Proceedings of the 12th European Conference on Knowledge ...

Ravinder Singh Kahlon and Man-Chie Tse
organisation ei<strong>the</strong>r small or large because implicit communication will always be implicitly vital. The
strength <strong>of</strong> this model follows a similar document, process or code driven. The disadvantage <strong>of</strong> this
model is that <strong>the</strong>re is a variety <strong>of</strong> practices exist which may not be included as part <strong>of</strong> <strong>the</strong> attributes
within <strong>the</strong> model, which can impede and impact <strong>the</strong> evaluation and <strong>the</strong> overall analysis in an
organisation.
2.2 IT Approach
Early adopters <strong>of</strong> incorporating conventional IT reported encouraging results such as increased
productivity or systematically identifying cultivated knowledge. IT approaches attempts to make
complex and conceptual essence <strong>of</strong> infrastructure technology to support and make knowledge
incrementally explicit. Ultimately, a retrospective from past literatures shows IT model solutions are
ideal for medium to large sized organisations. The strength <strong>of</strong> this model supports technology transfer
and aid development towards dynamic system thinking (Kahlon, 2009; Tse, 2009).
3. Methodology
A Composite Features Diagramming (CFD) Framework developed by Georgiadou (2003) was
adopted for <strong>the</strong> comparative evaluation for Non-IT and IT. The first initial step was to list <strong>the</strong> primary,
secondary, and tertiary attributes for an ‘Ideal Model’ (See Appendix A) to measure KM in an
organisation. The primary feature attributes were devised using <strong>the</strong> model components encompassing
<strong>of</strong> Bhatt (2000) People, Process and Technology. Expanding on from <strong>the</strong> primary features, <strong>the</strong> work
<strong>of</strong> Alavi and Leider (1999) was incorporated, which derived <strong>the</strong> primary, secondary and tertiary
attributes. Therefore, this model acted as a questionnaire, depicted to enable building visual
representation taxonomy. These attributes were chosen because <strong>the</strong>y illustrate an overall constituent
perspective <strong>of</strong> KM features in an organisation, thus <strong>the</strong> ideal model can be validated to be applied to
any organisation. The gradual decomposition <strong>of</strong> composite features to sub features into lower levels
enabled <strong>the</strong> construction <strong>of</strong> multiple taxonomies and visual representation shown in Appendix A
(secondary and tertiary). This ideal model mechanism was <strong>the</strong>n used for mapping Non-IT (Figure 1)
and IT (Figure 2) applicable valid attributes. Values (data) for each leaf branch were to be collected
from a survey sample size <strong>of</strong> 50 participants to compare which contextually reflected <strong>the</strong> healthcare
organisation articulation, to help select or reject and evolve. Table 1 (see Appendix B) shows <strong>the</strong>
attributes and <strong>the</strong>ir gradual decomposition to lower layers. This tabular comparison shows <strong>the</strong>
presence and absence <strong>of</strong> features in <strong>the</strong> two KMM.
4. Mapping Features to <strong>the</strong> Ideal CFD
4.1 Qualitative/Visual Comparison
Figure 1: The CFD <strong>of</strong> <strong>the</strong> Non-IT Model
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