Interpretive Structural Modeling (ISM) of Intellectual Capital Components

Abstract

In recent years, many organizations have made attempts to identify, measure, and manage their intellectual capital (IC). The efficiency of IC largely depends on identifying its main components and their relationships. So far, however, no study has been conducted to clarify the interactions among those components or to develop a model for laying out a hierarchy of IC components. There is, indeed, an urgent need to analyze the behavior of IC components so that the corresponding policies may be successfully implemented. This paper aims to identify the relationships among the IC components with a focus on the banking industry. A literature review was used to identify the 16 most important IC components. The Interpretive Structural Modeling technique was practiced to determine the interrelationships among these components, based on the data gathered from the Export Development Bank of Iran. The interconnections between the components were clarified. Furthermore, MICMAC analysis and classifying them into four categories including autonomous, driver, dependent, and linkage components regarding their driving and dependence power is a new effort in the field of IC. A hierarchical structure was proposed through prioritizing, sequencing, and leveling of the components. The adoption of such an ISM-based model of IC components in the banking industry would provide insights for managers, decision makers and policy makers for a better understanding of these components and to focus on the major components while managing their IC in their organizations.