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  1. NTU Theses and Dissertations Repository
  2. 管理學院
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請用此 Handle URI 來引用此文件: http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/42002
完整後設資料紀錄
DC 欄位值語言
dc.contributor.advisor(Ken Yaotsung Chen)
dc.contributor.authorSuyantoen
dc.contributor.author蘇陽托zh_TW
dc.date.accessioned2021-06-15T00:41:25Z-
dc.date.available2009-11-20
dc.date.copyright2008-11-20
dc.date.issued2008
dc.date.submitted2008-11-06
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Agrawal, A., and S. Chadha. 2005. Corporate Governance and Accounting Scandals. Journal of Law and Economics 48:371-406.
Albrecht, W. S., C. C. Albrecht, and C. O. Albrecht. 2006. Fraud Examination. Thomson South-Western.
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Bell, T. B., and J. V. Carcello. 2000. A Decision Aid for Assessing the Likelihood of Fraudulent Financial Reporting. Auditing: A Journal of Practice 19 (1):169-184.
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Chen, K. Y., and R. J. Elder. 2007. Fraud Risk Factors and the Likelihood of Fraudulent Financial Reporting:Evidence from Statement on Auditing Standards No. 43 in Taiwan. In Working Paper: National Taiwan University and Syracuse University, 36.
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Ge, W., and S. McVay.2005. The disclosure of Material Weaknesses in Internal Control after the Sarbanes-Oxley Act. Accounting Horizons 19(3): 137-158.
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Persons, O. S. 1995. Using Financial Statement Data to Identify Factors Associated with Fraudulent Financial Reporting. Journal of Applied Business Research 11 (3):38.
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dc.identifier.urihttp://tdr.lib.ntu.edu.tw/jspui/handle/123456789/42002-
dc.description.abstract本研究之目的乃透過實證方法去辨認財務報表舞弊的風險因素,並且以美國會計師協會查核準則第99號公報為依據,建立一個模型以預測財務報表舞弊之可能性。決定舞弊有三個因素:壓力(Pressure)、機會(Opportunity)和合理化(Rationalization)。透過Logit模型分析探討143間公司,本實證結果顯示對於壓力之代理變數,像是資產報酬率,以及機會之代理變數,像是存貨對總資產之比率、關係企業交易、以及四大事務所,皆與財務報表舞弊有顯著相關。然而,沒有任何一個針對合理化此舞弊風險因素之代理變數是與財務報表舞弊顯著相關的。與學術上先前之研究結果一致,壓力與機會之代理變數相較於合理化之代理變數更能使財務報表舞弊之可能性被大眾所觀察。所建立之模型能正確地分類有相對較高成功機率的公司。更有甚者,值得注意的是財務報表舞弊之可能性與沙氏法案第302條以及第404條制定前後無攸關的差異。zh_TW
dc.description.abstractThe goals of this study are to empirically identify fraud risk factors and construct a model to predict the likelihood of financial statement fraud based on SAS No. 99. By employing logistic regression to 143 firms, this research finds that fraud risk factor proxies for Pressure—i.e. net profit/total assets—and Opportunity— inventory/total assets ratio, related party transaction, and Big 4—are significantly associated with fraudulent financial statement, whereas none of the fraud risk factor proxies for Rationalization is significantly associated with fraudulent financial statement. Consistent with prior research, it seems that the likelihood of fraudulent financial statement is easier to be publicly observed by using fraud risk factor proxies for Pressure and Opportunity rather than Rationalization. The constructed model can correctly classify firms with relatively high success rate. Furthermore, it is important to note that no relevant difference could be established before and after the enactment of SOA’s Section 302 and Section 404 toward the likelihood of fraudulent financial statement.en
dc.description.provenanceMade available in DSpace on 2021-06-15T00:41:25Z (GMT). No. of bitstreams: 1
ntu-97-R95722047-1.pdf: 1463410 bytes, checksum: e18adf483d42d5308527860d5f99837d (MD5)
Previous issue date: 2008
en
dc.description.tableofcontentsAbstract v
Chapter 1: Introduction 1
Chapter 2: Theory and Hypotheses Development 4
Pressure Variables 7
1. Financial Leverage - Total Liability/Total Assets (LEV) 7
2. Capital Turnover - Sales/Total Assets (SALTA) 8
3. Profitability - Net Profit/Total Assets (NPROFTA) 8
Opportunity Variables 9
1. Related Party Transaction (RPTRANS) 9
2. Big 4 (BIG4) 10
3. Inventory/Total Assets (INVTA) 10
Rationalization Variables 11
1. Auditor Change (CPA) 12
2. Audit Opinion (AO) 12
3. Going Concern (GC) 13
Chapter 3: Sample Selection and Description 15
Fraud Firm Selection 15
Comparing Fraud Firms to No-Fraud Firms 16
Chapter 4: Research Design 18
Chapter 5: Empirical Results and Additional Analyses 20
Regression Result 20
Model 1: Pressure 21
Model 2: Opportunity 21
Model 3: Rationalization 21
Model 4: Full Regression of Fraud Triangle 22
Additional Analysis 22
Predictive Fraud Model and Robustness 22
The Effects of the Enactment of Sarbanes Oxley Act 24
Chapter 6: Conclusion 25
Reference 29
List of Appendix
Appendix 1: Example of Fraud Risk Factors in SAS No. 99 30
Appendix 2: List of Sample Firms 31
List of Table
Table 1: Sample Selection Method 34
Table 2: Descriptive Statistic 35
Table 3: T-tests and Wilcoxon Sign-Rank Test 36
Table 4: Correlations among Dependent and Independent Variables 38
Table 5: Initial Logistic Regression 41
Table 6: Logistic Regression of the Likelihood of Fraudulent Financial Reporting 42
Table 7: Fraud Prediction Model 44
Table 8: Discriminate Analysis 45
Table 9: The Effect of Sarbanes-Oxley Act 46
dc.language.isoen
dc.subject欺詐三角形zh_TW
dc.subject欺詐風險因素zh_TW
dc.subject的SAS 99zh_TW
dc.subject財務報表的欺詐行為zh_TW
dc.subjectfinancial statement frauden
dc.subjectfraud risk factorsen
dc.subjectSAS 99en
dc.subjectfraud triangleen
dc.title舞弊風險因子與欺詐財務報表的可能性
—以SAS No.99為證
zh_TW
dc.titleFraud Risk Factors and the Likelihood of Fraudulent Financial Reporting: Evidence from Statement on Auditing Standards (SAS) No. 99en
dc.typeThesis
dc.date.schoolyear96-2
dc.description.degree碩士
dc.contributor.oralexamcommittee(Chih Yang Tseng),(Wang Wann Cherng)
dc.subject.keyword財務報表的欺詐行為,欺詐三角形,的SAS 99,欺詐風險因素,zh_TW
dc.subject.keywordfinancial statement fraud,fraud triangle,SAS 99,fraud risk factors,en
dc.relation.page57
dc.rights.note有償授權
dc.date.accepted2008-11-07
dc.contributor.author-college管理學院zh_TW
dc.contributor.author-dept會計學研究所zh_TW
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