Analysis of interaction among the intellectual capital components using interpretive structural modeling and MICMAC approach

In the age of a knowledge-based economy, identifying, measuring, and managing the intellectual capital (IC) of organizations has become very significant. These depend on identifying the main components of intellectual capital 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 prioritize the IC components based on the identified 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. At the first stage, 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. At the second stage, the application of Analytic Network Process for the prioritizing of IC components has been demonstrated. MICMAC analysis and classifying them into four categories including the 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 leveling of the components. And finally, the importance and priorities of the components are calculated with the help of the fuzzy analytic network process. The adoption of such an ISM-ANP model of IC components in the banking industry would provide insights for managers, decision-makers and policymakers for a better understanding of these components and to focus on the major components while managing their IC in their organizations.