Knowledge creation measurement methods

Abstract

PurposeThis paper sets out to examine the operationalisation of knowledge creation. Given the importance of knowledge creation for national and corporate wealth, assessing its measurement is a valuable exercise; however, current research utilises a range of measures, and this lack of agreed construct operationalisation is a barrier to robust empirical investigation. This paper aims to review current measurement methods and to construct a taxonomy of knowledge creation measures.Design/methodology/approachA four‐step classification method is followed. In order to generate information on the essential properties of measurement methods, relevant empirical research is reviewed and a content analysis performed on the resultant measures. The literature review includes key‐term searches on bibliographic databases, yielding a sample of 63 empirical papers that incorporated knowledge creation measures. Both of the authors independently created a cognitive map of these measures based on three different attributes.FindingsThe main contribution of the paper is the development of a hierarchical taxonomy of knowledge creation measures. This taxonomy, in which movement up the hierarchy provides broader conceptual classification and movement down provides conceptual refinement, advances knowledge creation research by categorising measures in a way that facilitates assessment against existing comparable definitions.Research limitations/implicationsThe limitations of the research stem from issues of bias. In addition to sampling bias, some bias may have entered the coding with respect to placement of measures into process or output categories.Originality/valueThe research has significant implications for future research in knowledge creation: the taxonomy facilitates consistency between knowledge construct definition and measurement, and differentiation between knowledge creation and other, related constructs, such as innovation. Such a taxonomy makes it easier to clarify similarities and differences among knowledge creation measures, develop new propositions for future investigation, and identify neglected areas of study.

Knowledge processes, knowledge‐intensity and innovation: a moderated mediation analysis

“…Darroch, 2003;Zack et al, 2009;Alavi and Leidner, 2001;Kulkarni and St Louis, 2003;Marqué s and Simó n, 2006;Mitchell and Boyle, 2010). However, as knowledge management discipline is still in the development phase, various authors model the knowledge processes (both their number and their content) somewhat differently, and commonly accepted operationalizations of these concepts do not exist.…”

Knowledge management and measurement: a critical review

“…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.…”

Starting with small health data opportunities for Mhealth in Africa

“…Within knowledge management, Allard [52] posits that the creation of knowledge (sometimes referred in the literature as knowledge creation or generation) is viewed as essential to an organisation. Table 2 provides the definition for knowledge creation as being described as a process, output or outcome as proposed by Mitchell and Boyle [56].…”