English  |  正體中文  |  简体中文  |  Post-Print筆數 : 11 |  Items with full text/Total items : 88865/118572 (75%)
Visitors : 23548647      Online Users : 624
RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version
    政大機構典藏 > 學術期刊 > 會計評論 > 期刊論文 >  Item 140.119/114780
    Please use this identifier to cite or link to this item: http://nccur.lib.nccu.edu.tw/handle/140.119/114780


    Title: 資料探勘技術在繼續經營疑慮意見診斷模型之應用
    Going Concern Opinion: Application of Data Mining Technologies
    Authors: 盧鈺欣
    林昱成
    林育伶
    Lu, Yu-Hsin
    Lin, Yu-Cheng
    Liao, Jung-Ling
    Keywords: 繼續經營疑慮意見;資料探勘技術;特徵選擇;分類技術
    Going concern opinion;Data mining technologies;Feature selection;Classifier technique
    Date: 2016-07
    Issue Date: 2017-11-15 16:01:10 (UTC+8)
    Abstract: 會計師決定是否出具繼續經營疑慮意見時,涉及專業判斷且考量因素眾多與複雜。因此,評估公司繼續經營假設是否有重大疑慮的分析性資訊對會計師而言非常重要。本文之目的係以資料探勘技術建構繼續經營疑慮意見診斷模型,並提供會計師有用之決策資訊,藉以輔助其評估對受查客戶出具繼續經營疑慮意見書之依據。首先,本文利用特徵選擇工具自眾多影響會計師出具繼續經營疑慮意見的相關變數中,篩選出6 個重要影響因素。再輔以分類技術-決策樹建構繼續經營疑慮意見診斷模型,並產出決策表供會計師參酌。實證結果顯示,本文決策表所提供之10 條分類規則,能有效區別繼續經營疑慮意見書類型,其預測準確率高達91.35%,有助於會計師評估繼續經營疑慮意見時之參考依據,降低審計風險。
    The auditors' going concern opinion usually involves complex professional judgment and considerations. Therefore, information that may raise auditors' substantial doubts as to whether a going-concern opinion should be issued is important during the audit process. This study adopts the data mining technology to build up a going concern diagnostic model from which the auditors can obtain useful information to assess clients’ ability of remaining as a going concern. Specifically, the auditors’ going concern opinion is determined by considering six critical factors extracted from a feature selection tool and a decision table created by a diagnostic model built from a decision tree. The empirical results indicate that the 10 classification rules generated by the decision table can effectively distinguish different types of going concern audit reports with a prediction accuracy of 91.35%. Overall, this decision table facilitates the auditors in assessing clients' likelihood of continuing as a going concerns and, therefore, reducing audit risk.
    Relation: 會計評論, 63, 77-108
    Data Type: article
    DOI 連結: http://dx.doi.org/10.6552/JOAR.2016.63.3
    DOI: 10.6552/JOAR.2016.63.3
    Appears in Collections:[會計評論] 期刊論文

    Files in This Item:

    File Description SizeFormat
    63-3.pdf648KbAdobe PDF310View/Open


    All items in 政大典藏 are protected by copyright, with all rights reserved.


    社群 sharing

    著作權政策宣告
    1.本網站之數位內容為國立政治大學所收錄之機構典藏,無償提供學術研究與公眾教育等公益性使用,惟仍請適度,合理使用本網站之內容,以尊重著作權人之權益。商業上之利用,則請先取得著作權人之授權。
    2.本網站之製作,已盡力防止侵害著作權人之權益,如仍發現本網站之數位內容有侵害著作權人權益情事者,請權利人通知本網站維護人員(nccur@nccu.edu.tw),維護人員將立即採取移除該數位著作等補救措施。
    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - Feedback