Purpose: The purpose of this paper is to explore the impact of Artificial Intelligence on the performance of Indian Banks in terms of financial metrics. The study focused specifically on the NIFTY Bank Index. The paper also advocates that a greater transparency in disclosing AI related information in a Bank’s annual report is required even if it is voluntary. Design/Methodology/Approach: The paper uses a mixed method approach where quantitative and qualitative analysis is combined. A dynamic panel data model is used to understand the impact of AI of Return on Equity (RoE) of 12 Indian Banks in the NIFTY Bank Index over a five-year period. In addition to that, Content analysis of annual reports of banks was conducted to examine AI related disclosure and transparency. Findings: The paper highlights that the integration of Artificial Intelligence (AI) significantly influences the financial performance of sample banks of India. Return on Equity the specific parameter positively influenced with adoption of AI. The profitability of banks is positively impacted by reduced errors and improved operational efficiency. The content analysis of annual reports of the banks indicates different approach for AI disclosure where some banks give detailed information and some are not transparent about AI initiatives. The findings suggest that a higher level of transparency could enhance confidence of all stakeholders. Theoretical Implications: The positive relation between adoption of AI and financial performance, specifically ROE, gives a foundation for academic research to explore the dynamics of emerging technology and financial systems. The study can be extended to explore the impact on other performance indicators in different sectors. Practical Implications: The findings of this study emphasize the importance of transparent AI related disclosures. A detailed reporting about integration of AI helps in enhanced stakeholders’ confidence in case of banking industry. The regulatory framework of banks may also consider making mandatory AI disclosure practices to ensure due accountability to maximize the benefits of AI in banking.

This study investigates the factors influencing student satisfaction at higher education institutions in Pathum Thani Province, Thailand. The research uses structural equation modeling (SEM) to analyze the connections among College Reputation, Student Expectation, Perception Value, and Student Satisfaction based on a sample of 660 students. The results indicate that the student population is diverse, with most students enrolled in the Faculty of Business Administration in their first year. The Pearson’s correlation matrix and structural equation modeling (SEM) findings indicate significant positive correlations between the dimensions, emphasizing the crucial influence of College Reputation on both Student Expectation and Student Satisfaction. The goodness-of-fit indices validate the model’s strength, indicating a significant correspondence between the theoretical components and the observed data. This study enhances the comprehension of how student satisfaction changes in Thai higher education and offers practical suggestions for institutional policies to improve student’s educational experiences and achievements. Higher education institutions may create a more fulfilling and effective learning environment by prioritizing reputation improvement, ensuring student expectations match reality, and providing perceived value to improve education quality and equality for Thailand.

This article explores the landscape of entrepreneurship education in Indonesia amid the wave of digital transformation. The research method uses Systematic Literature Review (SLR) to review research results sourced from journals indexed in Sinta or nationally accredited journals in Indonesia which can be accessed on Google Scholar. The conclusion, (i) Digital transformation-based entrepreneurship education creates a new learning model in colleges with the aim of developing entrepreneurial attitudes and values among young people, especially students, so as to produce entrepreneurial intentions. (ii) Higher education as an entrepreneur education provider must follow the progress of digital transformation in the teaching process of entrepreneurship education so that digital literacy among lecturers and students is getting better. (iii) The participation of stakeholders, the Government, college and the business world, is expected to provide support in policy making, especially curriculum changes in accordance with current circumstances in creating new business actors or entrepreneurial intentions.

The study aims to explore the impact of examination-oriented education on Chinese English learners and the importance of cultural intelligence in second language acquisition. Through a questionnaire administered to postgraduate students majoring in English in China, the research discovered that the emphasis on test scores and strategies in China’s higher English education system has led to a neglect of cultural backgrounds and cross-cultural communication. The findings underscore the necessity for reforms in English teaching within Chinese higher education to cultivate students’ intercultural intelligence and enhance their readiness for international careers in the era of globalization.

Poverty is a major challenge caused by various situations as well as cultural, social, economic, and political interactions. Therefore, poverty alleviation programs and strategies require an integrated approach carried out in consistent and organized stages. It required the participation of all parties, both regional heads, Regional People’s Representative Assembly (RPRA) members, entrepreneurs, and other elements of society. This study aimed to investigate the effect of local spending efficiency on public welfare in Indonesia, using a quantitative and explanatory method. The analysis method used in this study is the panel data regression model. The research population in all provinces in Indonesia was 34 provinces, and a purposive sampling method was used, where a total of 26 provinces were selected. The research period is 2017–2021. The efficiency of local spending (education, health, and infrastructure) is estimated using the Stochastic Frontier Analysis (SFA) cost function approach. The results showed that the higher the efficiency of education spending, the more it will increase public welfare in Indonesia. Meanwhile, the health spending efficiency and the infrastructure spending efficiency do not affect public welfare. The implications of this study for the development of science are that the efficient allocation of education spending will be able to improve the quality of education which is a long-term solution to overcome poverty in Indonesia and for policymakers to be able to optimize education spending to achieve the expected educational goals.