{"title":"Stakeholders’ expectations versus standard setters’ outcome about crypto assets accounting: A PLS-SEM analysis","authors":"Adriana Tiron-Tudor, Stefania Mierlita, Cristina Stefanescu","doi":"10.1016/j.accinf.2026.100772","DOIUrl":"10.1016/j.accinf.2026.100772","url":null,"abstract":"<div><div>This research aims to explore the interplay between stakeholders and the US accounting standard setter on the accounting treatment of crypto assets. We applied the beliefs-actions-outcomes (BAO) model to capture stakeholders’ expectations, expressed in their comment letters in response to the Financial Accounting Standards Board’s Exposure Draft (FASB’s ED) on Topic 350, and to assess their expectations’ reflection in the revised version of the standard. We analysed the relationship between stakeholders’ beliefs, proposed actions, and the final standard’s outcome using PLS-SEM (partial least squares structural equation modelling) in SmartPLS. Furthermore, we examine whether feedback from the accountancy profession, a significant stakeholder group in this process, acts as a moderator of the belief-action relationship. The results confirm that the beliefs significantly influence the proposed actions but have a minimal impact on the outcome, with a small number of suggestions for improvement being integrated. The involvement of the accountancy profession moderated the relationship between beliefs and actions, only for the scope and measurement categories, reflecting their specialised knowledge and technical expertise. Through empirical results, current research contributes to the debate on crypto asset regulation by examining stakeholders’ expectations and how their participation has influenced this regulatory field, emphasising the standard-setting body’s responsiveness to their input. The study offers theoretical and practical insights into the interplay between stakeholders’ beliefs, their proposed actions, and the development of crypto accounting regulation (the outcome).</div></div>","PeriodicalId":47170,"journal":{"name":"International Journal of Accounting Information Systems","volume":"57 ","pages":"Article 100772"},"PeriodicalIF":6.0,"publicationDate":"2026-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146160150","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Government intervention or market incentives: which more effectively accelerates enterprise IT adoption in accounting systems? evidence from China’s financial shared service centers","authors":"Yuan Qian","doi":"10.1016/j.accinf.2025.100770","DOIUrl":"10.1016/j.accinf.2025.100770","url":null,"abstract":"<div><div>Under China’s policy interventions, the financial shared service center (FSSC), as an innovative application of information technology in corporate accounting systems, has shifted from being primarily market-driven to being jointly promoted by government policies and market forces. Using data from Chinese A-share listed companies from 2003 to 2022 and manually collected FSSC data, this study compares the effectiveness of government promotion versus market forces in driving FSSC implementation. We employ Cox proportional hazards models to investigate the drivers of firms establishing FSSCs. We find that state-owned enterprises (SOEs) establish FSSCs primarily in response to government promotion, whereas non-SOEs are motivated by market competition. Using propensity score matching and multi-period DID models, we find that FSSCs implemented by non-SOEs significantly improve financial reporting quality, whereas those established by SOEs show no measurable impact. These results hold after a series of robustness tests. Furthermore, cross-sectional analysis shows that the effectiveness of FSSCs is particularly pronounced in firms with more subsidiaries, wider geographic dispersion of subsidiaries, stronger subsidiary control, lower earnings management incentives, and adoption of robotic process automation (RPA), with such effects exclusively present in non-SOEs. Our results suggest that market-driven FSSCs generate substantive improvements, while government-promoted implementations fail to yield measurable outcomes. Therefore, when promoting FSSCs, the government needs to pay more attention to firms’ actual conditions and enhance follow-up supervision.</div></div>","PeriodicalId":47170,"journal":{"name":"International Journal of Accounting Information Systems","volume":"57 ","pages":"Article 100770"},"PeriodicalIF":6.0,"publicationDate":"2026-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145693220","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Digital transformation and cybersecurity risks","authors":"Nida Türegün","doi":"10.1016/j.accinf.2025.100749","DOIUrl":"10.1016/j.accinf.2025.100749","url":null,"abstract":"<div><div>This study analyzes the impact of integrating cybersecurity measures on the financial performance of banks. Utilizing regression analysis with data from 100 financial institutions, the findings reveal that banks prioritizing cybersecurity perform better financially. This study demonstrates that it is the quality and strategic integration of cybersecurity measures, as revealed through disclosures, that significantly influence financial outcomes, rather than the sheer scale of investment. A subsample analysis suggests that larger banks appear more resilient to cybersecurity threats due to scale-related advantages<strong>,</strong> while smaller banks can also improve their financial performance by adopting proportionate, strategically aligned cybersecurity measures. Effective cybersecurity integration correlates with improved financial metrics such as return on assets and equity. Furthermore, the severity of cybersecurity incidents negatively impacts financial performance, emphasizing the importance of proactive risk management. This study underscores the critical role of cybersecurity in financial strategy, enabling banks to navigate digital transformation challenges effectively.</div></div>","PeriodicalId":47170,"journal":{"name":"International Journal of Accounting Information Systems","volume":"56 ","pages":"Article 100749"},"PeriodicalIF":4.1,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144212226","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Strategic AI disclosures and legitimacy: Impression management in UK FTSE100 annual reports","authors":"Nader Elsayed","doi":"10.1016/j.accinf.2025.100757","DOIUrl":"10.1016/j.accinf.2025.100757","url":null,"abstract":"<div><div>By incorporating impression management strategies with legitimacy theory, this study investigates how UK FTSE100 corporations strategically communicate their AI disclosures to achieve, sustain, and/or restore legitimacy. It employs a mixed-methods content analysis to analyse textual AI data from the annual reports of 80 UK non-financial corporations listed in the FTSE100 index (2020 to 2023). Results reveal an increasing trend among UK corporations to disclose AI narratives. This study finds that FTSE100 corporations employ a blend of ‘assertive’ and ‘defensive’ impression management tactics in AI disclosures to influence stakeholder perceptions and maintain their legitimacy. Findings also indicate a significant post-crisis shift from defensive to assertive AI disclosures, underscoring how FTSE100 corporations strategically adapted their impression management tactics to reinforce pragmatic, moral, and cognitive legitimacy. This study contributes to the literature by demonstrating how impression‑management tactics shape AI legitimacy, offering practitioners strategies for transparent communication, informing legislators on ethical AI regulation, and enabling stakeholders to interpret AI disclosures as indicators of corporate conduct.</div></div>","PeriodicalId":47170,"journal":{"name":"International Journal of Accounting Information Systems","volume":"56 ","pages":"Article 100757"},"PeriodicalIF":6.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145157274","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Artificial intelligence and accounting research: a framework and agenda","authors":"Theophanis C. Stratopoulos , Victor Xiaoqi Wang","doi":"10.1016/j.accinf.2025.100760","DOIUrl":"10.1016/j.accinf.2025.100760","url":null,"abstract":"<div><div>Recent advances in artificial intelligence, particularly generative AI (GenAI) and large language models (LLMs), are fundamentally transforming accounting research, creating both opportunities and competitive threats for scholars. This paper proposes a framework that classifies AI-accounting research along two dimensions: research focus (accounting-centric versus AI-centric) and methodological approach (AI-based versus traditional methods). We apply this framework to papers from the IJAIS special issue and recent AI-accounting research published in leading accounting journals to map existing studies and identify research opportunities. Using this same framework, we analyze how accounting researchers can leverage their expertise through strategic positioning and collaboration, revealing where accounting scholars’ strengths create the most value. We further examine how GenAI and LLMs transform the research process itself, comparing the capabilities of human researchers and AI agents across the entire research workflow. This analysis reveals that while GenAI democratizes certain research capabilities, it simultaneously intensifies competition by raising expectations for higher-order contributions where human judgment, creativity, and theoretical depth remain valuable. These shifts call for reforming doctoral education to cultivate comparative advantages while building AI fluency.</div></div>","PeriodicalId":47170,"journal":{"name":"International Journal of Accounting Information Systems","volume":"56 ","pages":"Article 100760"},"PeriodicalIF":6.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145525623","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Marc Eulerich , Qing Huang , Justin Pawlowski , Miklos A. Vasarhelyi
{"title":"Using process mining as an assurance tool in the three-lines-model","authors":"Marc Eulerich , Qing Huang , Justin Pawlowski , Miklos A. Vasarhelyi","doi":"10.1016/j.accinf.2025.100731","DOIUrl":"10.1016/j.accinf.2025.100731","url":null,"abstract":"<div><div>One broadly accepted approach to structure the corporate governance of an organization is the so called “Three-Lines-Model” (TLM), which consists of different assurance providers like internal controls, risk management or internal auditing. While previous studies in the field of process mining showed different specific use cases in different related areas of this TLM, like e.g. internal controls, there is not approach that directly links process mining to the TLM. Thus, this paper directly links process mining to all three lines of the TLM and validates the conceptual use cases with real corporate data from a multinational company. The results show the benefits of a TLM-wide implementation of process mining. Thus, our study contributes to the ongoing practical and academic discussions in several ways. First, it leverages the power of the TLM to construct the company’s assurance lines through process mining. Second, the real-world application in a multinational company provides a deep understanding of existing controls and monitoring environment. Third, it offers a broad variety of validated use cases that are aligned with the different lines and can be used as a generic framework for using process mining for different assurance activities.</div></div>","PeriodicalId":47170,"journal":{"name":"International Journal of Accounting Information Systems","volume":"56 ","pages":"Article 100731"},"PeriodicalIF":4.1,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143049959","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Excessive custom XBRL tag usage in 10-K filings and SEC oversight","authors":"Joung W. Kim , Daeun Lee","doi":"10.1016/j.accinf.2025.100742","DOIUrl":"10.1016/j.accinf.2025.100742","url":null,"abstract":"<div><div>We conduct an in-depth examination of excessive custom XBRL tag usage in 10-K filings among U.S. firms. We discuss why some firms are prone to creating custom tags in 10-K filings and assess whether such excessive usage is associated with heightened regulatory attention from the SEC. First, we find that firms with weak internal controls are more likely to create custom tags in 10-K filings. Next, we observe a positive association between excessive custom tag usage and SEC oversight, evidenced by a higher likelihood of receiving comment letters and increased SEC involvement, which raises concerns over substantive disclosure deficiencies. In response to increased regulatory scrutiny, we document that firms reduce the proportion of custom tags in subsequent filings, and we find that SEC-reviewed custom tags enhance the informativeness of financial reports for investors. Collectively, our findings suggest that the excessive use of custom tags reflects a manifestation of firms’ disclosure deficiencies, which are mitigated during the SEC review process.</div></div>","PeriodicalId":47170,"journal":{"name":"International Journal of Accounting Information Systems","volume":"56 ","pages":"Article 100742"},"PeriodicalIF":4.1,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143678306","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Earnings management visualization and prediction using machine learning methods","authors":"David Veganzones , Eric Séverin","doi":"10.1016/j.accinf.2025.100743","DOIUrl":"10.1016/j.accinf.2025.100743","url":null,"abstract":"<div><div>To create new insights and understanding of earnings management, this study attempts to diagnose firms’ financial profiles using machine learning methods and thereby provide a visual representation of the financial profiles that characterize earnings management strategies (upward and downward) and tools (accruals and real activities). By applying a novel machine learning method to detect signs of earnings management, this research reveals diverse financial profiles related to earnings management. Firms that conduct downward manipulation (accruals and real activities) share a sound financial profile. For firms that manipulate earnings upward, different types of financial distress influence the earnings management tool they use: Companies with liquidity constraints undertake accruals earnings management; companies with solvency difficulties are prone to real activities management. Notably, the proposed machine learning method outperforms traditional prediction methods in detecting signals of earnings management.</div></div>","PeriodicalId":47170,"journal":{"name":"International Journal of Accounting Information Systems","volume":"56 ","pages":"Article 100743"},"PeriodicalIF":4.1,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143579594","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Yu-Cheng Lin , Roni Padliansyah , Yu-Hsin Lu , Wen-Rang Liu
{"title":"Bankruptcy prediction: Integration of convolutional neural networks and explainable artificial intelligence techniques","authors":"Yu-Cheng Lin , Roni Padliansyah , Yu-Hsin Lu , Wen-Rang Liu","doi":"10.1016/j.accinf.2025.100744","DOIUrl":"10.1016/j.accinf.2025.100744","url":null,"abstract":"<div><div>Accurately predicting a company’s future performance is vital for both management and investors. This study employs the Explainable Artificial Intelligence (XAI) approach, utilizing a Convolutional Neural Network model (CNN) to forecast company financial conditions based on their financial ratios. By transforming financial data into images, we introduce a Bankruptcy Prediction Model (BPM) that enhances interpretability through techniques like Shapley Additive exPlanations (SHAP) and Local Interpretable Model-Agnostic Explanations (LIME). These XAI methods aim to clarify AI decisions in the BPM, addressing the ongoing debate within the financial research community regarding the most informative ratios for bankruptcy prediction. This research marks a significant advancement in financial accounting by merging the transparency of XAI with effective bankruptcy prediction, offering a more comprehensive understanding of financial ratio analysis.</div></div>","PeriodicalId":47170,"journal":{"name":"International Journal of Accounting Information Systems","volume":"56 ","pages":"Article 100744"},"PeriodicalIF":4.1,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143609497","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A practical guide to implementing ChatGPT as a secondary coder in qualitative research","authors":"Eva Blondeel, Patricia Everaert, Evelien Opdecam","doi":"10.1016/j.accinf.2025.100754","DOIUrl":"10.1016/j.accinf.2025.100754","url":null,"abstract":"<div><div>Analyzing interview data provides in-depth insights into qualitative research topics, but is often a time-consuming and costly process. This research aims to enhance this process by leveraging transformative technologies influencing the accounting field, like ChatGPT. ChatGPT is capable of generating human-like text and performing text-based analyses by using a pre-trained model. Specifically, this research illustrates ChatGPT’s role as a secondary coder in deductive qualitative accounting research, analyzing interview transcripts using content analysis with a predefined coding scheme. Data was collected through semi-structured interviews with 36 business economics students. First, the primary researcher manually analyzed the data using a deductive approach. Next, a second human researcher and ChatGPT (ChatGPT-4o Plus) were appointed as secondary coders to independently verify and validate the coding. The paper demonstrates ChatGPT’s potential to assist in coding interview transcripts, emphasizing its role as a supplementary tool in qualitative research. The coding results from both secondary coders were compared with those of the primary human coder, revealing over 99% agreement for both secondary coders. In addition, a step-by-step illustration, best practices, prompts, and critical reflections are shared. This study serves as a foundational step in understanding and leveraging ChatGPT’s use in the analysis of interview transcripts.</div></div>","PeriodicalId":47170,"journal":{"name":"International Journal of Accounting Information Systems","volume":"56 ","pages":"Article 100754"},"PeriodicalIF":4.1,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144631360","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}