When Do Auditors Use Specialists' Work to Improve Problem Representations of and Judgments about Complex Estimates?

• 成果类型: Article
• 署名作者: Griffith, Emily E.
• 署名单位: University of Wisconsin System; University of Wisconsin Madison
• 刊物名称: ACCOUNTING REVIEW
• ISSN/ISSBN: 0001-4826
• DOI: 10.2308/accr-51926
• 发表日期: 2018
• 页码: 177-202
• 关键词: fair value measurements; source credibility; attitudes; MODEL; quantification; identification; incentives; expertise; BIAS

摘要

Auditors are more likely to identify misstatements in complex estimates if they recognize problematic patterns among an estimate's underlying assumptions. Rich problem representations aid pattern recognition, but auditors likely have difficulty developing them given auditors' limited domain-specific expertise in this area. In two experiments, I predict and find that a relational cue in a specialist's work highlighting aggressive assumptions improves auditors' problem representations and subsequent judgments about estimates. However, this improvement only occurs when a situational factor (e.g., risk) increases auditors' epistemic motivation to incorporate the cue into their problem representations. These results suggest that auditors do not always respond to cues in specialists' work. More generally, this study highlights the role of situational factors in increasing auditors' epistemic motivation to develop rich problem representations, which contribute to high-quality audit judgments in this and other domains where pattern recognition is important.