Title: Predicting the value of intellectual capital: a performance contribution model based on neural networks

Authors: Ibrahim Elsiddig Ahmed; Riyadh Mehdi

Addresses: College of Business Administration, Ajman University, P.O. Box 346, Ajman, UAE ' College of Business Administration, Ajman University, P.O. Box 346, Ajman, UAE

Abstract: The study aims to predict the value of intellectual capital (IC) based on the performance contribution approach. Theoretically, through the development of a derivative model (DM) that explains the relationship between IC and the firm's performance. The study develops a DM of 16 equations to construct the relationship between the investment in IC and its effectiveness in generating income. This is one of the few studies in predicting IC and the only empirical study applied to UAE listed companies. The study applies the neural network system of 47 firms listed in DFM over five years. The study ranks return on assets, p/e ratio, market value of assets, and return on equity as predictors of IC. It helps managers in predicting and determining investment in IC and its impact on performance. In the future, other than financial factors' need to be included, increase the sample, and conduct research on predicting the components of IC.

Keywords: intellectual capital; performance measures; IC contribution model; return on assets; ROA; neural networks; derivative model.

DOI: 10.1504/IJIPM.2021.117178

International Journal of Intellectual Property Management, 2021 Vol.11 No.3, pp.219 - 235

Received: 10 Jun 2019
Accepted: 05 May 2020
Published online: 20 Aug 2021 *

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