Please use this identifier to cite or link to this item: https://ah.lib.nccu.edu.tw/handle/140.119/36942
DC FieldValueLanguage
dc.contributor.advisor劉文卿zh_TW
dc.contributor.author鐘冠智zh_TW
dc.creator鐘冠智zh_TW
dc.date2008en_US
dc.date.accessioned2009-09-18T12:14:02Z-
dc.date.available2009-09-18T12:14:02Z-
dc.date.issued2009-09-18T12:14:02Z-
dc.identifierG0094356037en_US
dc.identifier.urihttps://nccur.lib.nccu.edu.tw/handle/140.119/36942-
dc.description碩士zh_TW
dc.description國立政治大學zh_TW
dc.description資訊管理研究所zh_TW
dc.description94356037zh_TW
dc.description97zh_TW
dc.description.abstract台灣上市公司不預警地宣布重整,跳票、全額交割或下市,造成投資大眾的損失,因此,必須建立企業信用模型來偵測其經營狀況。本研究發現財務比率自企業危機前五年起逐漸惡化,表示財務比率在危機發生前有惡化現象,另外危機發生後幾年財務比率仍有影響,故本研究視企業危機為一逐年遞增或遞減的變數,使用模糊數轉化,加入危機發生前後的總體變數,並且結合統計多變量分析和資料探勘中的乏析理論建立模型,使用窮舉法找出解釋力最佳之企業信用模型,結果顯示,採用模糊數轉化之應變數相當顯著。zh_TW
dc.description.abstractThe listed companies in Taiwan suddenly announced restructuring, bankruptcy or out of stock, and their investors lost a lot. Therefore, we must set up the enterprise credit model to detect and examine their management states. We discover that the financial ratios decrease gradually since the past five years of enterprise`s crisis. Besides, financial ratios still diminish after the crisis take place. Therefore, this research regards enterprise`s crisis as one parameter, and we transform the parameter by fuzzy numbers. In addition, we use the macro economical parameters and combine multivariate analysis and fuzzy logic theory to find out a higher significant model. The result shows it is high significant to adopt the fuzzy number dependent variable.en_US
dc.description.tableofcontents目錄\n壹 前言 1\n貳 文獻探討 3\n一、 檢測方法 3\n二、 變數選取 12\n參 研究方法 15\n一、 企業危機 15\n二、 研究流程設計 16\n三、 樣本選取 17\n四、 模糊邏輯轉化 17\n肆 研究架構 17\n一、 財務變數 18\n二、 總體變數 18\n三、 應變數:危機程度 18\n伍 模型結果 20\n一、 模糊應變數模式測試結果 20\n二、 變數描述 23\n三、 各模型比較 25\n陸 結論與建議 28\n參考文獻 30\n附錄 32\n\n\n表目錄\n表1違約定義 21\n表2 塑化業模糊組合 22\n表3塑化業模糊組合(續) 23\n表4 食品業模糊組合 23\n表5 食品業模糊組合(續) 24\n表6塑化業模糊化應變數 24\n表7食品業模糊化應變數 25\n表8塑化業逐步回歸 26\n表9食品業逐步回歸 26\n表10塑化業變數描述 27\n表11食品業選取變數描述 27\n表12塑化業各模型描述 28\n表13食品業各模型描述 29\n表14財務危機預警制度英文文獻回顧摘要: 34\n表15財務危機預警制度中文文獻回顧摘要: 35\n表16財務危機預警制度中文文獻回顧摘要:(續) 36\n表17財務危機預警制度中文文獻回顧摘要:(續) 37\n表18總經變數 38\n表19財務比率 39\n表20財務比率(續) 40\n\n\n圖目錄\n圖1 三角模糊數 8\n圖2 梯形模糊數 8\n圖3 研究分類 15\n圖4企業危機三角形模糊數 16\n圖5企業危機梯形模糊數 17zh_TW
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dc.source.urihttp://thesis.lib.nccu.edu.tw/record/#G0094356037en_US
dc.subject模糊數zh_TW
dc.subject企業信用模型zh_TW
dc.subject財務比率zh_TW
dc.subjectFuzzy numberen_US
dc.subjectEnterprise credit modelen_US
dc.subjectFinancial ratiosen_US
dc.title企業信用模型建置與驗證—使用乏析應變數以塑化業及食品業為例zh_TW
dc.typethesisen
dc.relation.reference中文文獻zh_TW
dc.relation.reference林文修,1996,演化式類神經網路為基底的企業危機診斷模型:智慧資本之應用,第一屆台灣資管博士論文研討會,高雄,中山大學。zh_TW
dc.relation.reference黃焜煌、卓統佑,1998,模糊邏輯在財務危機預測上之應用。朝陽學報,第三期,47~68。zh_TW
dc.relation.reference劉向麗,2001,依銀行融資觀點看企業財務預警問題,國立中山大學財務管理系碩士論文。zh_TW
dc.relation.reference林金賢,陳育成,劉沂佩,鄭育書,2004,具學習性之模糊專家系統在財務危機預測上之應用,管理學報,21 卷,3 期,291~309。zh_TW
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dc.relation.reference沈中華、黃博怡,2006,台灣中小企業產業別信用風險模型,中小企業發展季刊,第一期。zh_TW
dc.relation.reference吳雅娟,2006,以模糊理論建構台灣上市櫃電子公司財務危機預警模型與實證,國立成功大學高階管理碩士在職專班碩士論文。zh_TW
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dc.relation.referenceLensberg, T. , Eilifsen, A. & Mckee,T.E. 2004. Bankruptcy Theory Development and Classification via Genetic Programming. Journal of Operational Research.zh_TW
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