財務危機預警模型藉由企業財務及非財務資訊判別企業是否有財務危機之疑慮，本研究另將景氣與產業因子納入邏輯斯迴歸與DEA-DA模型中以期建構更準確的預警模型。實證結果顯示在所有情況下，採用DEA-DA建構的模型皆可提供較佳的準確度。同時，考量景氣好壞與產業因素後確可提高預警模型的準確度。當景氣下降時，企業需要特別注意應收帳款週轉率與償債能力的變化。而當景氣上升時，企業則愈需要注重資產管理的效率、董監持股率與台灣企業信用風險指標（TCRI）。對不同的產業而言，電子業除了需重視償債能力與資產周轉率外，並應強化公司治理及制定適當的分紅配股制度；營建業平時要注意董監質押比率及償債能力，愈接近危機發生時，尤其要注意獲利能力的變化。

Financial distress prediction model is generally using financial and nonfinancial information to observe the operation condition of a company, and discriminate whether a company is financial distress entity or not. This study takes consideration of the economic condition and industrial factors into logistic regression and DEA-DA models to construct a financial distress prediction model. The empirical results reveal that the DEA-DA model predicts the distress event better than logistic regression model during the economic downturn and upturn. In addition, the empirical results also suggest that considering economic condition and industrial factors can improve the accuracy of financial distress prediction models. In the period of economic recession, firms should pay more attention to the turnover of accounts receivable and solvency for avoiding the occurrence of financial distress. However, in the facing of economic expansion period, firms must focus on the issues of operation efficiency, percentage of equity ownership held by directors and Taiwan Corporate Credit Risk Index (TCRI). For the electronic industry, firms should emphasize how to reinforce the corporate governance and how to set up the appropriate stock option plan in addition to the solvency capacity and asset turnover ratio issues. With regard to the construction industry, firms should pay more attention to the percentage of equity ownership held by directors and solvency capacity during the normal period. Furthermore, they should watch carefully for the changes of profitability and TCRI at financial distress time.