TY  - CHAP
A1  - Grum, Marcus
A1  - Gronau, Norbert
A2  - Shishkov, Boris
T1  - Adaptable knowledge-driven information systems improving knowledge transfers
T2  - Business modeling and software design : 10th International Symposium, BMSD 2020, Berlin, Germany, July 6-8, 2020, Proceedings
N2  - A growing number of business processes can be characterized as knowledge-intensive. The ability to speed up the transfer of knowledge between any kind of knowledge carriers in business processes with AR techniques can lead to a huge competitive advantage, for instance in manufacturing. This includes the transfer of person-bound knowledge as well as externalized knowledge of physical and virtual objects. The contribution builds on a time-dependent knowledge transfer model and conceptualizes an adaptable, AR-based application. Having the intention to accelerate the speed of knowledge transfers between a manufacturer and an information system, empirical results of an experimentation show the validity of this approach. For the first time, it will be possible to discover how to improve the transfer among knowledge carriers of an organization with knowledge-driven information systems (KDIS). Within an experiment setting, the paper shows how to improve the quantitative effects regarding the quality and amount of time needed for an example manufacturing process realization by an adaptable KDIS.
KW  - augmented reality
KW  - knowledge transfers
KW  - empirical studies
KW  - context-aware computing
KW  - adaptable software systems
KW  - business process improvement
Y1  - 2020
UR  - https://publishup.uni-potsdam.de/frontdoor/index/index/docId/60557
SN  - 978-3-030-52305-3
SN  - 978-3-030-52306-0
VL  - 391
SP  - 202
EP  - 220
PB  - Springer International Publishing
CY  - Cham
ER  -