Search

Copyright of Contemporary Accounting Research is the property of Canadian Academic Accounting Association and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

SUMMARY: In this paper, we provide theoretical and practical guidance on experimental design choices when incorporating auditor-client communication in audit research. We structure our discussion around Social Presence Theory, noting how elements of social presence impact theoretical predictions and the related experimental design. We then compare non-interactive, highly controlled paper/computer-based studies with studies that involve automated interaction, interaction with an actor, or interaction between participants. We provide a discussion of best practices and pitfalls related to these different experimental design choices, including theoretical and logistical considerations, as well as recent innovations in this area. While our methodological discussion is nested in auditor-client communication research, these methods and logistical considerations are applicable to most accounting experiments designed to address research questions steeped in social psychology (i.e., contexts of human interaction). [ABSTRACT FROM AUTHOR]

Prior research suggests individuals have difficulty comprehending large magnitude numbers commonly associated with government spending (e.g., millions and billions). We conduct an experiment investigating how the disclosure format of large numbers in government spending affects voter support. We find participants' support for proposed government spending is insensitive to cost when presented in total (e.g., "$718 billion" versus "718 million") but becomes cost-sensitive in response to a practical intervention, disclosing the dollar amounts in more understandable per-household terms (e.g., "$5,744 per U.S. household" versus "5.74 per U.S. household"), and find participant support becomes cost-sensitive after viewing this disclosure format. This research demonstrates how support for government spending can change significantly depending on different (but economically equivalent) disclosure formats. Specifically, the per-household disclosure format increases stakeholders' understanding of large magnitude spending policies and helps them form judgments better informed by their cost-sensitive preferences. [ABSTRACT FROM AUTHOR]

SUMMARY: Recent research suggests that an auditor's choice to conduct audit inquiry via email versus in person can adversely impact both auditor and client behavior. In this study, I review recent research on this important topic, and I present additional survey-based evidence that describes how clients perceive auditor email versus in-person inquiries. I find that clients generally view auditors' in-person requests as more important and urgent than email requests, and clients feel they can more carefully craft their responses to support their company's preferred reporting position via email compared to in person. Further, clients expect that auditors will question an aggressive response more quickly in person than over email. Although audit partners have expressed concerns that email communication could impede auditor-client relationship building, I find no differences in how much clients like the auditor or in clients' willingness to work again with the auditor after receiving an email or in-person request. However, recent research suggests that email requests can lead to more negative feelings toward the auditor, which could affect the auditor-client relationship over time. I discuss implications for audit firms and provide suggestions for future research. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) and machine learning (ML) are transforming organizations and will soon transform auditing. Many promising areas of AI and ML are within the continuous auditing context. However, the field has yet to recognize how AI and ML can be used for audit inquiry, an essential feature of both traditional audits and continuous auditing. In this research note, we discuss the potential viability of AI-enhanced audit inquiry using "bots" that automatically generate audit inquiries as well as evaluate client responses. In addition, we discuss opportunities for future research in this specific area of automated auditing. [ABSTRACT FROM AUTHOR]