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Preface for the Third Edition - Read

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402 B. Concepts and Theories<br />

an organizational knowledge base, matter most <strong>for</strong> a subsequent KM initiative<br />

(Amelingmeyer 2000, 176ff).<br />

environment/market<br />

knowledge<br />

balance<br />

sheet (t )<br />

0<br />

financial<br />

balance<br />

sheet (t )<br />

0<br />

opening<br />

balance<br />

sheet<br />

business<br />

goals<br />

knowledge<br />

goals<br />

change incentives<br />

to motivate<br />

knowledge creation<br />

and sharing<br />

transfer<br />

best practices<br />

implement<br />

ICT infrastructure<br />

interventions<br />

employees<br />

motivated to<br />

apply knowledge<br />

improved use<br />

of ICT<br />

reduced<br />

operative<br />

costs<br />

accelerated<br />

decisions<br />

FIGURE B-78. Framework to measure knowledge and knowledge trans<strong>for</strong>mations 620<br />

The existing approaches to measure an organization’s intangible assets in general<br />

and <strong>the</strong> success of KM initiatives in particular as briefly reviewed above lack<br />

operationalization. Probst et al. simply suggest to measure system use of e.g., an<br />

Intranet as part of <strong>the</strong> operative assessment of knowledge goals (Probst et al. 1998,<br />

336). O<strong>the</strong>r than that, success or failure of a KMS in <strong>the</strong>se frameworks is only<br />

assessed at a highly aggregate level, e.g., with respect to measures such as turnover<br />

per employee or <strong>the</strong> share of investments in ICT infrastructure as compared to <strong>the</strong><br />

organization’s total value added, <strong>the</strong> fluctuation of experts or <strong>the</strong> share of customers<br />

that improve <strong>the</strong> organization’s competencies (also Sveiby 1998, 263). These<br />

are all measures that are influenced by <strong>the</strong> use of KMS, but also by a large number<br />

of o<strong>the</strong>r interventions into an organization’s way of handling knowledge and environmental<br />

changes as well.<br />

Thus, <strong>the</strong> frameworks have to be detailed in order to provide an instrument<br />

which can be applied to <strong>the</strong> assessment of <strong>the</strong> success of KMS. As KMS are a special<br />

group of in<strong>for</strong>mation systems, <strong>the</strong> literature dealing with measuring success of<br />

in<strong>for</strong>mation systems provides a good starting point <strong>for</strong> <strong>the</strong> development of a more<br />

detailed framework to assess <strong>the</strong> success of KMS.<br />

8.3 In<strong>for</strong>mation systems success<br />

This section reviews <strong>the</strong> literature on IS success measurement (section 8.3.1). On<br />

<strong>the</strong> basis of this literature review, <strong>the</strong> DeLone/McLean (1992) model <strong>for</strong> IS success<br />

620. Source: North et al. 1998, 164.<br />

improved understanding<br />

of<br />

customer needs<br />

products better<br />

meet customer<br />

requirem ents<br />

higher<br />

product quality<br />

accelerated<br />

response time<br />

intermediate effects<br />

measure results<br />

improved<br />

customer<br />

benefits<br />

improved<br />

customer<br />

satisfa c tion<br />

more orders<br />

higher market<br />

penetration<br />

aggregated<br />

operational<br />

results<br />

in <strong>the</strong><br />

time interval<br />

[t ;t ]<br />

0 1<br />

knowledge<br />

balance<br />

sheet (t )<br />

1<br />

financial<br />

balance<br />

sheet (t )<br />

1<br />

closing<br />

balance<br />

sheet

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