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A new Public Company Accounting Oversight Board (PCAOB) standard requires the reporting of critical audit matters (CAMs) within the audit report. This change has lengthened the audit report but may provide investors with cues about auditor credibility and audit quality. Utilizing an experiment and 140 nonprofessional investors, we find evidence that the disclosure of a CAM improves perceived auditor credibility, but the disclosure also has the unintended consequence of increasing feelings of information overload. More importantly, the disclosure of a CAM has a significant, positive total effect on perceived audit quality. This effect, in turn, lowers investors' perceptions of investment risk. These findings highlight the potential for CAMs to impact investor perceptions and, possibly, subsequent decision making. Data Availability: Data are available from the authors upon request. [ABSTRACT FROM AUTHOR]

This study examines the impact of deterrence and inertia on information security policy changes. Corporations recognize the need to prioritize information security, which sometimes involves designing and implementing new security measures or policies. Using an online survey, we investigate the effect of deterrent sanctions and inertia on respondents' intentions to comply with modifications to company information security policies. We find that certainty and celerity associated with deterrent sanctions increase compliance intentions, while inertia decreases respondents' compliance intentions related to modified information security policies. Therefore, organizations must work to overcome employees' reluctance to change in order to improve compliance with security policy modifications. They may also consider implementing certain and timely sanctions for noncompliance. [ABSTRACT FROM AUTHOR]

Computer abuse by employees has increased the potential for security vulnerabilities for organizations. Organizations have established various security countermeasures to prevent computer abuse and protect organizational information. However, these policies are only effective if followed. Thus, it is important for organizations to understand the factors that motivate employees to follow computer usage polices. We investigate the impact of different countermeasures, such as perceived sanctions, and awareness of being monitored on compliance with computer usage policies by drawing upon agency theory and general deterrence theory. After testing the hypothesized relationships using survey data, the results indicate that perceived sanction severity and certainty significantly influence intention to comply with computer usage policies. Furthermore, awareness of being monitored is found to significantly impact penalties. Study results further indicate that penalties may be effective only to the extent that organizations can detect employees' deviant behavior through managerial controls, such as computer monitoring. [ABSTRACT FROM AUTHOR]

This study experimentally tests whether the techniques of neutralisation as identified in the criminal justice literature influence graduate student willingness to engage in questionable research practices (QRPs). Our results indicate that US-born graduate students are more willing to add an undeserved coauthor if the person who requests it is a faculty member in the student's department as opposed to a fellow student. Students are most likely to add an undeserving author if a faculty member is also their advisor. In addition, four techniques of neutralisation, 'diffusion of responsibility', 'defence of necessity', 'advantageous comparison' and 'euphemistic labelling', are associated with student willingness to act unethically. Participants who had received responsible conduct of research training were no less likely to commit the violation than those who had not. Knowledge of these influencing factors for QRPs will provide for opportunities to improve research ethics education strategies and materials. [ABSTRACT FROM AUTHOR]

This study examines the impact of moral intensity and inconsistent ethical tone on Bring Your Own Device (BYOD) policy compliance. Organizations use BYOD policies to address the heightened risks of data and privacy breaches that arise when employees use their personal devices to access or store company data. These policies are a key part of an organization's system of internal controls that protect organizational assets by prescribing appropriate behavior for individuals who have access to them. We conducted an online experiment to evaluate (1) how the moral intensity of a policy compliance decision influences policy compliance behavior, (2) the efficacy of an intervention designed to increase moral intensity and thus foster compliance, and (3) how an inconsistent ethical tone affects both the perceived ethicality of a policy compliance decision and individuals' intentions to comply with the policy. We find that moral intensity is positively related to policy compliance, and that a simple intervention effectively fosters policy compliance through its impact on moral intensity. Furthermore, we provide evidence that an inconsistent ethical tone erodes policy compliance intentions, and can spill over to affect another work-related behavior. These findings have important theoretical and practical implications. [ABSTRACT FROM AUTHOR]

This article identifies research opportunities in the use of artificial neural networks in credit scoring and related business intelligence situations, particularly as they have been emerging in the global economy. In the literature review, particular attention is paid to commercial lending credit risk assessment and consumer credit scoring. Investors and auditors need models that can predict whether a customer will stay viable. Lenders must manage their credit risk to maximize profits and cash flow, while minimizing losses. As the global economic recession continues, investors are tightening their investment belts and need models that help them make better investment decisions, while lenders must strengthen lending practices and better identify both good and bad credit risks. Artificial neural networks may help firms improve their credit model development, and thereby their credit decisions and profitability. Such technology may also help improve development in emerging economies. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The Securities and Exchange Commission (SEC) has recently expanded the communication channels available for management when it determined that personal social media pages are recognized channels for financial disclosures, provided Reg FD and the 2008 Guidance are correctly applied. However, social media channels are more widely available to investors, both nonprofessional and sophisticated, and allow for interaction between users via postings and comments. The opinions of others, as expressed in their comments on social media, may influence investors' perception of the news in a manner that is beyond that of the traditional disclosures envisioned by the SEC. This research explores this issue by examining the influence of disclosures and attached comments via social media on nonprofessional investors' perceptions of the news, valuation judgments, and perceptions of management's credibility. Grounded in the herding and majority influence theories, the research hypotheses are tested using a between-subjects experimental design. Results indicate that the attached comments shared via social media influence the participants' perceptions and reactions to the news. [ABSTRACT FROM AUTHOR]

Employees' use of online social networking (OSN) is dramatically increasing the risk exposure of companies. This study extends previous information security policy compliance research to include factors influencing employees to play OSN games on company-owned computers. An online factorial survey method experiment collected data from a sample of white-collar workers for testing hypotheses based upon accountability and boundary theories. The likelihood to play OSN games is tested with and without a policy related to this behavior. Results indicate that the presence of a social networking policy, logging awareness, and monitoring practices reduced participants' likelihood of playing OSN games on company-owned computers. After splitting the sample on the presence/absence of an OSN policy, results show that in the presence of a policy, monitoring practices and age significantly reduced the participants' likelihood of playing. In the absence of a policy, logging and monitoring reduced the likelihood of playing. [ABSTRACT FROM AUTHOR]

The purpose of this study is to examine the factors that determine whether employees follow Bring Your Own Device (BYOD) policies through the lens of the Protection Motivation Theory. BYOD is rapidly becoming the norm rather than the exception. As a result, firms are establishing BYOD policies to address the risk inherent in allowing individuals to use their own devices to access or store company data. This paper reports the results of a survey of accounting students, non-accounting students, and full-time employees. Results demonstrate that participants' intentions to comply with a BYOD policy were primarily motivated by Self Efficacy and Response Efficacy. Further, Threat Severity was more salient for accountants than non-accountants, perhaps due to their sensitivity to confidential data. Finally, when actual compliance behavior was considered, costs to comply were much more salient to employees and could be strong deterrents to full compliance. These findings have important theoretical and practical implications. [ABSTRACT FROM AUTHOR]

The article presents a survey to gauge the level of adoption on extensible business reporting language (XBRL) by companies in the U.S. It distributed an online survey to decision makers from various organizations to assess their level of adoption, perceptions of the costs and benefits associated with XBRL and how they learned about XBRL. Results indicate a slight majority of firms (52.6%) are either outsourcing the conversion process or do not use XBRL at all. Furthermore, 28.4% of the sample indicated that they are using XBRL for some internal purpose.

Poor credit granting decisions are coming back to haunt providers of loan finance. Past poor credit granting decisions are in part due to the Equal Credit Opportunity Act (1975). This act requires lenders to explain the decision to grant or refuse credit. As a result, models such as artificial neural networks, which offer improved ability to identify poor credit risks but which do not offer easy explanations of why a loan applicant has scored badly, remain unused. This paper investigates whether these models can be interpreted so that explanations for credit application rejection can be provided. The results indicate that while the artificial neural networks can be used (with caution) to develop credit scoring models, the limitations imposed by the credit granting process make their use unlikely until interpretation techniques are developed that are more robust and that can interpret multiple hidden-layer artificial neural networks. Copyright © 2008 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

This paper reviews the nature of accounting and auditing problems and the need for application of artificial intelligence (AI) technologies to the discipline. The discussion includes current accounting issues for which new AI development should be fruitful, particularly auditing and assurance. Copyright © 2007 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

This article discusses XBRL, its impacts on users and on the characteristics of financial information, and provides an impacts framework for XBRL. XBRL will both simplify disclosure and ease the communication of financial information to users, analysts, and regulators via the Internet. The potential impacts that XBRL is expected to have on users, accountants, regulators, and the financial communication process are addressed. Research on XBRL is examined and future research directions and priorities are identified. A more rigorous look at the myriad range of potential impacts of XBRL is needed. [ABSTRACT FROM AUTHOR]

In this study, an adaptive network-based fuzzy inference system (ANFIS) and a neural network were tested for the ability of these techniques to forecast the annual excess returns of three large publicly traded companies from a time series of said returns. The predictive ability of these techniques was compared with that of an autoregressive moving average (ARMA) model. The Fair–Shiller test was used in the comparisons in order to obtain results that were not subjective and so that conclusions could be made regarding the information used by the techniques in the generation of their forecasts. Since predictive ability does not translate to profitability, a simple trading strategy was used to determine the ability to generate profits from trading upon the forecasts of the respective techniques. As hypothesized, the ANFIS and neural network techniques are able to generate forecasts with significant predictive ability. However, neither technique dominates the other or the ARMA model. In tests of the ability of the techniques to generate profits from their forecasts, a simple trading strategy was used (trading on the predicted sign of the return). The ANFIS and the neural network generated profits in all of the trading scenarios. However, neither technique dominated the other, nor did they consistently outperform the traditional and naive models (strategies). The mixed results in the predictive ability tests and the profitability tests indicate that the conclusions from the study differ based upon the context in which the forecasts are used. Copyright © 2005 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]