How Does Readability Influence Investors' Judgments? Consistency of Benchmark Performance Matters

• 成果类型: Article
• 署名作者: Tan, Hun-Tong; Wang, Elaine Ying; Zhou, Bo
• 署名单位: Nanyang Technological University; University of Massachusetts System; University of Massachusetts Amherst; Shanghai University of Finance & Economics
• 刊物名称: ACCOUNTING REVIEW
• ISSN/ISSBN: 0001-4826
• DOI: 10.2308/accr-50857
• 发表日期: 2015
• 页码: 371-393
• 关键词: processing fluency; CURRENT EARNINGS; comprehension; management; disclosure; MODEL

摘要

We conduct two experiments to investigate how readability (high versus low) and benchmark performance consistency (consistent versus inconsistent) influence investors' judgments. Using prior management guidance and year-ago quarter performance as two benchmarks against which to assess actual earnings performance, we manipulate whether the valence of guidance performance (positive or negative) and the valence of trend performance (positive or negative) are consistent with each other. We also manipulate the readability of trend performance in our main experiment. Our results show that when benchmark performance is inconsistent, higher as opposed to lower readability of positive (negative) trend performance leads to more (less) favorable investors' performance judgments. This effect of readability is smaller when benchmark performance is consistent. We also show that higher readability in the inconsistent benchmark performance condition improves investors' understanding of the firm's current-quarter performance, which in turn influences their judgments on the firm's future performance. In a supplementary experiment, we manipulate the readability of guidance performance in an inconsistent benchmark performance setting, and replicate the key finding that higher readability of positive guidance performance leads to more positive judgment on the firm's future performance.