Relative Importance of Intellectual Capital Determinants, Using an Artificial Neural Network Approach: Case Study - Mellat Bank of Iran

Mona Safarnejad Shad, Arman Nedjati, Mohsen Shafiei
2017 Journal of Business & Financial Affairs  
it is essential to offer valuations associate with shares of intangible properties, since administrators require to spot their company's most precious resources. Furthermore, focusing on how much important these assets are, it is valuable to determine the intangible assets' status in value creation procedure. When generating value, competitive advantage is accomplished with the ideal use of intangibles [13] . Whenever a company's administration is not conscious of what its intangible properties
more » ... are, it could miss beneficial opportunities depending on these intangible capitals, since key decisions will made without considering all possible variables [14] . The main aim of this paper is identifying and quantifying the relative importance of various IC determinants in Mellat Bank of Iran. The ANN and Hierarchy Process (AHP) methods are used to determine and quantify the three main determinants of the IC. The ANN results are compared with direct evaluating of human by AHP. Many scholars have examined categorization models for projects selection and evaluation by Analytic Hierarchy Process method [15] [16] [17] [18] [19] [20] [21] and Mehralian et al. [22] , used fuzzy TOPSIS for Prioritization of IC indicators; But innovation of this research is evaluating the relative importance of IC factors by ANN. Intellectual capital background By a close review of Intellectual Capital literature, it is observed that all existing models of IC evaluation are identified three similar determinants for IC [23] . Based on some pioneers opinion IC is composed of three main components [11, [24] [25] [26] [27] [28] : • Structural capital, Abstract Intellectual capital (IC) is the main part of intangible assets and provides competitive advantages for organizations. Therefore, evaluating these assets has a significant value for companies. The aim of this study is to determine the relative importance of IC determinants. Two kinds of questionnaires related to IC were used to collect data for Artificial Neural Network (ANN) and Analytic Hierarchy Process (AHP) methods. In the next step the accuracy of ANN is compared with Multiple Linear Regression and Nonlinear Least Square Fitting methods. Factor analysis is also applied to validate the model and reduction of indicators. Finally, to gain assurance about the ANN results, the results are compared with the AHP's outcome. The obtained importance order of three IC determinants in the studied banking system is relational capital, human capital and structural capital respectively.
doi:10.4172/2167-0234.1000285 fatcat:kph6xmb6yfae7p6iy3o2gnmfbi