A Case of Obstructing Conditions in Knowledge Flow Dynamics

dc.contributor.author Lo, Lina
dc.date.accessioned 2019-01-03T00:40:52Z
dc.date.available 2019-01-03T00:40:52Z
dc.date.issued 2019-01-08
dc.description.abstract Knowledge flows unevenly throughout an organization and the problem is that the fundamental dynamics of these flows are still not well characterized in theoretical and computational models. This study built on existing work—knowledge-flow theory, need knowledge generation, and the critical success factors for enterprise resource planning implementation—to examine the multi-dimensional knowledge-flow phenomenon in context, and used the case study methodology for knowledge-flow theory building. The research question was two-pronged: how can need knowledge and its flow across stakeholders within an organization be explained using a multidimensional knowledge-flow model and how can Nissen’s five-dimensional knowledge-flow model be validated using a real-life immersion case? This case study suggests enabling need knowledge determinants and obstructing conditions are in play in determining the path of need knowledge flow. These two research artifacts should be considered together to provide a fresh research avenue towards better understanding of knowledge flow dynamics.
dc.format.extent 10 pages
dc.identifier.doi 10.24251/HICSS.2019.683
dc.identifier.isbn 978-0-9981331-2-6
dc.identifier.uri http://hdl.handle.net/10125/60002
dc.language.iso eng
dc.relation.ispartof Proceedings of the 52nd Hawaii International Conference on System Sciences
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject Reports from the Field: Knowledge and Learning Applications in Practice
dc.subject Knowledge Innovation and Entrepreneurial Systems
dc.subject Critical Success Factors
dc.subject Enterprise Resource Planning
dc.subject Knowledge Flow
dc.subject Knowledge Management
dc.subject Need Knowledge
dc.title A Case of Obstructing Conditions in Knowledge Flow Dynamics
dc.type Conference Paper
dc.type.dcmi Text
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