TY - JOUR A1 - Kluge, Annette A1 - Gronau, Norbert T1 - Intentional forgetting in organizations BT - the Importance of Eliminating Retrieval Cues for Implementing New Routines JF - Frontiers in psychology N2 - To cope with the already large, and ever increasing, amount of information stored in organizational memory, "forgetting," as an important human memory process, might be transferred to the organizational context. Especially in intentionally planned change processes (e.g., change management), forgetting is an important precondition to impede the recall of obsolete routines and adapt to new strategic objectives accompanied by new organizational routines. We first comprehensively review the literature on the need for organizational forgetting and particularly on accidental vs. intentional forgetting. We discuss the current state of the art of theory and empirical evidence on forgetting from cognitive psychology in order to infer mechanisms applicable to the organizational context. In this respect, we emphasize retrieval theories and the relevance of retrieval cues important for forgetting. Subsequently, we transfer the empirical evidence that the elimination of retrieval cues leads to faster forgetting to the forgetting of organizational routines, as routines are part of organizational memory. We then propose a classification of cues (context, sensory, business process-related cues) that are relevant in the forgetting of routines, and discuss a meta-cue called the "situational strength" cue, which is relevant if cues of an old and a new routine are present simultaneously. Based on the classification as business process-related cues (information, team, task, object cues), we propose mechanisms to accelerate forgetting by eliminating specific cues based on the empirical and theoretical state of the art. We conclude that in intentional organizational change processes, the elimination of cues to accelerate forgetting should be used in change management practices. KW - change management KW - multi-actor routines KW - business processes KW - knowledge management KW - organizational memory KW - situational strength Y1 - 2018 U6 - https://doi.org/10.3389/fpsyg.2018.00051 SN - 1664-1078 VL - 9 PB - Frontiers Research Foundation CY - Lausanne ER - TY - JOUR A1 - Teichmann, Malte A1 - Ullrich, André A1 - Bender, Benedict A1 - Gronau, Norbert T1 - Mobile IIoT-Technologien in hybriden Lernfabriken T1 - Using Mobile IIoT-Technologies in Hybrid Learning Factories BT - Szenariobasierte Entwicklung von Handlungskompetenz im Anwendungszentrum Industrie 4.0 BT - a Scenario-Based Development of Acting Capability in the Application Center Industry 4.0 JF - Industrie 4.0 Management N2 - Der Wandel zur automatisierten Produktion, die fortschreitende Digitalisierung der Wertschöpfungsprozesse sowie die stetige Implementierung von mobilen Industrial Internet of Things-Technologien (IIoT) in diese zur Unterstützung der Mitarbeiter stellen betriebliche Weiterbildung vor Herausforderungen. Komple-xere Anforderungen und veränderte Tätigkeitsprofile erfordern Handlungskom-petenzen bei Mitarbeitern im Sinne der Fähigkeit, in unbekannten Situationen auf Basis eigenen Könnens handlungsfähig zu bleiben. Jene sowie dafür notwendiges umfassendes Verständnis gegenüber digitalisierten Produktions-prozessen kann jedoch durch konventionelle Lehrmethoden nicht realisiert werden, da diese der erhöhten Anforderungskomplexität und den komplexen Rückkopplungen im Rahmen der Steuer- und Regelkreise nicht gerecht werden können. Diese Aspekte aufgreifend wird im Folgenden ein szenariobasierter Wei-terbildungsansatz für eine Lernfabrik vorgestellt, der insbesondere die Potenziale mobiler IIoT-Technologien zur Ausgestaltung dieser in den Blick nimmt. N2 - Recently, implementation procedures of automatic production, digitalization and Industrial Internet of Things technologies (IIoT) play an increasing role in industrial manufacturing processes. Subsequently, the competence requirements for employees change. These changes cannot be anticipated by traditional learning approaches. The following contribution faces this challenge and will show a new integrated learning factory approach which combines the application of new technologies with a flexible production environment. Thus establishing production surroundings that are familiar to the learner. The contribution demonstrates this approach using a quality control process in the context of logistics. KW - Mobile IIoT-Technologie KW - Lernszenario KW - Anwendungszentrum Industrie 4.0 KW - Lernfabrik KW - mobile IIoT-technologies KW - learning scenario KW - application center Industrie 4.0 KW - digital learning factory Y1 - 2018 U6 - https://doi.org/10.30844/I40M_18-3_S21-24 SN - 2364-9208 VL - 34 IS - 3 SP - 21 EP - 24 PB - GITO CY - Berlin ER - TY - JOUR A1 - Gronau, Norbert T1 - Industrie 4.0 JF - Von Industrial Internet of Things zu Industrie 4.0. Band 2 Y1 - 2018 SN - 978-3-95545-261-2 SP - 191 EP - 228 PB - Gito CY - Berlin ER - TY - GEN A1 - Kluge, Annette A1 - Gronau, Norbert T1 - Intentional forgetting in organizations BT - the importance of eliminating retrieval cues for implementing new routines T2 - Postprints der Universität Potsdam : Wirtschafts- und Sozialwissenschaftliche Reihe N2 - To cope with the already large, and ever increasing, amount of information stored in organizational memory, "forgetting," as an important human memory process, might be transferred to the organizational context. Especially in intentionally planned change processes (e.g., change management), forgetting is an important precondition to impede the recall of obsolete routines and adapt to new strategic objectives accompanied by new organizational routines. We first comprehensively review the literature on the need for organizational forgetting and particularly on accidental vs. intentional forgetting. We discuss the current state of the art of theory and empirical evidence on forgetting from cognitive psychology in order to infer mechanisms applicable to the organizational context. In this respect, we emphasize retrieval theories and the relevance of retrieval cues important for forgetting. Subsequently, we transfer the empirical evidence that the elimination of retrieval cues leads to faster forgetting to the forgetting of organizational routines, as routines are part of organizational memory. We then propose a classification of cues (context, sensory, business process-related cues) that are relevant in the forgetting of routines, and discuss a meta-cue called the "situational strength" cue, which is relevant if cues of an old and a new routine are present simultaneously. Based on the classification as business process-related cues (information, team, task, object cues), we propose mechanisms to accelerate forgetting by eliminating specific cues based on the empirical and theoretical state of the art. We conclude that in intentional organizational change processes, the elimination of cues to accelerate forgetting should be used in change management practices. T3 - Zweitveröffentlichungen der Universität Potsdam : Wirtschafts- und Sozialwissenschaftliche Reihe - 127 KW - change management KW - multi-actor routines KW - business processes KW - knowledge management KW - organizational memory KW - situational strength Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-446022 SN - 1867-5808 IS - 127 ER - TY - GEN A1 - Grum, Marcus A1 - Gronau, Norbert T1 - Process modeling within augmented reality BT - the bidirectional interplay of two worlds T2 - Business Modeling and Software Design, BMSD 2018 N2 - The collaboration during the modeling process is uncomfortable and characterized by various limitations. Faced with the successful transfer of first process modeling languages to the augmented world, non-transparent processes can be visualized in a more comprehensive way. With the aim to rise comfortability, speed, accuracy and manifoldness of real world process augmentations, a framework for the bidirectional interplay of the common process modeling world and the augmented world has been designed as morphologic box. Its demonstration proves the working of drawn AR integrations. Identified dimensions were derived from (1) a designed knowledge construction axiom, (2) a designed meta-model, (3) designed use cases and (4) designed directional interplay modes. Through a workshop-based survey, the so far best AR modeling configuration is identified, which can serve for benchmarks and implementations. KW - Augmented reality KW - Process modeling KW - Simulation process building KW - Generalized knowledge constructin axiom KW - Meta-model KW - Use cases Morphologic box KW - Industry 4.0 KW - CPS KW - CPPS KW - Internet of things Y1 - 2018 SN - 978-3-319-94214-8 SN - 978-3-319-94213-1 U6 - https://doi.org/10.1007/978-3-319-94214-8_7 SN - 1865-1348 VL - 319 SP - 99 EP - 115 PB - Springer CY - Berlin ER - TY - BOOK A1 - Gronau, Norbert A1 - Gäbler, Andreas T1 - Einführung in die Wirtschaftsinformatik : Bd. 1 T3 - Skripte zur Wirtschafsinformatik Y1 - 2018 SN - 978-3-95545-233-9 PB - Gito CY - Berlin ET - 7. überarb. Aufl. ER - TY - JOUR A1 - Grum, Marcus A1 - Bender, Benedict A1 - Alfa, A. S. A1 - Gronau, Norbert T1 - A decision maxim for efficient task realization within analytical network infrastructures JF - Decision support systems : DSS ; the international journal N2 - Faced with the increasing needs of companies, optimal dimensioning of IT hardware is becoming challenging for decision makers. In terms of analytical infrastructures, a highly evolutionary environment causes volatile, time dependent workloads in its components, and intelligent, flexible task distribution between local systems and cloud services is attractive. With the aim of developing a flexible and efficient design for analytical infrastructures, this paper proposes a flexible architecture model, which allocates tasks following a machine-specific decision heuristic. A simulation benchmarks this system with existing strategies and identifies the new decision maxim as superior in a first scenario-based simulation. KW - Analytics KW - Architecture concepts KW - Cyber-physical systems KW - Internet of things KW - Task realization strategies KW - Simulation Y1 - 2018 U6 - https://doi.org/10.1016/j.dss.2018.06.005 SN - 0167-9236 SN - 1873-5797 VL - 112 SP - 48 EP - 59 PB - Elsevier CY - Amsterdam ER -