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.

The purpose of this study is to investigate the relationship between the use of business intelligence applications in accounting, particularly in invoice handling, and the resultant disruption and technical challenges. Traditionally a manual process, accounting has fundamentally changed with the incorporation of BI technology that automates processes and allows for sophisticated data analysis. This study addresses the lack of understanding about the strategic implications and nuances of implementation. Data was collected from 467 accounting stakeholder surveys and analyzed quantitatively using correlational analysis. Multiple regression was utilized to investigate the effect of BI adoption, technical sophistication on operational and organizational performance enhancements. The results show a weak association between the use of BI tools and operational enhancements, indicating that the time for processing invoices has decreased. Challenges due to information privacy and bias were significant and negative on both operational and organizational performance. This study suggests that a successful implementation of a BI technology requires an integrated plan that focuses on strategic management, organizational learning, and sound policies This paper informs practitioners of how accounting is being transformed in the digital age, motivating accountants and policy makers to better understand accounting as it evolves with technology and for businesses to invest in concomitant advances.

Using generative artificial intelligence systems in the classroom for law case analysis teaching can enhance the efficiency and accuracy of knowledge delivery. They can create interactive learning environments that are appropriate, immersive, integrated, and evocative, guiding students to conduct case analysis from interdisciplinary and cross-cultural perspectives. This teaching method not only increases students’ interest and participation in learning but also helps cultivate their interdisciplinary thinking and global vision. However, the application of generative artificial intelligence systems in legal education also faces some challenges and issues. If students excessively rely on these systems, their ability to think independently, make judgments, and innovate may be weakened, leading to over-trust in machines and reinforcement of value biases. To address these challenges and issues, legal education should focus more on cultivating students’ questioning skills, self-analysis abilities, critical thinking, basic legal literacy, digital skills, and humanistic spirit. This will enable students to respond to the challenges brought by generative artificial intelligence and ensure their comprehensive development in the new era.

The cars industry has undergone significant technological advancements, with data analytics and artificial intelligence (AI) reshaping its operations. This study aims to examine the revolutionary influence of artificial intelligence and data analytics on the cars sector, particularly in terms of supporting sustainable business practices and enhancing profitability. Technology-organization-environment model and the triple bottom line technique were both used in this study to estimate the influence of technological factors, organizational factors, and environmental factors on social, environmental (planet), and economic. The data for this research was collected through a structured questionnaire containing closed questions. A total of 327 participants responded to the questionnaire from different professionals in the cars sector. The study was conducted in the cars industry, where the problem of the study revolved around addressing artificial intelligence in its various aspects and how it can affect sustainable business practices and firms’ profitability. The study highlights that the cars industry sector can be transformed significantly by using AI and data analytics within the TOE framework and with a focus on triple bottom line (TBL) outputs. However, in order to fully benefit from these advantages, new technologies need to be implemented while maintaining moral and legal standards and continuously developing them. This approach has the potential to guide the cars industry towards a future that is environmentally friendly, economically feasible, and socially responsible. The paper’s primary contribution is to assist professionals in the industry in strategically utilizing Artificial Intelligence and data analytics to advance and transform the industry.

This empirical study explores the influence of Hollywood product placements on cultural perceptions and teaching practices of preservice English teachers in higher education in China. Hollywood movies and TV series routinely use product placements as a tactic to blend commercial goals with compelling storylines, which could possibly influence the perceptions, and potential teaching practice of Chinese preservice English teachers. The purpose of this study is to determine the degree to which material culture in the form of product placement in Hollywood affects preservice English teachers’ image of America, and their future teaching practice, altering their expectations and goals as well as how they view the West. The study uses a quantitative study method by means of an online questionnaire (N = 497) and applies structural equation modelling to conduct data analysis. The results find notable significant relationships including those from food, architecture, transportation, and electronic devices to positive image of America, as well as architecture and transportation to potential teaching practice. The most prominent path is from image to teaching. However, certain relationships, including those from fashion to image and food to teaching, do not demonstrate statistical significance. These results contribute to the theoretical and practical understanding of how preservice English teachers see Hollywood’s material culture, and how it affects their perception and possible teaching methods. The findings also demonstrate how preservice teachers’ perceptions and educational approaches are shaped by Hollywood’s material culture in the form of product placement, while simultaneously emphasizing the significance of integration of media literacy and upholding their cultural identity amidst these influences.

This research addresses environmental, ethical, and health concerns related to high meat consumption, and aims to identify key predictors that encourage a shift towards sustainable diets among young adults. A cross-sectional survey involving 340 students from ten Malaysian universities was conducted using a structured questionnaire. The findings indicate that attitudes, subjective norms, perceived behavioral control, and personal norms significantly predict the intention to adopt plant-based diets. These results have practical implications, suggesting that policymakers, educators, and health professionals should create supportive environments and educational programs that emphasize the benefits of plant-based diets and equip students with the necessary knowledge and skills. Theoretically, the study reinforces the TPB framework’s applicability in understanding dietary behaviors and underscores the importance of personal and social factors in shaping dietary intentions. Ultimately, promoting plant-based diets among university students necessitates a comprehensive approach and strategy addressing attitudes, social norms, perceived control, and personal values. By leveraging these insights, stakeholders can foster sustainable and healthy eating practices among young adults, contributing to broader environmental and public health objectives for sustainable development.