THE EFFECT OF INCREASED AUDIT DISCLOSURE ON INVESTORS\u27 PERCEPTIONS OF MANAGEMENT, AUDITORS, AND FINANCIAL REPORTING: AN EXPERIMENTAL INVESTIGATION

Standard setters recently proposed increasing audit disclosures and reporting. Two experiments examine the effects of auditor-provided disclosures on financial statement users’ perceptions of auditor independence, management credibility, reporting quality, materiality, and investment decisions. In the first experiment, I manipulate auditor agreement with management’s estimates and whether the estimates are incentive-consistent for management. I find that users view auditors as more (less) independent when they agree (disagree) with management, given an unqualified opinion. I also find that users are able to identify management bias using audit disclosures, and that the disclosures are value-relevant. In the second experiment, I provide users with either an explicit or implicit materiality disclosure and elicit users’ materiality judgments either before or after the disclosure. I find that users’ materiality judgments are closer to the auditor’s when elicited after an explicit materiality disclosure. Path analysis demonstrates that users’ materiality judgments affect subsequent investment and audit-related judgments but do not affect important decisions related to auditor liability and investment. The findings provide empirical support for the argument that additional audit disclosures would increase the transparency and value-relevance of the audit report

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe