IDEAS home Printed from https://ideas.repec.org/a/eee/ijoais/v12y2011i2p126-135.html
   My bibliography  Save this article

An introduction to evidential reasoning for decision making under uncertainty: Bayesian and belief function perspectives

Author

Listed:
  • Srivastava, Rajendra P.

Abstract

The main purpose of this article is to introduce the evidential reasoning approach, a research methodology, for decision making under uncertainty. Bayesian framework and Dempster–Shafer theory of belief functions are used to model uncertainties in the decision problem. We first introduce the basics of the DS theory and then discuss the evidential reasoning approach and related concepts. Next, we demonstrate how specific decision models can be developed from the basic evidential diagrams under the two frameworks. It is interesting to note that it is quite efficient to develop Bayesian models of the decision problems using the evidential reasoning approach compared to using the ladder diagram approach as used in the auditing literature. In addition, we compare the decision models developed in this paper with similar models developed in the literature.

Suggested Citation

  • Srivastava, Rajendra P., 2011. "An introduction to evidential reasoning for decision making under uncertainty: Bayesian and belief function perspectives," International Journal of Accounting Information Systems, Elsevier, vol. 12(2), pages 126-135.
    • Handle: RePEc:eee:ijoais:v:12:y:2011:i:2:p:126-135
    DOI: 10.1016/j.accinf.2010.12.003
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1467089510000904
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.accinf.2010.12.003?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Rajendra P. Srivastava & Theodore J. Mock & Jerry L. Turner, 2009. "Bayesian Fraud Risk Formula for Financial Statement Audits," Abacus, Accounting Foundation, University of Sydney, vol. 45(1), pages 66-87, March.
    2. Mock, Theodore J. & Sun, Lili & Srivastava, Rajendra P. & Vasarhelyi, Miklos, 2009. "An evidential reasoning approach to Sarbanes-Oxley mandated internal control risk assessment," International Journal of Accounting Information Systems, Elsevier, vol. 10(2), pages 65-78.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Adi Masli & Matthew G. Sherwood & Rajendra P. Srivastava, 2018. "Attributes and Structure of an Effective Board of Directors: A Theoretical Investigation," Abacus, Accounting Foundation, University of Sydney, vol. 54(4), pages 485-523, December.
    2. Desai, Vikram & Bucaro, Anthony C. & Kim, Joung W. & Srivastava, Rajendra & Desai, Renu, 2023. "Toward a better expert system for auditor going concern opinions using Bayesian network inflation factors," International Journal of Accounting Information Systems, Elsevier, vol. 49(C).
    3. Shi Qiu & Yuansheng Luo & Hongwei Guo, 2021. "Multisource evidence theory‐based fraud risk assessment of China's listed companies," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(8), pages 1524-1539, December.
    4. Hironori Fukukawa & Theodore J. Mock & Rajendra P. Srivastava, 2014. "Assessing the Risk of Fraud at Olympus and Identifying an Effective Audit Plan," The Japanese Accounting Review, Research Institute for Economics & Business Administration, Kobe University, vol. 4, pages 1-25, December.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Adi Masli & Matthew G. Sherwood & Rajendra P. Srivastava, 2018. "Attributes and Structure of an Effective Board of Directors: A Theoretical Investigation," Abacus, Accounting Foundation, University of Sydney, vol. 54(4), pages 485-523, December.
    2. Caplan, Dennis & Dutta, Saurav K., 2016. "Managing the risk of misleading financial metrics in annual reports: A first step towards providing assurance over management's discussion," Journal of Accounting Literature, Elsevier, vol. 36(C), pages 1-27.
    3. Heise, David & Strecker, Stefan & Frank, Ulrich, 2014. "ControlML: A domain-specific modeling language in support of assessing internal controls and the internal control system," International Journal of Accounting Information Systems, Elsevier, vol. 15(3), pages 224-245.
    4. Jans, Mieke & Lybaert, Nadine & Vanhoof, Koen, 2010. "Internal fraud risk reduction: Results of a data mining case study," International Journal of Accounting Information Systems, Elsevier, vol. 11(1), pages 17-41.
    5. Arzhenovskiy S.V. & Bakhteev A.V. & Sinyavskaya T.G. & Hahonova N.N., 2019. "Audit Risk Assessment Model," International Journal of Economics & Business Administration (IJEBA), International Journal of Economics & Business Administration (IJEBA), vol. 0(Special 1), pages 74-85.
    6. Dennis M. Lopez & Pamela C. Smith, 2010. "Auditor Type and Audit Quality Differences in Nonprofit Healthcare Organizations – U.S. Evidence," Working Papers 0107, College of Business, University of Texas at San Antonio.
    7. Abernathy, John L. & Barnes, Michael & Stefaniak, Chad, 2013. "A summary of 10 years of PCAOB research: What have we learned?," Journal of Accounting Literature, Elsevier, vol. 32(1), pages 30-60.
    8. Shaio Yan Huang & Chi-Chen Lin & An-An Chiu & David C. Yen, 2017. "Fraud detection using fraud triangle risk factors," Information Systems Frontiers, Springer, vol. 19(6), pages 1343-1356, December.
    9. Dieter De Smet & Anne-Laure Mention, 2011. "Improving auditor effectiveness in assessing KYC/AML practices: Case study in a Luxembourgish context," Managerial Auditing Journal, Emerald Group Publishing, vol. 26(2), pages 182-203, January.
    10. Shaio Yan Huang & Chi-Chen Lin & An-An Chiu & David C. Yen, 0. "Fraud detection using fraud triangle risk factors," Information Systems Frontiers, Springer, vol. 0, pages 1-14.
    11. Tjiptogoro Dinarjo Soehari & Iffah Budiningsih, 2020. "Model of Bureaucratic Corruption Prevention," International Journal of Asian Social Science, Asian Economic and Social Society, vol. 10(10), pages 638-646, October.
    12. Hironori Fukukawa & Theodore J. Mock & Rajendra P. Srivastava, 2014. "Assessing the Risk of Fraud at Olympus and Identifying an Effective Audit Plan," The Japanese Accounting Review, Research Institute for Economics & Business Administration, Kobe University, vol. 4, pages 1-25, December.
    13. Muhammad Azizul Islam, 2014. "Bribery and corruption in Australian local councils," Public Money & Management, Taylor & Francis Journals, vol. 34(6), pages 441-446, November.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ijoais:v:12:y:2011:i:2:p:126-135. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/international-journal-of-accounting-information-systems/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.