Global Nexus of Multidisciplinary Research

Work–life balance has emerged as a critical concern in the higher education sector, particularly for women faculty members employed in self-financing colleges. These institutions, driven largely by market-oriented models and financial sustainability goals, often impose intensive workloads, performance pressures, and extended working hours on academic staff. Women faculty members, who simultaneously manage professional responsibilities and socio-cultural expectations, related to family and caregiving roles, face compounded challenges in maintaining a healthy balance between work and personal life. This article explores the experiences of women faculty in self-financing colleges, focusing on institutional pressures that influence their work–life balance. Drawing upon existing literature, contextual analysis, and experiential insights, the study examines key stressors such as workload intensification, job insecurity, administrative demands, gendered expectations, and limited institutional support mechanisms. The article concludes with policy recommendations aimed at fostering gender-sensitive institutional practices and promoting sustainable academic work environments.

Youth employment has emerged as a significant socio-economic issue in rural areas of Tamil Nadu, where limited employment opportunities and inadequate skill development often affect the livelihoods of young individuals. The present study aims to analyze the challenges faced by rural youth in obtaining employment opportunities and to examine the potential initiatives that can promote youth employment in rural Tamil Nadu. The study is based on both primary and secondary data. Primary data were collected from 150 rural youth respondents through structured questionnaires and interviews, while secondary data were gathered from government reports, journals, and related publications. A descriptive research design was adopted, and statistical tools such as percentage analysis, descriptive statistics, multiple regression analysis, and ANOVA were used for data analysis through SPSS software. The findings of the study reveal that limited educational qualifications, lack of skill development opportunities, and inadequate awareness about employment programs are major factors affecting youth employment in rural areas. The analysis also indicates that agriculture and small-scale businesses remain the primary sources of livelihood for rural youth. However, skill development programs, government employment schemes, and rural entrepreneurship initiatives provide significant opportunities for improving employment prospects. The study concludes that strengthening vocational training, promoting entrepreneurship, and improving rural infrastructure can significantly enhance employment opportunities for rural youth. Effective collaboration between government institutions, educational organizations, and local communities is essential to ensure sustainable youth employment and balanced rural development in Tamil Nadu.

Higher education plays an important role in promoting economic growth, social development, and human capital formation. In recent decades, the demand for higher education in Tamil Nadu has increased significantly due to population growth, technological advancement, and rising career aspirations among students. Government and aided institutions alone have not been able to meet this growing demand, leading to the rapid expansion of self-financing colleges across the state. These institutions have emerged as an important component of the higher education system by providing additional educational opportunities and introducing diverse academic and professional programs. The present study aims to analyze the role of self-financing colleges in the development of higher education in Tamil Nadu and to examine the challenges and opportunities associated with these institutions in providing quality education. The study adopts a descriptive research design and uses both primary and secondary data. Primary data were collected from 150 students studying in selected self-financing colleges using a structured questionnaire, while secondary data were obtained from journals, books, and educational reports. Statistical tools such as Percentage Analysis, Factor Analysis, ANOVA, Chi-Square Test, and Multiple Regression Analysis were used to analyze the data. The findings of the study reveal that self-financing colleges have significantly contributed to the expansion of higher education by increasing student enrolment, improving infrastructure facilities, and offering skill-oriented courses. The results also indicate that factors such as infrastructure facilities, teaching quality, and skill development programs play a significant role in enhancing higher education development. However, the study also identifies several challenges faced by students, including high tuition fees, limited research facilities, and inadequate industry exposure. The study suggests that effective regulatory policies, improved faculty development programs, and stronger industry collaboration can enhance the quality and accessibility of higher education in self-financing colleges.

Financial inclusion has emerged as a critical pillar for sustainable economic growth, particularly in developing economies. The integration of digital currencies and financial technology (FinTech) platforms has significantly transformed the traditional banking landscape by expanding access to financial services. This paper examines how digital currencies and FinTech innovations contribute to financial inclusion and analyzes their potential role in reducing Non-Performing Assets (NPAs) in the banking sector. By enhancing credit assessment mechanisms, improving transparency, and strengthening repayment monitoring systems, digital financial ecosystems can mitigate credit risk and improve asset quality. The study concludes that strategic adoption of digital financial infrastructure can simultaneously deepen inclusion and strengthen banking stability.

The rapid advancement of Artificial Intelligence (AI) and Big Data technologies has significantly transformed the financial technology (FinTech) trading ecosystem. Traditional trading systems relied heavily on human judgment and limited historical data analysis. However, the integration of AI-driven algorithms and large-scale data analytics has enhanced trading efficiency, predictive accuracy, and risk management. This paper explores the role of AI and Big Data in FinTech trading, focusing on algorithmic trading, predictive modeling, sentiment analysis, fraud detection, and portfolio optimization. AI technologies such as machine learning, deep learning, and natural language processing enable traders and institutions to process vast volumes of structured and unstructured data in real time. Big Data analytics facilitates high-frequency trading, pattern recognition, and data-driven decision-making. The study also examines the benefits, including improved market efficiency and reduced transaction costs, alongside challenges such as data privacy concerns, algorithmic bias, regulatory issues, and systemic risks. Through secondary data analysis and review of recent industry developments, the paper highlights how AI-powered trading platforms are reshaping global financial markets. The findings suggest that while AI and Big Data enhance competitiveness and innovation in FinTech trading, appropriate governance frameworks and ethical standards are essential to ensure market stability and transparency. The paper concludes that AI and Big Data will continue to play a pivotal role in shaping the future of automated trading and financial market operations.