TECHNOLOGY READINESS AND ACCEPTANCE PREDICT TAX AUDITORS’ DIGITAL ADOPTION

Asqolani Asqolani; Agus Praises Priyono

doi:10.37641/riset.v7i2.2684

Authors

Asqolani Asqolani Polytechnic of State Finance STAN
Agus Praises Priyono Directorate General of Taxes

DOI:

https://doi.org/10.37641/riset.v7i2.2684

Keywords:

Computer Assisted Audit Techniques (CAATs), Technology Readiness Index (TRI), Tax Auditors, Technology Acceptance Model (TAM)

Abstract

In recent developments, incorporating digital technologies into auditing practices has accelerated, notably through the widespread use of Computer-Assisted Audit Tools and Techniques (CAATs). However, the readiness of tax auditors to embrace these innovations varies considerably, shaped by individual psychological traits and attitudes toward technology. This study investigates how tax auditors’ technology readiness influences their perceptions and acceptance of CAATs within the Coretax implementation by the Directorate General of Taxes (DGT). This study combines the Technology Readiness Index (TRI) 2.0 with the Technology Acceptance Model (TAM) framework. Empirical data were obtained from 85 tax auditors across 13 offices within the DGT Banten area and examined using Partial Least Squares Structural Equation Modeling (PLS-SEM). The findings indicate that optimism significantly and positively influences perceived usefulness and ease of use. These perceptions subsequently play a crucial role in shaping the behavioral intention to implement CAATs. The study suggests that enhancing auditors' confidence and positive outlook toward technology adoption can foster greater acceptance of audit digitization tools. This research adds to the scarce body of empirical studies that merge TRI and TAM frameworks in public sector contexts, providing actionable perspectives on digital transformation in tax audit settings.

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References

Al-Adwan, A. S., Li, N., Al-Adwan, A., Abbasi, G. A., Albelbisi, N. A., & Habibi, A. (2023). Extending the Technology Acceptance Model (TAM) to Predict University Students’ Intentions to Use Metaverse-Based Learning Platforms. Education and Information Technologies, 28(11), 15381–15413. https://doi.org/10.1007/s10639-023-11816-3

Al-Ateeq, B., Sawan, N., Al-Hajaya, K., Altarawneh, M., & Al-Makhadmeh, A. (2022). Big Data Analytics in Auditing and The Consequences for Audit Quality: A Study Using The Technology Acceptance Model (TAM). Corporate Governance and Organizational Behavior Review, 6(1), 64–78. https://doi.org/10.22495/cgobrv6i1p5

Alhasan, K., Alhasan, K., & Al Hashimi, S. (2023). Roblox in Higher Education. International Journal of Emerging Technologies in Learning (IJET), 18(19), 32–46. https://doi.org/10.3991/ijet.v18i19.43133

Ali, I., & Warraich, N. F. (2023). Impact of Personal Innovativeness, Perceived Smartphone Ease of Use and Mobile Self-Efficacy on Smartphone-Based Personal Information Management Practices. The Electronic Library, 41(4), 419–437. https://doi.org/10.1108/EL-12-2022-0262

Alvin, A., & Kurniawati, K. (2019). Analysis of Software Audit Acceptance for External Auditors Using The Technology Acceptance Model (TAM) Approach. Balance Vocation Accounting Journal, 3(2), 1–17. https://doi.org/10.31000/bvaj.v3i2.2236

Bakhri, S. (2025). The Effect of Perceived Ease and Benefits on Intention and Behavior to use E-Learning Islamic Higher Education. Journal of Education Technology, 9(1), 163–171. https://doi.org/10.23887/jet.v9i1.86537

Chairina, R. R. L. (2021). The Effect of Perceived Usefulness and Perceived Ease of Use on Perceived Value and Actual Usage of Technology on The Online Service of PT. Garuda Indonesia Tbk. Journal of Research in Business and Management, 9(4), 59–65. https://sipora.polije.ac.id/4967/

Chao, C.-M. (2019). Factors Determining The Behavioral Intention to Use Mobile Learning: An Application and Extension of The UTAUT Model. Frontiers in Psychology, 10(1652), 1–14. https://doi.org/10.3389/fpsyg.2019.01652

Ciftci, O., Berezina, K., & Kang, M. (2021). Effect of Personal Innovativeness on Technology Adoption in Hospitality and Tourism: Meta-analysis. Information and Communication Technologies in Tourism 2021.

Clark, B. B., Robert, C., & Hampton, S. A. (2016). The Technology Effect: How Perceptions of Technology Drive Excessive Optimism. Journal of Business and Psychology, 31(1), 87–102. https://doi.org/10.1007/s10869-015-9399-4

Creswell, J. W., & Creswell, J. D. (2018). Research Design: Qualitative, Quantitative, and Mixed Methods Approaches (5th ed.). New York: SAGE Publications.

Darussalam, D., & Septriadi, D. (2021). Indonesia Embraces The Next Stage of Tax Digitisation: What Can Be Expected? International Tax Review. https://www.internationaltaxreview.com/article/2a68rfy5bw2ycq1zyexpl/indonesia-embraces-the-next-stage-of-tax-digitisation-what-can-be-expected

Denovan, R. F., & Marsasi, E. G. (2025). Perceived Ease of Use, Perceived Usefulness and Satisfaction to Maximize Behavioral Intention with The Technology Acceptance Model in Generation Y and Z Consumers. Jurnal Pamator : Jurnal Ilmiah Universitas Trunojoyo, 18(1), 1–36. https://doi.org/10.21107/pamator.v18i1.29461

Dimetheo, G., Salsabila, A., & Izaak, N. C. A. (2023). Implementation of The Core Tax Administration System as an Effort to Encourage Tax Compliance in Indonesia. Prosiding Seminar Nasional Ekonomi Dan Perpajakan, 3(1), 10–25.

Elvis, T. E., & Kim, H.-K. (2022). Unified Perspective of Technology Readiness Index (TRI) and Technology Acceptance Model (TAM) for Adoption of Digital Pills. Journal of System and Management Sciences, 12(4), 101–114. https://doi.org/10.33168/JSMS.2022.0407

Gunawan, F., Ali, M. M., & Nugroho, A. (2019). Analysis of The Effects of Perceived Ease of Use and Perceived Usefulness on Consumer Attitude and Their Impacts on Purchase Decision on PT Tokopedia In Jabodetabek. European Journal of Business and Management Research, 4(5), 1–6. https://doi.org/10.24018/ejbmr.2019.4.5.100

Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2022). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM) (3rd ed.). Thousand Oakes: SAGE Publications.

Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to Use and How to Report The Results of PLS-SEM. European Business Review, 31(1), 2–24. https://doi.org/10.1108/EBR-11-2018-0203

Hallikainen, H., & Laukkanen, T. (2016). How Technology Readiness Explains Acceptance and Satisfaction of Digital Services in B2B Healthcare Sector? PACIS 2016 Proceedings. https://aisel.aisnet.org/pacis2016/294

Han, D., Hou, H. (Cynthia), Wu, H., & Lai, J. H. K. (2021). Modelling Tourists’ Acceptance of Hotel Experience-Enhancement Smart Technologies. Sustainability, 13(4462), 1–19. https://doi.org/10.3390/su13084462

Ho, C.-W., & Wu, C.-C. (2021). Exploring Intention toward Using an Electric Scooter: Integrating The Technology Readiness and Acceptance into Norm Activation Model (TRA-NAM). Energies, 14(6895), 1–11. https://doi.org/10.3390/en14216895

Jefferson, J., & Efrata, T. C. (2023). Personal Innovativeness, Perceived Usefulness, Perceived Ease of Use, and Trust Asdeterminants of Mobile Payment Utilization. Review of Management and Entrepreneurship, 7(2), 251–270. https://doi.org/10.37715/rme.v7i2.4157

Jeong, S., Kim, S., & Lee, S. (2025). Effects of Perceived Ease of Use and Perceived Usefulness of Technology Acceptance Model on Intention to Continue Using Generative AI: Focusing on the Mediating Effect of Satisfaction and Moderating Effect of Innovation Resistance. In Advances in Conceptual Modeling (pp. 99–106). Lisbon: Springer Nature Link. https://doi.org/10.1007/978-3-031-75599-6_7

Judijanto, L., Lubis, A. F., Amir, J., & Hidayati, N. (2023). A Bibliometric Analysis of The Development of Research on Environmental Issues and Sustainability in Modern Society’s Built Environment Studies in Indonesia. West Science Social and Humanities Studies, 1(6), 477–486. https://doi.org/10.58812/wsshs.v1i06.519

Khashan, M. A., Alasker, T. H., Ghonim, M. A., & Elsotouhy, M. M. (2025). Understanding Physicians’ Adoption Intentions to Use Electronic Health Record (EHR) Systems in Developing Countries: An Extended TRAM Approach. Marketing Intelligence & Planning, 43(1), 1–27. https://doi.org/10.1108/MIP-05-2023-0225

Lai, Y. L., & Lee, J. (2020). Integration of Technology Readiness Index (TRI) Into the Technology Acceptance Model (TAM) for Explaining Behavior in Adoption of BIM. Asian Education Studies, 5(2), 10–17. https://doi.org/10.20849/aes.v5i2.816

Malatji, W. R., Eck, R. Van, & Zuva, T. (2020). Understanding The usage, Modifications, Limitations and Criticisms of Technology Acceptance Model (TAM). Advances in Science, Technology and Engineering Systems Journal, 5(6), 113–117. https://doi.org/10.25046/aj050612

Malik, H. A. S., Abdullah, N. A. H. N., & Fakhrorazi, A. (2025). Understanding Customer Loyalty in Mobile Wallet Apps: A Post-Pandemic Analysis With Customer Involvement as Moderator. Innovative Marketing, 21(1), 338–349. https://doi.org/10.21511/im.21(1).2025.27

Marikyan, D., Papagiannidis, S., & Alamanos, E. (2023). Cognitive Dissonance in Technology Adoption: A Study of Smart Home Users. Information Systems Frontiers, 25(3), 1101–1123. https://doi.org/10.1007/s10796-020-10042-3

Mayr, A., Stahmann, P., Nebel, M., & Janiesch, C. (2023). Unified Theory of Acceptance and Use of Technology (UTAUT) for Intelligent Process Automation. International Conference on Information Systems, ICIS 2023: “Rising like a Phoenix: Emerging from the Pandemic and Reshaping Human Endeavors with Digital Technologies.”

Nadzari, N. A. M., Yussof, S. H., Isa, K., & Zakaria, Z. (2024). Mapping The Shift to Digital Auditing: Trends and Insights from a Bibliometric Analysis. Labuan Bulletin of International Business and Finance (LBIBF), 22(2), 168–182. https://doi.org/10.51200/lbibf.v22i2.5867

Naeem, M., Jawaid, S. T., & Mustafa, S. (2023). Evolution of Modified TAM Associated with e-Banking Services Adoption: A Systematic PRISMA Review from 1975 to 2021. Journal of Modelling in Management, 18(3), 942–972. https://doi.org/10.1108/JM2-10-2021-0251

Nangin, M. A., Barus, I. R. G., & Wahyoedi, S. (2020). The Effects of Perceived Ease of Use, Security, and Promotion on Trust and Its Implications on Fintech Adoption. Journal of Consumer Sciences, 5(2), 124–138. https://doi.org/10.29244/jcs.5.2.124-138

Nathania, L., Indarini, & Anandya, D. (2021). The Effects of External Factors on Perceived Ease of Use, Perceived Usefulness, Attitude Towards Use, and Behavioral Intention of Older Adults in Indonesia. Proceedings of the 18th International Symposium on Management (INSYMA 2021). https://doi.org/10.2991/aebmr.k.210628.025

Oematan, M. E., Rahayu, S., & Dyah, J. (2024). The Effect of Perceived Usefulness and Perceived Ease of Use on Behavioral Intention Mediated by User Satisfaction in E- Commerce Users. Jurnal Ekonomi, 13(3), 2278–2290.

Parasuraman, A., & Colby, C. L. (2015). An Updated and Streamlined Technology Readiness Index. Journal of Service Research, 18(1), 59–74. https://doi.org/10.1177/1094670514539730

Sarstedt, M., Ringle, C. M., & Hair, J. F. (2021). Partial Least Squares Structural Equation Modeling. In Handbook of Market Research (pp. 587–632). Springer International Publishing. https://doi.org/10.1007/978-3-319-57413-4_15

Su, J., Wang, Y., & Li, Z. (2024). Investigating User Acceptance of Mobile Cultural Applications in China: An Expanded Technology Acceptance Model (TAM). International Journal of Human–Computer Interaction, 1–16. https://doi.org/10.1080/10447318.2024.2406614

Sudirjo, F., Candra Dewi, L. K., Desty Febrian, W., Sani, I., & Dharmawan, D. (2024). The Measurement Analysis of Online Service Quality Toward State Banking Customers Using Structural Equation Modeling. Jurnal Informasi Dan Teknologi, 6(1), 50–56. https://doi.org/10.60083/jidt.v6i1.471

Sumargo, Y., & Indriastuti, H. (2021). The Effect of Perceived of Usefulness, Perceived Ease of Use, and Mindfulness on Attitude and Intention to Use Mobile Banking Maybank Bank (Study on people in Samarinda City). International Journal of Business and Management Invention (IJBMI) ISSN, 10(11), 47–54.

Tesalonika, R., & Wala, G. N. (2025). Study of The Implementation of The 2024 Digital Economy Taxation Law from a Legal Perspective and The Accounting Impact on Indonesian Technology Companies. Dinasti Accounting Review, 2(2), 47–59.

Utami, I., Gill, A., Purnomo, S., Ali, M., Fatama, A., & Salamah, U. (2022). The Role of Readiness Technology Optimism Influences The Use of Mobile Computing Devices Among Students. Proceedings of the 1st Warmadewa International Conference on Science, Technology and Humanity, WICSTH 2021. https://doi.org/10.4108/eai.7-9-2021.2317724

Utaminingsih, F., & Sumiyati. (2024). The Effect of Perceived Usefulness and Pereceived Ease of Use on Trust and Repeat Purchase Interest in Omnichannel Retailling. INOVASI: Jurnal Ekonomi, Keuangan, Dan Manajemen, 20(4), 917–926. https://doi.org/10.30872/jinv.v20i4.2414

Volodina, T., & Grossi, G. (2025). Digital Transformation in Public Sector Auditing: between Hope and Fear. Public Management Review, 27(5), 1444–1468. https://doi.org/10.1080/14719037.2024.2402346

Wang, A., Piao, M., Zhou, Y., Ma, H., Tang, X., Li, S., & Pei, R. (2024). The Acceptance of Using Large Language Model Among Older Adults: A Study Based on TAM. In Innovation in Applied Nursing Informatics (Vol. 35). Amsterdam: IOS Press. https://doi.org/10.3233/SHTI240160

Wong, K. K.-K. (2019). Mastering Partial Least Squares Structural Equation Modeling (PLS-SEM) with SmartPLS in 38 Hours. Bloomington: iUniverse.