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    Toward More Effective Knowledge Management: An Investigation Of Problems In Knowledge Identification

    166625_41519_Newk-Fon Hey Tow et al Published version.pdf (193.6Kb)
    Access Status
    Open access
    Authors
    Newk-Fon Hey Tow, William
    Venable, John
    Dell, Peter
    Date
    2011
    Type
    Conference Paper
    
    Metadata
    Show full item record
    Citation
    Newk-Fon Hey Tow, William and Venable, John and Dell, Peter. 2011. Toward More Effective Knowledge Management: An Investigation Of Problems In Knowledge Identification, in Seddon, P.B. and Gregor, S. (ed), PACIS 2011, Jul 7 2011. Brisbane, QLD: Association for Information Systems (AIS).
    Source Title
    Proceedings of the 15th Pacific Asia conference on information Systems
    Source Conference
    PACIS 2011
    ISBN
    9781864356441
    School
    School of Information Systems
    URI
    http://hdl.handle.net/20.500.11937/27826
    Collection
    • Curtin Research Publications
    Abstract

    One of the first knowledge management (KM) processes, on which subsequent processes depend, has been largely under-researched. A review of the literature shows that in contrast to other processes, the process of Knowledge Identification (KI) has been less researched. More specifically, what problems face KM stakeholders with respect to KI is yet to be understood. Despite this lack of understanding, a number of KI methods exist and new ones are emerging. This paper has identified and critiqued some of the KI methods. However, whether these KI methods areperceived as effective by KM stakeholders, what other KI methods are currently being used, and what factors influence the effectiveness of KI methods, remain unclear. These constitute research gaps which this research will contribute to fill. This research project will consist of three phases. To collect data, surveys, interviews, and case studies will be used. A mix of quantitative and qualitative data analysis methods will be carried out on data collected. The results of the data analysis will provide deeper understanding of the problems surrounding KI, and will be used to develop a model of factors influencing the effectiveness of KI methods.

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