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EXAMINING THE QUALITY OF KNOWLEDGE TRANSFERS – THE DRAFT OF AN EMPIRICAL RESEARCH

Published online by Cambridge University Press:  27 July 2021

Marcus Grum
Affiliation:
University of Potsdam
Monika Klippert*
Affiliation:
Karlsruhe Institute of Technology (KIT)
Albert Albers
Affiliation:
Karlsruhe Institute of Technology (KIT)
Norbert Gronau
Affiliation:
University of Potsdam
Christof Thim
Affiliation:
University of Potsdam
*
Klippert, Monika, Karlsruhe Institute of Technology (KIT), IPEK Institute of Product Engineering, Germany, monika.klippert@kit.edu

Abstract

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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.

Type
Article
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
The Author(s), 2021. Published by Cambridge University Press

References

Albers, A., Bursac, N. and Wintergerst, E. (2015), “Produktgenerationsentwicklung - Bedeutung und Herausforderungen aus einer entwicklungsmethodischen Perspektive”, in: Stuttgarter Symposium für Produktentwicklung, Vol. 2015.Google Scholar
Albers, A., Gronau, N., Rapp, A., Grum, M., Zaiser, A. and Weber, E. (2019a), Influencing factors and methods for knowledge transfer situations in Product Generation Engineering based on the SECI model, chapter Knowledge Transfer Velocity Model Implementation, Empirical Studies of Business Informatics, GITO, pp. 8-22.Google Scholar
Albers, A., Lüdcke, R., Bursac, N. and Will, J. (2014), “Process analysis and optimization by targeted application of knowledge management - a case study in the early stages of product development”, in: Methoden in der Produktentwicklung: Kopplung von Strategien und Werkzeugen im Produktentwicklungsprozess : 12. Gemeinsames Kolloquium Konstruktionstechnik Bayreuth, 16. - 17. Oktober 2014. Ed.: F. Rieg, Lehrstuhl für Konstruktionslehre und CAD, Universität Bayreuth, pp. 3342.Google Scholar
Albers, A., Rapp, A. and Grum, M. (2019b), Knowledge Transfer Speed Optimizations in Product Development Contexts, chapter Knowledge Transfer Velocity Model Implementation, Empirical Studies of Business Informatics, GITO, pp. 93104.Google Scholar
Arrow, K.J. (1969), “Classificatory notes on the production and transmission of technological knowledge”, The American Economic Review, Vol. 59 No. 2, pp. 2935.Google Scholar
ASQ (2020), Letter Q - Quality Glossary of Terms, Acronyms and Definitions with Letter Q, Quality glossary, American Society for Quality, Available at: https://asq.org/quality-resources/qualityglossary/q.Google Scholar
Becker, J., Rosemann, M. and Schütte, R. (1995), “Grundsätze ordnungsmäßiger Modellierung”, Wirtschaftsinformatik, Vol. 37 No. 5, pp. 435445.Google Scholar
Boghossian, P.A. (1989), “Content and self-knowledge”, Philosophical Topics, Vol. 17 No. 1, pp. 526.CrossRefGoogle Scholar
Connelly, C., Ford, D., Turel, O., Gallupe, B. and Zweig, D. (2014), “i'm busy (and competitive)!’ antecedents of knowledge sharing under pressure”, Knowledge Management Research & Practice, Vol. 12 No. 1, pp. 7485.CrossRefGoogle Scholar
Crosby, P.B. (1979), Quality is free: The art of making quality certain, Vol. 94, McGraw-hill, New York.Google Scholar
Dixon, N.M. (2000), Common knowledge: How companies thrive by sharing what they know, Harvard Business School Press.Google Scholar
Drucker, P. (1994), Post-capitalist Society, Butterworth-Heinemann.Google Scholar
Eckert, C., Alink, T., Albers, A. et al. (2010), “Issue driven analysis of an existing product at different levels of abstraction”, in: DS 60: Proceedings of DESIGN 2010, the 11th International Design Conference, Dubrovnik, Croatia, pp. 673682.Google Scholar
Gronau, N. (2019), Knowledge Modeling and Description Language 3.0 - Eine Einführung, Vol. 1, GITO mbH Verlag Berlin.Google Scholar
Gronau, N. and Grum, M. (2019), Knowledge Transfer Speed Optimizations in Product Development Contexts, chapter Towards a prediction of time consumption during knowledge transfer, Empirical Studies of Business Informatics, GITO, pp. 25-69.Google Scholar
Grum, M. and Gronau, N. (2018), “A visionary way to novel process optimizations - the marriage of the process domain and deep neuronal networks”, in: Shishkov, B. (Editor), Business Modeling and Software Design, Springer International Publishing, Cham, pp. 124.Google Scholar
Grum, M., Rapp, S., Gronau, N. and Albers, A. (2019), “Accelerating knowledge - the speed optimization of knowledge transfers”, in: Shishkov, B. (Editor), Business Modeling and Software Design, Springer International Publishing, Cham, pp. 95113.CrossRefGoogle Scholar
Hult, G.T.M., Ketchen, D.J. and Slater, S.F. (2004), “Information processing, knowledge development, and strategic supply chain performance”, Academy of Management Journal, Vol. 47 No. 2, pp. 241253.Google Scholar
Ignatow, G. (2007), “Theories of embodied knowledge: New directions for cultural and cognitive sociology?”, Journal for the Theory of Social Behaviour, Vol. 37 No. 2, pp. 115135.CrossRefGoogle Scholar
ISO, I. (2019), “Iec 25030 software and system engineering–software product quality requirements and evaluation (square)–quality requirements”, International Organization for Standarization.Google Scholar
Likert, R. (1932), “A technique for the measurement of attitudes”, Archives of Psychology, Vol. 22 No. 140, p. 55.Google Scholar
Lindemann, U., Lorenz, M. et al. (2008), “Uncertainty handling in integrated product development”, in: DS 48: Proceedings DESIGN 2008, the 10th International Design Conference, Dubrovnik, Croatia, pp. 175182.Google Scholar
Loewenstein, G. (1999), “Experimental economics from the vantage-point of behavioural economics”, The Economic Journal, Vol. 109 No. 453, pp. F25F34.CrossRefGoogle Scholar
March, J. (1994), A Primer on Decision-Making, Free Press, New York, NY.Google Scholar
Nonaka, I. and Takeuchi, H. (1995), The knowledge-creating company: How Japanese companies create the dynamics of innovation, Oxford university press.Google Scholar
Peffers, K., Tuunanen, T., Rothenberger, M.A. and Chatterjee, S. (2007), “A design science research methodology for information systems research”, Journal of management information systems, Vol. 24 No. 3, pp. 4577.CrossRefGoogle Scholar
Rhodes, J., Hung, R., Lok, P., Lien, B.Y.H. and Wu, C.M. (2008), “Factors influencing organizational knowledge transfer: implication for corporate performance”, Journal of knowledge management, Vol. 12 No. 3, pp. 84100.CrossRefGoogle Scholar
Sommerlatte, T., Beyer, G. and Seidel, G. (2006), Innovationskultur und Ideenmanagement, Symposion Publishing GmbH.Google Scholar
Szulanski, G. (1996), “Exploring internal stickiness: Impediments to the transfer of best practice within the firm”, Strategic Management Journal, Vol. 17 No. S2, pp. 2743.CrossRefGoogle Scholar
Szulanski, G. (2000), “The process of knowledge transfer: A diachronic analysis of stickiness”, Organizational Behavior and Human Decision Processes, Vol. 82 No. 1, pp. 9-27.CrossRefGoogle Scholar
Walter, B., Albers, A., Benesch, G. and Bursac, B. (2017), “ProVIL - Produktentwicklung im virtuellen Ideenlabor: Anwendungs- und Implementierungsmodell eines Live-Labs”, in: Binz, H. (Editor), 4. Stuttgarter Symposium für Produktentwicklung 2017, Fraunhofer Verlag, Stuttgart, Deutschland.Google Scholar
Walter, B., Albers, A., Haupt, F., Bursac, N. et al. (2016), “Produktentwicklung im virtuellen Ideenlabor - Konzipierung und Implementierung eines Live-Lab”, in: DFX 2016: Proceedings of the 27th Symposium Design for X, 5-6 October 2016, Jesteburg, Germany, pp. 283295.Google Scholar
Wang, R.Y. and Strong, D.M. (1996), “Beyond accuracy: What data quality means to data consumers”, Journal of management information systems, Vol. 12 No. 4, pp. 533.CrossRefGoogle Scholar
Zagzebski, L. (2017), What is Knowledge?, chapter 3, John Wiley and Sons, Ltd, pp. 92116.Google Scholar