@inproceedings{GrumBlunkRojahnetal.2020, author = {Grum, Marcus and Blunk, Oliver and Rojahn, Marcel and Fettke, Peter and Gronau, Norbert}, title = {Research challenges of knowledge modelling and the outline of a research agenda}, series = {Knowledge in digital age : IFKAD 2020}, booktitle = {Knowledge in digital age : IFKAD 2020}, publisher = {The Arts of Business Institute}, address = {Matera, Italy}, isbn = {978-88-96687-13-0}, issn = {2280-787X}, year = {2020}, 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} } @inproceedings{BenderGronauWinter2023, author = {Bender, Benedict and Gronau, Norbert and Winter, Robert}, title = {Minitrack introduction enterprise-level information systems}, series = {Proceedings of the 56th Hawaii International Conference on System Sciences}, booktitle = {Proceedings of the 56th Hawaii International Conference on System Sciences}, editor = {Bui, Tung X.}, publisher = {Hawaii International Conference on System Sciences}, address = {Honolulu, HI}, isbn = {978-0-9981331-6-4}, issn = {2572-6862}, pages = {5809 -- 5810}, year = {2023}, abstract = {While Information Systems (IS) Research on the individual and workgroup level of analysis is omnipresent, research on the enterprise-level IS is less frequent. Even though research on Enterprise Systems and their management is established in academic associations and conference programs, enterprise-level phenomena are underrepresented. This minitrack provides a forum to integrate existing research streams that traditionally needed to be attached to other topics (such as IS management or IS governance). The minitrack received broad attention. The three selected papers address different facets of the future role of enterprise-wide IS including aspects such as carbonization, ecosystem integration, and technology-organization fit.}, language = {en} } @inproceedings{BenderGronau2022, author = {Bender, Benedict and Gronau, Norbert}, title = {Introduction to the Minitrack on towards the future of enterprise systems}, series = {Proceedings of the 55th Hawaii International Conference on System Sciences}, booktitle = {Proceedings of the 55th Hawaii International Conference on System Sciences}, editor = {Bui, Tung}, publisher = {Hawaii International Conference on System Sciences}, address = {Honolulu, HI}, isbn = {978-0-9981331-5-7}, doi = {10.24251/HICSS.2022.869}, pages = {7232 -- 7233}, year = {2022}, abstract = {Enterprise systems have long played an important role in businesses of various sizes. With the increasing complexity of today's business relationships, specialized application systems are being used more and more. Moreover, emerging technologies such as artificial intelligence are becoming accessible for enterprise systems. This raises the question of the future role of enterprise systems. This minitrack covers novel ideas that contribute to and shape the future role of enterprise systems with five contributions.}, language = {en} } @inproceedings{BenderBertheauGronau2021, author = {Bender, Benedict and Bertheau, Clementine and Gronau, Norbert}, title = {Future ERP Systems}, series = {Proceedings of the 23rd International Conference on Enterprise Information Systems (ICEIS 2021)}, booktitle = {Proceedings of the 23rd International Conference on Enterprise Information Systems (ICEIS 2021)}, number = {2}, publisher = {Science and Technology Publications}, address = {Set{\´u}bal}, isbn = {978-989-758-509-8}, issn = {2184-4992}, doi = {10.5220/0010477307760783}, pages = {776 -- 783}, year = {2021}, abstract = {This paper presents a research agenda on the current generation of ERP systems which was developed based on a literature review on current problems of ERP systems. The problems are presented following the ERP life cycle. In the next step, the identified problems are mapped on a reference architecture model of ERP systems that is an extension of the three-tier architecture model that is widely used in practice. The research agenda is structured according to the reference architecture model and addresses the problems identified regarding data, infrastructure, adaptation, processes, and user interface layer.}, language = {en} } @inproceedings{GrumKlippertAlbersetal.2021, author = {Grum, Marcus and Klippert, Monika and Albers, Albert and Gronau, Norbert and Thim, Christof}, title = {Examining the quality of knowledge transfers}, series = {Proceedings of the Design Society}, volume = {1}, booktitle = {Proceedings of the Design Society}, publisher = {Cambridge University Press}, address = {Cambridge}, issn = {2732-527X}, doi = {10.1017/pds.2021.404}, pages = {1431 -- 1440}, year = {2021}, abstract = {Already successfully used products or designs, past projects or our own experiences can be the basis for the development of new products. As reference products or existing knowledge, it is reused in the development process and across generations of products. Since further, products are developed in cooperation, the development of new product generations is characterized by knowledge-intensive processes in which information and knowledge are exchanged between different kinds of knowledge carriers. The particular knowledge transfer here describes the identification of knowledge, its transmission from the knowledge carrier to the knowledge receiver, and its application by the knowledge receiver, which includes embodied knowledge of physical products. Initial empirical findings of the quantitative effects regarding the speed of knowledge transfers already have been examined. However, the factors influencing the quality of knowledge transfer to increase the efficiency and effectiveness of knowledge transfer in product development have not yet been examined empirically. Therefore, this paper prepares an experimental setting for the empirical investigation of the quality of knowledge transfers.}, language = {en} } @inproceedings{GrumBenderGronauetal.2020, author = {Grum, Marcus and Bender, Benedict and Gronau, Norbert and Alfa, Attahiru S.}, title = {Efficient task realizations in networked production infrastructures}, series = {Proceedings of the Conference on Production Systems and Logistics}, booktitle = {Proceedings of the Conference on Production Systems and Logistics}, publisher = {publish-Ing.}, address = {Hannover}, doi = {10.15488/9682}, pages = {397 -- 407}, year = {2020}, abstract = {As Industry 4.0 infrastructures are seen as highly evolutionary environment with volatile, and time-dependent workloads for analytical tasks, particularly the optimal dimensioning of IT hardware is a challenge for decision makers because the digital processing of these tasks can be decoupled from their physical place of origin. Flexible architecture models to allocate tasks efficiently with regard to multi-facet aspects and a predefined set of local systems and external cloud services have been proven in small example scenarios. This paper provides a benchmark of existing task realization strategies, composed of (1) task distribution and (2) task prioritization in a real-world scenario simulation. It identifies heuristics as superior strategies.}, 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{GronauGrumBender2016, author = {Gronau, Norbert and Grum, Marcus and Bender, Benedict}, title = {Determining the optimal level of autonomy in cyber-physical production systems}, series = {IEEE 14th International Conference on Industrial Informatics (INDIN)}, booktitle = {IEEE 14th International Conference on Industrial Informatics (INDIN)}, publisher = {IEEE}, address = {New York}, doi = {10.1109/INDIN.2016.7819367}, pages = {1293 -- 1299}, year = {2016}, abstract = {Traditional production systems are enhanced by cyber-physical systems (CPS) and Internet of Things. A kind of next generation systems, those cyber-physical production systems (CPPS) are able to raise the level of autonomy of its production components. To find the optimal degree of autonomy in a given context, a research approach is formulated using a simulation concept. Based on requirements and assumptions, a cyber-physical market is modeled and qualitative hypotheses are formulated, which will be verified with the help of the CPPS of a hybrid simulation environment.}, language = {en} } @inproceedings{PanzerBenderGronau2021, author = {Panzer, Marcel and Bender, Benedict and Gronau, Norbert}, title = {Deep reinforcement learning in production planning and control}, series = {Proceedings of the Conference on Production Systems and Logistics}, booktitle = {Proceedings of the Conference on Production Systems and Logistics}, publisher = {publish-Ing.}, address = {Hannover}, issn = {2701-6277}, doi = {10.15488/11238}, pages = {535 -- 545}, year = {2021}, abstract = {Increasingly fast development cycles and individualized products pose major challenges for today's smart production systems in times of industry 4.0. The systems must be flexible and continuously adapt to changing conditions while still guaranteeing high throughputs and robustness against external disruptions. Deep rein- forcement learning (RL) algorithms, which already reached impressive success with Google DeepMind's AlphaGo, are increasingly transferred to production systems to meet related requirements. Unlike supervised and unsupervised machine learning techniques, deep RL algorithms learn based on recently collected sensor- and process-data in direct interaction with the environment and are able to perform decisions in real-time. As such, deep RL algorithms seem promising given their potential to provide decision support in complex environments, as production systems, and simultaneously adapt to changing circumstances. While different use-cases for deep RL emerged, a structured overview and integration of findings on their application are missing. To address this gap, this contribution provides a systematic literature review of existing deep RL applications in the field of production planning and control as well as production logistics. From a performance perspective, it became evident that deep RL can beat heuristics significantly in their overall performance and provides superior solutions to various industrial use-cases. Nevertheless, safety and reliability concerns must be overcome before the widespread use of deep RL is possible which presumes more intensive testing of deep RL in real world applications besides the already ongoing intensive simulations.}, language = {en} }