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The Convergence of Big Data and Accounting


Special issue call for papers from Accounting Research Journal

Deadlines

  • Submission deadline: 15/02/2020
  • Acceptance deadline: 15/07/2020 (5 months from the last submission)
  • Planned publication = Late 2020

Background to issue

Big Data and smart devices have invaded business, academia, and personal lives. Trillions of Gigabytes of data are created every day around the world. The Internet-of-Things (IoT) and machine learning are likely to create unprecedented amount of data in different formats. The traditional data analytics and information systems will not have the capacity to respond. Big Data is a resource for those who know how to use properly.

Data is the heart of Accounting. Accountants need data to provide financial reporting, assess and manage risks, measure the performance, prepare corporate budgets, and to apply the activity-based techniques. Big Data technology arguably assists auditors to increase the audit assurance level. Some accounting techniques may suffer from data limitations or inaccurate predictions and estimations, such as ABC, Corporate Budgeting, and risk measurement. The Big Data predictive analytics could increase the accuracy of these techniques. The big question is how Big Data could improve the outcomes of these accounting techniques?
A significant convergence is evident between Big Data technology and different accounting techniques, since accounting is a data processing. The main objective of this special issue is to address the potential convergence between Big Data and Accounting and Auditing and discuss how Big Data will reshape Accounting profession, education, and standards.   

The potential submissions may address questions that include, but are not restricted to:

  • How could Big Data improve the Financial Reporting Quality?
  • How could Big Data improve the accuracy of performance measurement techniques, such as Balanced-scorecard?
  • How could Big Data increase the audit quality, the assurance level, and the reliability and the sufficiency of audit evidence?
  • How could Big Data improve the effectiveness of risk measurement and management?
  • How could Big Data improve the prediction and accuracy of corporate budgeting?
  • How could Big Data help avoid the drawbacks of Activity-based techniques?
  • How could Big Data change the different accounting theories such as agency theory, Stakeholders’ theory, and Legitimacy theory?
  • Does Big Data require unique data governance rules?

Special Issue Editors.

Dr. Awad Ibrahim, Senior Lecturer, Portsmouth Business School, Portsmouth University, United Kingdom
Awad.ibrahim@port.ac.uk
Prof. Khaled Hussainey, Professor of Accounting, Portsmouth Business School, Portsmouth University, United Kingdom, Khaled.hussainey@port.ac.uk

 

References

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2.    Alles, M. G. 2015. Drivers of the Use and Facilitators and Obstacles of the Evolution of Big Data by the Audit Profession. Accounting Horizons 29 (2):439-449.

3.    Alles, M., and G. L. Gray. 2016. Incorporating big data in audits: identifying inhibitors and a research agenda to address those inhibitors. Int. J. of Accounting Information Systems 22: 44-59.

4.    Appelbaum, D. 2016. Securing Big Data Provenance for Auditors: The Big Data Provenance Black Box as Reliable Evidence. Journal of Emerging Technologies in Accounting 13 (1):17-36.

5.    Appelbaum, D. A., A. Kogan., and M. A. Vasarhelyi. 2017. Big Data and Analytics in the modern audit engagement: Research needs. Auditing: A Journal of Practice & Theory 36 (4): 1-27. 

6.    Appelbaum, D. A., A. Kogan., and M. A. Vasarhelyi. 2018. Analytical procedures in external auditing: a comprehensive literature survey and framework for external audit analytics. Journal of Accounting Literature 40: 83-101.

7.    Arnaboldi, M., C. Busco., and S. Cuganesan. 2017. Accounting, Accountability, social media and Big Data: a revolution or hype? Accounting, Auditing & Accountability Journal 30 (4): 762-776.

8.    Baesens, B., V. V, Vlasselaer, and W. Verbeke. 2015. Fraud Analytics: Using Descriptive, Predictive, and Social Network Techniques. John Wiley & Sons Ltd, United Kingdom.

9.    Brown-Liburd, H., H. Issa, and D. Lombardi. 2015. Behavioural Implications of Big Data's Impact on Audit Judgment and Decision Making and Future Research Directions. Accounting Horizons 29 (2):451-468.

10.    Brown-Liburd, H., and M. A. Vasarhelyi. 2015. Big Data and Audit Evidence.  Journal of Emerging Technologies in Accounting 12 (1):1-16.

11.    Cao, M., R. Chychyla, and T. Stewart. 2015. Big Data Analytics in Financial Statement Audits. Accounting Horizons 29(2): 423-429.

12.    Chen, D. Q., D. S. Preston, and M. Swink. 2015. How the Use of Big Data Analytics Affects Value Creation in Supply Chain Management. Journal of Management Information Systems 32 (4):4-39.

13.    Enget, K., G. D. Saucedo., and N. S. Wright. 2017. Mystery, Inc.: A Big Data case. Journal of Accounting Education 38: 9-22.

14.    Fay, R., Eric, M., and Negangard. 2017. Manual journal entry testing: data analytics and the risk of fraud. Journal of Accounting Education 38: 37-49.

15.    Gepp, A., M. K., Linnenluecke., T. J., O’Neill., and T. Smith. 2018. Big Data Techniques in auditing research and practice: current trends and future opportunities. Journal of Accounting Literature 40: 102-115.

16.    Janvrin, D. J., and M. W. Watson. 2017. Big Data: A new twist to accounting. Journal of Accounting Education 38, 3-8.

17.    Jr, E. M., C. J. Yoos., and K. Snead. 2017. The need for skeptical accountants in the era of Big Data. Journal of Accounting Education 38: 63-80.

18.    Kokina, J., D. Pachamanova, and A. Corbett. 2017. The role of data visualisation and analytics in performance management: guiding entrepreneurial growth decisions. Journal of Accounting Education 38: 50-62.

19.    Krahel, J. P., and W. R. Titera. 2015. Consequences of Big Data and Formalization on Accounting and Auditing Standards.  Accounting Horizons 29 (2):409-422.

20.    Marr, B. 2016. Big Data in Practice: How 45 Successful Companies used Big Data Analytics to Deliver Extraordinary Results. John Wiley & Sons Ltd, United Kingdom.

21.    Riggins, F. J., and B. K. Klamm. 2017. Data governance case at Krause McMahon LLP in an era of self-service BI and Big Data. Journal of Accounting Education 38: 23-36.

22.    Vasarhelyi, M. A., A. Kogan., and B. M. Tuttle. 2015. Big Data in Accounting: An Overview. Accounting Horizons 29 (2):381-396.

23.    Warren, J. D., K. C. Moffitt, and P. Byrnes. 2015. How Big Data Will Change Accounting.  Accounting Horizons 29 (2):397-407.

24.    Xu, Z., G. L. Frankwick, and E. Ramirez. 2016. Effects of big data analytics and traditional marketing analytics on new product success: A knowledge fusion perspective.  Journal of Business Research 69 (5):1562-1566.

25.    Yoon, K., L. Hoogduin, and L. Zhang. 2015. Big Data as Complementary Audit Evidence.  Accounting Horizons 29 (2):431-438.

26.    Zhang, J., X. Yang, and D. Appelbaum. 2015. Toward Effective Big Data Analysis in Continuous Auditing.  Accounting Horizons 29 (2):469-476.