AIS research opportunities utilizing Machine Learning: From a Meta-Theory of accounting literature

IF 4.1 3区管理学 Q2 BUSINESS

International Journal of Accounting Information Systems Pub Date : 2023-12-27 DOI:10.1016/j.accinf.2023.100661

Adam Booker , Victoria Chiu , Nathan Groff , Vernon J. Richardson

引用次数: 0

Abstract

We use Accounting Information Systems (AIS) meta-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.

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利用机器学习的 AIS 研究机会：从会计文献的元理论出发

我们利用会计信息系统（AIS）元理论，建立了一个在会计研究中分析和使用机器学习的框架，强调：1）具体的会计研究任务；2）监督和非监督模型；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化，以及这些变化可能如何激励和影响未来的研究项目。最后，我们为机器学习在 AIS 研究中的未来工作提供了方向，并讨论了在实践中的潜在应用。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

International Journal of Accounting Information Systems Multiple-

CiteScore

9.00

自引率

6.50%

发文量

期刊介绍： The International Journal of Accounting Information Systems will publish thoughtful, well developed articles that examine the rapidly evolving relationship between accounting and information technology. Articles may range from empirical to analytical, from practice-based to the development of new techniques, but must be related to problems facing the integration of accounting and information technology. The journal will address (but will not limit itself to) the following specific issues: control and auditability of information systems; management of information technology; artificial intelligence research in accounting; development issues in accounting and information systems; human factors issues related to information technology; development of theories related to information technology; methodological issues in information technology research; information systems validation; human–computer interaction research in accounting information systems. The journal welcomes and encourages articles from both practitioners and academicians.