財務危機預警模型係利用企業之財務報表資訊觀察企業整體營運狀況，藉此判別企業是否有財務危機之疑慮。過去的研究指出破產成本相當巨大，不僅帶給企業經營者本身重大的虧損，甚至是投資人也蒙受損失。因此，如何建構出適合台灣經濟環境的財務危機預警模型是值得探討的議題。影響財務危機預警模型的因素眾多，除了企業本身的經營管理能力外，尚有包括景氣因素、產業因素與集團因素等重要因素。總體經濟狀態的差異會影響企業財務績效與財務報表上的表現；不同產業與是否為集團企業之經營方法各有特色亦會導致財務績效與報表上的差異。但是，目前國內外研究較少搭配上述因素於財務危機預警模型之建構方法上的探討。因此，本研究擬透過樣本分類，將景氣因子、產業因子與集團因子納入區別分析、邏輯斯迴歸與DEA-DA模型，三種財務危機預警模型討論。本研究預期建構出符合台灣集團企業，電子產業與營建業於景氣榮枯時實用的財務危機預警模型，除能提供給相關經營者與投資人參考外，並引導未來研究者一個重要的研究方向。實證結果顯示DEA-DA在全樣本、營建業樣本與集團樣本中，平均為最佳的模型，而區別分析在電子業則為最佳的模型。並發現在一般狀況下，愈接近危機時間點，愈需注重獲利能力；愈遠離危機時間點，愈需注重資本結構與營運能力。而TCRI信用評等與董監質押比率為必須隨時注意的變數。而電子業需要特別注意經理人持股，經理人可以運用配股方式來降低企業內的代理問題；營建業則注重董監質押比率、營運能力與資本結構比率，避免因為高期初投入成本，長應收帳款回收
期間所導致的週轉不靈。本研究實證結果可提供給投資人與經理人一個簡易判別財務危機的模型，並藉由選取出變數給予經理人參考，作為制定決策時的參考。

Financial distress prediction model is generally using financial statements to observe the whole operation condition of a company, and discriminate whether a company is financial distress corporation. Preview research has indicated the bankruptcy cost is very huge and important, it could damage firm operation and reputation and hurt investor with investment loss. Therefore, how to construct a financial distress model which is suit the business condition of Taiwan is worth to discuss. There are many factors might influence financial distress prediction model, including macroeconomic environment factor, industry factor and business group factor. The difference between economic boom and recession might influence financial performance and the information on corporate financial statements; industry factor and business group factor might effect the corporate management style, it will also effect financial performance.
Nevertheless, to date, there only few researchs consider to include the factors mentioned before into financial distress prediction models. Therefore, this project would investigate three financial distress prediction model, including discriminant analysis model, logit regression model and DEA-DA model and discuss the influence of the macroeconomic environment factor, industry factor and business group on prediction model by data classification. The goal of this research is to construct a practical financial distress prediction model for Taiwan business groups, firms in electronic and construction industry during economic up- trend and down- trend. We hope this research can provide corporate managers and investors some valuable information on their decision making and also lead to some important direction for future research.

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