Paper Info
Title
Analysing and classifying knowledge management publications - a proposed classification scheme.
Abstract
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.
Year
DOI
Venue
2018
10.1108/JKM-07-2017-0284
JOURNAL OF KNOWLEDGE MANAGEMENT
Keywords
Field
DocType
Content analysis,Taxonomy development,Classification scheme,Knowledge management literature
Content analysis,Computer science,Classification scheme,Knowledge management,Originality
Journal
Volume
Issue
ISSN
22.0
7.0
1367-3270
Citations 
PageRank 
References 
0
0.34
16
Authors
2
Name
Order
Citations
PageRank
Nora Fteimi132.40
Franz Lehner244479.29