Introduction: Analytics in Accounting and Auditing

Tarek Rana (), Jan Svanberg (), Peter Öhman () and Alan Lowe ()
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Tarek Rana: RMIT University
Jan Svanberg: Gävle University and Centre for Research on Economic Relations
Peter Öhman: Mid Sweden University
Alan Lowe: RMIT University

Chapter Chapter 1 in Handbook of Big Data and Analytics in Accounting and Auditing, 2023, pp 1-13 from Springer

Abstract: 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.

Keywords: Big data; Analytics; Artificial intelligence; Machine learning; Digital economy; Accounting; Auditing (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-981-19-4460-4_1

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DOI: 10.1007/978-981-19-4460-4_1

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