TY - JOUR A1 - Bender, Benedict A1 - Gronau, Norbert T1 - Coring on digital software platforms BT - Fundamentals and Examples from the Mobile Device Sector JF - Schriften zur Business Analytics und zum Informationsmanagement N2 - Today’s mobile devices are part of powerful business ecosystems, which usually involve digital platforms. To better understand the complex phenomenon of coring and related dynamics, this paper presents a case study comparing iMessage as part of Apple’s iOS and WhatsApp. Specifically, it investigates activities regarding platform coring, as the integration of several functionalities provided by third-party applications in the platform core. The paper makes three contributions. First, a systematization of coring activities is developed. Coring modes are differentiated by the amount of coring and application maintenance. Second, the case study revealed that the phenomenon of platform coring is present on digital platforms for mobile devices. Third, the fundamentals of coring are discussed as a first step towards theoretical development. Even though coring constitutes a potential threat for third-party developers regarding their functional differentiation, an idea of what a beneficial partnership incorporating coring activities could look like is developed here. KW - coring KW - digital platforms KW - digital marketplaces KW - mobile software ecosystems Y1 - 2021 SN - 978-3-658-34798-7 SN - 978-3-658-34799-4 U6 - https://doi.org/10.1007/978-3-658-34799-4_4 SN - 2946-0670 SN - 2946-0662 SP - 45 EP - 77 PB - Springer CY - Wiesbaden ER - TY - JOUR A1 - Grum, Marcus A1 - Sultanow, Eldar A1 - Friedmann, Daniel A1 - Ulrich, Andre A1 - Gronau, Norbert T1 - Tools des Maschinellen Lernens BT - Marktstudie, Anwendungsbereiche & Lösungen der Künstlichen Intelligenz N2 - Künstliche Intelligenz ist in aller Munde. Immer mehr Anwendungsbereiche werden durch die Auswertung von vorliegenden Daten mit Algorithmen und Frameworks z.B. des Maschinellen Lernens erschlossen. Dieses Buch hat das Ziel, einen Überblick über gegenwärtig vorhandene Lösungen zu geben und darüber hinaus konkrete Hilfestellung bei der Auswahl von Algorithmen oder Tools bei spezifischen Problemstellungen zu bieten. Um diesem Anspruch gerecht zu werden, wurden 90 Lösungen mittels einer systematischen Literaturrecherche und Praxissuche identifiziert sowie anschließend klassifiziert. Mit Hilfe dieses Buches gelingt es, schnell die notwendigen Grundlagen zu verstehen, gängige Anwendungsgebiete zu identifizieren und den Prozess zur Auswahl eines passenden ML-Tools für das eigene Projekt systematisch zu meistern. Y1 - 2021 SN - 978-3-95545-380-0 SN - 978-3-95545-318-7 U6 - https://doi.org/10.30844/grum_2020 PB - Gito CY - Berlin ER - TY - GEN A1 - Vladova, Gergana A1 - Ullrich, André A1 - Bender, Benedict A1 - Gronau, Norbert T1 - Students’ Acceptance of Technology-Mediated Teaching – How It Was Influenced During the COVID-19 Pandemic in 2020: A Study From Germany T2 - Postprints der Universität Potsdam Wirtschafts- und Sozialwissenschaftliche Reihe N2 - In response to the impending spread of COVID-19, universities worldwide abruptly stopped face-to-face teaching and switched to technology-mediated teaching. As a result, the use of technology in the learning processes of students of different disciplines became essential and the only way to teach, communicate and collaborate for months. In this crisis context, we conducted a longitudinal study in four German universities, in which we collected a total of 875 responses from students of information systems and music and arts at four points in time during the spring–summer 2020 semester. Our study focused on (1) the students’ acceptance of technology-mediated learning, (2) any change in this acceptance during the semester and (3) the differences in acceptance between the two disciplines. We applied the Technology Acceptance Model and were able to validate it for the extreme situation of the COVID-19 pandemic. We extended the model with three new variables (time flexibility, learning flexibility and social isolation) that influenced the construct of perceived usefulness. Furthermore, we detected differences between the disciplines and over time. In this paper, we present and discuss our study’s results and derive short- and long-term implications for science and practice. T3 - Zweitveröffentlichungen der Universität Potsdam : Wirtschafts- und Sozialwissenschaftliche Reihe - 141 KW - COVID-19 KW - digital learning KW - discipline differences KW - e-learning KW - TAM KW - technology acceptance KW - technology-mediated teaching KW - university teaching Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-521615 SN - 1867-5808 ER - TY - JOUR A1 - Vladova, Gergana A1 - Ullrich, André A1 - Bender, Benedict A1 - Gronau, Norbert T1 - Students’ acceptance of technology-mediated teaching – How it was influenced during the COVID-19 Pandemic in 2020 BT - A study from Germany JF - Frontiers in psychology / Frontiers Research Foundation N2 - In response to the impending spread of COVID-19, universities worldwide abruptly stopped face-to-face teaching and switched to technology-mediated teaching. As a result, the use of technology in the learning processes of students of different disciplines became essential and the only way to teach, communicate and collaborate for months. In this crisis context, we conducted a longitudinal study in four German universities, in which we collected a total of 875 responses from students of information systems and music and arts at four points in time during the spring–summer 2020 semester. Our study focused on (1) the students’ acceptance of technology-mediated learning, (2) any change in this acceptance during the semester and (3) the differences in acceptance between the two disciplines. We applied the Technology Acceptance Model and were able to validate it for the extreme situation of the COVID-19 pandemic. We extended the model with three new variables (time flexibility, learning flexibility and social isolation) that influenced the construct of perceived usefulness. Furthermore, we detected differences between the disciplines and over time. In this paper, we present and discuss our study’s results and derive short- and long-term implications for science and practice. KW - COVID-19 KW - digital learning KW - discipline differences KW - e-learning KW - TAM KW - technology acceptance KW - technology-mediated teaching KW - university teaching Y1 - 2020 U6 - https://doi.org/10.3389/fpsyg.2021.636086 SN - 1664-1078 VL - 12 PB - Frontiers Research Foundation CY - Lausanne ER - TY - JOUR A1 - Gronau, Norbert A1 - Schaefer, Martin T1 - Why metadata matters for the future of copyright JF - European Intellectual Property Review N2 - In the copyright industries of the 21st century, metadata is the grease required to make the engine of copyright run smoothly and powerfully for the benefit of creators, copyright industries and users alike. However, metadata is difficult to acquire and even more difficult to keep up to date as the rights in content are mostly multi-layered, fragmented, international and volatile. This article explores the idea of a neutral metadata search and enhancement tool that could constitute a buffer to safeguard the interests of the various proprietary database owners and avoid the shortcomings of centralised databases. KW - copyright KW - databases KW - metadata KW - music industry Y1 - 2021 SN - 0142-0461 VL - 43 IS - 8 SP - 488 EP - 494 PB - Sweet & Maxwell CY - London ER - TY - BOOK A1 - Gronau, Norbert T1 - ERP-Systeme BT - Architektur, Management und Funktionen des Enterprise Resource Planning T3 - De Gruyter Studium KW - ERP KW - Enterprise Resource Planning KW - Wirtschaftsinformatik KW - Industrie 4.0 Y1 - 2021 SN - 978-3-11-066339-6 SN - 978-3-11-066283-2 U6 - https://doi.org/10.1515/9783110663396 SN - 2365-7197 SN - 2365-7200 PB - De Gruyter Oldenbourg CY - Berlin ; Boston ET - 4. Auflage ER - TY - JOUR A1 - Grum, Marcus A1 - Hiessl, Werner A1 - Maresch, Karl A1 - Gronau, Norbert T1 - Design of a neuronal training modeling language BT - exemplified with the AI-based dynamic GUI adaption JF - AIS-Transactions on enterprise systems N2 - As the complexity of learning task requirements, computer infrastruc- tures and knowledge acquisition for artificial neuronal networks (ANN) is in- creasing, it is challenging to talk about ANN without creating misunderstandings. An efficient, transparent and failure-free design of learning tasks by models is not supported by any tool at all. For this purpose, particular the consideration of data, information and knowledge on the base of an integration with knowledge- intensive business process models and a process-oriented knowledge manage- ment are attractive. With the aim of making the design of learning tasks express- ible by models, this paper proposes a graphical modeling language called Neu- ronal Training Modeling Language (NTML), which allows the repetitive use of learning designs. An example ANN project of AI-based dynamic GUI adaptation exemplifies its use as a first demonstration. KW - AI and business informatics KW - development of AI-based systems KW - AI-based decision support system KW - cooperative AI (human-in-the-loop) KW - process-oriented knowledge acquisition KW - modeling language Y1 - 2021 UR - https://www.aes-journal.com/index.php/ais-tes/article/view/20/18 U6 - https://doi.org/10.30844/aistes.v5i1.20 SN - 1867-7134 VL - 5 IS - 1 PB - GITO-Publ., Verl. für Industrielle Informationstechnik und Organisation CY - Berlin ER - TY - JOUR A1 - Ullrich, André A1 - Teichmann, Malte A1 - Gronau, Norbert T1 - Fast trainable capabilities in software engineering-skill development in learning factories JF - Ji suan ji jiao yu = Computer Education / Qing hua da xue N2 - The increasing demand for software engineers cannot completely be fulfilled by university education and conventional training approaches due to limited capacities. Accordingly, an alternative approach is necessary where potential software engineers are being educated in software engineering skills using new methods. We suggest micro tasks combined with theoretical lessons to overcome existing skill deficits and acquire fast trainable capabilities. This paper addresses the gap between demand and supply of software engineers by introducing an actionoriented and scenario-based didactical approach, which enables non-computer scientists to code. Therein, the learning content is provided in small tasks and embedded in learning factory scenarios. Therefore, different requirements for software engineers from the market side and from an academic viewpoint are analyzed and synthesized into an integrated, yet condensed skills catalogue. This enables the development of training and education units that focus on the most important skills demanded on the market. To achieve this objective, individual learning scenarios are developed. Of course, proper basic skills in coding cannot be learned over night but software programming is also no sorcery. KW - learning factory KW - programming skills KW - software engineering KW - training Y1 - 2021 U6 - https://doi.org/10.16512/j.cnki.jsjjy.2020.12.002 SN - 1672-5913 IS - 12 SP - 2 EP - 10 PB - [Verlag nicht ermittelbar] CY - Bei jing shi ER - TY - CHAP A1 - Thim, Christof A1 - Grum, Marcus A1 - Schüffler, Arnulf A1 - Roling, Wiebke A1 - Kluge, Annette A1 - Gronau, Norbert ED - Andersen, Ann-Louise ED - Andersen, Rasmus ED - Brunoe, Thomas Ditlev ED - Larsen, Maria Stoettrup Schioenning ED - Nielsen, Kjeld ED - Napoleone, Alessia ED - Kjeldgaard, Stefan T1 - A concept for a distributed Interchangeable knowledge base in CPPS T2 - Towards sustainable customization: cridging smart products and manufacturing systems N2 - As AI technology is increasingly used in production systems, different approaches have emerged from highly decentralized small-scale AI at the edge level to centralized, cloud-based services used for higher-order optimizations. Each direction has disadvantages ranging from the lack of computational power at the edge level to the reliance on stable network connections with the centralized approach. Thus, a hybrid approach with centralized and decentralized components that possess specific abilities and interact is preferred. However, the distribution of AI capabilities leads to problems in self-adapting learning systems, as knowledgebases can diverge when no central coordination is present. Edge components will specialize in distinctive patterns (overlearn), which hampers their adaptability for different cases. Therefore, this paper aims to present a concept for a distributed interchangeable knowledge base in CPPS. The approach is based on various AI components and concepts for each participating node. A service-oriented infrastructure allows a decentralized, loosely coupled architecture of the CPPS. By exchanging knowledge bases between nodes, the overall system should become more adaptive, as each node can “forget” their present specialization. KW - learning KW - distributed knowledge base KW - artificial intelligence KW - CPPS Y1 - 2021 SN - 978-3-030-90699-3 SN - 978-3-030-90702-0 SN - 978-3-030-90700-6 U6 - https://doi.org/10.1007/978-3-030-90700-6_35 SP - 314 EP - 321 PB - Springer CY - Cham ER - TY - CHAP A1 - Grum, Marcus A1 - Thim, Christof A1 - Gronau, Norbert ED - Andersen, Ann-Louise ED - Andersen, Rasmus ED - Brunoe, Thomas Ditlev ED - Larsen, Maria Stoettrup Schioenning ED - Nielsen, Kjeld ED - Napoleone, Alessia ED - Kjeldgaard, Stefan T1 - Aiming for knowledge-transfer-optimizing intelligent cyber-physical systems T2 - Towards sustainable customization : cridging smart products and manufacturing systems N2 - Since more and more production tasks are enabled by Industry 4.0 techniques, the number of knowledge-intensive production tasks increases as trivial tasks can be automated and only non-trivial tasks demand human-machine interactions. With this, challenges regarding the competence of production workers, the complexity of tasks and stickiness of required knowledge occur [1]. Furthermore, workers experience time pressure which can lead to a decrease in output quality. Cyber-Physical Systems (CPS) have the potential to assist workers in knowledge-intensive work grounded on quantitative insights about knowledge transfer activities [2]. By providing contextual and situational awareness as well as complex classification and selection algorithms, CPS are able to ease knowledge transfer in a way that production time and quality is improved significantly. CPS have only been used for direct production and process optimization, knowledge transfers have only been regarded in assistance systems with little contextual awareness. Embedding production and knowledge transfer optimization thus show potential for further improvements. This contribution outlines the requirements and a framework to design these systems. It accounts for the relevant factors. KW - smart automation KW - smart production KW - human-machine-interaction Y1 - 2021 SN - 978-3-030-90699-3 SN - 978-3-030-90700-6 SN - 978-3-030-90702-0 U6 - https://doi.org/10.1007/978-3-030-90700-6_16 SP - 149 EP - 157 PB - Springer CY - Cham ER -