Analysing and classifying knowledge management publications – a proposed classification scheme

Purpose: The growing number of publications on knowledge management (KM) has addressed heterogeneous topics that lack integration and classification. This article closes the classification gap by presenting a classification scheme, providing an integrated overview of KM publications. Design/methodology/approach: The development of the classification scheme follows a multistep approach. By applying a taxonomy development method, the results of a previous content analysis of 4,290 publications were processed to integrate 3,780 keywords into a classification scheme. Findings: The classification scheme consists of 13 main categories and subcategories with six levels of detail. The scheme covers not only KM-specific keywords but also keywords from related disciplines, indicating a strong interdependence with related research domains. Research limitations/implications: The scheme provides a starting point for ongoing collaboration within the KM community with the aim of improving the classification results and refining the scheme to manifest the core identity. Practical implications: The scheme is helpful in understanding whether KM implementation activities in organisations are aligned with overall research activities and topics covered by publications. Originality/value: Developing a scheme based on a prior content analysis turns out to be a unique and innovative approach that has never before been done in the KM domain.