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AIS research opportunities utilizing Machine Learning: From a Meta-Theory of accounting literature
International Journal of Accounting Information Systems ( IF 4.1 ) Pub Date : 2023-12-27 , DOI: 10.1016/j.accinf.2023.100661
Adam Booker , Victoria Chiu , Nathan Groff , Vernon J. Richardson

We use Accounting Information Systems (AIS) -theory to develop a framework for analyzing and using machine learning in accounting research, emphasizing 1) specific accounting research tasks, 2) supervised and unsupervised models, and 3) inductive vs. deductive research designs. We apply our framework to organize AIS and accounting research and highlight opportunities for future AIS research using machine learning. We discuss the changes in technology that have made machine learning more feasible in practice and research and how these changes might motivate and influence future research projects. We conclude by providing directions for future work in machine learning in AIS research and discussing the potential application to practice.

中文翻译:


利用机器学习的 AIS 研究机会:来自会计文献的元理论



我们使用会计信息系统 (AIS) 理论开发一个在会计研究中分析和使用机器学习的框架,强调 1) 特定的会计研究任务,2) 监督和无监督模型,以及 3) 归纳与演绎研究设计。我们应用我们的框架来组织 AIS 和会计研究,并强调未来使用机器学习进行 AIS 研究的机会。我们讨论了使机器学习在实践和研究中更加可行的技术变革,以及这些变革如何激励和影响未来的研究项目。最后,我们为 AIS 研究中机器学习的未来工作提供了方向,并讨论了其在实践中的潜在应用。
更新日期:2023-12-27
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