An Application of Intellectual Capital on Financial Distress Models by Using Neural Network

As the era of knowledge economy is prevalent in U.S. during 1992, knowledge economy plays an important role around the world. The value and competition of the traditional companies accounted on tangible assets. However, in the era of knowledge economy, the value and continuing operation of the companies accounted on intangible assets. It is not sufficient in estimating the value of a company only by financial ratios (Bublita and Ettredge, 1989; Chauvin and Hirschey, 1993; Bontis et al., 2000). The previous researches found there is a close relationship between the intangible assets and the value of a firm. In this paper, a set of financial ratios, corporate governance variables and intellectual capital indicators will be investigated in a financial distress prediction by employing the Logit model and neural network model. The conclusion in this paper is that the prediction of the financial distress models is more accurate for one year prior to failure. The financial distress can be accurately predicted up to 89.2% or 91.53 with the accuracy diminishing after the first year. The finding is the same with that in previous literature. The profitability of a firm is the most important factor in the earlier stage. The firm with a poor profitability may have a financial distress in the short run. However, in the long run, the operation administration (such as account receivable) and the intellectual capital (such as patent and R&D expenditure) have a significant impact on the financial situation of a firm.