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.

A structured literature review of scientometric research of the knowledge management discipline: a 2021 update

“…In the previous study, Serenko (2013) emphasized a need for the development of a unified KM keyword classification scheme. Bedford (2015a) and Fteimi and Lehner (2018) answered his call in a very rigorous way, and future scientometric KM scholars are strongly recommended to make use of their work.…”

“…Even though knowledge sharing and transfer topics topped the list again (Kennedy and Burford, 2013;Costa and Monteiro, 2016;Ferguson, 2016;Fteimi et al, 2019), other popular themes signaled the breadth and further advancement of KM research. Examples of popular and growing research streams include communities of practice (Bolisani and Scarso, 2014), the consequences of knowledge spillover, loss and leakage (Ferenhof, 2016), knowledge-based urban development (Edvardsson et al, 2016), KM success factors (Fteimi and Lehner, 2018), public sector KM (Jussila et al, 2017), KM in project management (Cabral et al, 2014;Handzic and Durmic, 2015;Sareminia et al, 2016), adoption, use and diffusion of KM systems (Matayong and Mahmood, 2013), process capital (Matthies, 2014), social media for knowledge sharing (Sarka and Ipsen, 2017), the role of KM in innovation (Leon and Bolisani, 2016) and the intersection of KM and IT (Iskandar et al, 2017;Khan and Vorley, 2017;Usai et al, 2018). KM also includes knowledge-based development (Akude and Grunewald, 2014) and organizational learning (Song et al, 2014;Adz ˇi c, 2018;Castaneda et al, 2018) research streams, and it is closely connected to IC topics (Pereira and Machado, 2019).…”

“…A keyword search of the following databases: Emerald, ScienceDirect, ProQuest, JSTOR, Web of Science (WoS), IEEE Xplore and Google Scholar, based on the pairs of KM and scientometrics keywords. The KM keywords were selected from the KM classification scheme by Fteimi and Lehner (2018, pp. 1540-1554C.6.15;D.2.13;E.2;H.8.9;L.4.1.…”

O Ciclo Da Gestão Do Conhecimento Na Tomada De Decisão Sobre Hedge Cambial Em Uma Cooperativa Do Agronegócio

“…Essas duas possibilidades, abertas na gênese do campo, se materializaram em um número crescente de publicações. Até início de 2018, "knowledge management" retornava algo acima de 1 (um) milhão de resultados no Google Scholar e mais de 14 (quatorze) mil artigos publicados na base ScienceDirect desde o ano de 2000 (Fteimi & Lehner, 2018), com estimativas de aumento exponencial nas publicações para os próximos anos (Ragab & Arisha, 2013), mas despertando preocupações quanto a falta de robustez dos modelos prescritivos de implementação de Gestão do Conhecimento e falta de aplicabilidade prática (Fteimi & Lehner, 2018;Wong & Aspinwall, 2004).…”

Criteria as a Prelude for Guiding Taxonomy Evaluation

“…However, some authors state that the usefulness of taxonomies can only be evaluated by observing a [25,32,34,35,53,58,73], mutually exclusiveness [26,35,40,43,61,71], distinctiveness [26,33,43,45,46], reliability [11,45,54,74], utility [10,49,61,65], efficiency [10,41,51], stability [24,57], uniqueness [39,61], repeatability [38,39], sufficiency [41,70], construct validity [30,75], consistency [45,73], parsimoniousness [42,45], effectiveness [17,31] 2-8…”