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研究生:郭忠隆
研究生(外文):Chung-Long Kuo
論文名稱:訴訟風險預測-類神經網路之應用
論文名稱(外文):Litigation Risk Prediction : An Application of Artificial Neural Network
指導教授:陳雪如陳雪如引用關係
指導教授(外文):Hsueh-Ju Chen
學位類別:碩士
校院名稱:靜宜大學
系所名稱:會計學系研究所
學門:商業及管理學門
學類:會計學類
論文種類:學術論文
論文出版年:2005
畢業學年度:93
語文別:中文
論文頁數:103
中文關鍵詞:類神經網路舞弊內部控制預測邏輯斯迴歸
外文關鍵詞:Logistic RegressionArtificial Neural NetworkInternal controlPredictionFruad
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本研究主要之目的在於探討公司內部控制缺失與管理階層舞弊訴訟之關係,藉以建構一舞弊訴訟預警模型,進而提供會計師做為查核策略判斷之依據。研究樣本以國內上市櫃公司為主,採一家起訴公司配對二家非起訴公司之模式,共選取74家起訴公司,148家非起訴公司,總計222家公司。參考美國SAS No.82之分類,分為四個風險構面,並以27個舞弊風險要素,做為模型之輸入變數,並運用邏輯斯迴歸及類神經網路建構舞弊訴訟預警模型,以獲取內控缺失與發生起訴與否之關聯性。經其分析回函問卷,結果顯示我國上市櫃公司在管理當局特性構面中風險偏高,此與我國公司多為家族企業之特性相呼應。邏輯斯迴歸模型結果顯示,「公司營運及財務穩定性」和「資產不當配置」兩者之符號為負,顯示當公司營運及財務穩定性狀況不佳和資產配置不當時,則發生舞弊之機會愈高,但「管理當局能力」與預期方向不一致,表示管理階層的教育程度和能力愈高,則發生舞弊之機會愈高。透過類神經網路與邏輯斯迴歸方法做預測準確率、型一型二錯誤率及錯誤歸類成本之分析後,發現以類神經網路所建構之預警模型,預測效能最佳,並優於會計師之實際判斷。
The purpose of this study is to examine the relationship between the internal control system and litigation presence, hence to construct an early warning litigation presence model for assisting accountants on audit strategy making. The samples entirely collected from public companies and the selection strategy are 222 companies, which including 74 companies of sued and 148 companies of nonsued; and one sued company match two nonsued companies.Refer to SAS No. 82, the enter variable in this model has four risk components and 27 embezzlement risk factors; and then try using Logistic regression and Early Warning Litigation Presence Model of Artificial Neural Network to obtain the relationship between internal control fault and whether it would have sued or not. According to the response information of questionnaire, the risk of Management''s characteristics structure is higher in domestic public companies, which is respond to family enterprise.Logistic regression model displays the negative symbol between operation characteristics and financial stability and susceptibility of assets to misappropriation, that means the embezzlement may be happed when company is in bad operating, unsteady finance, and susceptibility of assets to misappropriation. However, the managerial capacity inconsistent.with anticipation, there may be an opportunity for company to be corrupt when the stratum of management has excellent ability and knowledge.To forecast the rate of accuracy by Artificial Neural Network and Logistic regression, and analyze the rate of error and classified error cost in type of 1 error and type of 2 error, it can be found the best forecast efficacy is Warning Model of Artificial Neural Network and it is superior to CPA’s judgment.
目 錄
第一章 緒論
第一節 研究動機 ……..…..………………………….……..1
第二節 研究目地………..………………………………….. 5
第三節 預期貢獻………..………………………………….. 5
第四節 研究架構………..………………………………….. 6

第二章 文獻探討
第一節 影響審計人員判斷之因素.………….………..…....7
第二節 內部控制、舞弊和訴訟之關聯性.….……..……...11
第三節 審計決策支援工具之運用與評估…..…….………16
第四節 邏輯斯迴歸、專家系統與類神經網路之比較.......22
第三章 研究方法與假說
第一節 觀念性架構…………………………….…............. 26
第二節 變數定義…………………………….…………..... 27
第三節 問卷設計及研究樣本選取………….…………... ..28
第四節 研究方法………………………………………….. 31
第四章 實證結果分析
第一節 敘述性統計及信度與效度分析………………….. 41
第二節 邏輯斯迴歸之結果………………………..….…... 46
第三節 類神經網路之結果………………………………..52
第五章 結論與建議
第一節 實證結論……………………………………….….60
第二節 研究限制………………………………......……... 61
第三節 研究建議及未來研究方向…………………….… 62
第四節 總結………………………………………..…..…..64
參考文獻…………………………………………….…………....... 65
附錄一 全國司法機關審理偵辦之舞弊案…………….………71
附錄二 公開發行公司問卷……………………………….……74
附錄三 被起訴案件舞弊風險因素判讀紀錄………….………77
附錄四 審計人員問卷…………………………………….……90
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