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Introduction: Analytics in Accounting and Auditing

In: Handbook of Big Data and Analytics in Accounting and Auditing

Author

Listed:
  • Tarek Rana

    (RMIT University)

  • Jan Svanberg

    (Gävle University and Centre for Research on Economic Relations)

  • Peter Öhman

    (Mid Sweden University)

  • Alan Lowe

    (RMIT University)

Abstract

Big data and analytics offer new opportunities and challenges for academics and practitioners in all business disciplines including accounting and auditing. In the backdrop of increasing growth of emerging technologies, the organizations in public, private and not-for-profit sectors are embracing digital economy and the fourth industrial revolution journey. This requires knowledge of better practice examples, lessons learned and future directions in addressing the new challenges and seizing new opportunities. In this chapter, we discuss the implications of data analytics, artificial intelligence and machine learning on the accounting and auditing practices. We focus on the technological, social, political, economic, institutional, and behavioral aspects of these technologies in the public, private, non-governmental and hybrid contexts. We present state-of-the-art research directions on philosophical, theoretical, methodological, and practical issues, new developments and innovations of big data, analytics, artificial intelligence, machine learning, blockchain, cryptocurrencies and other emerging technologies related to accounting and auditing.

Suggested Citation

  • Tarek Rana & Jan Svanberg & Peter Öhman & Alan Lowe, 2023. "Introduction: Analytics in Accounting and Auditing," Springer Books, in: Tarek Rana & Jan Svanberg & Peter Öhman & Alan Lowe (ed.), Handbook of Big Data and Analytics in Accounting and Auditing, chapter 0, pages 1-13, Springer.
    • Handle: RePEc:spr:sprchp:978-981-19-4460-4_1
    DOI: 10.1007/978-981-19-4460-4_1
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