Using Logit and Data Envelopment Analysis to Construct the Financial Alert Model－A Case of Electronic Company in Taiwan

• Main Authors: Ru-Chien Yeh, 葉儒謙
• Other Authors: Wun-Hua Jhang
• Format: Others
• Language: zh-TW
• Published: 2009
• Online Access: http://ndltd.ncl.edu.tw/handle/yc6t3b

碩士 === 國立臺北科技大學 === 工業工程與管理研究所 === 97 === Owing to the frequent hearing of financial distress which may contribute to great loss of investors and banks, it is an important issue to construct a financial alert system. Most researchers used financial balance variables to construct financial alert model, but few of them considered the relation between operating efficiencies and financial distress. For that reason, this study both made use of financial balance variables and operating efficiencies to construct financial alert model and compared the accurate rates with the model constructed only by financial balance variables. If the accurate rates increased, it would tell that operating efficiency is also one of the important reasons which cause financial distress. There were 64 companies selected as the samples which were separated into training and testing samples. The matching method is 1:1 and the period is from 2002 to 2006. Four models were constructed that are model 1: financial balance variables, model 2: financial balance variables combined with technical efficiency, model 3: financial balance variables combined with pure technical efficiency and model 4: financial balance variables combined with scale efficiency respectively. The study showed no matter what years before distress, debt ratio and rate of return on assets are important variables discriminating normal and distressed companies. The overall accurate rates were 83.33%, 77.08% and 73.61% respectively. It also showed the closer to the time that distress happened, the higher accurate rates were. Comparing to model 1, the model 4 which added scale efficiency had the higher accurate rate discriminating normal and distressed companies in all years; the model 3 and model 4 diminished the type II error rate comparing to model 1 in all years. Furthermore, contrary to normal companies, fixed assets decreased from three years before distress and should be considered as an important sign discriminating the happening of distress.