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

Sandra M<strong>of</strong>fett, Rodney McAdam and Paul Humphreys
introductory stages, while 120 organisations (20%) were growing. From <strong>the</strong>se figures one can
ascertain that <strong>the</strong> majority <strong>of</strong> organisations who responded to <strong>the</strong> survey are looking to KM as a
business improvement initiative and a way to sustain or increase market share. Surprisingly a large
number <strong>of</strong> respondents (n=183, 31%) failed to outline <strong>the</strong> stage <strong>of</strong> development <strong>the</strong>ir organisation is
currently in. Perhaps <strong>the</strong> participants deemed this question unnecessary as KM can be applied to all
organisations irrelevant <strong>of</strong> market position.
5. Analysis findings
Prior to investigation <strong>the</strong> dataset was re-coded according to organization size* with 54% within <strong>the</strong> 0-
250 employee bracket (SME) and 46% with over 251 employees (LARGE). Data collected was
subjected to statistical analysis using SPSS v17. This section presents <strong>the</strong> results <strong>of</strong> construct validity
and subsequent factor analysis for five categories (organisation climate, technical climate,
technological tools, information, people). Presentation <strong>of</strong> <strong>the</strong> results is followed by a comparative
discussion <strong>of</strong> <strong>the</strong> findings (section 6).
* SME defined by <strong>the</strong> UK Government's Small Business Service to mean any business with 0-250
employees
5.1 Organisational Climate (OC)
Originally 35 constructs were tested for reliability and appropriateness, however three failed to meet
<strong>the</strong> acceptable level <strong>of</strong> 0.30 and were removed from <strong>the</strong> data scale. From <strong>the</strong> resulting 32 variables
20 were above <strong>the</strong> 0.60 level. Therefore a total <strong>of</strong> 32 items-<strong>of</strong>-scale met reliability criteria and are
found to be internally consistent, with an alpha <strong>of</strong> .957. To verify <strong>the</strong> appropriateness <strong>of</strong> <strong>the</strong> remaining
organisational climate variables, both <strong>the</strong> Kaiser-Meyer-Olkin Measure <strong>of</strong> Sampling Adequacy and
Barlett’s Test <strong>of</strong> Sphericity were utilised. Variables for OC display a .933 KMO measure; a
meritorious value, showing that <strong>the</strong>se variables are acceptable for FA. Barlett’s test <strong>of</strong> Sphericity is
5594.162. This acceptable value indicates that <strong>the</strong> data is suitable for FA. Using Principal
Component Analysis (PCA), factors were extracted using <strong>the</strong> eigenvalue technique where only factors
with an eigenvalue over 1.0 are considered and all o<strong>the</strong>r factors are ignored.
Within <strong>the</strong> SME category total variance derived from relevant factors is 67.613. Factor loadings
(presented in table 1) confirm that significance criteria for all considered variables has been met;
37.5% (n=12) <strong>of</strong> <strong>the</strong> factor loadings are rated highly significant (above 0.7). Within <strong>the</strong> LARGE
category total variance <strong>of</strong> 60.862 was obtained extracted factors using <strong>the</strong> same variables as for
SMEs. Factor loadings confirm that <strong>the</strong> significance criteria for all considered variables has been met;
25% (n=8) <strong>of</strong> <strong>the</strong> factor loadings are rated highly significant (above 0.7). Factor descriptions capture
<strong>the</strong> underlying nature <strong>of</strong> <strong>the</strong> factor.
Making technology available and ready for use by employees is crucial for all organisations. In
LARGE organisations technology is used for efficiency and connectivity, linking internal people and
systems and externally to stakeholders such as customers and suppliers. In <strong>the</strong> SMEs column it is
interesting to note that one <strong>of</strong> <strong>the</strong> highest variables places emphasis on employees to contribute to
<strong>the</strong> content <strong>of</strong> technological systems, giving <strong>the</strong>m ownership <strong>of</strong> system content and its management.
5.2 Technology
To support TC findings, FA was conducted on technology data for both SMEs and LARGE
organisations, using <strong>the</strong> same processes as outlined in <strong>the</strong> previous sections. A total <strong>of</strong> 13 variables
with an alpha <strong>of</strong> .781 were included in data analysis, two additional scales were removed as <strong>the</strong>y did
not meet <strong>the</strong> acceptable threshold. Six items were above <strong>the</strong> 0.60 level (43%). Tests <strong>of</strong>
appropriateness <strong>of</strong> <strong>the</strong> remaining datascales indicated a .867 KMO measure; a meritorious value,
showing that <strong>the</strong>se variables are acceptable for FA. Barlett’s test <strong>of</strong> Sphericity is 5090.963. This
acceptable value indicates that <strong>the</strong> technology dataset is suitable for FA.
Within SMEs three factors are worthy <strong>of</strong> fur<strong>the</strong>r investigation, total variance from <strong>the</strong>se three is high at
87.581 (table 3). A similar story exists within LARGE organisations, where <strong>the</strong> three extracted factors
have a total variance <strong>of</strong> 86.209. The loading values selected are all above <strong>the</strong> highly significant rating
<strong>of</strong> >0.7.
639