Underreporting, or reporting fewer hours than actually worked, is a prevalent behavior among auditors at all levels. Underreporting can result in negative consequences, such as tight budgets and reductions in future audit quality. In this paper, I propose a low-cost budget formatting procedure that reduces underreporting. Using an experiment, I document that individuals with higher underreporting incentives underreport less when given an aggregated budget relative to a disaggregated budget. When individuals have lower underreporting incentives, aggregating the budget has a smaller effect on underreporting. I also provide evidence of the process by performing a mediation analysis. In a second experiment, I examine a budget formatting procedure that reduces underreporting while also mitigating the loss of data richness that results from aggregation. This study provides important insights to audit firms, partners, managers, and regulators who rely on audit hours for budgets, measures of staff efficiency, and measures of audit quality.

Auditing standards vary in their degree of prescriptive language—for example, stating that auditors “could” versus “should” do certain procedures. We posit that more prescriptive language primes an implemental mindset, thereby creating a feeling of regulatory fit with objective verification tasks and improving auditors' performance on these tasks. In an experiment with audit students, we find that participants who apply a more (versus less) prescriptive auditing standard perform better on a subsequent, unrelated ticking-and-tying task, and this effect is larger for participants who identify less with the audit profession. Theory-consistent evidence indicates that the interaction of regulatory fit and professional identity improves performance via increased motivation. Our study provides evidence that features of the audit environment prime mindsets, that these primed mindsets can affect performance on low-level tasks, and that the effect of regulatory fit for low-level tasks is particularly important for those who identify less with the audit profession.

We examine the effect of humanizing (naming) robo‐advisors on investor judgments, which has taken on increased importance as robo‐advisors have become increasingly common and there is currently little SEC regulation governing key aspects of their use. In our first experiment, we predict and find that investors are more likely to rely on the investment recommendation of an unnamed robo‐advisor, whereas they are more likely to rely on the investment recommendation of a named human advisor. Theory suggests one reason that naming a robo‐advisor may have drawbacks pertains to the complexity of the task the robo‐advisor performs. We explore the importance of task complexity in our second experiment. We predict and find that investors are less likely to rely on a named robo‐advisor when the advisor is perceived to be performing a relatively complex task, consistent with our first experiment, and more likely to rely on a named robo‐advisor when the advisor is perceived to be performing a relatively simple task, consistent with prior research on human‐computer interactions. Our findings contribute to the literature examining how technology influences the acquisition and use of financial information and the general literature on human‐computer interactions. Our study also addresses a call by the SEC to learn more about robo‐advisors. Lastly, our study has practical implications for wealth management firms by demonstrating the potentially negative effects of making robo‐advisors more humanlike in an attempt to engage and attract users.

Classification of financial statement elements into categories is an inherent, integral part of the financial reporting system. Although prior research documents that categories influence users’ perceptions of included items, we explore the reverse effect—how classifying items in a category can impact perceptions of the category itself and its other members. Using categorization theory from psychology and accounting literature and exploiting the classification challenges inherent to the crypto asset setting, we predict and find that classifying individual items into a category can impact equity analysts’ perceptions of the category itself and perceptions of the category's other members. We also explore the boundaries of this effect and find that categories like intangibles, with fewer common prototypical features, are more susceptible to these classification effects. Our results show several ways in which balance sheet classification could lead to unintended consequences for users.

In this paper, we investigate whether the current references to probability in standard setters' conceptual definitions of assets and liabilities cause individuals to believe that the probability of a future transfer of economic benefits must be above some meaningful threshold for an asset or a liability to exist—a belief that is contrary to standard setters' intent. Results of multiple experiments indicate that the majority of individuals do use a high probability threshold to determine asset existence, whereas for liabilities the majority use a very low threshold. Thus, even under ceteris paribus conditions, liabilities are more frequently judged to exist than assets—a phenomenon analogous to accounting conservatism, as has been discussed in terms of the performance statement. These findings are robust to variation in formal training and in type of liability, and cannot be explained by alternative approaches to judging existence. Consistent with standard setters' intentions, results also suggest that their proposed changes to the definitions of assets and liabilities—changes that attempt to clarify the intended role of probability—do cause a greater proportion of participants to indicate that the relevant financial statement element (asset or liability) exists, relative to participants with no definition. Our study provides important insights for standard setters as they continue work on their missions to update their Conceptual Frameworks and for researchers regarding the role of conservatism on the balance sheet.