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We highlight two mechanisms of limited attention for expert information intermediaries, i.e., analysts, and the effects of such limited attention on the market price discovery process. We approach analysts' limited attention from the perspective of day-to-day arrival of information and processing of tasks. We examine the attention-limiting role of competing tasks (number of earnings announcements and forecasts for portfolio firms) and distracting events (number of earnings announcements for non-portfolio firms) in analysts' forecast accuracy and the effects of such, on the subsequent price discovery process. Our results show that competing tasks worsen analysts' forecast accuracy, and competing task induced limited attention delays the market price adjustment process. On the other hand, distracting events can improve analysts' forecast accuracy and accelerate market price adjustments when such events relate to analysts' portfolio firms through industry memberships.

Investors frequently make judgments and decisions in the presence of affect (i.e., mood or emotion). Investors' moods may influence the extent to which they incorporate available financial information in their investment judgments. I propose that investors interpret their moods as signals of the extent to which financial information should be processed to make investment judgments, but only when other, more direct signals regarding the need for in-depth processing are unavailable. Consistent with research in psychology, my experimental results suggest that investors experiencing positive mood exert less effort to process available financial information than investors experiencing negative mood. Consequently, positive mood results in lower-quality financial judgments in my setting. However, when investors receive cues suggesting that initially received information is subjective, the effect of mood on effort to process financial information is mitigated. Overall, my results suggest that factors associated with positive investor mood (e.g., positive market sentiment) reduce the depth of investor analysis and lower judgment quality absent signals regarding the subjectivity of financial information.

Nonperforming assets in any banking system have stressed the economic health of nations. Resultantly, literature has given considerable impetus to predict failures and bankruptcy. Past studies have focused on the outcome of failures, while, there is a dearth of studies focusing on ongoing firms in bad shape. We plug this gap and attempt to identify underlying communication patterns for firms witnessing prolonged underperformance. Using text mining, we extract and analyze semantic, linguistic, emotional, and sentiment-based features in non-numeric communication channels of these poor-performing firms and their peers. These uncovered patterns highlight the use of vocabulary and tone of communication, in correspondence to their financial well-being. Furthermore, using such patterns, we deploy various Machine Learning algorithms to identify loser firm(s) way ahead in time. We observe promising accuracy over a time window of five years. Such early warning signals can be of critical importance to various stakeholders of a firm. Exploration of writing style-related features for any firm would help its investors, lending agencies to assess the likelihood of future underperformance. Firm management can use them to take suitable precautionary measures and preempt the future possibility of distress. While investors and lenders can be benefitted from this incremental information to identify the likelihood of future failures.

This study examines the effect of employees' perceptions of political connections on performance measurement systems (PMS) design choice and firm performance. In addition, this study explores the moderating effect of social networking, a very common and widely used factor by domestic and foreign multinational firms operating in China, and its joint effect with political connections or PMS design choice on firm performance. We collected survey responses from a sample of 110 managers from manufacturing firms in China. Our results reveal that highly politically connected managers use nonfinancial measures, leading to improved firm performance. Our results suggest that social networking interacts significantly with political connections, and nonfinancial and financial measures on firm performance. The theoretical and practical implications of our findings are discussed.

Nonfinancial information is becoming more readily available to investors, and thus, relative to annual financial reports, is having an increasing influence on investors' stock pricing decisions. Using Hogarth and Einhorn's (1992) belief-adjustment model, we examine how task familiarity (high, medium, and low) influences nonprofessional investor stock price decisions when these investors are presented with a stream of both positive and negative nonfinancial news. We find that task familiarity negatively correlates with reaction size for both positive and negative information, which creates arbitrage opportunities for those with more task familiarity. However, we find that assurance mitigates this effect, leveling the playing field for less task-familiar investors in most cases. These findings are important as the volume and variety of information types increase, and as more nonfinancial information enters the marketplace in discrete sound bites (e.g., social media, press releases, daily reports). Findings suggest that assurance is one way to lessen the biases exhibited by investors with less task familiarity. These results enhance our understanding of nonprofessional investor behavior through the lens of belief revision.

In crafting Auditing Standard No.3 (AS3), a primary objective of the PCAOB was to reduce auditors' exposure to litigation by raising the standard of care for audit documentation. We examine whether the increased documentation requirements of AS3 affect legal professionals' perceptions of audit quality and auditor responsibility in the event of an audit failure. Our experiment consists of a 3 × 2 between-participants design with law students serving as proxies for legal professionals. The results of our experiment indicate that when an audit procedure, namely the investigation of inconsistent evidence, is not required to be documented, legal professionals perceive the performance of the work itself but not its documentation to significantly increase audit quality and reduce the auditor's responsibility for an audit failure. When documentation of the procedure is required, as per AS3, legal professionals perceive enhanced audit quality and reduced auditor responsibility only if the performance of the work is documented.

This study provides evidence on the relationship between scale characteristics and participant responses for percentage-based scales (i.e., 101 points) in accounting research. A 4 × 1 between-subjects experiment examines how common labeling designs affect various statistical properties, including means, variance, normality of the distribution, and frequency of responses. The results indicate that labels on percentage-based scales have a significant impact on the distribution of participants' responses. Labeling only the endpoints is the lone condition that results in normally distributed data. Additional analyses suggest that labels on percentage-based scales influence participant responses in multiple ways. First, as the number of labels increases, participants may not adequately consider, and thus ultimately select, unlabeled points. Second, while participants seem to inherently interpret percentage-based scales in quartiles and deciles, labeling as such exacerbates this tendency. Finally, when more labels are present, participants seem to engage an anchoring heuristic when selecting their response. Taken as a whole, the results suggest that accounting researchers may benefit from labeling only the endpoints of percentage-based scales.

The specific purpose of this study is to understand how firm size and public/private affiliation (employment status) affect voluntary disclosure decisions concerning quantitatively immaterial nonfinancial information. Although the prior disclosure literature is large and has considered a variety of factors including size and to a lesser degree employment status, this study offers a new perspective by considering both factors in the context of qualitative materiality.

This paper presents 136 manager participants with 24 cues representing nonfinancial, realistic business events and solicits their disclosure judgments. The cues are adapted from Pinsker et al. and contain information that does not meet widely-accepted quantitative thresholds for disclosure (e.g. 5 percent of net income), yet were identified by the Securities and Exchange Commission (SEC) as more likely to be material. This paper uses a median split of total assets and total revenues to determine “large” and “small” firms. Managers' judgments are measured in an own-firm setting (The context is their current employer, which can be public or private.).

This paper finds that disclosure is positively linked to firm size, but this paper do not find an employer status effect. Additional testing reveals that private firm managers are sensitive to SEC oversight and other external, competitive pressures, suggesting that they face mimetic pressures to behave like their public firm counterparts. In sum, their findings contribute significantly to the disclosure, strategic management, institutional theory and judgment-and-decision-making (JDM) literatures.

Although there is a vast literature on public firm managers' voluntary disclosure behavior (mostly involving large firms), there is little research regarding the voluntary disclosure behavior of small or large private firm managers involving nonfinancial information.

This chapter aims to enhance understanding of the main drivers of internal auditors' moral courage to speak up about sensitive information and their cause-and-effect relationships. We use cognitive mapping method to analyze 20 chief audit executives' cognitive maps in Tunisia. A collective map was grounded through assembling the full individual maps. Using the Decision Explorer software for our analysis, we find that the state hope, whistle-blowing policy, self-efficacy, perceived supervisor support and independence of internal audit function are the main drivers for internal auditors' moral courage. Our findings are also supplemented by semi-structured interviews. Our chapter offers a novel methodological contribution to auditing literature as well as new empirical evidence (contribution to knowledge) on the drivers of internal auditors' moral courage.