Perceptions on Complexity of Decisions Involved in Choosing Intellectual Capital Assessment Methods

Abstract

Intellectual capital (IC) is increasingly acknowledged as a dominant strategic asset and a major source of competitive advantage for organisations. Despite an overwhelming body of literature on methods, models, systems and frameworks for assessment of IC, and increased awareness of the need for such assessment, relatively few organisations are actively and comprehensively assessing their IC. Choosing an appropriate method is problematic. It has been argued that, due to the complexities involved in choosing (selecting and customising) an appropriate method for assessing intellectual capital in a particular context, management support systems with knowledge components are needed for managing the evolving body of knowledge concerning the assessment of intellectual capital. To empirically test this argument, a survey making use of a self‑administered questionnaire was performed to test perceptions of suitable consultants, practitioners and researchers on the complexity levels of decisions to be made in selecting and customising methods for assessment of IC. Respondents were selected through convenience sampling coupled with snowball sampling. Data collected on respondents themselves confirms their expert status regarding IC and aspects thereof. The majority of these respondents indicated that, given any particular context, the decisions involved in selecting and customising an appropriate method for assessment of IC is often or always very complex. Decisions involved in selection are perceived as marginally more complex than decisions involved in customisation. Respondents provided valuable insights and rich examples of scenarios on the higher and lower regions of the complexity scale for the decisions involved in the selection, as well as, for the decisions involved in the customisation of IC assessment methods. It is concluded that the perceived complexity of the decisions involved in choosing IC assessment methods supports the notion that supporting systems are required to assist human decision makers in making sense of the complexities involved in choosing IC assessment methods.