The Impact of Big Data on Accounting Practices: Empirical Evidence from Africa
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Publisher
Springer International Publishing
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-18552-6_4
Reference58 articles.
1. Abedin, M. Z., Guotai, C., Colombage, S., & Moula, F. E. (2018). Credit default prediction by using a support vector machine and a probabilistic neural network. Journal of Credit Risk, 14(2), 1–27. https://doi.org/10.21314/JCR.2017.233
2. Abedin, M. Z., Guotai, C., Hajek, P., Tong, Z., & Moula, F. E. (2022). Combining weighted SMOTE with ensemble learning for the class-imbalanced prediction of small business credit risk. Complex & Intelligent Systems. https://doi.org/10.1007/s40747-021-00614-4
3. Aboud, A., & Robinson, B. (2020). Fraudulent financial reporting and data analytics: An explanatory study from Ireland. Accounting Research Journal, 35(1), 21–36.
4. Disrupt Africa. (2021). Disrupt Africa. Accessed from https://disrupt-africa.com/funding-report/
5. Al-Htaybat, K., & von Alberti-Alhtaybat, L. (2017). Big data and corporate reporting: Impacts and paradoxes. Accounting, Auditing & Accountability Journal, 30(4), 850–873.
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