A Comparative Study on Prediction of Human Capital Efficiency in Acquisition Using the Neurofuzzy System

Abstract

This study aims to identify the relevance of using the results obtained by applying the adaptive neural fuzzy inference system (ANFIS) methodology to make managerial decisions related to acquisitions as a strategic option. The aim of this study is to identify the outcomes of changes in human capital, represented by the human capital efficiency (HCE) indicator, which occurred as a consequence of the acquisition process, and to determine the impact of such changes on operating profit (OP), return on assets (ROAs), and productivity (PRO). An ANFIS was used to classify OP, ROA, and PRO based on the HCE before and after acquisition. Skillful prediction could play a pivotal role in management and improve socioeconomic domain. HCE recorded better prediction of PRO (R2 = 0.937) and ROA (R2 = 0.940) after acquisition than before acquisition (R2 = 0.649 and R2 = 0.674, respectively) for all dataset. The influence of HCE on OP remained substantial both prior to (R2 = 0.896) and subsequent to (R2 = 0.938) the acquisitions. The study considering different input parameters simultaneously is believed to be the first on a small scale and to attract interest not only for management and business but also for a wide range of one interested in different applications of ANFIS.