參考文獻
一、 中文部分
池千駒(1999),運用財務性、非財務性資訊建立我國上市公司財務困難預警模式,國立成功大學會計學研究所未出版之碩士論文。何太山(1977),運用區別分析建立商業放款信用評分制度,政治大學企業管理研究所未出版之碩士論文。何文榮、李復禮(2006),公司治理與財務危機關係之研究—以上市公司為例,華人前瞻研究,2(2),1-25。何文榮、彭俊豪(2001),以不同類神經網路建構上市公司財務預警模型,台灣土地金融季刊,38(3),1-22。
何文榮、鄭碧月(2005),「台灣上市公司營運危機預測模式之研究」,華人經濟研究, 3(1),71-92。余惠芳(2008),台灣集團企業財務危機預警模式之研究,臺灣科技大學企業管理研究所未出版之博士論文。李洪慧(1997),動態化財務預警模型之研究-以證券經紀商為例,東吳大學企業管理研究所未出版之碩士論文。李馨蘋,莊宗憲(2007),公司治理機制與公司績效之實證研究,東吳經濟商學學報,57,1-27。林修逸(2003),應用評分模型預測公司危機:三種方法兩種模型之比較,東吳大學國際貿易學系未出版之碩士論文。邱志榮(1990),公司營運危機之預測-財務比率與現金流量之比較,成功大學工業管理研究所未出版之碩士論文。邱怡華(2012),集團企業財務危機預警模型-經營權與所有權是否同一人比較,中國文化大學國際企業管理研究所未出版之碩士論文。邱碧芳(2001),公司財務危機預警資訊之研究-考慮現金流量因素,朝陽科技大學財務金融系未出版之碩士論文。徐中琦,曾煌鈞(2008),台灣企業公司治理及財務資訊構面預警系統建立之研究,國立台灣科技大學財務金融所未出版之碩士論文。
徐健進(1984),銀行放款信用評等模式之研究,國立政治大學企業管理研究所未出版之碩士論文。梁榮輝,魏雅芬(2006),企業財務危機預警模式之研究-以台灣地區上市公司為例,中國文化大學國際企業管理研究所未出版之碩士論文。莊嘉建,呂佩蓉(2008),股權結構、關係人交易與公司財務績效關聯性之研究,蘭陽學報,7,86-94。許崇源,王寬裕(2007),台灣金融機構企業徵信模式構建及其應用之研究,澳門科技大學行政與管理學院未出版之博士論文。
郭瓊宜(1994),類神經網路在財務危機預警模式之應用,淡江大學管理科學研究所未出版之碩士論文。陳怡雯(2003),企業財務危機預警模式-非財務指標之運用,真理大學財經研究所未出版之碩士論文。陳昭宏(2005),以事前控制觀點應用灰色預測理論與Logit式於財務危機預警模型之研究,商管科技季刊,6(4),655-676。陳肇榮(1983),運用財務比率預測企業財務危機之實證研究,國立政治大學企管所博士論文。陳肇榮(1984),財務危機之預測,華泰圖書文物公司。
黃振豊,呂紹強(2000),企業財務危機預警模式之研究-以財務及非財務因素構建,當代會計,1(1),19-40。榮泰生(2009),SPSS與研究方法第二版,台北:五南圖書出版股份有限公司,625-632。
潘玉葉(1990),台灣上市公司財務危機預警分析,私立淡江大學管理科學研究所未出版之博士論文。鄭育書(2002),企業失敗預測之實證研究,靜宜大學會計學系未出版之碩士論文。賴耀群(1977),銀行放款信用評估模式之研究,淡江大學管理科學研究所未出版之碩士論文。藍國益(1996),企業財務危機預警模式之研究-考慮股權結構之影響,東吳大學企業管理學系未出版之碩士論文。 二、 英文部分
Altman, E. I. (1968). Financial Ratios Discriminant and the Prediction of Corporate Bankruptcy. Journal of Finance, 23(4), 589-609.
Altman, E. I., Marco, G., & Varetto, F. (1994). Corporate Distress Di-agnosis: Comparisons using Linear Discriminant Analysis and Neural Networks. Journal of Banking and Finance, 18(3), 505-529.
Ball, C. A., & Tschoegl, A. E. (1982). The Decision to Establish a Foreign Bank Branch or Subsidiary:An Application of Binary Classification Proceduer. Journal of Financial and Quantitative Analysis, 17(3), 411-424.
Beaver, W. H. (1966). Financial Ratios as Predictors of Failure. Jour-nal of Accounting Research, 4, 71-111.
Betts, J., & Belhoul, D. (1987). The Effectiveness of Incorporating Stability Measures in Company Failure Model. Journal of Business Finance of Accounting, 14(3), 323-335.
Blum, M. (1974). Failing Company Discriminiant Analysis. Journal of Accounting Research, 12(1), 1-25.
Booth, P. J. (1983). Decomposition Measures and the Prediction of Financial Failure. Journal of Business Finance And Accounting, 10, 67-85.
Brickley, J. A., Lease, R. C. and Smith Jr., C.W (1988). Ownership Structure and Voting on Antitakeover Amendments. Journal of Financial Economics, 20, 267-291.
Chen, and Hu (2001). The Controlling Shareholder's Personal Stock Loan and Firm Performance. Expert Systems with Application, 21, 225-234.
Claessens, S., Djankov, S., Fan, J. P. H., and Lang, L. H. P. (2002). Disentangling the Incentive and Entrenchment Effects of Large Shareholdings. Journal of Finance, 57(6), 2741-2771.
Coats, P. K., & Fant, L.F. (1993). Recognizing Financial Distress Pat-terns Using aNetwork Tool. Financial Managemen , 2, 142-155.
Daily, C. M., & Dalton, D. R. (1994). Bankruptcy and Corporate Governance:The Impact of Board Composition and Structure Academy. Management Journal, 37(6), 1603-1617.
Deakin, E. B. (1972). A Discriminate Analysis of Predictors of Busi-ness Failure. Journal of Accounting Research, 10(1), 167-179.
Faccio, M. and Lang, L. H. P. (2000). The Separation of Ownership and Control : An Analysis of Ultimate Ownership in Western European Corporations. 2000 European Financial Management Association Annual Meeting.
Hopwood, W. (1994), A Reexamination of Auditor versus Model Ac-curacy Within the Context of the Going-Concern Opinion Deci-sion. Contemporary Accounting Research, 10(2), 409-431.
Kane, G.D., Patricia. L., & Richardson, F. M. (1998), The Impact of Recession on The Prediction of Coporate Failure. Journal of Business and Accounting, 25(1-2), 167-186.
Kesner, I. F. (1987). Director’s Stock Ownership & Organizational Performance: An Investigation Of Fortune 500 Companies. Journal of Management, 13(3), 499−508.
Lane, W. R., Looney, S.W., & Wansley, J. W. (1986). An Application of The Cox Proportional Hazards Model to Bank Failure. Jour-nal of Accounting and Finance, 10(1), 511-531.
Lau, H. L. (1987). A Five-State Financial Distress Prediction model. Journal of Accounting Research, 25(1), 127-138.
Lee, T. S., & Yeh, Y. H. ( 2004). Corporate Governance and Financial Distress: Evidence from Taiwan. Corporate Governance: An International Review, 12(3), 378-388.
Lieu, P. T., Lin, C. W., & Yu, H. F. (2008). Financial Early-Warning Models on Cross-holding Groups. Industrial Management and Data Systems, 108(8), 1060-1080.
Mensah, Y. M. (1984). An Examination of the Stationarity of Multi-variate Bankruptcy Prediction Models:A Methodological Study. Journal of Accounting Research, 22(1), 380-395.
Meyer, P. A., & Pifer, H. W. (1970). Prediction of Bank Failure. Jour-nal of Finance, 25(4), 853-868.
Nasir, M. L., John, R.. I., Bennett, S. C. & Russell, D. M. (2000). Pre-dicting Corporate Bankruptcy Using Modular Neural Networks. IEEE/IAFE/INFORMS Conference , 86 – 91.
Odom, M. D., & Sharda, R. (1990). A Neural Network Model for Bankruptcy Prediction. Proceedings of the IEEE International Conference on Networks, 2(1), 163-168.
Ohlson, J. A. (1980). Financial Ratios and the ProbabilisticPrediction of Bankruptcy. Journal of Accounting Research, 18,109-131.
Pinches, G. E., Mingo, K. A., & Caruthers, J. K. (1973). The Stability of Financial Patterns in Industrial Organizations. Journal of Fi-nance, 28(2), 389-396.
Tam, K. Y., & Kiang, M. Y. (1992). Managerial Applications of Neural Networks: The Case of Bank Failure Predictions. Management Science, 38(7), 926-947.
Ward. T. J., & Foster, B. P. (1997). A Note on Selecting a Response Measure for Financial Distress. Journal of Business Finance and Accounting, 24(6), 869-879.
Zmijewski, M. E., (1984). Methodological Issues Related to the Esti-mation of Financial Distress Prediction Models. Supplement to Journal of Accounting Research, 22, 59-82.