The primary objective of this research was to investigate the potential moderating role of audit fees in the relationship between audit committee characteristics and earnings management. Specifically, this study aimed to establish connections between audit committee features, such as committee size, member independence, and financial expertise, and the practice of earnings management. To address these research questions, a convenient sample of 46 service providers listed on the Amman Stock Exchange between 2016 and the subsequent year was employed. Descriptive statistical methods were applied to characterize the variables under investigation, while a multiple regression model was utilized to assess the study’s hypotheses. The findings of the study revealed that there was no significant correlation between the size of the audit committee and earnings management. However, a negative correlation was observed between the audit committee’s independence and the financial expertise of its members. Importantly, when audit fees were introduced as a moderating variable, the relationships between committee member independence and earnings management, as well as between committee member financial expertise and earnings management, were found to be weakened. These results have potential implications for policymakers and regulators in Jordan. They may offer valuable insights into corporate governance reforms that could assist Jordanian businesses in enhancing their earnings management practices.

Introduction: The study examined the ongoing issue of identifying financial fraud in emerging economies, concentrating on companies listed on the Amman Stock Exchange (ASE).Methods: A panel of 176 ASE-listed enterprises was studied from 2011 to 2021. Starting with a preliminary analysis of Beneish M-Score constituents and associated metrics, a supervised neural network (FNN) had been trained, and an ordinary least-squares (OLS) analysis was computed. The performance study was executed using reliability, recall, reliability, F1-score, and ROC-AUC.Results: The FNN achieved an accurate identification rate of 0.9844 with a recall of 1.0, indicating it accurately identified all fraudulent transactions in the experimental dataset. The ROC-AUC was 0.97. The OLS model, albeit less precise, demonstrated statistically significant correlations—particularly for GMI, SGAI, and LVGI—with the Beneish M-Score, thereby providing interpretable risk indicators.Conclusions: The study revealed that deep learning, namely a feedforward neural network (FNN), surpassed a traditional ordinary least squares (OLS) method in detecting fraud among ASE enterprises, whereas OLS offered contextual information about the factors associated with fraud. An integrated analytical framework was proposed to assist regulators and investors in achieving improved transparency and early warning in the Jordanian market.

A historical exploration of Islamic Accounting Standards is presented in this paper. The fundamental players’ roles in the emergence and expansion of Islamic accounting standards are also identified. To collect data, documents were examined and key players that are involved in the development of Islamic Accounting Standards were interviewed. It has been determined that the Dubai International Finance Centre (DIFC) primarily sets Islamic Accounting Standards in the UAE. Since the reporting standards and backgrounds of accountants may have global effects beyond their jurisdictions, this study suggests accounting standards setters with differences in the ideological and religious backgrounds should communicate with one another in an era of globalization.

Yet the boom in digital financial services has also resulted in deeper financial inclusion, but also greater exposure to fraud and cyberthreats — particularly for digital banks and microfinance providers operating in high-transaction, low-infrastructure contexts. We systematically chart the argument-theory that constitutes real-time fraud risk management in digital microfinance, featuring digital know your customer (KYC), large scale transaction-monitoring and adaptive risk-stratification. By way of a mapping systematic literature review, the study weaves together insights from transaction theory, digital trust models, and regulatory compliance strategies to identify organizing principles to overcome the tension between access and fraud risk. These captured and harvested circular contributions led, other than repeatedly identified obstacles for practical utilization such as integration barriers and scaling issues, to insights on what to do and how, to problematic deployment in a context-agnostic way. The results create best practice strategies and policy-relevant recommendations that are critical to resolving issues of trust and safeguarding clients. The primary original contribution is through a solid, absorptive experiential model towards the formation of fraud prevention interventions in digital microfinance that underpin institutional trust and financial service inclusion.

This study examines the factors influencing tax decision-making from the perspectives of income and sales auditors in Jordan. It explores how internal and external factors shape auditing processes and compliance. Using a sample of 215 tax auditors from 2018 to 2022, this study adopts a quantitative methodology and collects data through structured surveys. The findings highlight key variables such as auditor independence, professional experience, and taxpayer knowledge as significant factors influencing tax decisions. The study recommends enhancing auditor training, fostering independence, and improving taxpayer education to promote transparency and fairness in tax systems.

This study investigates the influence of digital leadership skills and dynamic, innovative work environments on firm performance in China’s IT sector, with digital innovation acting as a mediating factor. Drawing on the Dynamic Capabilities View (DCV) and the Resource-Based View (RBV), we develop and test a framework that combines leadership, workplace, and innovation perspectives. Using data from 338 managers in IT manufacturing companies in Guangdong and Zhejiang, the model was evaluated with PLS-SEM for causal links and Artificial Neural Networks (ANNs) for predictive validation. Results show that digital leadership significantly boosts performance both directly and indirectly through digital innovation, while workplace dynamism improves performance directly but not via innovation. This non-significant mediation suggests that in China’s IT sector, cultural and institutional factors may allow workplaces to influence outcomes independently of technological innovation. By combining SEM and ANN, the study offers a methodological contribution and clarifies how leadership and workplace dynamics jointly shape digital transformation outcomes in an emerging economy context.