Public Interest and Audit Innovation: Investigating Technology Use among Internal Auditors in Malaysia

Authors

Aishah binti Habibullah

Oriental Melaka Straits Medical Centre, Pusat Perubatan Klebang, 75200 Melaka (Malaysia)

Aida Hazlin Ismail

Faculty of Accountancy, Universiti Teknologi MARA Cawangan Selangor, Puncak Alam (Malaysia)

Hazlina Hassan

Faculty of Accountancy, Universiti Teknologi MARA Cawangan Selangor, Puncak Alam (Malaysia)

Article Information

DOI: 10.51244/IJRSI.2026.1315PH00029

Subject Category: Accounting

Volume/Issue: 13/15 | Page No: 1463-1474

Publication Timeline

Submitted: 2025-09-05

Accepted: 2025-09-11

Published: 2026-02-13

Abstract

This study investigates how internal auditors’ attributes influence technology adoption among internal auditors in Malaysia. Specifically, it examines the role of perceived benefits, technological challenges, and ease of use in shaping adoption behaviors, using the Technology Acceptance Model (TAM) as the theoretical foundation. A quantitative survey was conducted involving 87 internal auditors from listed companies in Malaysia. Descriptive statistics were used to assess the levels of technology adoption and the independent variables. Correlation analysis identified relationships among variables, while multiple regression analysis evaluated the effects of perceived benefits, technological challenges, and ease of use on technology adoption. The results indicate that perceived benefits and ease of use significantly influence technology adoption among internal auditors. However, technological challenges did not show a significant relationship. These findings highlight the importance of user perceptions and system usability in promoting successful technology adoption. The study’s findings are limited by the sample size and response rate, as not all registered internal auditors in Malaysia were included due to time constraints and non-responses. This limits the generalizability of the results. Organizations should emphasize the practical benefits and user-friendliness of technologies to increase adoption among internal auditors. Tailored training and support may further reduce resistance and enhance implementation success. This study contributes to the limited body of research on internal auditors and technology adoption in Malaysia. It provides a practical framework for understanding the key factors influencing technology acceptance within the internal audit profession.

Keywords

Technology Adoption, Internal Auditors, Technology Acceptance Model (TAM), Perceived Benefits, Ease of Use, and Technological Challenges

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References

1. AuditNet. (2012). Questionnaire of More Than 1,500 Auditors Concludes That Audit Professionals Are Not Maximizing Use of Available Audit Technology. http://www.auditnet.org/publications/auditnet-news-november-2012/auditnet-2012-state-of-technology-use-by-auditors-questionnaire-of-more-than-1500 auditorsconcludes-that-audit-professionals-are-not-maximizing-use-of-available-audit-technology [Google Scholar] [Crossref]

2. Bélanger, F., & Carter, L. (2008). Trust and risk in e-government adoption. The journal of strategic information systems, 17(2), 165-176. [Google Scholar] [Crossref]

3. Brynjolfsson, E., & McAfee, A. (2017). Machine, platform, crowd: Harnessing our digital future. WW New York: Norton & Company. [Google Scholar] [Crossref]

4. Brynjolfsson, E., & McAfee, A. (2014). The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies. W. W. Norton & Company. [Google Scholar] [Crossref]

5. Bolodeoku, P. B., Igbinoba, E., Salau, P. O., Chukwudi, C. K., & Idia, S. E. (2022). Perceived usefulness of technology and multiple salient outcomes: The improbable case of oil and gas workers. Heliyon, 8(9), e09322. https://doi.org/10.1016/j.heliyon.2022.e09322 [Google Scholar] [Crossref]

6. Chan, D. Y., Mo, P. L., & Tang, M. C. (2018). Exploring the Influence of Technology Adoption on Internal Audit Efficiency. Journal of Finance and Accounting, 6(3), 103-110. [Google Scholar] [Crossref]

7. DeZoort, F. T., & Harrison, P. D. (2016). Understanding auditors’ sense of responsibility for detecting fraud within organizations. Journal of business ethics, 149(4), 857-874. [Google Scholar] [Crossref]

8. Eulerich, M., Masli, A., Pickerd, J., & Wood, D. A. (2023). The Impact of Audit Technology on Audit Task Outcomes: Evidence for Technology‐Based Audit Techniques. Contemporary Accounting Research, 40(2), 981-1012. https://doi.org/10.1111/1911-3846.12847 [Google Scholar] [Crossref]

9. EY. (2014). Big Risks Require Big Data Thinking - Global Forensic Data Analytics Questionnaire(2014).http://www.ey.com/Publication/vwLUAssets/EY-GlobalForensic- Data-Analytics- Questionnaire-2014/$FILE/EY-Global-Forensic-Data-Analytics-Questionnaire- 2014.pdf [Google Scholar] [Crossref]

10. Fettry, S., Anindita, T., Wikansari, R., & Sunaryo, K. (2019). The future of accountancy profession in the digital era. In Abdullah, A. G., Widiaty, I., & Abdullah, C. U. (Eds.), Global Competitiveness: Business Transformation in the Digital Era (pp. 8-14). Routledge. [Google Scholar] [Crossref]

11. Fadzil, F., Ahmad, A., & Nasir, M. (2018). Examining the Influence of Perceived Benefits on Technology Adoption: The Case of Internal Auditors in Malaysia. Journal of Accounting and Finance in Emerging Economies, 4(2), 32-45. [Google Scholar] [Crossref]

12. Green, S. B. (1991). How many subjects does it take to do a regression analysis. Multivariate behavioral research, 26(3), 499-510. [Google Scholar] [Crossref]

13. Hair Jr, J. F., Matthews, L. M., Matthews, R. L., & Sarstedt, M. (2017). PLS-SEM or CB-SEM: updated guidelines on which method to use. International Journal of Multivariate Data Analysis, 1(2), 107-123. [Google Scholar] [Crossref]

14. Ibrahim, S. N. S., Shamsudin, A., Abdullah, S., Ibrahim, M. T., Jaaffar, M. Y., & Bani, H. (2021). Content Analysis of Voluntary Disclosures on Cybersecurity in Malaysia. International Journal of Academic Research in Accounting Finance and Management Sciences, 11(4), 10–28. https://doi.org/10.6007/ijarafms/v11-i4/11346 [Google Scholar] [Crossref]

15. Jollay, A. (2023). New Skills in Auditing: Embracing Emerging Technology in the Audit Profession (Doctoral dissertation, University Honors College, Middle Tennessee State University). [Google Scholar] [Crossref]

16. Khan, Nawsher, Yaqoob, Ibrar, Hashem, Ibrahim Abaker Targio, Inayat, Zakira, Mahmoud Ali, Waleed Kamaleldin, Alam, Muhammad, Shiraz, Muhammad, Gani, Abdullah, Big Data: Survey, Technologies, Opportunities, and Challenges, The Scientific World Journal, 2014, 712826, 18 pages, 2014. https://doi.org/10.1155/2014/712826 [Google Scholar] [Crossref]

17. KPMG. (2015). Questionnaire - Data and Analytics-enabled Internal Audit. http://www.kpmg.com/ZA/en/IssuesAndInsights/ArticlesPublications/RiskCompliance/Documents/DA%20Enabled%20Internal%20Audit%20Questionnaire.pdf [Google Scholar] [Crossref]

18. Information Technology Adoption By Internal Auditors In Public Sector: Antesedents And Consequences, SMAA Koesanto, F Husnatarina, Rahmaddian, F Madya Jurnal Organisasi dan Manajemen 17 (2), 217-233. [Google Scholar] [Crossref]

19. Loock, C., Staake, T., & Thiesse, F. (2013).Motivating Energy-Efficient Behavior with Green IS: An Investigation of Goal Setting and the Role of Defaults. MIS Quarterly, 37(4), 1313–1332. [Google Scholar] [Crossref]

20. Lee, M. (2017). Internal Audit Practices in Malaysia, Kuala Lumpur, Malaysia: Pearson/Prentice Hall. [Google Scholar] [Crossref]

21. Markus, M. L., & Tanis, C. (2000). The enterprise systems experience-from adoption to success. Framing the domains of IT research: Glimpsing the future through the past, 173(2000), 207-173. [Google Scholar] [Crossref]

22. Mitchell, A. (2023). Collaboration technology affordances from virtual collaboration in the time of COVID-19 and post-pandemic strategies. Information Technology & People, 36(5), 1982-2008. [Google Scholar] [Crossref]

23. Moore, G. C., & Benbasat, I. (1991). Development of an instrument to measure the perceptions of adopting an information technology innovation. Information systems research, 2(3), 192-222. [Google Scholar] [Crossref]

24. PWC. (2012). Data Analytics How Data Analytics Can Help Internal Audit Better Understand. Risk.https://www.pwc.com/en_US/us/industry/utilities/publications/assets/pwc-utility-company-internal-audit-data-analytics.pdf [Google Scholar] [Crossref]

25. Pathak, J. and Lind, M. (2010), “An e-business audit service model in the B2B context”. Information Systems Management, Vol. 27 No. 2, pp. 146-155 [Google Scholar] [Crossref]

26. Perić, M. a. (2015). Understanding the delivery of experience: conceptualising business modelsandsportstourism,assessingtwocasestudiesinIstria,Croatia. LocalEconomy, Vol.30 No. 8, pp. 1000-1016. [Google Scholar] [Crossref]

27. Rosli, K., Yeow, P. H., & Siew, E. G. (2012). Factors influencing audit technology acceptance by audit firms: A new I-TOE adoption framework. Journal of Accounting and Auditing, 2012, 1. [Google Scholar] [Crossref]

28. Sarens, G., & De Beelde, I. (2006). Internal auditors’ perceptions about their changing role: The impact of ERP systems. International Journal of Auditing, 10(1), 59-79. [Google Scholar] [Crossref]

29. Syed Ibrahim, S. N., Khaidzi, N. A., & Arshad, Y. (2023). Information Technology Governance Mechanisms and Audit Technology Performance in Malaysia. European Proceedings of Finance and Economics. [Google Scholar] [Crossref]

30. Singh, K., & Best, P. (2023). Auditing during a pandemic–can continuous controls monitoring (CCM) address challenges facing internal audit departments?. Pacific Accounting Review, 35(5), 727-745. [Google Scholar] [Crossref]

31. Thottoli M. M., Essia Ries Ahmed; Information technology and E-accounting: some determinants among SMEs. Journal of Money and Business 31 May 2022; 2 (1): 1–15. https://doi.org/10.1108/JMB-05-2021-0018 [Google Scholar] [Crossref]

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