Determinants of Adoption of Computer Assisted Auditing Techniques: A Survey of Auditors in Kano State, Nigeria

Authors

  • Hauwa Alfa Mohammed Bayero University Kano image/svg+xml
  • Najaatu Bala Rabiu Department of Accounting, Bayero University, Kano, Nigeria
  • Ibrahim Magaji Barde Department of Accounting, Bayero University, Kano, Nigeria

DOI:

https://doi.org/10.33003/fujafr-2023.v1i3.72.146-161

Keywords:

Computer Assisted Auditing Techniques, Performance Expectancy, Effort Expectancy, Facilitating Condition, Social Influence

Abstract

Computer assisted auditing techniques (CAATs) have been identified as a necessary and sufficient conditions for an effective and qualitative audit report. This study analyzed the determinants of adoption of computer assisted auditing techniques with focus on auditors practicing in Kano, Nigeria. The study adopted survey method where 125 auditors were sampled from seventeen audit firms through a multi-stage sampling technique. The data was analyzed using econometric methods (Ordered Logit Regression) in line with the Unified Theory of Acceptance and Use of Technology (UTAUT). Performance expectancy and effort expectancy were found to be statistically significant determinants of auditors’ total intention to CAATs adoption and usage. However, facilitating condition and social influence were not significant in explaining the auditor’s total intention to CAATs adoption and usage. The study recommends that, audit firms should invest in technological tools and train auditors on computer tools. Also, the regulatory bodies should consider computer proficiency as part of the regulatory checks. This adoption and usage of CAATs will help the auditors to produce an effective and qualitative audit report.

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31-12-2023

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Mohammed, H. A., Rabiu, N. B., & Barde, I. M. (2023). Determinants of Adoption of Computer Assisted Auditing Techniques: A Survey of Auditors in Kano State, Nigeria. FUDMA Journal of Accounting and Finance Research [FUJAFR], 1(3), 146-161. https://doi.org/10.33003/fujafr-2023.v1i3.72.146-161

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