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Title: GDP, Unemployment, Government Expenditure in Bangladesh: Testing the Relevance of Okun’s Law

Abstract: This study examines the dynamic relationship among Gross Domestic Product (GDP), unemployment, and government expenditure in Bangladesh from 2010 to 2025. The analysis highlights a period of robust economic performance, with GDP growth consistently averaging above 6%, driven primarily by manufacturing, garment exports, and the service sector. Despite the significant disruption caused by the COVID-19 pandemic in 2020, which saw growth dip to 3.45%, the economy demonstrated structural resilience and a rapid recovery. Concurrently, government expenditure has expanded significantly as a fiscal tool for development, particularly through large-scale infrastructure projects and social safety nets. Public spending rose from BDT 1,217 billion in 2016 to over BDT 2,218 billion by 2025. However, this expansionary stance has not fully addressed labor market inefficiencies. Unemployment has remained relatively stable between 3% and 5%, suggesting that the link between GDP growth and job creation is weak, thereby offering only limited support for Okun’s Law in the Bangladeshi context. The study identifies persistent structural challenges, including high youth unemployment and skill mismatches, and concludes that inclusive growth policies and labor market reforms are essential to translate macroeconomic gains into sustainable employment generation.

By S.K.S. Yadav, Imran Hosen, Dhwani Gupta
In Volume: 15,Issue: 1
Title: The Dynamics of Broadcasting Law and Reality TV in India: Legal and Ethical Challenges

Abstract: In India, television reality programs have become a popular genre thanks to its relevant themes and lively content. But their quick expansion has spurred discussions about moral behavior, the effects on society, and legal issues. With an emphasis on reality television, this essay critically evaluates India's broadcasting laws and regulations, assessing how well they handle issues with participant exploitation, content manipulation, and cultural deterioration. The paper explores the legal framework that governs broadcasting in India, including the Broadcasting Content Complaints Council (BCCC) and the Cable Television Networks (Regulation) Act, 1995. It draws attention to the shortcomings of current legislation, which is vague in addressing the subtleties of reality programs and results in problems like manufactured narratives, participant psychological suffering, and transgressions of decency standards. These difficulties are highlighted by case studies of well-known programs like Bigg Boss, Indian Idol, and Roadies, which offer insights into the sociocultural ramifications of such programming. The study also identifies areas for improvement by contrasting India's broadcasting laws with international regulatory standards. Among the recommendations are the introduction of specific rules for reality television, the reinforcement of self-control systems, and the encouragement of media literacy among audiences. Reforming broadcasting laws in the digital age is essential, according to the report, which promotes a balanced strategy that protects the public interest, participant welfare, and creative freedom. By emphasizing the necessity of strong controls in India's changing media landscape, this study seeks to advance the conversation on media ethics and policy.

By Jyoti Rawat Lohiya, Sarika Tyagi
In Volume: 15,Issue: 1
Title: Impact of AI-Powered Personalized Learning on Self-Regulated Learning, Academic Engagement, and Learning Autonomy among Secondary School Students

Abstract: There have been numerous ways in which Artificial Intelligence (AI) has revolutionized the educational process through its ability to deliver adaptive instruction, intelligent tutoring, feedback mechanisms, learning analytics, and learning through Generative AI. AI-driven personalized learning is able to provide personalized education for students, thus not only enhancing the academic achievements but also the processes involved in regulating and engaging in learning. Several studies have found that AI is able to facilitate self-regulated learning (SRL), depending on the technological design, instructional context, length of intervention and level of teacher and learner participation (Zhu & Sari, 2026; Xu et al., 2026). The current paper focuses on the possible effect of AI-driven personalized learning on three related learner outcomes including self-regulated learning, academic engagement, and learning autonomy among secondary school students. This research brings together international literature along with Indian literature such as Babbar, Raju and Kumari’s studies regarding Generative AI and Learning Efficiency in the Indian educational setting. The structured research approach and quantitative method are introduced, and then illustrated with statistical findings. The literature indicates that personalisation through AI can be effective in terms of helping learners to monitor and regulate their activities; however, it will not help in case the dependence on technology becomes too high and there is no pedagogical scaffolding present. That is why the paper concludes in favour of human-centered approach and AI as a tool rather than substitution of teachers and cognitive processes.

By Rajesh Kumar Raju, Monika Kumari
In Volume: 15,Issue: 1
Title: Innovative Business Models in Supplying Energy Finance as a Service and Leasing in México

Abstract: This research report examines innovative business models in energy finance as a service (EFaaS) and leasing mechanisms within the Mexican energy sector. As México transitions toward renewable energy and sustainable development goals, novel financing structures have emerged to overcome traditional barriers to energy infrastructure investment. Results demonstrate that energy leasing and service-based models have achieved significant market traction, particularly in commercial solar photovoltaic installations and energy efficiency projects. Findings reveal that successful models incorporate flexible payment structures, comprehensive maintenance services, and performance guarantees that align incentives between service providers and clients. The discussion addresses regulatory enablers, financing innovations, and technology integration strategies that facilitate model adoption. The report concludes that EFaaS and leasing models represent transformative mechanisms for accelerating Mexico's energy transition, with implications for policy development, financial sector engagement, and sustainable infrastructure deployment.

By José G. Vargas-Hernández, Dra. Patricia Villasana-Ramos, M. C. Omar C. Vargas-González
In Volume: 15,Issue: 1
Title: Financial Performance Evaluation of NSE AND BSE: A Comparative Assessment of Revenue Structure, Operating Efficiency, and Profitability (2020–2025)

Abstract: Stock exchanges play a crucial role in today’s financial systems by providing platforms for raising capital, enhancing market liquidity, and fostering economic growth. The National Stock Exchange of India Limited (NSE) and BSE Limited (BSE) in India have witnessed a sea change in the last decade due to technological advancements, regulatory reforms and increasing retail participation. They are regulated in the same way but differ in their revenue models, operating efficiencies and profitability. The present study has made a comparative analysis of the financial performance of NSE & BSE for the period 2020-2025 with the help of secondary data collected from the annual reports & financial statements. Various approaches such as trend analysis and comparative ratio analysis are studied for key performance indicators such as revenue growth, operating margin, and return on equity. Initial results show NSE is operationally more efficient and profitable mainly due to its dominance in the equity derivatives and technology-based product market. By contrast, BSE has focused on innovations in SME listings and mutual fund platforms, but its scale is small. This research adds to the literature on financial market infrastructure by providing insight to regulators, investors and researchers.

By Shamshad Khan, Arvind Kumar Yadav
In Volume: 15,Issue: 1
Title: Digital Payments and Fraud in India: A Systematic Review of UPI's Growth and Machine Learning-Based Detection Frameworks

Abstract: India's Unified Payment Interface (UPI) can be stated as the most revolutionary payment system of the twenty-first century. It processed over 21 billion transactions worth ?27.97 lakh crore in December 2025 alone. These figures dictate both its remarkable reach and the security challenges it presents. Since its launch in April 2016 by the National Payments Corporation of India (NPCI), UPI has outpaced traditional digital payment systems, and now over 85% of digital transactions in India are done using UPI. Though the growth is remarkable, it allows new kinds of frauds and scams to arise. Studies show that digital fraud has surged by 346% during COVID-19. This paper examines the empirical and review studies from 2017 to 2026 related to the intersection of UPI’s exponential growth and evolving landscape of digital payment frauds in India. The study critically evaluates the most dominant types of fraud typologies, like phishing, QR code manipulation, KYC impersonation, and social engineering scams, along with the methods used for the prevention of such types of fraud, like machine learning and deep learning architectures. The review finds that machine learning and deep learning architectures achieved over 99% accuracy in the detection of fraud. There are still persistent challenges like class imbalance, data privacy, and adaptive fraudulent behavior. The paper argues that effective fraud mitigation and prevention require more than algorithmic advancement. A multi-layered response integrating system, regulatory dimensions, and user awareness is still required to tackle and prevent fraudulent activities.

By Abhishek Mishra and Dr. Mahendra Pal Singh Yadav
In Volume: 15,Issue: 1

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