An investigation of knowledge protection practices in inter-organisational collaboration: protecting specialised engineering knowledge with a practice based on grey-box modelling
This paper reports about data-centric knowledge protection practices in the semi-conductor industry. The authors explore a grey-box modeling approach used for transferring data about machines and their operation in joint R&D projects. A total of 33 interviews have been conducted in two rounds: 30 interviews explore knowledge protection practices applied across a large project. SCHOLAR and APPLIER communicate using a data-centric knowledge protection practice, in that concrete parameter values are sensitive and hidden by communicating data within a wider parameter range. This practice balances the benefit that all three stakeholders have from communicating about specifics of machine design and operations. The line of thought described in this study is applicable to comparable collaboration constellations of a SUPPLIER of a machine, an APPLIER of a machine and a SCHOLAR who analyses and draws insights out of data. The paper fills a research gap by reporting on applied knowledge protection practices and characterising a data-centric knowledge protection practice around a grey-box model.
Kaiser, R., Thalmann, S. und Pammer-Schindler, V. (2020): An investigation of knowledge protection practices in inter-organisational collaboration: protecting specialised engineering knowledge with a practice based on grey-box modelling, in: VINE Journal of Information and Knowledge Management Systems, pp. 1-19, doi: https://doi.org/10.1108/VJIKMS-11-2019-0180 [24.7.2020].
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