@inproceedings{VladovaUllrichSultanowetal.2023,
  author    = {Vladova, Gergana and Ullrich, Andr{\´e} and Sultanow, Eldar and Tobolla, Marinho and Sebrak, Sebastian and Czarnecki, Christian and Brockmann, Carsten},
  title     = {Visual analytics for knowledge management},
  series = {Informatik 2023},
  booktitle = {Informatik 2023},
  editor    = {Klein, Maike and Krupka, Daniel and Winter, Cornelia and Wohlgemuth, Volker},
  publisher = {Gesellschaft f{\"u}r Informatik e.V. (GI)},
  address   = {Bonn},
  isbn      = {978-3-88579-731-9},
  issn      = {1617-5468},
  doi       = {10.18420/inf2023_187},
  pages     = {1851 -- 1870},
  year      = {2023},
  abstract  = {The management of knowledge in organizations considers both established long-term processes and cooperation in agile project teams. Since knowledge can be both tacit and explicit, its transfer from the individual to the organizational knowledge base poses a challenge in organizations. This challenge increases when the fluctuation of knowledge carriers is exceptionally high. Especially in large projects in which external consultants are involved, there is a risk that critical, company-relevant knowledge generated in the project will leave the company with the external knowledge carrier and thus be lost. In this paper, we show the advantages of an early warning system for knowledge management to avoid this loss. In particular, the potential of visual analytics in the context of knowledge management systems is presented and discussed. We present a project for the development of a business-critical software system and discuss the first implementations and results.},
  language  = {en}
}
@article{UllrichTeichmannGronau2021,
  author    = {Ullrich, Andr{\´e} and Teichmann, Malte and Gronau, Norbert},
  title     = {Fast trainable capabilities in software engineering-skill development in learning factories},
  series = {Ji suan ji jiao yu = Computer Education / Qing hua da xue},
  journal   = {Ji suan ji jiao yu = Computer Education / Qing hua da xue},
  number    = {12},
  publisher = {[Verlag nicht ermittelbar]},
  address   = {Bei jing shi},
  issn      = {1672-5913},
  doi       = {10.16512/j.cnki.jsjjy.2020.12.002},
  pages     = {2 -- 10},
  year      = {2021},
  abstract  = {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.},
  language  = {en}
}
@article{TeichmannUllrichWenzetal.2020,
  author    = {Teichmann, Malte and Ullrich, Andr{\´e} and Wenz, Julian and Gronau, Norbert},
  title     = {Herausforderungen und Handlungsempfehlungen betrieblicher Weiterbildungspraxis in Zeiten der Digitalisierung},
  series = {HMD Praxis der Wirtschaftsinformatik},
  volume    = {57},
  journal   = {HMD Praxis der Wirtschaftsinformatik},
  publisher = {Springer Vieweg},
  address   = {Wiesbaden},
  issn      = {1436-3011},
  doi       = {10.1365/s40702-020-00614-x},
  pages     = {512 -- 527},
  year      = {2020},
  abstract  = {Die Digitalisierung von Produktionsprozessen schreitet mit einer hohen Intensit{\"a}t voran. Weiterbildung hat eine hohe Relevanz f{\"u}r betriebliche Transformationsprozesse. Die betriebliche Weiterbildungspraxis ist den aktuellen Herausforderungen der Digitalisierung jedoch nicht gewachsen. Herausforderungen sind Kompetenzl{\"u}cken der Mitarbeiter, ungewisse Anforderungsprofile und T{\"a}tigkeitstypen, demographischer Wandel sowie veraltete didaktische Ans{\"a}tze. Zudem wird bestehender inhaltlicher und p{\"a}dagogischer Freiraum bei der Gestaltung von Weiterbildung oftmals nur unzureichend ausgenutzt. Die skizzierte Situation f{\"u}hrt dazu, dass der Mehrwert gegenw{\"a}rtiger Qualifizierungsangebote sowohl f{\"u}r Unternehmen als auch Besch{\"a}ftigte nicht ausgesch{\"o}pft wird. Ausgehend von Ver{\"a}nderungen durch Digitalisierung in der Produktion und deren Auswirkungen auf die Kompetenzentwicklung diskutiert dieser Beitrag Herausforderungen gegenw{\"a}rtiger betrieblicher Weiterbildung. Er leitet Handlungsempfehlungen ab, die mithilfe von Beispielen gewerkschaftlich unterst{\"u}tzter Weiterbildungspraxis illustriert werden. Im Ergebnis erhalten Interessierte einen {\"U}berblick {\"u}ber gegenw{\"a}rtige Herausforderungen und Handlungsempfehlungen f{\"u}r die Gestaltung und Durchf{\"u}hrung von Weiterbildung in Zeiten der Digitalisierung.},
  language  = {de}
}
@inproceedings{SultanowChircuWuestemannetal.2022,
  author    = {Sultanow, Eldar and Chircu, Alina and W{\"u}stemann, Stefanie and Schwan, Andr{\´e} and Lehmann, Andreas and Sept, Andr{\´e} and Szymaski, Oliver and Venkatesan, Sripriya and Ritterbusch, Georg David and Teichmann, Malte Rolf},
  title     = {Metaverse opportunities for the public sector},
  series = {International Conference on Information Systems 2022 : Special Interest Group on Big Data : Proceedings},
  booktitle = {International Conference on Information Systems 2022 : Special Interest Group on Big Data : Proceedings},
  publisher = {AIS},
  address   = {Atlanta},
  year      = {2022},
  abstract  = {The metaverse is envisioned as a virtual shared space facilitated by emerging technologies such as virtual reality (VR), augmented reality (AR), the Internet of Things (IoT), 5G, artificial intelligence (AI), big data, spatial computing, and digital twins (Allam et al., 2022; Dwivedi et al., 2022; Ravenscraft, 2022; Wiles, 2022). While still a nascent concept, the metaverse has the potential to "transform the physical world, as well as transport or extend physical activities to a virtual world" (Wiles, 2022). Big data technologies will also be essential in managing the enormous amounts of data created in the metaverse (Sun et al., 2022). Metaverse technologies can offer the public sector a host of benefits, such as simplified information exchange, stronger communication with citizens, better access to public services, or benefiting from a new virtual economy. Implementations are underway in several cities around the world (Geraghty et al., 2022). In this paper, we analyze metaverse opportunities for the public sector and explore their application in the context of Germany's Federal Employment Agency. Based on an analysis of academic literature and practical examples, we create a capability map for potential metaverse business capabilities for different areas of the public sector (broadly defined). These include education (virtual training and simulation, digital campuses that offer not just online instruction but a holistic university campus experience, etc.), tourism (virtual travel to remote locations and museums, virtual festival participation, etc.), health (employee training - as for emergency situations, virtual simulations for patient treatment - for example, for depression or anxiety, etc.), military (virtual training to experience operational scenarios without being exposed to a real-world threats, practice strategic decision-making, or gain technical knowledge for operating and repairing equipment, etc.), administrative services (document processing, virtual consultations for citizens, etc.), judiciary (AI decision-making aids, virtual proceedings, etc.), public safety (virtual training for procedural issues, special operations, or unusual situations, etc.), emergency management (training for natural disasters, etc.), and city planning (visualization of future development projects and interactive feedback, traffic management, attraction gamification, etc.), among others. We further identify several metaverse application areas for Germany's Federal Employment Agency. These applications can help it realize the goals of the German government for digital transformation that enables faster, more effective, and innovative government services. They include training of employees, training of customers, and career coaching for customers. These applications can be implemented using interactive learning games with AI agents, virtual representations of the organizational spaces, and avatars interacting with each other in these spaces. Metaverse applications will both use big data (to design the virtual environments) and generate big data (from virtual interactions). Issues related to data availability, quality, storage, processing (and related computing power requirements), interoperability, sharing, privacy and security will need to be addressed in these emerging metaverse applications (Sun et al., 2022). Special attention is needed to understand the potential for power inequities (wealth inequity, algorithmic bias, digital exclusion) due to technologies such as VR (Egliston \& Carter, 2021), harmful surveillance practices (Bibri \& Allam, 2022), and undesirable user behavior or negative psychological impacts (Dwivedi et al., 2022). The results of this exploratory study can inform public sector organizations of emerging metaverse opportunities and enable them to develop plans for action as more of the metaverse technologies become a reality. While the metaverse body of research is still small and research agendas are only now starting to emerge (Dwivedi et al., 2022), this study offers a building block for future development and analysis of metaverse applications.},
  language  = {en}
}
@article{RuedianVladova2021,
  author    = {R{\"u}dian, Sylvio Leo and Vladova, Gergana},
  title     = {Kostenfreie Onlinekurse nachhaltig mit personalisiertem Marketing finanzieren},
  series = {HMD Praxis der Wirtschaftsinformatik},
  volume    = {58},
  journal   = {HMD Praxis der Wirtschaftsinformatik},
  number    = {3},
  publisher = {Springer Vieweg},
  address   = {Wiesbaden},
  issn      = {1436-3011},
  doi       = {10.1365/s40702-021-00720-4},
  pages     = {507 -- 520},
  year      = {2021},
  abstract  = {Selbstbestimmtes Lernen mit Onlinekursen findet zunehmend mehr Akzeptanz in unserer Gesellschaft. Lernende k{\"o}nnen mithilfe von Onlinekursen selbst festlegen, was sie wann lernen und Kurse k{\"o}nnen durch vielf{\"a}ltige Adaptionen an den Lernfortschritt der Nutzer angepasst und individualisiert werden. Auf der einen Seite ist eine große Zielgruppe f{\"u}r diese Lernangebote vorhanden. Auf der anderen Seite sind die Erstellung von Onlinekursen, ihre Bereitstellung, Wartung und Betreuung kostenintensiv, wodurch hochwertige Angebote h{\"a}ufig kostenpflichtig angeboten werden m{\"u}ssen, um als Anbieter zumindest kostenneutral agieren zu k{\"o}nnen. In diesem Beitrag er{\"o}rtern und diskutieren wir ein offenes, nachhaltiges datengetriebenes zweiseitiges Gesch{\"a}ftsmodell zur Verwertung gepr{\"u}fter Onlinekurse und deren kostenfreie Bereitstellung f{\"u}r jeden Lernenden. Kern des Gesch{\"a}ftsmodells ist die Nutzung der dabei entstehenden Verhaltensdaten, die daraus m{\"o}gliche Ableitung von Pers{\"o}nlichkeitsmerkmalen und Interessen und deren Nutzung im kommerziellen Kontext. Dies ist eine bei der Websuche bereits weitl{\"a}ufig akzeptierte Methode, welche nun auf den Lernkontext {\"u}bertragen wird. Welche M{\"o}glichkeiten, Herausforderungen, aber auch Barrieren {\"u}berwunden werden m{\"u}ssen, damit das Gesch{\"a}ftsmodell nachhaltig und ethisch vertretbar funktioniert, werden zwei unabh{\"a}ngige, jedoch synergetisch verbundene Gesch{\"a}ftsmodelle vorgestellt und diskutiert. Zus{\"a}tzlich wurde die Akzeptanz und Erwartung der Zielgruppe f{\"u}r das vorgestellte Gesch{\"a}ftsmodell untersucht, um notwendige Kernressourcen f{\"u}r die Praxis abzuleiten. Die Ergebnisse der Untersuchung zeigen, dass das Gesch{\"a}ftsmodell von den Nutzer*innen grundlegend akzeptiert wird. 10 \% der Befragten w{\"u}rden es bevorzugen, mit virtuellen Assistenten - anstelle mit Tutor*innen zu lernen. Zudem ist der Großteil der Nutzer*innen sich nicht dar{\"u}ber bewusst, dass Pers{\"o}nlichkeitsmerkmale anhand des Nutzerverhaltens abgeleitet werden k{\"o}nnen.},
  language  = {de}
}
@article{RojahnWeberGronau2023,
  author    = {Rojahn, Marcel and Weber, Edzard and Gronau, Norbert},
  title     = {Towards a standardization in scheduling models},
  series = {International journal of industrial and systems engineering},
  volume    = {17},
  journal   = {International journal of industrial and systems engineering},
  number    = {6},
  publisher = {Inderscience Enterprises},
  address   = {Gen{\`e}ve},
  issn      = {1748-5037},
  pages     = {401 -- 408},
  year      = {2023},
  abstract  = {Terminology is a critical instrument for each researcher. Different terminologies for the same research object may arise in different research communities. By this inconsistency, many synergistic effects get lost. Theories and models will be more understandable and reusable if a common terminology is applied. This paper examines the terminological (in)consistence for the research field of job-shop scheduling by a literature review. There is an enormous variety in the choice of terms and mathematical notation for the same concept. The comparability, reusability and combinability of scheduling methods is unnecessarily hampered by the arbitrary use of homonyms and synonyms. The acceptance in the community of used variables and notation forms is shown by means of a compliance quotient. This is proven by the evaluation of 240 scientific publications on planning methods.},
  language  = {en}
}
@inproceedings{RojahnGronau2023,
  author    = {Rojahn, Marcel and Gronau, Norbert},
  title     = {Digital platform concepts for manufacturing companies},
  series = {10th International Conference on Future Internet of Things and Cloud (FiCloud)},
  booktitle = {10th International Conference on Future Internet of Things and Cloud (FiCloud)},
  publisher = {IEEE},
  address   = {[Erscheinungsort nicht ermittelbar]},
  isbn      = {979-8-3503-1635-3},
  doi       = {10.1109/FiCloud58648.2023.00030},
  pages     = {149 -- 158},
  year      = {2023},
  abstract  = {Digital Platforms (DPs) has established themself in recent years as a central concept of the Information Technology Science. Due to the great diversity of digital platform concepts, clear definitions are still required. Furthermore, DPs are subject to dynamic changes from internal and external factors, which pose challenges for digital platform operators, developers and customers. Which current digital platform research directions should be taken to address these challenges remains open so far. The following paper aims to contribute to this by outlining a systematic literature review (SLR) on digital platform concepts in the context of the Industrial Internet of Things (IIoT) for manufacturing companies and provides a basis for (1) a selection of definitions of current digital platform and ecosystem concepts and (2) a selection of current digital platform research directions. These directions are diverted into (a) occurrence of digital platforms, (b) emergence of digital platforms, (c) evaluation of digital platforms, (d) development of digital platforms, and (e) selection of digital platforms.},
  language  = {en}
}
@inproceedings{RojahnGronau2024,
  author    = {Rojahn, Marcel and Gronau, Norbert},
  title     = {Openness indicators for the evaluation of digital platforms between the launch and maturity phase},
  series = {Proceedings of the 57th Annual Hawaii International Conference on System Sciences},
  booktitle = {Proceedings of the 57th Annual Hawaii International Conference on System Sciences},
  editor    = {Bui, Tung X.},
  publisher = {Department of IT Management Shidler College of Business University of Hawaii},
  address   = {Honolulu, HI},
  isbn      = {978-0-99813-317-1},
  pages     = {4516 -- 4525},
  year      = {2024},
  abstract  = {In recent years, the evaluation of digital platforms has become an important focus in the field of information systems science. The identification of influential indicators that drive changes in digital platforms, specifically those related to openness, is still an unresolved issue. This paper addresses the challenge of identifying measurable indicators and characterizing the transition from launch to maturity in digital platforms. It proposes a systematic analytical approach to identify relevant openness indicators for evaluation purposes. The main contributions of this study are the following (1) the development of a comprehensive procedure for analyzing indicators, (2) the categorization of indicators as evaluation metrics within a multidimensional grid-box model, (3) the selection and evaluation of relevant indicators, (4) the identification and assessment of digital platform architectures during the launch-to-maturity transition, and (5) the evaluation of the applicability of the conceptualization and design process for digital platform evaluation.},
  language  = {en}
}
@incollection{RojahnAmbrosBiruetal.2023,
  author    = {Rojahn, Marcel and Ambros, Maximilian and Biru, Tibebu and Krallmann, Hermann and Gronau, Norbert and Grum, Marcus},
  title     = {Adequate basis for the data-driven and machine-learning-based identification},
  series = {Artificial intelligence and soft computing},
  booktitle = {Artificial intelligence and soft computing},
  editor    = {Rutkowski, Leszek and Scherer, Rafał and Korytkowski, Marcin and Pedrycz, Witold and Tadeusiewicz, Ryszard and Zurada, Jacek M.},
  publisher = {Springer},
  address   = {Cham},
  isbn      = {978-3-031-42504-2},
  doi       = {10.1007/978-3-031-42505-9_48},
  pages     = {570 -- 588},
  year      = {2023},
  abstract  = {Process mining (PM) has established itself in recent years as a main method for visualizing and analyzing processes. However, the identification of knowledge has not been addressed adequately because PM aims solely at data-driven discovering, monitoring, and improving real-world processes from event logs available in various information systems. The following paper, therefore, outlines a novel systematic analysis view on tools for data-driven and machine learning (ML)-based identification of knowledge-intensive target processes. To support the effectiveness of the identification process, the main contributions of this study are (1) to design a procedure for a systematic review and analysis for the selection of relevant dimensions, (2) to identify different categories of dimensions as evaluation metrics to select source systems, algorithms, and tools for PM and ML as well as include them in a multi-dimensional grid box model, (3) to select and assess the most relevant dimensions of the model, (4) to identify and assess source systems, algorithms, and tools in order to find evidence for the selected dimensions, and (5) to assess the relevance and applicability of the conceptualization and design procedure for tool selection in data-driven and ML-based process mining research.},
  language  = {en}
}
@misc{PanzerBenderGronau2022,
  author    = {Panzer, Marcel and Bender, Benedict and Gronau, Norbert},
  title     = {Neural agent-based production planning and control},
  series = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Wirtschafts- und Sozialwissenschaftliche Reihe},
  journal   = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Wirtschafts- und Sozialwissenschaftliche Reihe},
  issn      = {1867-5808},
  doi       = {10.25932/publishup-60477},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-604777},
  pages     = {26},
  year      = {2022},
  abstract  = {Nowadays, production planning and control must cope with mass customization, increased fluctuations in demand, and high competition pressures. Despite prevailing market risks, planning accuracy and increased adaptability in the event of disruptions or failures must be ensured, while simultaneously optimizing key process indicators. To manage that complex task, neural networks that can process large quantities of high-dimensional data in real time have been widely adopted in recent years. Although these are already extensively deployed in production systems, a systematic review of applications and implemented agent embeddings and architectures has not yet been conducted. The main contribution of this paper is to provide researchers and practitioners with an overview of applications and applied embeddings and to motivate further research in neural agent-based production. Findings indicate that neural agents are not only deployed in diverse applications, but are also increasingly implemented in multi-agent environments or in combination with conventional methods — leveraging performances compared to benchmarks and reducing dependence on human experience. This not only implies a more sophisticated focus on distributed production resources, but also broadening the perspective from a local to a global scale. Nevertheless, future research must further increase scalability and reproducibility to guarantee a simplified transfer of results to reality.},
  language  = {en}
}