International Journal of Accounting Information Systems最新文献

Leveraging ubiquitous digital data, advanced hardware, and sophisticated software, Big Data Analytics (BDA) enables unprecedented in-depth examination of business processes. This paper investigates how the Big 4 accounting firms promote their use of technology-enabled analytics in auditing practices on their official websites. We find that all the Big 4 market their audit analytics as offering operational insights that add value for clients. Historically, auditors have sought to share valuable perspectives gained during engagements beyond verifying that clients are in compliance with accounting principles. However, providing these value-adding insights is transitioning from a supplementary benefit to an essential selling point of audits. This behavior likely stems from BDA technology’s inherent duality–facilitating regulatory compliance and business intelligence. Incorporating artificial intelligence into audit firms’ technological arsenal will further enhance their ability to deliver client-valued insights. These developments necessitate further research into how the BDA application impacts auditor independence.

This study aims to analyze whether non-financial (NF) performance is influenced by the quality of accounting information system (AIS) and the quality/usefulness of financial information (FI) and whether this influence is more pronounced in companies managed by women. Data of 381 Portuguese companies were subjected to structural equations model analysis. The results reveal that (1) companies managed by women exhibit the highest quality in terms of AIS and FI, (2) the quality of the FI determines its usefulness in the decision-making process, and (3) quality and usefulness of the FI has a significant impact on NF performance. Within the framework of contingency theory, the research provides empirical evidence that the NF performance of Portuguese firms is associated with the presence of women in management, as they enhance the quality of financial reporting, essential for the success of any organization. This research is pertinent for accounting and management professionals, as it underscores the importance of quality financial reporting for the survival and growth of companies, while also emphasizing the significance of gender diversity in company management. © 2021 Published by Elsevier Inc. All rights reserved.

We investigate how graphical vividness and interactivity in displays of non-financial information following poor financial performance affect the judgments of nonprofessional investors. Leveraging the Hamilton and Winchel (2019) model of dual-process theories of persuasion in financial reporting, we hypothesize and find that graphical vividness and interactivity jointly influence nonprofessional investors. Despite negative news in financial information, investors perceive a firm’s performance more positively when favorable non-financial information is presented more vividly and with a user interactivity function. Finally, contributing to theory, we find that effort positively mediates the effects of user interactivity on nonprofessional investors’ judgments and decisions. The results lend empirical support to the Hamilton and Winchel (2019) model of dual-process theories of persuasion in financial reporting and have implications for designers of investor relations websites, investor groups consuming this information, and regulators concerned about the need for standards in the presentation of non-financial information in annual reports.

This study seeks to explore the potential of data-driven methods for developing a financial statement fraud prediction model. We emphasize that building a fraud prediction model that can be used to detect fraud in real-world applications should receive attention from researchers. However, the severe class imbalance issue and the complex nature of fraudulent activities make it a rather challenging task. To address these problems, we apply the combinations of different sampling techniques and tree-based ensemble classifiers to an extensive set of raw financial statement data. The results show that the models using an extensive set of raw financial data, undersampling techniques and boosting tree classifiers are superior in fraud detection. Moreover, several features without a priori knowledge are identified to be important for fraud prediction models by feature importance evaluation. Accordingly, this study provides a methodological guide for designing fraud prediction models for real-world applications and serves as a preliminary step of the knowledge discovery process to complement fraud detection knowledge systems.

Mobile payment has become increasingly popular in recent years. However, concerns remain about the information security risk management practices implemented by non-financial-institution mobile payment service providers, such as mobile phone carriers and technology companies, using tokenization systems and encryption mechanisms. Using the modified Delphi method and building on the COBIT 2019 framework, this study explores and suggests how these non-financial-institution mobile payment service providers can consider a more holistic list of information security risk items and their corresponding management practices. We believe the proposed practices will help non-financial-institution mobile payment service providers focus on the valuable aspects of information security risks.

Intelligent Information Technology (IIT) applications are crucial in the audit process, enhancing quality, effectiveness, and efficiency. The client acceptance process (CAP), one of the critical audit steps, involves subjective evaluations where business managers' claims intersect with independent audit firm managers' expectations. This subjective nature introduces the potential for errors or misjudgments, impacting audit time and costs. In this paper, therefore, we propose a decision support system considering both auditors' subjective judgments and financial data variations for accepting or rejecting a client enterprise. The decision support system consisting of the Fuzzy Analytic Hierarchy Process (AHP), the logistic regression model, and the fuzzy inference system comprises four phases. In the first phase, a logistic regression model is developed using financial ratios to determine the client's probability of being in a close monitoring market (CMM) which represents publicly traded firms that are struggling to meet specific financial indicators or that are exposed to certain risks. In the second phase, the evaluation criteria used by the audit firm to measure the market reputation of the client enterprise are defined, and the weights of the evaluation criteria are obtained by using Fuzzy AHP. In the third phase, the Client Acceptance Score (CAS) representing market reputation of the client is calculated by incorporating the results of a reputation survey and applying the weights assigned to the evaluation criteria obtained in the second phase. Finally, client acceptance risk level (CARL) is obtained by using a fuzzy inference system and a rule-based defined by auditors. The CMM probability value and CAS score obtained in previous phases are used as input values of the fuzzy inference system. The CARL score guides the audit firm in deciding whether to engage with the client. To illustrate the applicability of the proposed model, a case study has been given in the paper.

Information technology internal control material weaknesses (ITICMW)s can lead to misrepresentations of companies’ financial information and inefficiencies in financial decision-making because of the significant role of IT in financial reporting processes. Previous studies of ITICMWs are mostly based on ITICMWs in general. Despite a few studies addressing specific categories of ITICMWs, they used pre-2010 data and were unable to represent the state of ITICMWs given the fast evolvement of IT in recent years. Additionally, the trends, associations, and industry effects on ITICMWs remain to be explored. We collected SOX 404 Auditor Internal Control Opinion Reports from a recent five-year period (2014 ∼ 2018) and analyzed them using a combination of thematic analysis, association rule mining, and statistical analysis methods. The data analyses generate a categorization schema of ITICMWs, uncover an increasing trend in average ITICMW incident counts per report from 2016 to 2018, and indicate recent shifts in some specific categories of ITICMWs in comparison with the findings of previous studies. Our results also reveal cross-industry differences in ITICMW categories and identify their association patterns for the first time. This research not only contributes to the accounting information system and auditing literature in multiple aspects but also offers practical implications for improving the efficiency and effectiveness of internal control compliance, IT auditing and consulting practices, and financial decision-making.

Blockchain has been hyped and considered a potential game-changer for the recording of accounting transactions as it enables triple-entry accounting and real-time reporting. However, there is very little knowledge of the uptake of blockchain in accounting, and most blockchain accounting research is conceptual, lacking empirical evidence. This study addresses this gap and examines the organisational factors that drive and hinder the adoption of blockchain in accounting, as well as the perceived benefits. Using the technology-organisation-environment (TOE) framework, we analyse interview data collected from blockchain experts and accountants (N = 19). The findings confirm the influence of nine context-specific factors, highlighting the challenges and lack of knowledge in understanding the usage and benefits of blockchain in accounting, its complex integration with existing accounting systems, and the increased costs associated with the adoption intention. This study provides novel empirical evidence of the factors by adequately contextualising an established theoretical framework in the context of accounting. The findings are useful for practitioners and the broader accounting information systems research community as they provide empirical insights into how context-specific factors influence blockchain adoption in accounting.

Ever-increasing data breach incidents are destroying firms’ operations and financial sustainability. We examine the association between corporate social irresponsibility (CSIR) and data breach incidents, stock market reactions to these incidents, and how the affected firms respond to data breaches. Using a sample of 24,456 observations from 2005 to 2018, we find a positive and significant association between CSIR and the occurrence of data breaches. More importantly, CSIR, regarding employee, community, and corporate governance issues, is more likely to result in internal data breaches, and environmental concerns can trigger external attacks. In contrast, product concerns can lead to both internal breaches and external attacks. Consistent with our prediction, the negative stock market reaction to data breaches is more pronounced in CSIR than in non-CSIR firms. Finally, we show that firms respond to data breaches by establishing corporate social responsibility (CSR) committees. Firms with such committees, especially those with robust CSR committees, are more likely to react to data breaches by mitigating CSIR. Our results offer important and timely policy, practice, and research implications as data breaches persist.

This article aims to analyse the impacts of new technologies, namely robotic process automation (RPA) and artificial intelligence (AI), on auditing firms. In particular, we focus on the companies’ everyday activities, organisational structure, hiring practices, and the competitive gap between Big4 and non-Big4 auditing firms. To this end, the article is based on a field study involving 14 auditing companies, both Big4 and non-Big4, from the list provided by Consob. The results reveal auditors’ differing perceptions and opinions regarding the future of auditing firms. According to the first viewpoint, new technologies will have a positive impact on auditors as they will be allowed to focus on value-added activities. Second, some respondents do not expect changes to the traditional structure of the companies due to the application of digital tools, while other auditors hypothesised two different scenarios regarding structural changes. Third, the interviewees contend that auditors of the future should gain IT and data analytics skills, which could affect the hiring practices of these companies. Fourth, regarding the current differences between large and smaller firms, some participants stated that emerging technologies could widen that gap, while some auditors of non-Big4 firms claimed that modern tools offer an opportunity for the smaller companies to slightly reduce the gap. In sum, the findings reveal that, although RPA and AI are not widely used and the impact of these technologies on auditing firms is controversial, multiple changes are on the horizon in this regard.