Using Operating Efficiency to Establish the Diagnostic System to Predict Taiwan Electronic Industry Financial-Distress Corporation

• Main Authors: Kuang-huang Huang, 洪光宏
• Other Authors: Shiao-Yan Huang
• Format: Others
• Language: zh-TW
• Published: 2006
• Online Access: http://ndltd.ncl.edu.tw/handle/25572343530138103184

碩士 === 逢甲大學 === 會計所 === 94 === The operating status of a firm will be presented at its financial reports after all. However, it is too late that the investors knew a firm’s financial crisis because they generally knew it after the firm disclosed its financial reports. Many researchers used some information such as non-financial data, market price, macro-economic factors, to predict a firm’s financial crisis. However, the effect of operating efficiency is also important factor in predicting a firm’s financial crisis. In this research, the authors tried to structure the financial predictive model by using some efficient factors and to examine relationship between financial crisis and operating efficiency. The authors collected 56 crisis firms in Taiwan electronic industry and match with 112 normal companies during 2002 to 2005.The model uses the financial variable and operating efficiency to predict the business crisis. First, predictive model only using financial variable to establish pattern model after including over-efficiency、technical efficiency、scale efficiency in turn. The authors compared the predictive results from four models by logit model and artificial network approach. It indicates that the approach used both financial variables and scale efficiency to predict a firm’s crisis is more correct than the approach used only financial variables. It is also proved that there is a correlation between financial crisis and unhealthy operating performance. Moreover, it is found that the volumes of the fixed assets at a firm with crisis were declined gradually since 3 years ago. This factor should be recognized as an important discriminative factor. In this research, the model structured by logit model is better than the one structured by artificial neural network approach.