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Relevance of big data to forensic accounting practice and education

Author

Listed:
  • Zabihollah Rezaee
  • Jim Wang

Abstract

Purpose - This paper aims to examine the relevance of Big Data to forensic accounting practice and education by gathering opinions from a sample of academics and practitioners in China. Design/methodology/approach - The authors conduct a survey of academics and practitioners regarding the desired demand, importance and content of Big Data educational skills and topics for forensic accounting education to effectively respond to challenges and opportunities in the age of Big Data. Findings - Results indicate that the demand for and interest in Big Data/data analytics and forensic accounting will continue to increase; Big Data/data analytics and forensic accounting should be integrated into the business curriculum; many of the suggested Big Data topics should be integrated into forensic accounting education; and some attributes and techniques of Big Data are important in improving forensic accounting education and practice. Research limitations/implications - Readers should interpret the results with caution because of the sample size (95 academics and 103 practitioners) and responses obtained from academics and practitioners in one country (China) that may not be representative of the global population. Practical implications - The results are useful in integrating Big Data topics into the forensic accounting curriculum and in redesigning the forensic accounting courses/programs. Social implications - The results have implications for forensic accountants in effectively fulfilling their responsibilities to their profession and society by combating fraud. Originality/value - This study provides educational, research and practical implications as Big Data and forensic accounting are advancing.

Suggested Citation

  • Zabihollah Rezaee & Jim Wang, 2018. "Relevance of big data to forensic accounting practice and education," Managerial Auditing Journal, Emerald Group Publishing Limited, vol. 34(3), pages 268-288, October.
  • Handle: RePEc:eme:majpps:maj-08-2017-1633
    DOI: 10.1108/MAJ-08-2017-1633
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    Citations

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    Cited by:

    1. Johan Arifin, 2022. "Determinants of the effectiveness of audit procedures in revealing fraud: An attribution theory approach," International Journal of Research in Business and Social Science (2147-4478), Center for the Strategic Studies in Business and Finance, vol. 11(6), pages 378-387, September.
    2. Kanyarat (Lek) Sanoran & Jomsurang Ruangprapun, 2023. "Initial Implementation of Data Analytics and Audit Process Management," Sustainability, MDPI, vol. 15(3), pages 1-14, January.
    3. Prabhat Mittal & Amrita Kaur & Pankaj Kumar Gupta, 2021. "The Mediating Role of Big Data to Influence Practitioners to Use Forensic Accounting for Fraud Detection," European Journal of Business Science and Technology, Mendel University in Brno, Faculty of Business and Economics, vol. 7(1), pages 47-58.
    4. Francis Aboagye‐Otchere & Cletus Agyenim‐Boateng & Abdulai Enusah & Theodora Ekua Aryee, 2021. "A Review of Big Data Research in Accounting," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 28(4), pages 268-283, October.
    5. Yang, Chih-Hao & Lee, Kuen-Chang, 2020. "Developing a strategy map for forensic accounting with fraud risk management: An integrated balanced scorecard-based decision model," Evaluation and Program Planning, Elsevier, vol. 80(C).

    More about this item

    Keywords

    Big data; Big data analytics; Business curriculum; Forensic accounting education and practice; M40; M41; M42;
    All these keywords.

    JEL classification:

    • M40 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Accounting - - - General
    • M41 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Accounting - - - Accounting
    • M42 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Accounting - - - Auditing

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