The Frontier of Linearity in the Intellectual Capital Metaphor

Abstract

The purpose of this paper is to demonstrate that linearity is a major limitation of the metaphor Knowledge as Capital. This metaphor proposed by Daniel Andriessen as a challenging debate for ECIC 2009 has been extremely fruitful in promoting knowledge as a new field of interest in economic research and praxis. Since Capital is a core concept of any economic activity, using it as a semantic source for the newly coined expression, Intellectual Capital, proved to be a winning idea. However, any metaphor highlights certain things and hides others. There are some semantic frontiers in the source domain which constitute its limitations. The purpose of this paper is to analyse the linearity property of the source domain, and to demonstrate that it constitutes a major limitation of the IC metaphor. We begin with the mathematical definition of a linear space, and then we analyse how this definition requirements, which are fulfilled within the source domain, cannot be fulfilled within the target domain. We are interested especially in the following requirements of the linear space: commutativity, associativity, distributivity and the application of the principle of superposition. The Knowledge domain does not satisfy any of these requirements which means that the target domain is strongly nonlinear. Although many authors have used these concepts of linearity and nonlinearity in connection with knowledge and intellectual capital, none of them undertook a systematic analysis of the basic properties of linear spaces and how they fit within the knowledge field. Linearity is strongly related to the measurable property of the source domain, and this operational connection explains why many methods proposed to measure knowledge and intellectual capital failed to produce good results. We shall extend our analysis to linear and nonlinear thinking patterns, showing how the frontier of linearity can impair managerial decisions. We hope that our work will stimulate new research aiming at using properly the nonlinearity property of the Knowledge field.