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 - TY - CHAP A1 - Hafner, Julee A1 - Thim, Christof T1 - Innovation in organizations: learning, unlearning, and intentional forgetting T2 - Proceedings of the 55th Hawaii International Conference on System Sciences (HICSS) N2 - We welcome you to the 53rd Hawaii International Conference on System Sciences (HICSS) conference. After joining with Intentional Forgetting Minitrack last year, this is the fourth year of the Organizational Learning Minitrack. We add Unlearning, and Intentional Forgetting to proudly bring you the latest research focused on organizational learning issues within the Knowledge Innovation and Entrepreneurial Systems Track. The ability to update, change and use current knowledge effectively, especially in light of the ongoing knowledge explosion, can be costly for any organization. Organizations that consider themselves “learning” or “knowledge-based” organizations must develop a competent workforce using KM strategies. Success in organizations involves developing a variety of human factors for changing competencies. With technological change, modification and revisions, many skills require updating for a competitive advantage in the marketplace. The focus on new techniques and insights into how individuals and organizations use their knowledge is our focus for the improvement of organizational learning in this Minitrack. Y1 - 2022 SN - 978-099813315-7 SP - 4784 EP - 4785 PB - University of Hawai’i at Manoa Hamilton Library CY - Honolulu, HI ER - TY - CHAP A1 - Hafner, Julee A1 - Thim, Christof ED - Bui, Tung T1 - Knowledge, innovation and entrepreneurial systems track innovation in organizations BT - learning, unlearning, and intentional forgetting T2 - Proceedings of the 54th Hawaii International Conference on System Sciences N2 - We welcome you to the 54th Hawaii International Conference on System Sciences (HICSS-54) conference. This is the fifth year for the Organizational Learning Minitrack which has had the usual growing pains: two years ago, we added the topic of Unlearning and joined with the Intentional Forgetting Minitrack - as these topics are all organizationally-based knowledge management issues. We proudly bring you the latest research focused on the methods to develop and maintain organizational learning within the Knowledge Innovation and Entrepreneurial Systems Track. The ability to update, change and use current knowledge effectively, especially in light of the ongoing knowledge explosion, can be costly for any organization. Organizations that consider themselves “learning” or “knowledge-based” organizations must develop a competent workforce using KM strategies. Success in organizations involves developing a variety of human factors for changing competencies. With technological change, modification and revisions, many skills require updating for a competitive advantage in the marketplace. The focus on new techniques and insights into how individuals and organizations use their knowledge is our focus for the improvement of organizational learning in this Minitrack. Y1 - 2021 SN - 978-0-9981331-4-0 SP - 5046 EP - 5047 PB - University of Hawai'i at Manoa, Hamilton Library CY - Honolulu, HI ER - TY - CHAP 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 T2 - 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 - Rojahn, Marcel A1 - Gronau, Norbert ED - Bui, Tung X. T1 - Openness indicators for the evaluation of digital platforms between the launch and maturity phase T2 - Proceedings of the 57th Annual Hawaii International Conference on System Sciences N2 - 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. KW - federated industrial platform ecosystems KW - technologies KW - business models KW - data-driven artifacts KW - design-science research KW - digital platform openness KW - evaluation KW - morphological analysis Y1 - 2024 SN - 978-0-99813-317-1 SP - 4516 EP - 4525 PB - Department of IT Management Shidler College of Business University of Hawaii CY - Honolulu, HI ER - TY - CHAP A1 - Höchenberger, Ralf A1 - Hummel, Detlev A1 - Seitz, Jürgen ED - Sharma, Neha ED - Goje, Amol ED - Chakrabarti, Amlan ED - Bruckstein, Alfred M. T1 - Do women shy away from cryptocurrency investment? BT - cross-country evidence from survey data T2 - Data management, analytics and innovation N2 - This study utilizes cross-country survey data to analyze differences in attitudes toward cryptocurrency as an alternative to traditional money issued by a central bank. Particularly, we investigate women’s general attitude toward cryptocurrency systems. Results suggest that women invest less into cryptocurrency, show less interest in the future cryptocurrency investment, and see less economic potential in these systems than men do. Further evidence shows that these attitudes are directly connected with lower literacy in cryptocurrency systems. These findings support theory on gender differences in investment behavior. We contribute to the existing literature by conducting a cross-country survey on cryptocurrency attitudes in Europe and Asia, and hence show that this gender effect is robust across these cultures. KW - cryptocurrencies KW - bitcoin KW - financial literacy KW - gender gap KW - risk tolerance Y1 - 2023 SN - 978-981-99-1413-5 SN - 978-981-99-1414-2 U6 - https://doi.org/10.1007/978-981-99-1414-2_6 SP - 69 EP - 76 PB - Springer Nature CY - Singapore ER - TY - CHAP A1 - Grum, Marcus A1 - Blunk, Oliver A1 - Rojahn, Marcel A1 - Fettke, Peter A1 - Gronau, Norbert T1 - Research challenges of knowledge modelling and the outline of a research agenda T2 - Knowledge in digital age : IFKAD 2020 KW - knowledge management KW - process modelling KW - research challenges Y1 - 2020 SN - 978-88-96687-13-0 SN - 2280-787X PB - The Arts of Business Institute CY - Matera, Italy ER - TY - CHAP A1 - Schladebach, Marcus ED - Gräfe, Hans-Christian T1 - Satelliten-Megakonstellationen im Weltraumrecht T2 - Tagungsband zur Sommerkonferenz 2022 : Telemedicus – Recht der Informationsgesellschaft Y1 - 2022 UR - https://rainermuehlhoff.de/media/publications/telemedicus-2022-tagungsband-isbn-978-3-8005-1857-9.pdf SN - 978-3-8005-1857-9 VL - 6 SP - 68 EP - 75 PB - Fachmedien Recht und Wirtschaft, dfv Mediengruppe CY - Frankfurt am Main ER - TY - CHAP A1 - Schenke, Maren A1 - Schjeide, Brit-Maren A1 - Püschel, Gerhard A1 - Seeger, Bettina T1 - Human motor neurons diffentiated from plutipotent stem cells as superior traged cells for botulinum neuotoxin potency testing BT - In: German Pharm-Tox Summit 2020: abstracts of the 86th Annual Meeting of the German Society for Experimental and Clinical Pharmacology and Toxicology (DGPT) T2 - Naunyn-Schmiedeberg's archives of pharmacology Y1 - 2020 U6 - https://doi.org/10.1007/s00210-020-01828-y SN - 0028-1298 SN - 1432-1912 VL - 393 IS - SUPPL 1 SP - S10 EP - S10 PB - Springer CY - Berlin ; Heidelberg ER - TY - CHAP A1 - Clausen, Sünje A1 - Brünker, Felix A1 - Stieglitz, Stefan T1 - Towards responsible augmentation BT - identifying characteristics of AI-based technology with ethical implications for knowledge workers T2 - ACIS 2023 proceedings N2 - Artificial intelligence (AI)-based technologies can increasingly perform knowledge work tasks, such as medical diagnosis. Thereby, it is expected that humans will not be replaced by AI but work closely with AI-based technology (“augmentation”). Augmentation has ethical implications for humans (e.g., impact on autonomy, opportunities to flourish through work), thus, developers and managers of AI-based technology have a responsibility to anticipate and mitigate risks to human workers. However, doing so can be difficult as AI encompasses a wide range of technologies, some of which enable fundamentally new forms of interaction. In this research-in-progress paper, we propose the development of a taxonomy to categorize unique characteristics of AI-based technology that influence the interaction and have ethical implications for human workers. The completed taxonomy will support researchers in forming cumulative knowledge on the ethical implications of augmentation and assist practitioners in the ethical design and management of AI-based technology in knowledge work. KW - artificial intelligence KW - augmentation KW - taxonomy KW - human-AI interaction KW - ethics Y1 - 2023 UR - https://aisel.aisnet.org/acis2023/123/ PB - Australasian Association for Information Systems CY - Wellington ER -