隨著知識經濟時代的來臨，許多企業為獲取競爭優勢已不再侷限於傳統的有形資產，無形資產的重要性與日俱增，其中智慧資本成為企業的關鍵考量。此外，因經濟環境的快速變化，使得國內外公司相繼發生嚴重之財報舞弊案件，不但使自身財務及商譽遭受損害，也讓投資大眾對投資環境失去信心，嚴重影響股市的正常運作及社會經濟的安定。
以往傳統研究大都單純以企業財務性比率作為解釋變數進行模型探討，本研究採用羅吉斯迴歸(Logistic Regression)方法，於台灣上市(櫃)公司中，以一家舞弊公司配對約三家無舞弊公司之比例選取實證樣本，在財務資料的基礎上加入智慧資本，建構出整合傳統財務變數和智慧資本變數之財報舞弊預警模型，期望增進預測能力。經實證結果顯示加入智慧資本變數之財報舞弊模型預警準確度優良，模型穩定性強，適用於判斷舞弊之可能性。
研究建議將智慧資本指標納入預警模型之觀察變數中，相信對於企業財報舞弊預警有相當程度的貢獻。

關鍵字:知識經濟;智慧資本;財報舞弊;羅吉斯迴歸;舞弊預警模型

With the advent of the knowledge economy era , many enterprises to gain competitive advantage is no longer confined to the traditional tangible assets , the growing importance of intangible assets , including intellectual capital becomes the key considerations companies . In addition, due to the rapid changes in the economic environment , making domestic and foreign companies have been serious cases of fraud in the financial report , not only their financial and goodwill suffered damage , but also to the investing public to lose confidence in the investment environment has seriously affected the normal functioning of the stock market and socio-economic stability .
Most previous studies simply to traditional corporate finance ratios as explanatory variables the model discussed in this study using logistic regression (Logistic Regression) methods listed in Taiwan ( OTC) , and paired with a fraud company about three non- fraud company the proportion of positive samples selected , adding intellectual capital on the basis of financial information to construct the integration of traditional financial variables and the variables of intellectual capital earnings fraud warning model , expected to enhance the predictive ability . The empirical results show that adding intellectual capital model variables earnings warning fraud excellent accuracy , stability and strong model for the possibility of fraud judgment .
Research suggests that the observed variables intellectual capital indicators into early warning model , I believe that corporate earnings fraud warning for a considerable degree of contribution.

Keywords : knowledge-based economy ; intellectual capital ; earnings fraud ; logistic regression ; Fraud Warning Model

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