No abstract

ABSTRACT:We study moral judgments regarding budgetary slack made by participants at the end of a participative budgeting experiment in which an expectation for a truthful budget was present. We find that participants who set budgets under a slackinducing pay scheme, and therefore built relatively high levels of budgetary slack, judged significant budgetary slack to be unethical on average, whereas participants who set budgets under a truth-inducing pay scheme did not. This suggests that the slack-inducing pay scheme generated a moral frame by setting economic self-interest against common social norms such as honesty or responsibility. We also find that participants who scored high in traditional values and empathy on a pre-experiment personality questionnaire ͑JPI-R͒ were more likely to judge significant budgetary slack to be unethical. These results suggest that financial incentives play a role in determining the moral frame of the budgeting setting and that personal values play a role in determining how individuals respond to that moral frame.

ABSTRACT:We study moral judgments regarding budgetary slack made by participants at the end of a participative budgeting experiment in which an expectation for a truthful budget was present. We find that participants who set budgets under a slackinducing pay scheme, and therefore built relatively high levels of budgetary slack, judged significant budgetary slack to be unethical on average, whereas participants who set budgets under a truth-inducing pay scheme did not. This suggests that the slack-inducing pay scheme generated a moral frame by setting economic self-interest against common social norms such as honesty or responsibility. We also find that participants who scored high in traditional values and empathy on a pre-experiment personality questionnaire ͑JPI-R͒ were more likely to judge significant budgetary slack to be unethical. These results suggest that financial incentives play a role in determining the moral frame of the budgeting setting and that personal values play a role in determining how individuals respond to that moral frame.

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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.