TY - CHAP A1 - Grum, Marcus A1 - Gronau, Norbert ED - Shishkov, Boris T1 - Quantification of knowledge transfers BT - the design of an experiment setting for the examination of knowledge transfers T2 - Business modeling and software design : 11th International Symposium, BMSD 2021, Sofia, Bulgaria, July 5–7, 2021, Proceedings N2 - Faced with the triad of time-cost-quality, the realization of knowledge-intensive tasks at economic conditions is not trivial. Since the number of knowledge-intensive processes is increasing more and more nowadays, the efficient design of knowledge transfers at business processes as well as the target-oriented improvement of them is essential, so that process outcomes satisfy high quality criteria and economic requirements. This particularly challenges knowledge management, aiming for the assignment of ideal manifestations of influence factors on knowledge transfers to a certain task. Faced with first attempts of knowledge transfer-based process improvements [1], this paper continues research about the quantitative examination of knowledge transfers and presents a ready-to-go experiment design that is able to examine quality of knowledge transfers empirically and is suitable to examine knowledge transfers on a quantitative level. Its use is proven by the example of four influence factors, which namely are stickiness, complexity, competence and time pressure. KW - knowledge management KW - knowledge transfer KW - conversion KW - empirical examination KW - experiment Y1 - 2021 SN - 978-3-030-79975-5 SN - 978-3-030-79976-2 U6 - https://doi.org/10.1007/978-3-030-79976-2_13 VL - 422 SP - 224 EP - 242 PB - Springer International Publishing CY - Cham ER - TY - CHAP A1 - Grum, Marcus ED - Shishkov, Boris T1 - Context-aware, intelligent musical instruments for improving knowledge-intensive business processes T2 - Business modeling and software design N2 - With shorter song publication cycles in music industries and a reduced number of physical contact opportunities because of disruptions that may be an obstacle for musicians to cooperate, collaborative time consumption is a highly relevant target factor providing a chance for feedback in contemporary music production processes. This work aims to extend prior research on knowledge transfer velocity by augmenting traditional designs of musical instruments with (I) Digital Twins, (II) Internet of Things and (III) Cyber-Physical System capabilities and consider a new type of musical instrument as a tool to improve knowledge transfers at knowledge-intensive forms of business processes. In a design-science-oriented way, a prototype of a sensitive guitar is constructed as information and cyber-physical system. Findings show that this intelligent SensGuitar increases feedback opportunities. This study establishes the importance of conversion-specific music production processes and novel forms of interactions at guitar playing as drivers of high knowledge transfer velocities in teams and among individuals. KW - business process KW - knowledge transfer KW - CPS KW - prototype Y1 - 2022 SN - 978-3-031-11509-7 SN - 978-3-031-11510-3 U6 - https://doi.org/10.1007/978-3-031-11510-3_5 VL - 453 SP - 69 EP - 88 PB - Springer CY - Cham ER - TY - JOUR A1 - Klippert, Monika A1 - Stolpmann, Robert A1 - Grum, Marcus A1 - Thim, Christof A1 - Gronau, Norbert A1 - Albers, Albert T1 - Knowledge transfer quality improvement BT - the quality enhancement of knowledge transfers in product engineering JF - Procedia CIRP N2 - Developing a new product generation requires the transfer of knowledge among various knowledge carriers. Several factors influence knowledge transfer, e.g., the complexity of engineering tasks or the competence of employees, which can decrease the efficiency and effectiveness of knowledge transfers in product engineering. Hence, improving those knowledge transfers obtains great potential, especially against the backdrop of experienced employees leaving the company due to retirement, so far, research results show, that the knowledge transfer velocity can be raised by following the Knowledge Transfer Velocity Model and implementing so-called interventions in a product engineering context. In most cases, the implemented interventions have a positive effect on knowledge transfer speed improvement. In addition to that, initial theoretical findings describe factors influencing the quality of knowledge transfers and outline a setting to empirically investigate how the quality can be improved by introducing a general description of knowledge transfer reference situations and principles to measure the quality of knowledge artifacts. To assess the quality of knowledge transfers in a product engineering context, the Knowledge Transfer Quality Model (KTQM) is created, which serves as a basis to develop and implement quality-dependent interventions for different knowledge transfer situations. As a result, this paper introduces the specifications of eight situation-adequate interventions to improve the quality of knowledge transfers in product engineering following an intervention template. Those interventions are intended to be implemented in an industrial setting to measure the quality of knowledge transfers and validate their effect. KW - knowledge transfer KW - product generation engineering KW - improvement KW - quality KW - intervention Y1 - 2023 U6 - https://doi.org/10.1016/j.procir.2023.02.171 SN - 2212-8271 VL - 119 SP - 919 EP - 925 PB - Elsevier CY - Amsterdam ER - TY - CHAP A1 - Vladova, Gergana A1 - Ullrich, André A1 - Sultanow, Eldar A1 - Tobolla, Marinho A1 - Sebrak, Sebastian A1 - Czarnecki, Christian A1 - Brockmann, Carsten ED - Klein, Maike ED - Krupka, Daniel ED - Winter, Cornelia ED - Wohlgemuth, Volker T1 - Visual analytics for knowledge management BT - advantages for organizations and interorganizational teams T2 - Informatik 2023 N2 - 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. KW - knowledge management KW - visual analytics KW - knowledge transfer KW - teamwork KW - knowledge management system KW - tacit knowledge KW - explicit knowledge Y1 - 2023 SN - 978-3-88579-731-9 U6 - https://doi.org/10.18420/inf2023_187 SN - 1617-5468 SP - 1851 EP - 1870 PB - Gesellschaft für Informatik e.V. (GI) CY - Bonn ER -