財務危機預警模型之實證研究-考慮家族企業因素

The Financial Distress Predicted Model- Considering the Impact of Family Enterprise Factors

10.6342/NTU201603101

謝智穎

財務危機預警模型 ； 家族企業 ； 羅吉斯模型 ； financial distress predicted model ； family enterprise ； logistic model

國立臺灣大學國際企業學系學位論文

2016年

碩士

洪茂蔚

繁體中文

企業財務危機預警研究已經非常多年，國內外相關文獻眾多，早期財務危機預警模型之研究，大多以財務比率為基礎，但是企業之財務報表常會透過不同的方法進行窗飾，藉此美化報表上的資訊，因此大幅降低早期以財務比例為基礎所建構出的財務危機預警模型。另外，家族企業的在世界經濟中一直扮演著舉足輕重的角色，保守估計，家庭所有或經營的企業在全世界企業中佔65%到80%之間，全世界500強企業中有40%由家庭所有或經營。 故本論文目的首先探討家族企業因素是否和一間公司將來發生財務危機相關，接著利用羅吉斯迴歸分析法建立兩組財務危機預警模型，將非財務變數-家族企業因素納入解釋變數中來解決財務資訊窗飾的問題，並且探討家族企業因素是否會使財務危機預警模型預測更準確。經過實證研究得出，家族企業因素與一家公司是否發生財務危機是相關的，且是正面的：家族企業公司相較於非家族企業公司，發生財務危機的機率較低。另外將家族企業變數納入財務危機預警模型中，與僅考慮財務變數之模型相比更能有效地預測一家公司將來發生財務危機的機率。

The financial distress predicted model has been researched for many years so there are many theses not only domestic but oversea. In the past, most of the predicted models were basic in the financial data. However, the enterprise’s financial reports were usually window dressed through specific methods to be beautified so that it caused some bias and reduce the exactness for the financial distress predicted model considering only financial ratio. Besides, the family enterprise has been the important role in the economy of the world. In conservative estimates, family enterprise in the world accounted for between 65% to 80%. And the world’s top 500 enterprises, the family enterprise accounted for 40%. Therefore, there are two purposes for this study. First, research whether there is correlation between the family enterprise factor and the company financial distressing. Second, adopt logistic regression method to establish the financial distress predicted model considering the family enterprise factors and then compare with the model only considering financial ratios to study whether the model having the family enterprise factor increase the performance. According to the result, the family enterprise factor and financial distress are not independent and there is positive correlation. Then, the model considering the variables of enterprise factors would increase the model’s performance.

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