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 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: Ontology of Knowledge and KM, Knowledge Management Systems, Role of Information Technology, Managerial and Social issues, and 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 novel taxonomy of KM research providing researchers with new insights for future applied research, and offers a comprehensive critical review of major knowledge measurement frameworks.

Measuring Knowledge

“…Sveiby (2010) mentions that the financial methods are useful in merger and acquisition situations and for stock market valuations, as well as, for comparisons between companies within the same industry. However, as Ragab and Arisha (2013) points out, financial methods do not always clarify where problems exist and the value-adding contribution (or lack) of different intellectual capital components. Kannan and Aulbur (2004) add that intangibles such as staff competencies, customer relationships, business models, and computer and administrative systems receive no recognition in the traditional financial methods.…”

“…The various components of intellectual capital are identified and indicators and indices are generated and reported in scorecards or as graphs (Sveiby, 2010). In cases where metrics measure a qualitative attribute (such as motivation) scale-based surveys are used to convert qualitative values into quantitative figures (Ragab & Arisha, 2013). A composite index may or may not be produced (Sveiby, 2010).…”

“…Finally, relational capital (or customer capital, relationship capital, external structure) concerns knowledge embedded in customer relationships, market channels, intra-organizational relationships and technological networking embedded in the organizational external relationships (Roos 1997 as cited in Hendriks & Sousa, 2013). In other words, it refers to the combined value of an organization's external relationships with stakeholders, such as suppliers and customers, who are valuable sources of both revenue and market knowledge for the organization (Ragab & Arisha, 2013). …”

“…Based on the finding of Ragab and Arisha (2013), Sveiby (2010), Kankanhalli andTan (2004), andBose (2004), when measuring knowledge at organization level, it is possible to review the level (amount) of knowledge, which is at the disposal of an organization, or to focus on reviewing how effectively it is worked with knowledge, for example when evaluating the effectivity of sharing knowledge within the organization. It means the classification of methods of measuring knowledge at organizational level can be as follows:…”

“…Furthermore, the findings might assist organizations in identifying the measures which are suitable for them, for improving the quality of metrics they use; and assist researchers in identifying future research needs related to knowledge measurement metrics as well as in deciding about the methods and techniques suitable for their research. There were done several similar reviews, e.g., Ragab and Arisha (2013), Sveiby (2010), Kankanhalli and Tan (2004), and Bose (2004), but this review combines their findings and offers a more comprehensive overview. Additionally, the group level knowledge measurement was not discussed in prior studies.…”