The adoption of eXtensible Business Reporting Language (XBRL) requires management to label all information in their firm's financial statements and corresponding notes with either standardor custom extended tags. While prior literature has found that the rate of customization is associated with increased financial reporting complexity, there could be an unintended, beneficial consequence to tax reporting. We examine how the relative use of tax-related XBRL tag extensions could highlight unique tax activity characteristics, in turn increasing tax accrual quality and improving tax reporting transparency. We find that having a higher relative rate of extended tax tags is associated with higher tax accrual quality. That is, utilizing more tax tag extensions can assist in providing useful tax information, especially when a high number of total XBRL tags are used. Our results also suggest the need to reexamine the standard taxonomy to include more tax-oriented terms to improve financial reporting comparability.

Advances in information technology have greatly changed communications and business transactions between firms and their customers and suppliers. As a result, cybersecurity risk attracts ever increasing attention from firms, regulators, customers, shareholders, and academics. For instance, the Securities and Exchange Commission has released guidance on the disclosure of cybersecurity risks and incidents, along with potential internal control solutions, in the managers' discussion and analysis section of 10-K annual financial reports. Despite increasing interest in cybersecurity research, the literature lacks an integrative review of existing researchidentifying opportunities for future cybersecurity developments. In this study, we conduct an extensive analysis of cybersecurity-related papers in the accounting, information systems, computer science, and general business disciplines. Our review integrates and classifies 68cybersecurity papers, examines cybersecurity determinants, consequences, and remedial strategies, and identifies future research opportunities based on the current state of the literature.

While prior research suggests that the market responds negatively to data breach disclosures, how nonprofessional investors assess factors surrounding these disclosures has only been assessed anecdotally. We examine whether investor judgments are influenced by whether a breached company is the first to disclose a data breach and whether a significant amount of time has lapsed between the breach and disclosure. We find evidence that investors respond to a company originating disclosure with lower investment judgments than if disclosure comes from an external source, without consistent regard to the timing of disclosure. We also find that investors make the least favorable investment judgments when the breached company initiates the data breach disclosure and when there is a significant delay between the data breach and initial public disclosure. Our study provides a greater understanding of one consequence of data breaches, that is, how timing and disclosure initiative influence nonprofessional investors' judgments. JEL Classifications: G41; M41.

ChatGPT, a language-learning model chatbot, has garnered considerable attention for its ability to respond to users’ questions. Using data from 14 countries and 186 institutions, we compare ChatGPT and student performance for 28,085 questions from accounting assessments and textbook test banks. As of January 2023, ChatGPT provides correct answers for 56.5 percent of questions and partially correct answers for an additional 9.4 percent of questions. When considering point values for questions, students significantly outperform ChatGPT with a 76.7 percent average on assessments compared to 47.5 percent for ChatGPT if no partial credit is awarded and 56.5 percent if partial credit is awarded. Still, ChatGPT performs better than the student average for 15.8 percent of assessments when we include partial credit. We provide evidence of how ChatGPT performs on different question types, accounting topics, class levels, open/closed assessments, and test bank questions. We also discuss implications for accounting education and research.

This study examines factors that influence a public firm’s decision to early adopt blockchain technology. Blockchain technology has the potential to disrupt how firms collect, process, and maintain information about a wide range of firm activities including transactions and supply chain interactions. We examine several determinants of early adopt blockchain including patented technology, agency costs, complexity, and external monitoring. Our results suggest that blockchain early adoption involves opportunistic managerial behavior. Further, firms with greater technology innovations, proxied by number of patents, are more likely to disclose early adoption, possibly to overcome productivity concerns or attract inter-firm opportunities. We also examine the consequences of early adoption using a market-based approach. Our results suggest that blockchain adoption could be a lengthy and costly process. Our study provides evidence on why firms adopt this disruptive technology and informs regulators and policy makers on how managers can influence the blockchain early adoption decision.