Big Data Analytics-Based Audit System Quality And Public Sector Audit Performance: Audit Judgment As Mediator

Authors

  • Hafiez Sofyani Department of Accounting, Universitas Muhammadiyah Yogyakarta, Indonesia
  • Wildan Mujibur Rohman Department of Accounting, Universitas Muhammadiyah Yogyakarta, Indonesia
  • Kanza Della Oktavia Department of Accounting, Universitas Muhammadiyah Yogyakarta, Indonesia
  • Aqilla Nur Efsari Department of Accounting, Universitas Muhammadiyah Yogyakarta, Indonesia

DOI:

https://doi.org/10.22219/jrak.v15i1.36375

Keywords:

Audit Judgment, Audit Performance, Big Data Analytics, Public Sector

Abstract

Purpose: This study examines some hypotheses about the impact of quality of Big Data Analytics (BDA)-based audit system on audit performance in the public sector, focusing on the mediating role of audit judgment.

Methodology/approach: A quantitative method was employed, using primary data from a survey of 137 government auditors across Indonesia. Data were analyzed using Structural Equation Modeling based on Partial Least Squares (SEM-PLS).

Findings: The results show that audit judgment mediates the relationship between the BDA-based audit system's quality and public sector audit performance.

Practical implications: The findings emphasize the need for effective audit judgment to optimize audit technology's role in enhancing the audit performance of government auditors.

Originality/value: This study fills the research gap regarding the inconsistent results on adopting audit technologies and performance, specifically in the public sector.

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Author Biography

Hafiez Sofyani, Department of Accounting, Universitas Muhammadiyah Yogyakarta, Indonesia

Scopus: https://www.scopus.com/authid/detail.uri?authorId=57203309417&eid=2-s2.0-85051163825

Google Scholar ID: https://scholar.google.co.id/citations?user=fbZ4AZ8AAAAJ&hl=en

Sinta: sinta2.ristekdikti.go.id/authors/detail?id=5974288&view=overview

References

Ahmad, F. (2019). A systematic review of the role of Big Data Analytics in reducing the influence of cognitive errors on the audit judgement: Una revisión sistemática del papel del" Big Data Analytics" en la reducción de la influencia de los errores cognitivos en el juicio de auditoría. Revista de Contabilidad-Spanish Accounting Review, 22(2), 187-202.

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.

Al‐Mamary, Y., & Al-Shammari, K. K. (2023). Determining factors that can influence the understanding and acceptance of advanced technologies in universities’ teaching and learning. International Journal of Advanced and Applied Sciences, 10(3), 87-95.

Alles, M., & Gray, G. L. (2024). The marketing on Big 4 websites of Big Data Analytics in the external audit: Evidence and consequences. International Journal of Accounting Information Systems, 54, 100697.

Appelbaum, D., Kogan, A., & Vasarhelyi, M. A. (2017). Big Data and analytics in the modern audit engagement: Research needs. Auditing: A Journal of Practice & Theory, 36(4), 1-27.

Balios, D., Kotsilaras, P., Eriotis, N., & Vasiliou, D. (2020). Big data, data analytics and external auditing. Journal of Modern Accounting and Auditing, 16(5), 211-219.

Bierstaker, J., Janvrin, D., & Lowe, D. J. (2014). What factors influence auditors' use of computer-assisted audit techniques? Advances in Accounting, 30(1), 67-74.

Chin, W. W. (1998). Commentary: Issues and opinion on structural equation modeling. In (pp. vii-xvi): JSTOR.

Chin, W. W., Marcolin, B. L., & Newsted, P. R. (2003). A partial least squares latent variable modeling approach for measuring interaction effects: Results from a Monte Carlo simulation study and an electronic-mail emotion/adoption study. Information systems research, 14(2), 189-217.

Chong, J., & Olesen, K. (2017). A technology-organization-environment perspective on eco-effectiveness: A meta-analysis. Australasian journal of information systems, 21.

Coon, J. J., van Riper, C. J., Morton, L. W., & Miller, J. R. (2020). Evaluating nonresponse bias in survey research conducted in the rural Midwest. Society & Natural Resources, 33(8), 968-986.

Curtis, M. B., & Payne, E. A. (2008). An examination of contextual factors and individual characteristics affecting technology implementation decisions in auditing. International Journal of Accounting Information Systems, 9(2), 104-121.

Dagilienė, L., & Klovienė, L. (2019). Motivation to use big data and big data analytics in external auditing. Managerial Auditing Journal, 34(7), 750-782.

Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of marketing research, 18(1), 39-50.

Gepp, A., Linnenluecke, M. K., O’Neill, T. J., & Smith, T. (2018). Big data techniques in auditing research and practice: Current trends and future opportunities. Journal of Accounting Literature, 40(1), 102-115.

Hair, J. F., Astrachan, C. B., Moisescu, O. I., Radomir, L., Sarstedt, M., Vaithilingam, S., & Ringle, C. M. (2021). Executing and interpreting applications of PLS-SEM: Updates for family business researchers. Journal of Family Business Strategy, 12(3), 100392.

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.

Hamdam, A., Jusoh, R., Yahya, Y., Abdul Jalil, A., & Zainal Abidin, N. H. (2022). Auditor judgment and decision-making in big data environment: a proposed research framework. Accounting Research Journal, 35(1), 55-70.

Hammersley, J. S. (2011). A review and model of auditor judgments in fraud-related planning tasks. Auditing: A Journal of Practice & Theory, 30(4), 101-128.

Handoko, B. L., Mulyawan, A. N., Tanuwijaya, J., & Tanciady, F. (2020). Big data in auditing for the future of data driven fraud detection. International Journal of Innovative Technology and Exploring Engineering, 9(3), 2902-2907.

Hosban, A., & Hamdan, M. N. (2015). Role for Internal Auditor to Cope with IT Risks and IT Infrastructure in Jordan Commercial Banks. International Journal of Business and Management, 10(3), 295.

Irawati, S. A., & Solikhah, B. (2018). The factors affecting audit judgment. Accounting Analysis Journal, 7(1), 34-42.

Jiang, S. (2020). Research on the influence of big data to audit. 2020 International Conference on Big Data Economy and Information Management (BDEIM),

Joshi, P. L., & Marthandan, G. (2020). Continuous internal auditing: can big data analytics help? International Journal of Accounting, Auditing and Performance Evaluation, 16(1), 25-42.

Kadous, K., & Zhou, Y. (2019). How does intrinsic motivation improve auditor judgment in complex audit tasks? Contemporary accounting research, 36(1), 108-131.

Lee, I., & Mangalaraj, G. (2022). Big data analytics in supply chain management: A systematic literature review and research directions. Big data and cognitive computing, 6(1), 17.

Logie, J., & Maroun, W. (2021). Evaluating audit quality using the results of inspection processes performed by an independent regulator. Australian accounting review, 31(2), 128-149.

Lotlikar, P., & Mohs, J. (2021). Examining the Role of Artificial Intelligence on Modern Auditing Techniques.

Louis, R. R., Sulaiman, N. A., & Zakaria, Z. (2022). Accounting firms’ talent management practices: perceived importance and its impact on auditors’ performance. Pacific Accounting Review, 34(2), 274-292.

Memon, M. A., Ting, H., Cheah, J.-H., Thurasamy, R., Chuah, F., & Cham, T. H. (2020). Journal of Applied Structural Equation Modeling.

Mujahed, H., Mohammed,, Elsadig Musa Ahmed, & Samikon, S. A. (2020). Mobile Banking Adoption in Organization: Review of Empirical Literature. International Journal of Innovative Science and Research Technology, 5(9), 2456-2165 https://doi.org/https://doi.org/10.38124/ijisrt20sep288

Ng, P. M., Lit, K. K., & Cheung, C. T. (2022). Remote work as a new normal? The technology-organization-environment (TOE) context. Technology in Society, 70, 102022.

Parker, L. D., Jacobs, K., & Schmitz, J. (2018). New public management and the rise of public sector performance audit: Evidence from the Australian case. Accounting, Auditing & Accountability Journal, 32(1), 280-306.

Podsakoff, P. M., MacKenzie, S. B., Lee, J.-Y., & Podsakoff, N. P. (2003). Common method biases in behavioral research: a critical review of the literature and recommended remedies. Journal of applied psychology, 88(5), 879.

Prakoso, B., & Khudri, T. Y. (2022). Adoption of Continuous Auditing in The Internal Audit Unit of SKK Migas Using TOE Framework. 7th Sriwijaya Economics, Accounting, and Business Conference (SEABC 2021),

Rosli, K., Siew, E.-G., & Yeow, P. H. (2016). Technological, organisational and environmental aspects of audit technology acceptance. International Journal of Business and Management, 11(5), 140-145.

Saetang, W., Tangwannawit, S., & Jensuttiwetchakul, T. (2020). The effect of technology-organization-environment on adoption decision of big data technology in Thailand. Int J Electr Comput, 10(6), 6412.

Sahidah, S., Putra, R. R., & Julito, K. A. (2023). The Effect of Good Corporate Governance and Auditor Performance on Audit Quality with Integrity as a Moderating Variable. JASa (Jurnal Akuntansi, Audit dan Sistem Informasi Akuntansi), 7(2), 345-356.

Samiolo, R., Spence, C., & Toh, D. (2024). Auditor judgment in the fourth industrial revolution. Contemporary accounting research, 41(1), 498-528.

Sarstedt, M., Ringle, C. M., & Hair, J. F. (2021). Partial least squares structural equation modeling. In Handbook of market research (pp. 587-632). Springer.

Sofyani, H., & Darma, E. S. (2024). Effect of architecture and efficiency of mobile banking application on the intention to continue using Islamic bank: does data security matter? Journal of Islamic Marketing, 15(6), 1479-1497.

Tiron-Tudor, A., & Deliu, D. (2022). Reflections on the human-algorithm complex duality perspectives in the auditing process. Qualitative Research in Accounting & Management, 19(3), 255-285.

Wedemeyer, P. D. (2010). A discussion of auditor judgment as the critical component in audit quality–A practitioner's perspective. International Journal of Disclosure and Governance, 7(4), 320-333.

Widuri, R., Handoko, B. L., & Prabowo, I. C. (2019). Adoption of information technology in public accounting firm. Proceedings of the 4th International Conference on Big Data and Computing,

Xing, Z., Yuan, S., & Xiongzhi, C. (2020). Study on the Impact of Big Data Technology on the Audit and its Application. 2020 IEEE International Conference on Power, Intelligent Computing and Systems (ICPICS),

Yani, I., & Nazaruddin, I. (2024). Impact Of Interactive Control In Improving Academics' Performance: Mediating Role Of Fairness. Jurnal Akuntansi, 28(1), 80-99.

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Published

2025-03-03