Extending a System for Measuring Dynamic Knowledge: Reconsidering Knowledge Flow Efficiency for Decision Support

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dc.contributor.authorNissen, Mark
dc.date.accessioned2020-01-04T08:11:15Z
dc.date.available2020-01-04T08:11:15Z
dc.date.issued2020-01-07
dc.description.abstractKnowledge is key to competitive advantage, but it is inherently invisible, intangible and resistant to quantification, particularly when in dynamic motion. Recent research builds upon emerging knowledge measurement techniques and well-established knowledge flow theory to develop a system for measuring dynamic knowledge in the organization. Results from application to archetypical organization processes are highly consistent with extant theory. However, they also lead us to question some theoretic concepts and correspondences. In this article, we extend the measurement system and reconsider the effects of knowledge flow efficiency through dynamic measurement. We then illustrate how such extension establishes a novel decision support capability.
dc.format.extent10 pages
dc.identifier.doi10.24251/HICSS.2020.596
dc.identifier.isbn978-0-9981331-3-3
dc.identifier.urihttp://hdl.handle.net/10125/64338
dc.language.isoeng
dc.relation.ispartofProceedings of the 53rd Hawaii International Conference on System Sciences
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectKnowledge Flow, Transfer, Sharing, and Exchange
dc.subjectdecision support
dc.subjectdynamics
dc.subjectflow
dc.subjectknowledge
dc.subjectmeasurement
dc.titleExtending a System for Measuring Dynamic Knowledge: Reconsidering Knowledge Flow Efficiency for Decision Support
dc.typeConference Paper
dc.type.dcmiText

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