The artificial intelligence in auditing: Corporate behaviour and technological adoption in an emerging market

The objective of this research is to offer an empirically grounded assessment of the intention of the auditing profession to adopt "disruptive" technologies. This study investigates, using data collected from employees of the Big Four firms in Tunisia, the determinants that drive auditors to adopt blockchain technology (BT). To achieve this objective, in 2022, 53 auditors from the "big four" enterprises in Tunisia, including both certified auditors and auditing students in training, participated in a survey. The study employs statistical methods and ordinary least squares (OLS) regression to identify the associations between the intention to implement BT and the five variables under investigation. The study examines perceived utility, ease of use, trust, support cost (SC), and facilitating condition (FC) while drawing on a number of theories, including the Technology Acceptance Model (TAM). Results show that two factors, particularly perceived utility for auditing (PUA) practice and trust, drive auditing professionals' intention among Big Four companies to use BT. This study results illuminate the factors motivating Big Four companies to embrace BT, enabling the development of strategies to expedite the adoption and utilization of this technology in developing accounting and auditing firms. The study fills a gap in the literature about adopting BT in emerging economies by concentrating on this specific setting. This study contributes to the knowledge of technology adoption and provides valuable recommendations for accelerating the uptake and application of BT in this particular setting.

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Publication Details

Journal
International Journal of Applied Economics Finance and Accounting
Published
2024-10-25
DOI
https://doi.org/10.33094/ijaefa.v20i2.1953
Citations
2
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
1.06

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article

The artificial intelligence in auditing: Corporate behaviour and technological adoption in an emerging market

Ines Bouaziz Daoud, Ameni Mhiri Rekik
2 citations
International Journal of Applied Economics Finance and Accounting
Big Data and Business Intelligence
1.06
article

The artificial intelligence in auditing: Corporate behaviour and technological adoption in an emerging market

Ines Bouaziz Daoud, Ameni Mhiri Rekik
article en
2 citations

Abstract

The objective of this research is to offer an empirically grounded assessment of the intention of the auditing profession to adopt "disruptive" technologies. This study investigates, using data collected from employees of the Big Four firms in Tunisia, the determinants that drive auditors to adopt blockchain technology (BT). To achieve this objective, in 2022, 53 auditors from the "big four" enterprises in Tunisia, including both certified auditors and auditing students in training, participated in a survey. The study employs statistical methods and ordinary least squares (OLS) regression to identify the associations between the intention to implement BT and the five variables under investigation. The study examines perceived utility, ease of use, trust, support cost (SC), and facilitating condition (FC) while drawing on a number of theories, including the Technology Acceptance Model (TAM). Results show that two factors, particularly perceived utility for auditing (PUA) practice and trust, drive auditing professionals' intention among Big Four companies to use BT. This study results illuminate the factors motivating Big Four companies to embrace BT, enabling the development of strategies to expedite the adoption and utilization of this technology in developing accounting and auditing firms. The study fills a gap in the literature about adopting BT in emerging economies by concentrating on this specific setting. This study contributes to the knowledge of technology adoption and provides valuable recommendations for accelerating the uptake and application of BT in this particular setting.

International Journal of Applied Economics Finance and AccountingVol. 20(2)
University of Sfax (TN)
Université de Sfax
Openalex Percentile: Top 16%
Big Data and Business Intelligence
1.06
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