Dynamizing intellectual capital through enablers and learning flows

Abstract

Purpose

The main aim of this research is to relate intellectual capital (IC) and organizational performance through intermediate variables, enablers and learning flows. To this end, the paper defines a new theoretical model of relations and presents an empirical study to contrast the model.

Design/methodology/approach

The proposed theoretical model is contrasted by means of a quantitative study of Spanish firms from the biotechnology sector. The statistical analysis applies a method based on variance using partial least squares.

Findings

The theoretical model proposes a total of 15 relations, 13 of which are statistically significant, which demonstrates the close relationship between IC and performance using enablers and learning flows as intermediate variables.

Originality/value

From the theoretical model proposed and its subsequent empirical contrast, the research shows the close relations that exist between areas of knowledge that traditionally appear separately in the literature. The proposed model thus allows us to explain and predict the dynamization of the components of IC due to enablers and learning flows, and the effect of these elements on organizational performance.

Citation

Nancy Vargas, M. and Begoña Lloria, M. (2014), "Dynamizing intellectual capital through enablers and learning flows", Industrial Management & Data Systems, Vol. 114 No. 1, pp. 2-20. https://doi.org/10.1108/IMDS-04-2013-0190