TY - JOUR A1 - de Paula, Danielly A1 - Marx, Carolin A1 - Wolf, Ella A1 - Dremel, Christian A1 - Cormican, Kathryn A1 - Uebernickel, Falk T1 - A managerial mental model to drive innovation in the context of digital transformation JF - Industry and innovation N2 - Industry 4.0 is transforming how businesses innovate and, as a result, companies are spearheading the movement towards 'Digital Transformation'. While some scholars advocate the use of design thinking to identify new innovative behaviours, cognition experts emphasise the importance of top managers in supporting employees to develop these behaviours. However, there is a dearth of research in this domain and companies are struggling to implement the required behaviours. To address this gap, this study aims to identify and prioritise behavioural strategies conducive to design thinking to inform the creation of a managerial mental model. We identify 20 behavioural strategies from 45 interviewees with practitioners and educators and combine them with the concepts of 'paradigm-mindset-mental model' from cognition theory. The paper contributes to the body of knowledge by identifying and prioritising specific behavioural strategies to form a novel set of survival conditions aligned to the new industrial paradigm of Industry 4.0. KW - Strategic cognition KW - mental models KW - industry 4.0 KW - digital transformation KW - design thinking Y1 - 2022 U6 - https://doi.org/10.1080/13662716.2022.2072711 SN - 1366-2716 SN - 1469-8390 PB - Routledge, Taylor & Francis Group CY - Abingdon ER - TY - CHAP A1 - Grum, Marcus A1 - Thim, Christof A1 - Roling, Wiebke A1 - Schüffler, Arnulf A1 - Kluge, Annette A1 - Gronau, Norbert ED - Masrour, Tawfik ED - El Hassani, Ibtissam ED - Barka, Noureddine T1 - AI case-based reasoning for artificial neural networks T2 - Artificial intelligence and industrial applications N2 - Faced with the triad of time-cost-quality, the realization of production tasks under economic conditions is not trivial. Since the number of Artificial-Intelligence-(AI)-based applications in business processes is increasing more and more nowadays, the efficient design of AI cases for production processes as well as their target-oriented improvement is essential, so that production outcomes satisfy high quality criteria and economic requirements. Both challenge production management and data scientists, aiming to assign ideal manifestations of artificial neural networks (ANNs) to a certain task. Faced with new attempts of ANN-based production process improvements [8], this paper continues research about the optimal creation, provision and utilization of ANNs. Moreover, it presents a mechanism for AI case-based reasoning for ANNs. Experiments clarify continuously improving ANN knowledge bases by this mechanism empirically. Its proof-of-concept is demonstrated by the example of four production simulation scenarios, which cover the most relevant use cases and will be the basis for examining AI cases on a quantitative level. KW - case-based reasoning KW - neural networks KW - industry 4.0 Y1 - 2023 SN - 978-3-031-43523-2 SN - 978-3-031-43524-9 U6 - https://doi.org/10.1007/978-3-031-43524-9_2 VL - 771 SP - 17 EP - 35 PB - Springer CY - Cham ER - TY - JOUR A1 - Vladova, Gergana A1 - Wotschack, Philip A1 - Lareiro, Patricia de Paiva A1 - Gronau, Norbert A1 - Thim, Christof T1 - Lernen mit Assistenzsystemen T1 - Learning with assistance systems BT - vor lauter Aufgaben den Prozess nicht sehen? BT - not seeing the process for the tasks? JF - Industrie 4.0 Management : Gegenwart und Zukunft industrieller Geschäftsprozesse N2 - Der Beitrag beschreibt die Konzeption und Durchführung und bietet einen Einblick in die ersten Ergebnisse einer Untersuchung mit experimentellem Design in einer simulierten Prozessumgebung im Forschungs- und Anwendungszentrum Industrie 4.0 in Potsdam. Im Mittelpunkt stehen Anlernprozesse im Bereich der Einfacharbeit (Helfertätigkeiten) und ihre Gestaltung durch den Einsatz digitaler Assistenzsysteme. In der Arbeitsforschung finden sich Hinweise darauf, dass mit dem Einsatz dieser Systeme Prozesswissen verloren geht, im Sinne einer guten Kenntnis des gesamten Arbeitsprozesses, in den die einzelnen Tätigkeiten eingebettet sind. Das kann sich als Problem erweisen, vor allem wenn unvorhersehbare Situationen oder Fehler eintreten. Um die Rolle von Prozesswissen beim Einsatz von digitalen Assistenzsystemen zu untersuchen, wird im Experiment eine echte Fabriksituation simuliert. Die Probanden werden über ein Assistenzsystem Schritt für Schritt in ihre Aufgabentätigkeit angelernt, einem Teil der Probanden wird allerdings am Anfang zusätzlich Prozesswissen im Rahmen einer kurzen Schulung vermittelt. N2 - The paper describes the conception and implementation as well as offers an insight into the first results of a study with experimental design in a simulated process environment at the Research and Application Center Industry 4.0 in Potsdam. The focus is on learning processes in the field of simple work and their organization through the use of digital assistance systems. In labour research, there are indications that process knowledge is lost with the use of these systems, in the sense of a good knowledge of the entire work process in which the individual activities are embedded. To investigate the role of process knowledge in the use of digital assistance systems, a real factory situation is simulated in the experiment. KW - Assistenzsysteme KW - Industrie 4.0 KW - Prozesswissen KW - Lernfabrik KW - assistance systems KW - industry 4.0 KW - process knowledge KW - learning factory Y1 - 2020 U6 - https://doi.org/10.30844/I40M_20-3_S16-20 SN - 2364-9208 VL - 36 IS - 3 SP - 16 EP - 20 PB - GITO mbH Verlag CY - Berlin ER - TY - CHAP A1 - Ullrich, André A1 - Gronau, Norbert ED - Panetto, Hervé ED - Madani, Kurosh ED - Smirnov, Alexander T1 - Time to change BT - considering the 4th Industrial Revolution from three sustainability perspectives T2 - Proceedings of the International Conference on Innovative Intelligent Industrial Production and Logistics N2 - Industry 4.0 leads to a radical change that is progressing incrementally. The new information and communication technologies provide many conceivable opportunities for their application in the context of sustainable corporate management. The combination of new digital technologies with the ecological and social goals of companies offers a multitude of unimagined potentials and challenges. Although companies already see the need for action, there was in the past and currently still is a lack of concrete measures that lever the potential of Industry 4.0 for sustainability management. During the course of this position paper we develop six theses (two from each sustainability perspective) against the background of the current situation in research and practice, and policy. KW - industry 4.0 KW - sustainability KW - triple bottom line Y1 - 2020 SN - 978-989-758-476-3 U6 - https://doi.org/10.5220/0010148601090116 SP - 109 EP - 116 PB - SciTePress CY - [Erscheinungsort nicht ermittelbar] ER -