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Articles School of Marketing
2013
Knowledge Management and Measurement: a Critical Review Knowledge Management and Measurement: a Critical Review
Amr Arisha
Technological University Dublin
, amr.arisha@tudublin.ie
Mohamed Ragab
Technological University Dublin
, mohamed.af.ragab@gmail.com
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Arisha, A. and Ragab, M. Knowledge management and measurement: a critical review. Journal of
Knowledge Management, Vol. 17 Issue: 6,
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Knowledge Management and Measurement: A Critical Review
Abstract
Purpose
Knowledge is the currency of the current economy, a vital organisational asset and a key to
creating a sustainable competitive advantage. The consequent interest in Knowledge
Management (KM) has spurred an exponential increase in publications covering a broad
spectrum of diverse and overlapping research areas. The purpose of this paper is to provide a
literature review and categorised analysis of the rapidly growing number of KM publications,
and offer a comprehensive reference for new-comers embarking on research in the field with
a particular focus on the area of Knowledge Measurement.
Design/Methodology/Approach
A total of 350 articles published in peer-reviewed journals and conferences over the last
decade are carefully reviewed, analysed and categorised according to their specific subject
matter in the KM context.
Findings
KM research tends to fall in one of five categories: (1) Ontology of Knowledge and KM, (2)
Knowledge Management Systems, (3) Role of Information Technology, (4) Managerial&
Social issues, and (5) Knowledge Measurement. Despite the accumulation of extensive
publication efforts in some areas, a series of disagreements and a theory-practice gap are
revealed as challenging issues that need to be addressed.
Research Limitations/Implications
The scope of this study does not cover KM research in its entirety due to the vast nature of
the research field.
Originality/Value
This paper presents a new birds-eye view of the KM landscape through a comprehensive
taxonomy of KM research providing researchers with new insights for future applied
research, and offers a critical review of major knowledge measurement frameworks.
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1. Introduction
Knowledge has been recognised as a valuable organisational resource from a strategic
perspective (James, 2004) and a foundation for competitive advantage in today’s business
environment (Erden et al., 2008). Its value is magnified by it being closely related to another
important organisational resource in today’s dynamic global markets - time. Today’s
organisations are viewed as “wellsprings of knowledge” (Leonard, 1995) and thus cannot
afford to lose time “reinventing the wheel” (Dani et al., 2006) or looking for old knowledge
they are unable to retrieve by trying to “know what they know” (Sieloff, 1999).
Such knowledge losses, which can have detrimental consequences for any organisation, can
occur as a result of many internal and external factors such as lay-offs, resignations,
retirements, restructuring and outsourcing (Delen and Al-Hawamdeh, 2009). When
employees leave, they are likely to take away with them years of experience and valuable
knowledge that could be priceless to their organisations (Du Plessis, 2005, Hofer-Alfeis,
2008). Attempting a valuation, a U.S. Fortune-500 company estimated the loss of only one
experienced marketing manager to exceed $1 million due to the loss of knowledge (Parise et
al., 2006).The potential loss of knowledge is expected to increase as workforce mobility,
employee turnover and layoffs caused by downsizing increase, especially during the current
global financial crisis (Serban and Luan, 2002, Martins and Meyer, 2012).
The subsequent growing interest in Knowledge Management (KM) has resulted in an
exponential growth in KM publications over the last decade at a rate of almost 50% per year
(Bontis and Serenko, 2009, Serenko and Bontis, 2004, Zack, 1999). A study of research
published in 11 key KM journals identified 3,109 unique authors affiliated to 1,450
institutions between 1994 and 2008 (Serenko et al., 2010). The real numbers of KM
publications may be multiples of those reported, since a significant portion of KM research is
published in non-KM journals (Ma and Yu, 2010). This is because - unlike other fields - the
KM field has no clear boundaries (Lloria, 2008) but rather a heterogeneous nature that creates
overlaps with other domains (Figure 1). This paper therefore attempts to characterise KM as a
crucial business area by presenting a comprehensive literature review and a categorised
analysis of KM research publications.
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Figure 1: Overlapping areas between KM and other fields
2. Methodology
The literature review process was conducted in light of the frameworks proposed by Jesson et
al. (2011) and Tranfield et al. (2003). First, a research plan was devised to outline the scope
and methodology of the review and the publication selection criteria. The criteria for
inclusion were English peer-reviewed journal and conference articles retrieved from the
Emerald Insight and Science Direct databases and published during the period; 1995 to
present. This time period represents the prosperous period of KM research (Ma and Yu,
2010) with particular emphasison publications in the last five years (Figure 2). Non-academic
research, publications in other languages or in other databases were criteria of exclusion.
Database search used the general keywords knowledge management and knowledge
measurement. In total, this study has extensively reviewed more than 350 references, of
which 213 are cited in this article, with the majority (89%) of references being peer-reviewed
journal articles. Almost 50% of the articles were published in the Journal of Knowledge
Management, the oldest (Lambe, 2011) and highest ranked journal in the field (Bontis and
Serenko, 2009). Other publications from theJournal of Intellectual Capital and Knowledge
Management Research and Practice and key publications of books or reports in KM (i.e. top
cited) were also included.
Figure 2: Chronological distribution of references
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A review and thematic analysis were carried on publications with an objective of developing
acomprehensive framework. The inductive approach was used to classify articles and was not
based on a predefined classification (Rynes et al., 2001, Crilly et al., 2010). As the review
progressed, the authors developed the boundaries of a taxonomic framework of KM
subdomains in which each paper was categorised under a certain theme according to its
content and the taxonomy was iteratively refined. Since an exhaustive review of the KM
literature is practically impossible due to the immense scope of the field (Kalling, 2003), this
study adopted Glaser and Strauss’s (1967) ‘theoretical saturation’ notion. They define
saturation as being achieved when “no additional data are being found whereby the
researcher can develop properties of the category” and he/she “becomes empirically
confident that a category is saturated” and hence concludes the review when the contribution
of further studies is perceived to add little value (Mitchell and Boyle, 2010). Analysis of each
category in the framework has enabled the authors to critically conclude the key findings and
highlight the potential future areas of interest in the domain with a particular interest in
knowledge measurement.
3. Classification of KM Literature
The resultant proposed taxonomy presented a degree of similarity to that of Maier (2002) in
the overall framework, however, there were still significant differences with regards to
literature categories and subcategories. Overall, KM studies were classified into one of five
categories: (1) Ontology of Knowledge and KM, (2) Knowledge Management Systems, (3)
Role of Information Technology, (4) Managerial & Social issues and (5) Knowledge
Measurement (Figure 3).
Figure 3: Classification of KM literature
