Timing of Resources Exploration in the Behavior of Firm-Comparative Approaches on ARMAX, BPNN, ANFIS, and ASVR

Abstract

We have insight into the importance of resource exploration derived from the quest for sustaining competitive advantage as well as the growth of the firm, which are well-explicated in the resourcesbased view. However, we really do not know when the firm will seriously commit to this kind of activities. Therefore, this study proposes comparative approaches using auto-regressive moving-average regression (ARMAX), back-propagation neural network (BPNN), adaptive neuro-fuzzy inference system (ANFIS), or adaptive support vector regression (ASVR) to constitute the relationship among five indicators, the growth rate of long-term investment, the firm size, the return on total asset, the return on common equity, and the return on sales. In such a way, the methods we build can explain the timing of resources exploration in the behavior of firm. Meanwhile, the performance between these methods is compared quantitatively.