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In order to be able to assess the value of the individual

elements proposed in the literature for linking ICT to

knowledge management, some idea of what knowledge

management stands for needs to be obtained. Arriving

at a clear-cut, unambiguous conception of knowledge

management is no trivial task. The growing attention

that knowledge management is receiving has led to a

proliferation of viewpoints, approaches, theoretical discursions

and practical tools and methods. To say the

least, these do not converge on a clear and unambiguous

notion of knowledge management. In an attempt to

provide an overview, Verwijs et al. (1999) used two distinctions

for sorting the various approaches. First, they

distinguished between engineering approaches and

management approaches. An engineering approach to

knowledge management is based on the presumption

that problems can be solved systematically by breaking

down the problem into parts, solving the partial problems

and integrating the partial solution into an overall

solution. A management or holistic approach stresses

the need for considering the 'whole' knowledge-related

situation, including the organizational context in which

problems occur and become meaningful. It argues that

the complexities characteristic of knowledge-related

issues preclude the full understanding and control of

knowledge in organizations in identiЋ able subproblems.

Because the management approach claims that aspects

can only be fully understood as related to the context

that deЋ nes them and not only as elements in themselves,

it denies the validity of the thesis underlying the

engineering approach, i.e. that a satisfactory solution to

knowledge-related problems can be attained by summing

up the partial solutions.

Second, Verwijs et al. (1999) distinguished between

four classes of approaches on the basis of their main focus

as regards content: knowledge storage approaches,

knowledge processes or knowledge Џ ow approaches,

organizational learning approaches and knowledge

measurement or knowledge asset approaches. The

knowledge storage approaches typically have an engineering

focus. They concentrate on explicit knowledge

dissociated from the human knowledge carrier, as tacit

knowledge can only be stored after having been made

explicit. Recently, these approaches have shown a growing

interest in the ideas of knowledge engineering and

knowledge-based systems originating from artiЋ cial

intelligence research (e.g. Abecker et al., 1997; Meltsner,

1997; Van Heijst



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