The purpose of this study is to investigate the influence of environmental disclosure and corporate governance on the financial performance of Islamic banks in Saudi Arabia. This study highlights that sustainable practices are transparent with financial objectives using the religious framework of Islamic finance. This research is based on Worldwide Vision 2030, which covers sustainable development and promotes environmental, social, and governance (ESG) principles, as well as corporate governance factors, such as board composition and Shariah Supervisory Boards (SSBs). We use a hybrid approach for our findings, with a dataset spanning 2011–2023 for the quantitative analysis and 20 semi-structured analyses conducted for a qualitative approach that aligns with objectives. We found that environmental disclosure boosts profits and stakeholder trust. Corporate governance structures, such as environmental boards and sustainability committees, improve the environmental disclosure of financial performance in Islamic banks. In this positive interaction, specialized governance drives Sharia-compliant sustainability initiatives. SSBs help Islamic banks integrate sustainability and meet religious and ESG environmental standards. Board diversity and dedication in the sustainability committee both play important roles in enhancing environmental disclosure practices; in return, these improved financial performances. The interaction of environmental disclosure and board environmental expertise has a positive impact on the overall performance, which indicates that governance structure supports sustainability-related decision-making, aligning with transparency. This study suggests that Islamic banks standardize ESG frameworks, improve board environmental expertise, and invest in real-time sustainability reporting digital solutions. Saudi Islamic banks can lead regional and global sustainable banking by adopting these strategies to align with global sustainability trends, improve financial performance, and meet ethical finance expectations.

With the use of digital technologies in today’s innovation era, the financial sector has transformed how they facilitate customer business and generate a high level of revenue. This study aims to explore the relationship between innovative work behavior (IWB), digital transformation (DT), and organizational financial performance (OFP) to analyze the mediating role of workers’ psychological empowerment (PE) between independent and dependent variables. Further, we examined the moderating role of smart technologies (ST) between PE and OFP. This study collected data from Saudi banking sector employees using a well-structured questionnaire adopted from previous literature. Next, Smart-PLS was used to analyze the data using the structural equation modeling-partial least squares (SEM-PLS) approach. The results reveal that IW positively relates to OFP, with PE mediating this relationship. Furthermore, DT positively affects OFP. ST acts as a positive moderator that enhances workers’ PE and OFP. Meanwhile, PE, as a mediator, positively relates DT and IWB to OFP. Overall, this study makes valuable theoretical, empirical, and practical contributions, which can benefit bank management, policymakers, and future academic research.

This study investigates the impact of human-like features and student perceptions on the intention to adopt Artificial Intelligence (AI)-based teaching assistants (AITAs) in higher education. Grounded in the Technology Acceptance Model, the study explores the roles of anthropomorphism, social language use, engagement quality, perceived usefulness, and ease of communication in shaping students' attitudes toward AITAs and their subsequent intention to adopt these technologies. Data were collected from 385 students in Ha'il Province, Saudi Arabia, using a structured questionnaire. The data were analyzed through Partial Least Squares Structural Equation Modeling to assess both direct and mediating effects. The findings reveal that all proposed factors have a positive influence on students' attitudes, which, in turn, significantly predict their intention to adopt AITAs. Furthermore, students' attitudes mediate the relationships between human-like features and adoption intentions. This research offers both theoretical insights and practical implications for integrating AITAs in educational contexts, highlighting the importance of designing AI systems that facilitate human-like interactions and promote positive student perceptions.