed the reasons’ importance for causing deviance in routine and nonroutine processes, two process types that capture the nature of processes in terms of variation and variety. Our results contribute to the descriptive knowledge on process deviance and serve as foundation for prescriptive research. © 2018, The Author(s).

关键词： Business process management Delphi study Process deviance

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(How) can blockchain contribute to the management of systemic risks in global supply networks? 1

(How) can blockchain contribute to the management of systemi...

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1st Workshop on Systemic Risks in Global Networks, SysRisk 2019

作者： Fridgen, Gilbert Körner, Marc-Fabian Sedlmeir, Johannes Weibelzahl, Martin FIM Research Center University of Bayreuth Wittelsbacherring 10 Bayreuth Germany Project Group Business and Information Systems Engineering of the Fraunhofer FIT Wittelsbacherring 10 Bayreuth Germany

Even though globalization has led to larger, faster, and more efficient supply chains, at the same time the new worldwide interconnection has also resulted in major challenges with respect to hidden systemic risks. In particular, there is a lack of a holistic perspective on the entire supply network. This missing global view prohibits the anamnesis and management of underlying risks. Against this backdrop, in this paper we discuss the potential contributions of Blockchain technology to systemic risk management in global supply chains and networks. Given the increasing number of recent initiatives of businesses in the context of Blockchain, we argue that Blockchain technology can lower the hurdle for the use of secure multiparty computation. Ultimately, it may be possible to implement a corresponding monitoring mechanism for systemic risks without (i) the need of a central authority and (ii) revealing competition relevant, confidential information to other supply network participants. © 2019 CEUR-WS. All rights reserved.

关键词： Blockchain

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Technical debt and agile software development practices and processes: An industry practitioner survey

arXiv

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arXiv 2021年

作者： Holvitie, Johannes Licorish, Sherlock A. Spínola, Rodrigo O. Hyrynsalmi, Sami MacDonell, Stephen G. Mendes, Thiago S. Buchan, Jim Leppänen, Ville Turku Centre for Computer Science Software Development Laboratory Turku Finland University of Turku Department of Information Technology Turku Finland University of Otago Department of Information Science Otago Dunedin New Zealand Salvador University Graduate Program in Systems and Computer Bahia Salvador Brazil Federal University of Bahia Fraunhofer Project Center for Software and System Engineering Salvador Brazil Tampere University of Technology Pori Campus Pori Finland Federal Institute of Bahia Information Technology Department Bahia Santo Amaro Brazil Auckland University of Technology School of Engineering Computer and Mathematical Sciences Auckland New Zealand

Context: Contemporary software development is typically conducted in dynamic, resource-scarce environments that are prone to the accumulation of technical debt. While this general phenomenon is acknowledged, what remains unknown is how technical debt specifically manifests in and affects software processes, and how the software development techniques employed accommodate or mitigate the presence of this debt. Objectives: We sought to draw on practitioner insights and experiences in order to classify the effects of agile method use on technical debt management, given the popularity and perceived success of agile methods. We explore the breadth of practitioners' knowledge about technical debt;how technical debt is manifested across the software process;and the perceived effects of common agile software development practices and processes on technical debt. In doing so, we address a research gap in technical debt knowledge and provide novel and actionable managerial recommendations. Method: We designed, tested and executed a multi-national survey questionnaire to address our objectives, receiving 184 responses from practitioners in Brazil, Finland, and New Zealand. Results: Our findings indicate that: 1) Practitioners are aware of technical debt, although, there was under utilization of the concept, 2) Technical debt commonly resides in legacy systems, however, concrete instances of technical debt are hard to conceptualize which makes it problematic to manage, 3) Queried agile practices and processes help to reduce technical debt;in particular, techniques that verify and maintain the structure and clarity of implemented artifacts (e.g., Coding standards and Refactoring) positively affect technical debt management. Conclusions: The fact that technical debt instances tend to have characteristics in common means that a systematic approach to its management is feasible. However, notwithstanding the positive effects of some agile practices on technical debt management, comp

关键词： Legacy systems

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