A framework of knowledge management systems: issues and challenges for theory and practice

TLDR

Knowledge management systems are increasingly viewed as key to value creation, yet they are often adopted without addressing core knowledge problems. This study proposes an inductively derived framework that classifies KMS by knowledge locus and content structuring to guide research. The framework enables exploration of KMS issues and unifies dimensions across different system types. The identified contingencies—network size and diversity, knowledge flow maintenance, and long‑term KMS effects—highlight interdisciplinary insights and suggest promising research directions.

Abstract

As the basis of value creation increasingly depends on the leverage of the intangible assets of firms, knowledge management systems (KMS) are emerging as powerful sources of competitive advantage. However, the general recognition of the importance of such systems seems to be accompanied by a technology-induced drive to implement systems with inadequate consideration of the fundamental knowledge problems that the KMS are likely to solve. This paper contributes to the stream of research on knowledge management systems by proposing an inductively developed framework for this important class of information systems, classifying KMS based on the locus of the knowledge and the a priori structuring of contents. This framework provides a means to explore issues related to KMS and unifying dimensions underlying different types of KMS. The contingencies that we discuss—the size and diversity of networks, the maintenance of knowledge flows and the long term effects of the use of KMS—provide a window into work in a number of reference disciplines that would enrich the utility of KMS and also open up fruitful areas for future research.