In Accounting Research, a Move Toward the Inductive?

Data analytics and machine learning are transforming the world of accounting research, says Maryland Smith’s Lawrence A. Gordon.

Gordon’s recent paper on the topic, "The Role of Data Analytics and Machine Learning in Resurrecting Inductive-based Accounting Research," was recently published as the lead article in the journal Transactions on Machine Learning and Artificial Intelligence.

He says the research paper was the outgrowth of his keynote address at the 2019 Accounting Horizons Conference on data analytics in accounting, held at Baruch College.

“My appreciation for the potential impact that data analytics and machine learning are having on accounting research has increased significantly as a result of writing this paper,” says Gordon, EY Alumni Professor of Managerial Accounting and Information Assurance at the University of Maryland’s Robert H. Smith School of Business. Gordon is also an affiliate professor in the University of Maryland Institute for Advanced Computer Studies.

In his paper, Gordon assessed the impact of data analytics and machine learning on accounting research, noting the inductive nature of those technologies, and observing an important trend in the way accounting research is being done. “Indeed,” he writes, “as a result of the recent developments of DA and ML, a rebalancing is taking place between inductive-based and deductive-based research in accounting.”

As a result, he notes a “resurrection of inductive-based accounting research.”

Read more: "The Role of Data Analytics and Machine Learning in Resurrecting Inductive-based Accounting Research," was recently published in Transactions on Machine Learning and Artificial Intelligence.