This study aims to analyze, investigate the implications, and identify differences in the progress of the effect of institutional changes and organizational transformation in Indonesian higher education. The structuration analysis shows that examining the conditions that have resulted in the replication and modification of social systems is the focus of the structuration analysis. The image of structuration theory conveys both a sense of regularity and continuity, as well as respect for the labor that must be done daily and the mundane but essential tasks that must be completed. The finding of this study is that with the mandate that universities have been given to implement the three primary pillars that support Indonesia’s higher education system, the difficulty level of the problem facing Indonesia’s higher education system has increased. We suggest a future research agenda and highlight the changes and transformations in power, interests, and alliances that affect the evolution of higher education institutions.

The advent of the COVID-19 pandemic has precipitated a paradigm shift in education, marked by an increasing reliance on technology and virtual platforms. This study delves into the post-pandemic landscape of Islamic higher education at the State Islamic Institute of Palangka Raya, Central Kalimantan, Indonesia, focusing on students’ readiness, attitudes, and interests toward sustained engagement with e-learning. A cohort of 300 students across all semesters of Islamic Education partook in the investigation. Utilising Structural Equation Modelling, the study gauged students’ preparedness, perceptions, and inclinations toward online learning. Results indicate a general readiness among students for online learning, with a pivotal role attributed to technological devices and internet connectivity. Positive attitudes toward online learning were prevalent, with flexibility and accessibility emerging as significant advantages. Moreover, students showed keen interest in online learning, valuing its technological advancements, affordability, and intellectually challenging nature. These findings highlight the digital transformation of traditional teaching methods among Islamic higher education students, who are typically known for their emphasis on direct interaction in teaching and learning. Their receptivity to innovative learning modalities and adaptability to the digital era’s difficulties highlight the need for educational institutions to leverage this enthusiasm. Comprehensive online learning platforms, robust technological support, and a conducive learning environment are advocated to empower Islamic higher education students in navigating the digital landscape and perpetuating their pursuit of knowledge and enlightenment.

This paper investigates the impact of financial inclusion on financial stability in BRICS countries from 2004 to 2020. Using a panel smooth transition regression model, the results reveal a U-shaped relationship between financial inclusion and financial stability. Financial inclusion reduces financial stability up to a threshold of 44.7%. Beyond this point, financial inclusion contributes to greater financial stability, through gradual transitions. Enhanced financial inclusion supports banks in stabilizing their deposit funding by facilitating access to more stable, long-term funds and alleviating the negative impacts of fluctuations in returns. Furthermore, the study examines the role of institutional quality in shaping the financial inclusion-financial stability nexus, indicating a significant positive effect, especially in the upper regime. These findings provide valuable insights for financial regulatory authorities, highlighting the importance of promoting financial inclusion in BRICS economies and adapting regulations to mitigate potential risks to global financial stability.

The financial services industry is experiencing a swift adoption of artificial intelligence (AI) and machine learning for a variety of applications. These technologies can be employed by both public and private sector entities to ensure adherence to regulatory requirements, monitor activities, evaluate data accuracy, and identify instances of fraudulent behavior. The utilization of artificial intelligence (AI) and machine learning (ML) has the potential to provide novel and unforeseen manifestations of interconnectivity within financial markets and institutions. This can be represented by the adoption of previously disparate data sources by diverse institutions. The researchers employed convenience sampling as the sampling method. The form was filled out over the period spanning from July 2023 to February 2024, and it was designed to be both anonymous and accessible through online and offline platforms. To assess the reliability and validity of the measurement scales and evaluate the structural model, we employed Partial Least Squares (PLS) for model validation. Specifically, we have used the software package Smart-PLS 3 with a bootstrapping of 5000 samples to estimate the significance of the parameters. The results indicate a positive and direct connection between artificial intelligence (AI) and either financial services or financial institutions. On the contrary, machine learning (ML) exhibits a strong and positive association among financial services and financial institutions. Similarly, there exists a positive and direct connection between AI and investors, as well as between ML and investors.

The rapid advancement of financial technology (Fintech) has revolutionized the way financial transactions are conducted, with E-payment services becoming increasingly integral to daily commerce. This paper examines consumer perceptions and attitudes towards E-payment services offered by Fintech companies, identifying key factors that influence their acceptance and usage. Employing a quantitative approach, the research integrates quantitative data from surveys and applied SEM (Structural Equation Modelling) through AMOS. Out of 450, 420 respondents have given their views on perceptual preferences and attitudes with the help of SPSS. KMO and Bartlett’s Test are executed to understand and to check the factors for implementing factor analysis further through extractions. Anticipated findings are expected to reveal a spectrum of consumer attitudes shaped by factors such as trust, security, convenience, and technological familiarity. It contributes to the existing literature by providing updated insights into consumer behaviour in the Fintech sector and suggesting actionable strategies for service providers to enhance user engagement and satisfaction. It holds the potential to inform both theoretical frameworks in technology acceptance and practical marketing strategies for Fintech companies aiming to optimize E-payment services for diverse consumer bases.