In this paper, we propose extensions to the resource-event-agent (REA) framework to encompass the information requirements of the balanced scorecard and other management systems that incorporate nonfinancial measures. The REA conceptual accounting framework was designed to describe the information architecture related to an organization's economic activity (e.g., McCarthy 1982;Dunn et al. 2005). Geerts and McCarthy (2001b, 2002) extended the original REA to include value-chain level configurations, task-level configurations, and encompass a broader array of business economic phenomena. Yet, the REA framework remains closely tied to its accounting roots, with a focus on economic events and financial resources. A substantial number of organizations are adopting strategic management systems that include both financial and nonfinancial measures to overcome known limitations of systems based on traditional financial data alone (e.g., Said et al. 2003;Eccles et al. 2001;Ittner et al. 2003). We therefore examine whether the REA framework supports the information requirements of this broader domain and propose extensions to fill the gaps identified.
A call to action has been sounded in accounting: Become a profession utilizing data analytics or become a profession bound for the history books. Accounting firms and corporations are investing in data analytics capabilities, but it is not clear whether accounting professionals are following their lead. Practitioner press indicates accountants resist the move beyond Excel even as organizations hire data scientists rather than accountants. This paper uses Status Quo Bias Theory to examine the resistance to data analytics technology by accounting and finance professionals. Surprisingly results indicate the perceived value does not mediate the effect of switching benefits and costs on resistance. Rather, switching benefits and perceived value are aligned as a single factor to reduce resistance, while switching costs directly increase resistance. Researchers have focused substantial effort toward data analytics in education and business. The troubling findings here suggest a number of accounting professionals resist adopting new analytics technology.
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.
While many business publications stress the importance of data analytics skills and technology, The Wall Street Journal reports strong reactions of accountants faced with a move away from Excel. Accountants are traditionally the reliable source for business information, but that position may be eroded by the emerging profession of data analysts. Looking to the future, Big Four accounting firms stress the need for data analysis skills, and universities are launching degree programs. But what is the reaction of current working professionals? Are they heeding the call for data analytics? Evidence indicates there is some resistance to adoption of data analytics practices. This research proposes the use of Status Quo Bias Theory to investigate the reactions of accounting professionals across the spectrum of accounting sub-disciplines. The study seeks to understand factors that may influence practicing accountants' resistance to adopting new data analysis technologies.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.