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The Journal of Emerging Technologies in Accounting (JETA), an American Accounting Association journal, reached its ten-year milestone in 2013. This study provides a comprehensive bibliometric and comparative analysis of the 66 main research articles and citations of the contributions, which were published from 2004 to 2013. The analysis of the characteristics of the articles comprises the research methodologies and accounting areas as used in the Brigham Young University Accounting Research Rankings, novel classifications based on an expansion of the Brown and Vasarhelyi (1994) accounting research taxonomy, and the AACSB A7 data terms, artificial intelligence, contributing authors, and institutions. The citation analysis reports and compares scholarly and patent results. Some major differences between the citations in Google Scholar, Web of Science, and Scopus came to light.

ChatGPT, a language-learning model chatbot, has garnered considerable attention for its ability to respond to users’ questions. Using data from 14 countries and 186 institutions, we compare ChatGPT and student performance for 28,085 questions from accounting assessments and textbook test banks. As of January 2023, ChatGPT provides correct answers for 56.5 percent of questions and partially correct answers for an additional 9.4 percent of questions. When considering point values for questions, students significantly outperform ChatGPT with a 76.7 percent average on assessments compared to 47.5 percent for ChatGPT if no partial credit is awarded and 56.5 percent if partial credit is awarded. Still, ChatGPT performs better than the student average for 15.8 percent of assessments when we include partial credit. We provide evidence of how ChatGPT performs on different question types, accounting topics, class levels, open/closed assessments, and test bank questions. We also discuss implications for accounting education and research.

How would an inventor, entrepreneur, investor, or patent examiner quantify the extent to which the inventive claims listed in a patent document align with patent specification? Since a specification that is poorly aligned with the inventive claims can render an invention unpatentable and can invalidate an already issued patent, an effective measure of alignment is necessary. We define a novel measure of drafting alignment using Latent Dirichlet Allocation (LDA). The measure is defined for each patent document by first identifying the latent topics underlying the claims and the specification, and then using the Hellinger distance to find the proximity between the topical coverages. We demonstrate the use of the novel measure for data processing patent documents related to cybersecurity. The properties of the proposed measure are further investigated using exploratory data analysis, and it is shown that generally alignment is positively associated with the prior patenting efforts as well as the tendency to include figures in a document.

This study aims to help educators advance the integration of scholarly data analytics knowledge using emerging technology tools in accounting throughout the curriculum, thereby contributing to teaching for future-oriented practice. It provides an analysis of 215 peer-reviewed data analytics contributions including 16 classroom applications published from 2004 to 2018 in the six journals that have largely served as destinations of technology-related accounting research of all kinds and are commonly referred to as AIS journals, which are the Journal of Information Systems, International Journal of Accounting Information Systems, Journal of Emerging Technologies in Accounting, International Journal of Digital Accounting Research, AIS Educator Journal and Intelligent Systems in Accounting, Finance and Management. Accounting educators find detailed guidance on which peer-reviewed data analytics research contributions and tools are available to be integrated into financial and managerial accounting, auditing, accounting information systems, and tax courses.