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

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Sandra M<str<strong>on</strong>g>of</str<strong>on</strong>g>fett, Rodney McAdam and Paul Humphreys<br />

and Barlett’s Test <str<strong>on</strong>g>of</str<strong>on</strong>g> Sphericity were utilised. Variables for organisati<strong>on</strong>al climate display a .886 KMO<br />

measure; this is c<strong>on</strong>sidered a meritorious value, showing that <str<strong>on</strong>g>the</str<strong>on</strong>g>se variables are acceptable for factor<br />

analysis. Barlett’s test <str<strong>on</strong>g>of</str<strong>on</strong>g> Sphericity is 3347.737. This is a relatively low value, indicating that <str<strong>on</strong>g>the</str<strong>on</strong>g><br />

tools dataset may be unsuitable for factor analysis, however as <str<strong>on</strong>g>the</str<strong>on</strong>g> purpose <str<strong>on</strong>g>of</str<strong>on</strong>g> this secti<strong>on</strong> is purely to<br />

classify technological tools utilised for KM <str<strong>on</strong>g>the</str<strong>on</strong>g> analysis will proceed.<br />

Figure 2: Technologies with training provided<br />

Using PCA, factors were extracted using <str<strong>on</strong>g>the</str<strong>on</strong>g> eigenvalue technique, three factors have eigenvalues<br />

over 1.0 with total variance <str<strong>on</strong>g>of</str<strong>on</strong>g> 84.018. This high figure represents almost 85% <str<strong>on</strong>g>of</str<strong>on</strong>g> <str<strong>on</strong>g>the</str<strong>on</strong>g> total factor.<br />

Table 4 presents <str<strong>on</strong>g>the</str<strong>on</strong>g> results <str<strong>on</strong>g>of</str<strong>on</strong>g> this selecti<strong>on</strong> process. Of <str<strong>on</strong>g>the</str<strong>on</strong>g> 16 variables, six (37.5%) are above <str<strong>on</strong>g>the</str<strong>on</strong>g><br />

0.7 threshold. Factor descripti<strong>on</strong>s have been included to capture <str<strong>on</strong>g>the</str<strong>on</strong>g> underlying nature <str<strong>on</strong>g>of</str<strong>on</strong>g> <str<strong>on</strong>g>the</str<strong>on</strong>g> factor.<br />

Table 4: Factor Loadings – Technology Tools<br />

Variables SME LARGE<br />

Factor 1 – DATA MANAGEMENT TOOLS<br />

<strong>Knowledge</strong>-based Systems .692 .572<br />

Electr<strong>on</strong>ic Publishing Systems .678 .460<br />

Data Warehousing .674 .770<br />

Data Mining Tools .651 .831<br />

Intelligent Support Systems .636 .715<br />

Document Management Systems .562 .649<br />

Meeting Support Systems .449 .456<br />

Factor 2 – SUPPORT TOOLS<br />

Extranet .619 .820<br />

<strong>Knowledge</strong> Directories .478 .744<br />

Help-desks .550 .597<br />

Factor 3 – COMMERCE TOOLS<br />

Agents/Filters/Navigati<strong>on</strong> Tools .439 .820<br />

Electr<strong>on</strong>ic Commerce .645 .720<br />

Factor 4 – IN-HOUSE TOOLS<br />

Informati<strong>on</strong> Retrieval Engines .560 .725<br />

Intranet .701 .722<br />

Groupware/Workflow Systems .471 .536<br />

Factor 5 – GENERAL USE TOOLS<br />

Office Automati<strong>on</strong> Systems .695 .757<br />

Internet .682 .724<br />

In LARGE organisati<strong>on</strong>s, <str<strong>on</strong>g>the</str<strong>on</strong>g> focus <str<strong>on</strong>g>of</str<strong>on</strong>g> technological tools is to capture informati<strong>on</strong> from external<br />

sources to cherry pick relevant informati<strong>on</strong> so it can be applied internally. To this end emphasis is<br />

awarded to external scanning tools (extranet, data mining tools and agents/filters/navigati<strong>on</strong> tools<br />

642

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