This research intends to find out the compliance acts based on the manufacturing industry of Bangladesh and lead to the development of the integrated theory of compliance model. There are several compliance regulations, that are separately dealt with in any manufacturing organization. These compliance regulations are handled at various ends of the organization making the process quite scattered, time-consuming, and tedious. To fix this problem, the integration of organizational compliance regulations is brought under one platform. Researchers have applied the qualitative approach with multiple case studies methodology scrutinizing the in-depth interviews and transcripts. Furthermore, the NVIVO tool has been used to analyze, where the necessary themes of the Organizational Compliance Regulations are found. Therefore, we have proposed a conceptual framework to inaugurate a standalone combined framework, which is an innovative and novel measure.

This study examines how Artificial Intelligence (AI) enhances Sharia compliance within Islamic Financial Institutions (IFIs) by improving operational efficiency, ensuring transparency, and addressing ethical and technical challenges. A quantitative survey across five Saudi regions resulted in 450 validated responses, analyzed using descriptive statistics, ANOVA, and regression models. The findings reveal that while AI significantly enhances transparency and compliance processes, its impact on operational efficiency is limited. Key barriers include high implementation costs, insufficient structured Sharia datasets, and integration complexities. Regional and professional differences further underscore the need for tailored adoption strategies. It introduces a novel framework integrating ethical governance, Sharia compliance, and operational scalability, addressing critical gaps in the literature. It offers actionable recommendations for AI adoption in Islamic finance and contributes to the global discourse on ethical AI practices. However, the Saudi-specific focus highlights regional dynamics that may limit broader applicability. Future research could extend these findings through cross-regional comparisons to validate and refine the proposed framework. By fostering transparency and ethical governance, AI integration aligns Islamic finance with socio-economic goals, enhancing stakeholder trust and financial inclusivity. The study emphasizes the need for targeted AI training, the development of structured Sharia datasets, and scalable solutions to overcome adoption challenges.

This study examines the compliance between the accounting standard for Property, Plant and Equipment (PPE) and accountants’ practices in terms of disclosure and measurement, in order to determine its levels and drivers. Based on the assumption that a higher level of compliance is associated with a higher quality of the accounting information system, compliance indices are proposed and econometric regressions are used to analyze the determinants of this accounting compliance for Portuguese firms. The empirical evidence shows that compliance is not high, and that it tends to be higher for disclosing rather than for measuring. Moreover, the results suggest that firm size has a positive impact on compliance, both for measurement and disclosure, consistent with larger firms being subject to greater scrutiny. Liquidity, on the other hand, tends to have a negative effect on compliance, as more liquid firms are less dependent on external financing. Furthermore, while leverage tends to have a positive effect on measurement compliance, profitability has no effect on accounting compliance. Therefore, this study adds evidence straight from the perceptions of practitioners who interpret and apply accounting standards and then influence the quality of financial reporting, providing valuable insights that have the potential to affect confidence in firms.