企業危機的發生不僅直接影響公司利害關係人之權益，並且對於協力互助的供應鏈體系亦會引起連串的危機反應，甚而導致整個社會也可能遭受巨大的損害，因此建立一個企業危機診斷模型，篩選出具顯著性的特徵變數，用以偵測企業危機發生之警訊，以使經營階層能儘早採取措施予以因應，實有其必要性與實務性。
本研究建構一以實數值遺傳演算法結合支援向量機作為企業危機診斷的模型，其間比較財務指標與智慧資本指標對診斷模型的影響，以及透過鑑別分析法以比較本模型的優越性與穩定性，並以鑑別分析法與顯著性分析法篩選出對診斷模型具顯著性的特徵變數，以提升診斷模型的效率與效能。
經由實證分析結果，本研究獲得以下的結論：企業危機診斷的特徵變數應以財務與智慧資本的指標為佳；GA-SVM的方法較傳統的鑑別分析法優越與穩定；適當的縮減特徵變數對診斷模型的準確度有相當的助益；顯著性分析法所篩選出的8個特徵變數對診斷模型的助益較傳統鑑別分析法所篩選出的6個特徵變數為佳。
本研究期望藉由此診斷模型的運作而找出對企業危機具有顯著敏感度的8個特徵變數，可以作為企業界於做自我診斷與衡量時的參考。

A business crisis affects not only the rights and interests of stake holders, but also causes a series of crises in collaboration systems and supply chains.
Furthermore, these situations cause considerable loss and damage to society in general. Therefore, it is necessary to establish a diagnostic model for business crises and determine their warning signs to help business managers prepare earlier counter measures.
This study uses a real-valued genetic algorithm integrated with a SVM model as a diagnostic model for business crises. This study then compares financial indicators and intellectual capital indicators to evaluate the influence of accuracy on the diagnostic model. Using a discriminant analysis method, this study further compares the accuracy and stability of the proposed model. Additionally, a discriminant analysis method and a saliency analysis method are applied to the 8 significant features in the diagnostic model, improving both efficiency and effectiveness.
Results indicate that eight features for business crises diagnosis are based on the indicators of financial and intellectual capital. The GA-SVM has better performance and stability than traditional discriminant analysis methods. An appropriately reduced number of feature variables should be quite helpful in improving the accuracy of diagnostic models. The eight features screened by the saliency analysis method are actually more helpful than the six features selected by traditional discriminant methods.
This research identifies the eight features with significant sensitivity to business crises using a diagnostic model. These can be used by firms for self-diagnosis and evaluation.

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3、陳肇榮，「運用財務比率預測企業危機之實證研究」，國立政治大學企業管理研究所，博士論文，1983。
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