Jul 2026· Current: Jurnal Kajian Akuntansi dan Bisnis Terkini· Vol 7, pp. 468-486· 0 citations
TL;DR
This study examines the determinants of electronic audit quality by integrating Resource-Based View and UTAUT by establishing that organizational digital capability amplifies AI quality contributions in a type-specific rather than uniform manner, offering evidence-based guidance for sustainable audit technology adoption.
Abstract
The rapid adoption of artificial intelligence (AI) and digital audit systems has produced inconsistent findings regarding their impact on audit quality. This study examines the determinants of electronic audit quality (E-AQ) by integrating Resource-Based View (RBV) and Unified Theory of Acceptance and Use of Technology (UTAUT), with Sustainable Audit Digital Innovation (SADI) as a moderating variable. A quantitative approach was applied to 243 auditors from 25 non-Big Four public accounting firms in Semarang using convenience sampling and PLS-SEM. General qualification, electronic qualification, independence, due professional care, assisted AI, augmented AI, autonomous AI, and SADI positively influence E-AQ, while task complexity negatively affects it. SADI moderation is selectively synergistic, significant only for augmented AI among the three AI types. Theoretically, this study extends RBV and UTAUT by establishing that organizational digital capability amplifies AI quality contributions in a type-specific rather than uniform manner, offering evidence-based guidance for sustainable audit technology adoption.
This study proposes a theoretical framework to explain auditors’ intention to use AI in Vietnam and proposes willingness to learn AI (WLA) is proposed as a mediating mechanism through which performance expectancy, effort expectancy, and social influence affect intention to use AI.
Linh-Giang Le Nguyen· Journal of Economics, Busine...· 0 citations
The rapid advancement of digital technologies has transformed audit practices, creating opportunities and challenges for maintaining audit quality. Drawing on the Theory of Planned Behavior, this study investigates the effects of Artificial Intelligence (AI), Big Data Analytics (BDA), and Time Pressure on audit quality, while examining the moderating role of Ethical Culture. Using a quantitative approach, questionnaire data were collected from 99 external auditors across 25 Public Accounting Firms in Semarang, Indonesia, and analyzed using Partial Least Squares Structural Equation Modeling. The results indicate that AI and Time Pressure significantly improve audit quality, whereas BDA has no significant effect. Ethical Culture weakens the relationship between Time Pressure and audit quality but does not moderate the effects of AI or BDA. These findings extend the Theory of Planned Behavior by demonstrating that organizational ethical conditions influence how auditors respond to time constraints in technology-enabled audit environments. Practically, the study highlights the need to strengthen ethical culture, organizational readiness, and auditors' digital capabilities to optimize technology adoption and sustain audit quality.
This study examines the determinants of AI-enhanced modern audit capabilities and their effects on audit quality and work performance in an emerging market context, using evidence from certified public accountants in Thailand. AI-enhanced modern auditing is conceptualized as intelligent planning, AI-assisted procedures, and adaptive audit responses. Comprehensive audit expertise reflects technical proficiency, professional experience, and rigorous risk assessment, while audit quality management captures adherence to professional standards and ethical discipline. Grounded in Dynamic Capability Theory and the Resource-Based View, audit quality is specified as a mediating mechanism linking these capability dimensions to work performance. Survey data from 208 certified public accountants were analyzed using covariance-based structural equation modeling. The findings indicate that AI-enhanced modern auditing, audit expertise, and audit quality management have statistically significant positive effects on audit quality and work performance. Audit quality also positively contributes to work performance and partially mediates the relationships among the capability constructs. However, the results exhibit limited explanatory power, suggesting that these capabilities function as necessary but modest drivers of audit outcomes. The study integrates technological, human capital, and governance-based perspectives and provides emerging market evidence on the constrained yet meaningful role of AI-enabled audit capabilities in supporting audit quality and auditor performance.
Artificial intelligence is rapidly transforming marketing by improving customer engagement and operational efficiency. Small and medium-sized enterprises (SMEs), especially in Qatar, are not able to adopt AI due to high adoption costs, poor technological skills and employee resistance. A thorough and methodological literature review was conducted to get a grasp on the factors influencing AI adoption and the subsequent effect on marketing performance. In accordance with the PRISMA guidelines, 32 peer-reviewed publications from 2020 to 2025 were analysed by applying a CASP/AMSTAR checklist, thematic coding and narrative analysis. The literature review has identified that technological readiness, managerial support, digital literacy and environmental factors are the major facilitators of AI adoption. However, context and organisational challenges are the main inhibitors of AI adoption. Nevertheless, the literature affirms that AI adoption increases the marketing performance of SMEs, and the TOE and DOI models are supported, while recommending a merger with the dynamic capabilities theory. Finally, the literature review asserts that policymakers and SME managers need to prioritise training, infrastructure and digital readiness to ease the path for AI adoption.
Salma El-Gohary, Mohamed Slim Ben Mimoun, Hatem El-Gohary· Journal of Cultural Analysis...· 0 citations
In the digital economy era, digital transformation has become a key strategy for enterprises to improve competitiveness. This study uses data from Shanghai and Shenzhen A-share listed companies in China from 2010 to 2023 to examine the impact of corporate digital transformation on audit quality and audit inputs. The results show that digital transformation significantly improves audit quality by enhancing internal control and information transparency. At the same time, it increases audit inputs because of greater operational and system complexity. The effects exhibit significant heterogeneity across audit firms. Non-Big Four auditors achieve greater audit-quality improvement but face substantially increased audit effort, while Big Four firms experience limited changes in both audit quality and audit inputs. The findings reveal a digital divide in audit capabilities, in which technological disparities between large and small audit firms lead to different adaptation patterns. This study provides empirical evidence for understanding how enterprise digital transformation reshapes audit risk assessment, audit-resource allocation, and audit-service quality in the digital economy.
Y. N. He, S. Li, Y. Wu et al.· Advanced Electromagnetics· 0 citations
The digital transformation of the auditing profession is
accelerating as firms adopt technologies such as artificial
intelligence, blockchain, big data analytics, and robotic
process automation. While a growing body of international
literature documents the benefits and risks of these tools,
there is a lack of knowledge about auditors’ perceptions in
the Middle East. This study responds to that gap by
examining how Lebanese auditors perceive the benefits,
challenges, costs, and impacts of emerging technologies.
Building on the Technology Acceptance Model and recent
audit innovation literature, hypotheses were developed
that perceived usefulness (benefits) and ease of use
(captured through perceived costs and challenges)
influence auditors’ intention to adopt digital tools. A cross
sectional survey was distributed to Lebanese external
auditors. Eighty-four responses were analyzed using
descriptive statistics and Mann-Whitney U tests to
compare perceptions between technology users and non-
users. Results indicate that big data analytics is the most
widely adopted technology among Lebanese auditors.
Specifically, users of big data analytics reported
significantly higher median scores for perceived benefits
(e.g., improved audit quality, the ability to analyze
complete data sets, and real-time auditing) compared to
non-users. Its users also report significantly higher
benefits (e.g., improved audit quality, the ability to analyze
complete data sets, and real-time auditing) and impacts
on their work compared with non-users. Conversely,
adoption of artificial intelligence, blockchain, robotic
process automation, and metaverse tools remains limited,
and no significant differences were found between their
users and non-users.Across all technologies, auditors expressed high levels of
concern about cyber security, skills shortages, legal
uncertainties, and start up costs were perceived as high.
The findings contribute to audit technology literature by
providing evidence from a developing country context and
by extending Technology Acceptance Model to
incorporate perceived cost and risk factors. Practical
implications for regulators and practitioners include the
need for targeted training programs, supportive regulatory frameworks, and incentives to encourage investment in digital tools. Directions for future research are also
discussed.
Walaa Khoder Kattar, Mehmet Nuri Salur· Audit Financiar· 0 citations
