Developing effective knowledge management systems

Abstract

Knowledge Management Systems (KMS) are computerized systems intended to support the management and application of organizational knowledge. Despite the many potential benefits from KMS> industry reports show that companies are having difficulties in realizing these benefits. This dissertation sets out to identify the reasons for those difficulties - from a requirements analysis point of view - and to propose a way to improve the design of KMS in order to enhance their benefits to companies. We develop a theory-based approach to the evaluation of Knowledge Management Systems and identify the main shortfalls of existing systems. The findings show two inter-related problems. First, the lack of a conceptual model such as an organizational ontology or of additional knowledge about the knowledge might inhibit KMS ability to support specific organizational KM processes. Second - the lack of an integrated KM product reduces organization's ability to attain an overall solution for the management of organizational knowledge. In addition, the analysis pinpoints the inability of current technology to support effective management of tacit knowledge - an important aspect of KMS design. In the second part of the dissertation we focus on one of the problems identified - namely, the lack of a unified meta-knowledge set - and identify the specific meta-knowledge that should be incorporated into the design of KMS. The expected benefits from the inclusion of meta-knowledge are better management of organizational memory and enhanced adoption of knowledge by KMS users. We conduct an empirical investigation - using conjoint analysis - to identify specific attributes of knowledge and of knowledge sources that individuals take into account when making their knowledge use decision, and propose that these attributes should be included as meta-knowledge in the KMS design. The results indicate that the 'accuracy' and 'relevance' of the knowledge are the top two important attributes in the knowledge selection decision and 'extent of knowledge' and 'trustworthiness' are the top two important attributes in the selection of a knowledge source. In addition the results show that knowledge plays a slightly more important role than knowledge source in the overall decision. Finally, several demographic and contextual variables - such as the knowledge search task and organization size - are shown to affect the importance of different attributes in the overall evaluation of knowledge and of knowledge source by individuals.

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