資訊管理學報
李天行;唐筱菁;
頁: 161-189
日期: 2004/04
摘要: 隨著知識經濟時代的來臨，促使企業的競爭優勢不再只源於傳統的有形資產，還必需考量企業的無形資產，使得智慧資本扮演的重要性與日俱增。此外，由於整體經濟環境的快速變遷，造成企業財務危機發生的可能性隨之逐年增加，因此建立一個有效的企業危機診斷模式，是當前學術界與實務界相當重視的課題。為解決上述問題，本研究提出一整合財務比率與智慧資本之企業危機診斷模式，並利用多元適應性雲形迴歸輔助類神經網路之兩階段模式建構程序，主要目的是希望能發展一個更為快速、精確的診斷技術。此外，為驗證所提方法之有效性，本研究以民國87至89年間發生財務危機公司之相關資料，進行企業危機診斷模式的實證研究。實證結果顯示加入智慧資本指標有助於偵測企業危機的發生，提昇模式之鑑別效果；而將多元適應性雲形迴歸模式篩選之顯著變數作為類神經網路輸入變數之整合模式，無論在個別或整體正確判別率皆有優於單一模式之鑑別結果，提供企業或投資者事前洞悉公司經營危機的徵兆與投資判斷之參考依據。
關鍵字: 財務危機診斷;財務比率;智慧資本;倒傳遞類神經網路;多元適應性雲形迴歸;
Abstract: In 1998, many public companies were facing series financial distress in Taiwan. It is important for investors to take necessary actions to protect their own interests if endangered signals can be observed. And hence financial distress predictive model has become an important topic during the past decade. Intellectual capital represents assets that frequently do not appear in the balance sheet. Intellectual capital has gained more and more attention since it is the core weapon for many companies. Today, to measure the assets of companies, it is important to note that intellectual capital's value and strength tends to vary depending on the goals of the organization. In other words, including intellectual capital and traditional financial ratios in enterprise distress diagnosis model has become a very important and necessary task. The main purpose of this paper is to explore the performance of enterprise distress diagnosis incorporating financial ratios and intellectual capital by integrating the neural networks with multivariate adaptive regression spines (MARS) approach. The obtained results are expected to greatly expand the application of neural networks and MARS in enterprise distress diagnosis. And in terms of the successful identification of the relationship within data, better business modeling and investment decisions can be found and implemented.
Keywords: corporate distress diagnosis;financial ratios;intellectual capital;neural networks;multivariate adaptive regression splines;
瀏覽次數: 12253 下載次數: 78
引用 導入Endnote
頁: 161-189
日期: 2004/04
摘要: 隨著知識經濟時代的來臨，促使企業的競爭優勢不再只源於傳統的有形資產，還必需考量企業的無形資產，使得智慧資本扮演的重要性與日俱增。此外，由於整體經濟環境的快速變遷，造成企業財務危機發生的可能性隨之逐年增加，因此建立一個有效的企業危機診斷模式，是當前學術界與實務界相當重視的課題。為解決上述問題，本研究提出一整合財務比率與智慧資本之企業危機診斷模式，並利用多元適應性雲形迴歸輔助類神經網路之兩階段模式建構程序，主要目的是希望能發展一個更為快速、精確的診斷技術。此外，為驗證所提方法之有效性，本研究以民國87至89年間發生財務危機公司之相關資料，進行企業危機診斷模式的實證研究。實證結果顯示加入智慧資本指標有助於偵測企業危機的發生，提昇模式之鑑別效果；而將多元適應性雲形迴歸模式篩選之顯著變數作為類神經網路輸入變數之整合模式，無論在個別或整體正確判別率皆有優於單一模式之鑑別結果，提供企業或投資者事前洞悉公司經營危機的徵兆與投資判斷之參考依據。
關鍵字: 財務危機診斷;財務比率;智慧資本;倒傳遞類神經網路;多元適應性雲形迴歸;
Incorporating Financial Ratios and Intellectual Capital in Business Failure Predictions Using Artificial Neural Networks and Multivariate Adaptive Regression Splines
Abstract: In 1998, many public companies were facing series financial distress in Taiwan. It is important for investors to take necessary actions to protect their own interests if endangered signals can be observed. And hence financial distress predictive model has become an important topic during the past decade. Intellectual capital represents assets that frequently do not appear in the balance sheet. Intellectual capital has gained more and more attention since it is the core weapon for many companies. Today, to measure the assets of companies, it is important to note that intellectual capital's value and strength tends to vary depending on the goals of the organization. In other words, including intellectual capital and traditional financial ratios in enterprise distress diagnosis model has become a very important and necessary task. The main purpose of this paper is to explore the performance of enterprise distress diagnosis incorporating financial ratios and intellectual capital by integrating the neural networks with multivariate adaptive regression spines (MARS) approach. The obtained results are expected to greatly expand the application of neural networks and MARS in enterprise distress diagnosis. And in terms of the successful identification of the relationship within data, better business modeling and investment decisions can be found and implemented.
Keywords: corporate distress diagnosis;financial ratios;intellectual capital;neural networks;multivariate adaptive regression splines;
瀏覽次數: 12253 下載次數: 78
引用 導入Endnote