Denetimde Makine Öğreniminin Kullanımına Yönelik Bibliyometrik Bir Analiz

Yazarlar

DOI:

https://doi.org/10.63556/tisej.2025.1465

Anahtar Kelimeler:

Muhasebe- Denetim- Makine Öğrenmesi- R-Studyo- Bibliyometrik

Özet

Bu çalışmanın amacı denetim alanında kullanılan en uygun makine öğrenmesi yöntemlerini belirlemek ve bu yöntemlerin denetim alanına katkılarını ortaya koymaktır. Bu bağlamda bibliyometrik analiz yöntemi kullanılmıştır. Bu analiz kapsamında, Scopus veri tabanından 147, Web of Science veri tabanından ise 99 olmak üzere toplam 246 çalışma incelenmiştir. Verilerin birleştirilmesinin ardından analiz için 160 çalışma seçilmiştir. Bibliyometrik verilerin analizi Biblioshiny yardımıyla R-Studio programında Bibliometrix paketi kullanılarak yapılmıştır. Bulgular, lojistik regresyon ve doğrusal regresyon analizinin 1980'lerden bu yana denetimde yaygın olarak kullanılan makine uygulamaları olmaya devam ettiğini göstermektedir. Ayrıca analizler son yıllarda derin öğrenme, Uzun-Kısa Süreli Bellek, Beetle Antennae Search, Rastgele Orman ve XGBoost gibi ileri uygulamaların daha fazla tercih edildiğini göstermektedir. Bu çalışma, denetim alanında makine öğrenimi üzerine araştırma yapmak için kapsamlı bir yol haritası geliştirmeyi amaçlayan gelecekteki araştırmacılar için değerli içgörüler sunmaktadır. Çalışma ayrıca, denetimin muhasebe disiplini içinde, ancak disiplinler arası bir bakış açısıyla ele alınmasının gerekliliğini vurgulamakta ve bu çerçevede literatüre yeni bakış açıları kazandırmaktadır.

Kaynaklar

Abou-El-Sood, H. (2008). The Usefulness of Accounting Information, Economic Variables, and Corporate Governance Measures to Predict Corporate Failure [SSRN Scholarly Paper]. Rochester, NY: Social Science Research Network. Retrieved from https://papers.ssrn.com/abstract=2967010

Agus, A., & Aziza, N. (2020). The Effects of Ethical Factors in Financial Statement Examination: Ethical Framework of the Input Process Output (IPO) Model in Auditing System Basis. International Journal of Financial Research, 11(2), 136. https://doi.org/10.5430/ijfr.v11n2p136

Agustí, M. A., & Orta-Pérez, M. (2023). Big data and artificial intelligence in the fields of accounting and auditing: a bibliometric analysis. Spanish Journal of Finance and Accounting/Revista Española de Financiación y Contabilidad, 52(3),412-438. https://doi.org/10.1080/02102412.2022.2099675

Ahsan, M. M., Luna, S. A., & Siddique, Z. (2022). Machine-Learning-Based Disease Diagnosis: A Comprehensive Review. Healthcare, 10(3), 541. https://doi.org/10.3390/healthcare10030541

Alharasis, E. E. (2023). Evaluation Of Ownership Structure And Audit-Quality In The Wake Of The Covid-19 Crisis: Empirical Evidence From Jordan. International Journal of Law and Management, 65(6), 635–662. (world). https://doi.org/10.1108/IJLMA-03-2023-0035

Alsmady, A. A. (2023). The Moderating Role Of Audit Quality Between Earning Management And Sustainable Investment Opportunities: Evidences From Gulf Cooperation Council Countries. International Journal of Applied Economics, Finance and Accounting, 16(1), 18–32. https://doi.org/10.33094/ijaefa.v16i1.874

Aria, M., & Cuccurullo, C. (2017). Bibliometrix: An R-Tool For Comprehensive Science Mapping Analysis. Journal of Informetrics, 11(4), 959–975. https://doi.org/10.1016/j.joi.2017.08.007

Ashtiani, M. N., & Raahemi, B. (2023). An Efficient Resampling Technique for Financial Statements Fraud Detection: A Comparative Study. 2023 3rd International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME), 1–7. Tenerife, Canary Islands, Spain: IEEE. https://doi.org/10.1109/ICECCME57830.2023.10253185

Baatour, K., & Saada, M. B. (2022). Regulatory Accounting Environment, Cultural Values And Board Efficacy In Developing Countries. PSU Research Review, 8(2), 428–442. (world). https://doi.org/10.1108/PRR-07-2021-0036

Bakumenko, A., & Elragal, A. (2022). Detecting Anomalies in Financial Data Using Machine Learning Algorithms. Systems, 10(5), 130. https://doi.org/10.3390/systems10050130

Barta, G. (2018). The Increasing Role Of IT Auditors In Financial Audit: Risks And Intelligent Answers. Business, Management and Economics Engineering, 16, 81–93. https://doi.org/10.3846/bme.2018.2142

Bellucci, M., Bianchi, D. C., & Manetti, G. (2022). Blockchain In Accounting Practice And Research: Systematic Literature Review. Meditari Accountancy Research, 30(7), 121–146. (world). https://doi.org/10.1108/MEDAR-10-2021-1477

Bertomeu, J., Cheynel, E., Floyd, E., & Pan, W. (2021). Using Machine Learning To Detect Misstatements. Review of Accounting Studies, 26(2), 468–519. https://doi.org/10.1007/s11142-020-09563-8

Biczyk, P., & Wawrowski, Ł. (2023). Detecting and Isolating Adversarial Attacks Using Characteristics of the Surrogate Model Framework. Applied Sciences, 13(17), 9698. https://doi.org/10.3390/app13179698

Bineid, M., Beloff, N., Khanina, A., & White, M. (2023). CADM: Big Data to Limit Creative Accounting in Saudi-Listed Companies. 2023 18th Conference on Computer Science and Intelligence Systems (FedCSIS), 103–110. https://doi.org/10.15439/2023F3888

Brown, N. C., Crowley, R. M., & Elliott, W. B. (2020). What Are You Saying? Using topic to Detect Financial Misreporting. Journal of Accounting Research, 58(1), 237–291. https://doi.org/10.1111/1475-679X.12294

Cardona, L. F., Guzmán-Luna, J. A., & Restrepo-Carmona, J. A. (2024). Bibliometric Analysis of The Machine Learning Applications in Fraud Detection on Crowdfunding Platforms. Journal of Risk and Financial Management, 17(8), 352. https://doi.org/10.3390/jrfm17080352

Chen, H., Tan, X., & Cao, Q. (2021). Air Pollution, Auditors’ Pessimistic Bias And Audit Quality: Evidence From China. Sustainability Accounting, Management and Policy Journal, 12(1), 74–104. https://doi.org/10.1108/SAMPJ-07-2019-0277

Chen, Y., & Wu, Z. (2022). Financial Fraud Detection of Listed Companies in China: A Machine Learning Approach. Sustainability, 15(1), 105. https://doi.org/10.3390/su15010105

Chen, Y., Wu, Z., & Yan, H. (2022). A Full Population Auditing Method Based on Machine Learning. Sustainability, 14(24), 17008. https://doi.org/10.3390/su142417008

Chi, D. J., & Shen, Z. D. (2022). Using Hybrid Artificial Intelligence and Machine Learning Technologies for Sustainability in Going-Concern Prediction. Sustainability, 14(3), 1810. https://doi.org/10.3390/su14031810

Chi, D.-J., & Chu, C.-C. (2021). Artificial Intelligence in Corporate Sustainability: Using LSTM and GRU for Going Concern Prediction. Sustainability, 13(21), 11631. https://doi.org/10.3390/su132111631

Chien, C.-C., Chen, K. Y., & Wu, S.-Y. (2008). Corporate Governance And Auditor Selection: Evidence From Taiwan. Corporate Ownership & Control, 492, 66.

Cho, S., Vasarhelyi, M. A., Sun, T. (Sophia), & Zhang, C. (Abigail). (2020). Learning from Machine Learning in Accounting and Assurance. Journal of Emerging Technologies in Accounting, 17(1), 1–10. https://doi.org/10.2308/jeta-10718

Dai, X., & Zhu, W. (2022). Intelligent Financial Auditing Model Based on Deep Learning. Computational Intelligence and Neuroscience, 2022, 1–5. https://doi.org/10.1155/2022/8282854

Davalos, S., & Feroz, E. H. (2022). A Textual Analysis of The US Securities And Exchange Commission’s Accounting And Auditing Enforcement Releases Relating to The Sarbanes–Oxley Act. Intelligent Systems in Accounting, Finance and Management, 29(1), 19–40. https://doi.org/10.1002/isaf.1506

Dbouk, B., & Zaarour, I. (2017). Towards A Machine Learning Approach For Earnings Manipulation Detection. Asian Journal of Business and Accounting, 10(2), 215–251.

Dewayanto, T. (2021). A Bibliometric Analysis and Visualization Of Accounting Fraud Detection Using Machine Learning Research. Fokus Ekonomi : Jurnal Ilmiah Ekonomi, 16(2), 455–471. https://doi.org/10.34152/fe.16.2.455

Do, D. T., Dang, V. S., Pham, V. D., Le, V. L., & Dang, V. T. (2023). Influence Of Local Independent Audit Firms’ Service Quality on Customer Satisfaction. Corporate Governance and Organizational Behavior Review, 7(3, special issue), 307.

Dong, W., Liao, S., & Zhang, Z. (2018). Leveraging Financial Social Media Data for Corporate Fraud Detection. Journal of Management Information Systems, 35(2), 461–487. https://doi.org/10.1080/07421222.2018.1451954

Donthu, N., Kumar, S., Mukherjee, D., Pandey, N., & Lim, W. M. (2021). How To Conduct A Bibliometric Analysis: An Overview and Guidelines. Journal of Business Research, 133, 285–296. https://doi.org/10.1016/j.jbusres.2021.04.070

Duan, H. K., Vasarhelyi, M. A., Codesso, M., & Alzamil, Z. (2023). Enhancing The Government Accounting Information Systems Using Social Media Information: An Application of Text Mining and Machine Learning. International Journal of Accounting Information Systems, 48, 100600. https://doi.org/10.1016/j.accinf.2022.100600

Eldyasty, M. M., & Elamer, A. A. (2023). Audit (Or) Type and Audit Quality In Emerging Markets: Evidence from Explicit Vs. Implicit Restatements. Review of Accounting and Finance, 22(4), 489–507. https://doi.org/10.1108/RAF-02-2023-0046

Elgattani, T., & Hussainey, K. (2021). The Impact of AAOIFI Governance Disclosure on Islamic Banks Performance. Journal of Financial Reporting and Accounting, 19(3), 434–454. https://doi.org/10.1108/JFRA-03-2020-0053

El-Halaby, S., & Hussainey, K. (2016). Determinants Of Compliance with AAOIFI Standards By Islamic Banks. International Journal of Islamic and Middle Eastern Finance and Management, 9(1), 143–168. https://doi.org/10.1108/IMEFM-06-2015-0074

El-Halaby, S., Albarrak, H., & Grassa, R. (2020). Influence Of Adoption AAOIFI Accounting Standards on Earning Management: Evidence from Islamic Banks. Journal of Islamic Accounting and Business Research, 11(10), 1847–1870. https://doi.org/10.1108/JIABR-10-2019-0201

Elmghaamez, I. K., Gerged, A. M., & Ntim, C. G. (2020). Financial Market Consequences of Early Adoption of International Standards on Auditing: International Evidence. Managerial Auditing Journal, 35(6), 819–858. https://doi.org/10.1108/MAJ-04-2019-2233

Erdoğan, M., & Erdoğan, E. O. (2020). Financial Statement Manipulation: A Beneish Model Application. In S. Grima, E. Boztepe, & P. J. Baldacchino (Eds.), Contemporary Studies in Economic and Financial Analysis (pp. 173–188). Emerald Publishing Limited. https://doi.org/10.1108/S1569-375920200000102014

Ever, D., & Demi̇rci̇oğlu, E. N. (2022). Yapay Zekâ Teknolojilerinin Kalite Maliyetleri Üzerine Etkisi. Çukurova Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 31(1), 59–72. https://doi.org/10.35379/cusosbil.1023004

Ferris, K. R. (1982). A Note on The Use of Regression Analysis In Accounting: Coping With Multicollinearity. Accounting & Finance, 22(1), 41–53. https://doi.org/10.1111/j.1467-629X.1982.tb00129.x

Fukas, P., Menzel, L., & Thomas, O. (2022). Augmenting Data with Generative Adversarial Networks to Improve Machine Learning-Based Fraud Detection. Wirtschaftsinformatik 2022 Proceedings. Retrieved from https://aisel.aisnet.org/wi2022/analytics_talks/analytics_talks/4

Gaganis, C., & Pasiouras, F. (2007). A Multivariate Analysis of The Determinants Of Auditors’ Opinions On Asian Banks. Managerial Auditing Journal, 22(3), 268–287. https://doi.org/10.1108/02686900710733143

Gaio, C., Gonçalves, T., & Pereira, A. (2021). Financial Crisis and Impairment Recognition in Non-Financial Assets. Review of Business Management, 23(2), 370–387. https://doi.org/10.7819/rbgn.v23i2.4108

Harun, M. S., Hussainey, K., Mohd Kharuddin, K. A., & Farooque, O. A. (2020). CSR Disclosure, Corporate Governance and Firm Value: A study on GCC Islamic Banks. International Journal of Accounting & Information Management, 28(4), 607–638. https://doi.org/10.1108/IJAIM-08-2019-0103

Hezam, Y. A., Anthonysamy, L., & Suppiah, S. D. K. (2023). Big data analytics and auditing: A review and synthesis of literature. Emerging Science Journal, 7(2), 629-642. http://dx.doi.org/10.28991/ESJ-2023-07-02-023

https://doi.org/10.3390/su132111631

Iyer, V. M., Bamber, E. M., & Griffin, J. (2012). Characteristics Of Audit Committee Financial Experts: An Empirical Study. Managerial Auditing Journal, 28(1), 65–78. https://doi.org/10.1108/02686901311282506

Kang, H. (2024). Optimization of Enterprise Accounting Audit Risk Identification and Prevention Strategy Based on Machine Learning. Journal of Electrical Systems, 20(9s), 79–84.

Kateb, I., & Belgacem, I. (2024). Navigating Governance and Accounting Reforms In Saudi Arabia’s Emerging Market: Impact of Audit Quality, Board Characteristics, And IFRS Adoption On Financial Performance. International Journal of Disclosure and Governance, 21(2), 290–312. https://doi.org/10.1057/s41310-023-00193-5

Kateb, I., Nafti, O., & Zeddini, A. (2023). How To Improve the Financial Performance Of Islamic Banks In The MENA Region? A Shariah Governance Perspective. International Journal of Emerging Markets, ahead-of-print(ahead-of-print). (world). https://doi.org/10.1108/IJOEM-03-2023-0434

Khan, A. T., Cao, X., Li, S., Katsikis, V. N., Brajevic, I., & Stanimirovic, P. S. (2022). Fraud Detection in Publicly Traded U.S Firms Using Beetle Antennae Search: A Machine Learning Approach. Expert Systems with Applications, 191, 116148. https://doi.org/10.1016/j.eswa.2021.116148

Khorsheed, H. S., Ismael, N. B., & Mahmod, S. H. O. (2024). The Impact Of Artificial Intelligence and Machine Learning On Financial Reporting And Auditing Practices. International Journal of Advanced Engineering, Management and Science, 10(6), 30–37. https://doi.org/10.22161/ijaems.106.4

Khuzaae, M. H. A., Almihna, Z. A. K., & Al-bdairi, A. A. K. (2019). The Impact Of Corporate Governance And Supply Chain Management On The Accounting and Auditing Environment. International Journal of Supply Chain Management, 8(1), 367-373. https://www.researchgate.net/publication/351985165

Kiliç, M., Uyar, A., & Ataman, B. (2016). Preparedness Of the Entities for The IFRS For Smes: An Emerging Country Case. Journal of Accounting in Emerging Economies, 6(2), 156–178. https://doi.org/10.1108/JAEE-01-2014-0003

Krieger F, Drews P, &Velte P. (2021). Explaining The (Non-) Adoption of Advanced Data Analytics in Auditing: A Process Theory. Int J Account Inf Syst 2021;41: 100511. https://doi.org/10.1016/j.accinf.2021.100511

Krieger, F., Drews, P., & Velte, P. (2021). Explaining The (Non-) Adoption Of Advanced Data Analytics in Auditing: A Process Theory. International Journal of Accounting Information Systems, 41, 100511. https://doi.org/10.1016/j.accinf.2021.100511

Kulk, G. P., Peters, R. J., & Verhoef, C. (2009). Quantifying IT estimation risks. Science of Computer Programming, 74(11), 900–933. https://doi.org/10.1016/j.scico.2009.09.001

Lamboglia, R., Lavorato, D., Scornavacca, E., & Za, S. (2021). Exploring the relationship between audit and technology. A bibliometric analysis. Meditari Accountancy Research, 29(5), 1233-1260. https://doi.org/10.1108/MEDAR-03-2020-0836

Land, J. K. (2010). CEO Turnover Around Earnings Restatements And Fraud. Pacific Accounting Review, 22(3), 180–198. https://doi.org/10.1108/01140581011091666

Law, P. (2011). Corporate Governance and No Fraud Occurrence In Organizations: Hong Kong Evidence. Managerial Auditing Journal, 26(6), 501–518. https://doi.org/10.1108/02686901111142558

Lee, H.-L., & Lee, H. (2013). Do Big 4 Audit Firms Improve the Value Relevance Of Earnings And Equity? Managerial Auditing Journal, 28(7), 628–646. (world). https://doi.org/10.1108/MAJ-07-2012-0728

Liao, B., Huang, Z., Cao, X., & Li, J. (2022). Adopting Nonlinear Activated Beetle Antennae Search Algorithm for Fraud Detection of Public Trading Companies: A Computational Finance Approach. Mathematics, 10(13), 2160. https://doi.org/10.3390/math10132160

Liaras, E., Nerantzidis, M., & Alexandridis, A. (2024). Machine Learning In Accounting And Finance Research: A Literature Review. Review of Quantitative Finance and Accounting, 63(4), 1431–1471. https://doi.org/10.1007/s11156-024-01306-z

Lin Lindawati, A. S., & Handoko, B. L. (2022). How Information Technology Literacy Moderated Factors Affecting Quality of Computer-Based Audit. 2022 4th International Conference on Cybernetics and Intelligent System (ICORIS), 1–6. https://doi.org/10.1109/ICORIS56080.2022.10031571

Máté, D., Sadaf, R., Oláh, J., Popp, J., & Szűcs, E. (2019). The Effects of Accountability, Governance Capital, And Legal Origin on Reported Frauds. Technological and Economic Development of Economy, 25(6), 1213–1231. https://doi.org/10.3846/tede.2019.10717

Nielsen, S. (2022). Management Accounting and The Concepts of Exploratory Data Analysis and Unsupervised Machine Learning: A Literature Study And Future Directions. Journal of Accounting & Organizational Change, 18(5), 811–853. https://doi.org/10.1108/JAOC-08-2020-0107

Nyakurukwa, K. (2022). The Zimbabwe Code on Corporate Governance (Zimcode) and Financial Performance. Journal of African Business, 23(3), 549–567. https://doi.org/10.1080/15228916.2021.1889871

Oala, L., Murchison, A. G., Balachandran, P., Choudhary, S., Fehr, J., Leite, A. W., … Wiegand, T. (2021). Machine Learning for Health: Algorithm Auditing & Quality Control. Journal of Medical Systems, 45(12), 105. https://doi.org/10.1007/s10916-021-01783-y

Ocak, M., Ozkan, S., & Can, G. (2022). Continuing Professional Education and Audit Quality: Evidence from an Emerging Market. Asian Review of Accounting, 30(4), 432–464. https://doi.org/10.1108/ARA-12-2021-0235

Oyerogba, E. O. (2021). Forensic Auditing Mechanism and Fraud Detection: The Case of Nigerian Public Sector. Journal of Accounting in Emerging Economies, 11(5), 752–775. https://doi.org/10.1108/JAEE-04-2020-0072

Papík, M., & Papíková, L. (2019). Detection Models for Unintentional Financial Restatements. Journal of Business Economics and Management, 21(1), 64–86. https://doi.org/10.3846/jbem.2019.10179

Pérez Pérez, Y., Camacho Miñano, M. D. M., & Segovia-Vargas, M. J. (2021). Risk On Financial Reporting in The Context of The New Audit Report In Spain. Revista de Contabilidad, 24(1), 48–61. https://doi.org/10.6018/rcsar.363001

Ramzan, S., & Lokanan, M. (2024). The Application of Machine Learning To Study Fraud in The Accounting Literature. Journal of Accounting Literature, ahead-of-print(ahead-of-print). (world). https://doi.org/10.1108/JAL-11-2022-0112

Ranta, M., Ylinen, M., & Järvenpää, M. (2023). Machine Learning in Management Accounting Research: Literature Review and Pathways for the Future. European Accounting Review, 32(3), 607–636. https://doi.org/10.1080/09638180.2022.2137221

Sadique, R. B. M., Ismail, A. M., Roudaki, J., Alias, N., & Clark, M. B. (2019). Corporate Governance Attributes in Fraud Detterence. International Journal of Financial Research, 10(3), 51. https://doi.org/10.5430/ijfr.v10n3p51

Saeedi, A. (2023). A High-Dimensional Approach to Predicting Audit Opinions. Applied Economics, 55(33), 3807–3832. https://doi.org/10.1080/00036846.2022.2118224

Salem, R. B., Damak-Ayadi, S., & Saïhi, M. (2017). Determinants of full IFRS adoption. International Journal of Managerial and Financial Accounting. (world). Retrieved from https://www.inderscienceonline.com/doi/10.1504/IJMFA.2017.084776

Sánchez-Serrano, J. R., Alaminos, D., García-Lagos, F., & Callejón-Gil, A. M. (2020). Predicting Audit Opinion in Consolidated Financial Statements with Artificial Neural Networks. Mathematics, 8(8), 1288. https://doi.org/10.3390/math8081288

Schreyer, M., Sattarov, T., & Borth, D. (2022). Federated and Privacy-Preserving Learning of Accounting Data in Financial Statement Audits. Proceedings of the Third ACM International Conference on AI in Finance, 105–113. New York, NY, USA: Association for Computing Machinery. https://doi.org/10.1145/3533271.3561674

Shahroor, H. G., & Ismail, A. I. (2022). Corporate Governance Mechanisms and Earnings Management Activities: Evidence from the UAE Banking Sector. FIIB Business Review, 23197145221099099. https://doi.org/10.1177/23197145221099099

Shapovalova, A., Kuzmenko, O., Polishchuk, O., Larikova, T., & Myronchuk, Z. (2023). Modernization Of the National Accounting And Auditing System Using Digital Transformation Tools. Financial & Credit Activity: Problems of Theory & Practice, 4(51). https://doi.org/10.55643/fcaptp.4.51.2023.4102

Sheela, S., Alsmady, A. A., Tanaraj, K., & Izani, I. (2023). Navigating the Future: Blockchain’s Impact on Accounting and Auditing Practices. Sustainability, 15(24), 16887. https://doi.org/10.3390/su152416887

Shepherd, B. E., & Yu, C. (2011). Accounting for Data Errors Discovered from an Audit in Multiple Linear Regression. Biometrics, 67(3), 1083–1091. https://doi.org/10.1111/j.1541-0420.2010.01543.x

Soltani, M., Kythreotis, A., & Roshanpoor, A. (2023). Two Decades Of Financial Statement Fraud Detection Literature Review; Combination Of Bibliometric Analysis And Topic Modeling Approach. Journal of Financial Crime, 30(5), 1367–1388. https://doi.org/10.1108/JFC-09-2022-0227

Souza, F. Ê. A. de, Botinha, R. A., Silva, P. R., & Lemes, S. (2015). Comparability of Accounting Choices in Future Valuation of Investment Properties: An Analysis of Brazilian and Portuguese Listed Companies. Revista Contabilidade & Finanças, 26, 154–166. https://doi.org/10.1590/1808-057x201500580

Staszkiewicz, P., & Werner, A. (2021). Reporting and Disclosure of Investments in Sustainable Development. Sustainability, 13(2), 908. https://doi.org/10.3390/su13020908

Tran, T. C. T., Ha, X. T., Le, T. H. P., & Nguyen, N. T. (2019). Factors affecting IFRS adoption in listed companies: Evidence from Vietnam. Management Science Letters, 2169–2180. https://doi.org/10.5267/j.msl.2019.7.035

Ucoglu, D. (2020). Current Machine Learning Applications in Accounting And Auditing. Pressacademia, 12(1), 1–7. https://doi.org/10.17261/Pressacademia.2020.1337

Ullah, Md. H., Khanam, R., & Tasnim, T. (2018). Comparative Compliance Status Of AAOIFI And IFSB Standards: An Empirical Evidence From Islami Bank Bangladesh Limited. Journal of Islamic Accounting and Business Research, 9(4), 607–628. https://doi.org/10.1108/JIABR-11-2014-0040

Ur Rehman, Z., Zahid, M., Rahman, H. U., Asif, M., Alharthi, M., Irfan, M., & Glowacz, A. (2020). Do Corporate Social Responsibility Disclosures Improve Financial Performance? A Perspective of the Islamic Banking Industry in Pakistan. Sustainability, 12(8), 3302. https://doi.org/10.3390/su12083302

Waresul Karim, A. K. M., van Zijl, T., & Mollah, S. (2013). Impact Of Board Ownership, CEO‐Chair Duality And Foreign Equity Participation On Auditor Quality Choice of IPO Companies. International Journal of Accounting & Information Management, 21(2), 148–169. https://doi.org/10.1108/18347641311312285

Wasito, I., Simon, F. E. B. R. Y. A. N. T. I., & Diandra, K. (2023). Time Series Classification for Financial Statement Fraud Detection Using Recurrent Neural Networks Based Approaches. Journal of Theoretical and Applied Information Technology, 15, 23.

Westland, C., J. (2017). An Empirical Investigation of Analytical Procedures Using Mixture Distributions. Intelligent Systems in Accounting, Finance and Management, 24(4), 111-124. https://doi.org/10.1002/isaf.1405

Yang, M. (2024). Topic Modeling of Financial Accounting Research Over 70 Years. International Studies of Economics, 19(4), 617–643. https://doi.org/10.1002/ise3.88

Yang, Y., & Simnett, R. (2023). Determinants And Quality of Audits and Reviews of Small Charities Financial Statements. International Journal of Auditing, 27(4), 220–240. https://doi.org/10.1111/ijau.12310

Zahra, S. A., & Rusfian, E. Z. (2022). Effects Of Company Structure On The Relationship Between Environmental Auditing and Financial Reporting Quality. Procedia Environmental Science, Engineering and Management, 8(4), 995-1002.

Zhang, C. (Abigail), Cho, S., & Vasarhelyi, M. (2022). Explainable Artificial Intelligence (XAI) in auditing. International Journal of Accounting Information Systems, 46, 100572. https://doi.org/10.1016/j.accinf.2022.100572

Zhou, Y., Liu, J., & Lei, D. (2024). The Effect of Financial Reporting Regimes On Audit Report Lags and Audit Fees: Evidence from Firms Cross-Listed In The USA. Journal of Financial Reporting and Accounting, 22(4), 917-941. https://doi.org/10.1108/JFRA-09-2021-0261

Yayınlanmış

22-09-2025

Nasıl Atıf Yapılır

EVER, D., & ÇANKAL, A. (2025). Denetimde Makine Öğreniminin Kullanımına Yönelik Bibliyometrik Bir Analiz. Üçüncü Sektör Sosyal Ekonomi Dergisi, 60(3), 3103–3129. https://doi.org/10.63556/tisej.2025.1465

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