تأثير استخدام الخوارزميات المحاسبية الذكية على جودة المعلومات المحاسبية

Appelbaum, D., Kogan, A., Vasarhelyi, M., & Yan, Z. (2017). Impact of business analytics and enterprise systems on management accounting. International Journal of Accounting Information Systems, 25, 29-44. https://www.sciencedirect.com/science/article/abs/pii/S1467089517300490

Atrous, R. (2025). Artificial intelligence and the evolution of accounting and audit practices: A systematic review. International Journal of Economics, Business and Management Research, 9(1), 125-143. https://doi.org/10.51505/IJEBMR.2025.9110

Bodnar, G. H., & Hopwood, W. S. (2019). Accounting information systems (15th ed.). Pearson.

Carollo, M., Lauri, L., Bardozzo, F. et al. (2026) Exploring the efficiency of GPT models in automating trial balance mapping: applications and insights. Soft Comput 30, 1693–1709. https://doi.org/10.1007/s00500-025-10983-4

COSO. (2017). Enterprise risk management: Integrating with strategy and performance. COSO, https://www.coso.org/Documents/2017-COSO-ERM-Integrating-with-Strategy-and-Performance-Executive-Summary.pdf

Deloitte. (2025). The role of algorithms in financial reporting and decision making. https://www.deloitte.com/reports/example.

Field, A. (2018). Discovering statistics using IBM SPSS statistics (5th ed.). SAGE Publications.

George, D., & Mallery, P. (2010). SPSS for Windows Step by Step: A Simple Guide and Reference, 17.0 Update (10th ed.). Allyn & Bacon.

Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2019). Multivariate data analysis (8th ed.). Cengage Learning.

Han, J., Kamber, M., & Pei, J. (2011). Data mining: Concepts and techniques (3rd ed.). Morgan Kaufmann.

Hnylytska, L., & Sattarov, A. (2025). Conceptual foundations of integrating intelligent agents into the enterprise accounting ecosystem. Digital Economy and Economic Security, (6-21), 21-29. https://doi.org/10.32782/dees.21-4

Ionescu, L. (2022). Big data algorithms and artificial intelligence technologies in cloud-based accounting information systems. Analysis and Metaphysics, (21), 42-57. https://www.ceeol.com/search/article-detail?id=1088894

Kieso, D. E., Weygandt, J. J., & Warfield, T. D. (2019). Intermediate accounting (17th ed.). Wiley.

Kokina, J., & Davenport, T. H. (2017). The emergence of artificial intelligence: How automation is changing auditing. Journal of Emerging Technologies in Accounting, 14(1), 115–122. https://doi.org/10.2308/jeta-51730

Krejcie, R. V., & Morgan, D. W. (1970). Determining sample size for research activities. Educational and Psychological Measurement, 30(3), 607–610. https://doi.org/10.1177/001316447003000308

Laudon, K. C., & Laudon, J. P. (2012). Management information systems: Managing the digital firm (12th ed.). Prentice Hall.

Li, H., Gao, H., Wu, C., & Vasarhelyi, M. A. (2025). Extracting financial data from unstructured sources: Leveraging large language models. Journal of Information Systems, 39(1), 135-156. https://doi.org/10.2308/ISYS-2023-047

Menard, S. (2002). Applied Logistic Regression Analysis. SAGE Publications.

Moffitt, K. C., Rozario, A. M., & Vasarhelyi, M. A. (2018). Robotic process automation for auditing. Journal of Emerging Technologies in Accounting, 15(1), 1–10.

https://doi.org/10.2308/jeta-51935

Nobes, C., & Parker, R. (2020). Comparative international accounting (14th ed.). Pearson.

Nuritdinovich, A. S., Karimov, B., & Soliev, I. (2025). Integration of artificial intelligence and blockchain in modern accounting systems: Enhancing transparency and efficiency. Journal of Advanced Research in Economics and Administrative Sciences, 6(1), 45-62. https://doi.org/10.47631/jareas.v6i1.1042

Pallant, J. (2020). SPSS survival manual: A step-by-step guide to data analysis using IBM SPSS (7th ed.). Routledge.

Reinking, J., et al. (2020). Artificial intelligence in accounting: The importance of understanding AI. Journal of Information Systems, 34(1), 35–60.

https://doi.org/10.2308/isys-52609

Romney, M. B., Steinbart, P. J., Summers, S. L., & Wood, D. A. (2021). Accounting information systems (15th ed.). Pearson.

Russell, S. J., & Norvig, P. (2021). Artificial intelligence: A modern approach (4th ed.). Pearson.

Sampaio, J., & Silva, R. (2025). Digital transformation in accounting: An assessment of automation and AI integration. International Journal of Financial Studies, 13(1), 15-32. https://doi.org/10.3390/ijfs13010015.

Sekaran, U., & Bougie, R. (2016). Research methods for business: A skill building approach (7th ed.). John Wiley & Sons.

Sekinobe, M., Mukasa, K., Nayebale, F. I., & Kato, J. (2025). An interdisciplinary framework for the development of intelligent accounting automation systems integrating predictive risk analytics and dynamic internal control mechanisms to enhance regulatory compliance and fraud mitigation in high-risk economic sectors. International Journal of Innovative Science and Research Technology, 10(12), 2520-2533. https://ideas.repec.org/a/cvr/ijisrt/202512ijisrt25dec1138.html

Sutton, S. G., Holt, M., & Arnold, V. (2016). The reports of my death are greatly exaggerated—Artificial intelligence research in accounting. International Journal of Accounting Information Systems, 22, 60–73.https://doi.org/10.1016/j.accinf.2016.07.005

Tiron-Tudor, A., & Deliu, D. (2021). The future of accounting profession in the digital era: The impact of technology. Journal of Risk and Financial Management, 14(8), 382. https://doi.org/10.3390/jrfm14080382

Warren, J. D., Moffitt, K. C., & Byrnes, P. (2015). How Big Data will Control the History of Accounting and Outcomes. Accounting Horizons, 29(2), 397-407. https://www.scirp.org/reference/referencespapers?referenceid=2371058

Zhang, C., Sun, T., & Vasarhelyi, M. A. (2020). Framework for managing the algorithmic risk of artificial intelligence in auditing. Journal of Emerging Technologies in Accounting, 17(2), 1-16. https://doi.org/10.2308/JETA-2020-025