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.
Abstract: Artificial Intelligence (AI) has emerged as a transformative force that is redefining the way organizations approach digital transformation. By enabling intelligent automation, advanced data analysis, predictive decision-making, and personalized customer experiences, AI has become a key driver of innovation and organizational competitiveness. Despite its growing adoption, organizations continue to face several challenges, including ethical concerns, data privacy issues, cybersecurity risks, workforce adaptation, and implementation costs. This study examines the role of Artificial Intelligence in digital transformation by synthesizing evidence from recent academic literature, industry reports, and credible institutional publications. The paper adopts a qualitative approach based on secondary sources to explore how AI contributes to organizational transformation across different sectors. The analysis highlights that successful digital transformation depends not only on technological adoption but also on organizational readiness, effective leadership, employee capabilities, and responsible governance. The study further discusses the opportunities created by AI, the barriers affecting its implementation, and the future directions that can support sustainable digital transformation. The findings provide valuable insights for researchers, business leaders, and policymakers seeking to understand the evolving relationship between Artificial Intelligence and digital transformation in the modern business environment.
Abstract: Democracy is a way of life. It provides “Possibility of concurrence in action without the preliminary necessity of shared religion, moral conviction or political program. The democratic temper may lead to readiness to accept an other’s truth to be as good as his own, and therefore to enter into community, so far as it is possible to secure a reconciliation. ‘Democracy is traditional to level for the so called fundamental issues, which in any view, remain fundamental even if a number of schools apparently consider them obsolete’. The expressions ‘democracy’ and ‘democratic’ have been used in varying senses in different countries and in many places have been subjected to denote the state of affairs which is in complete negation of the meaning in which they are understood. The three spheres of Democracy are Political, economic and social. Political democracy means the Government by the people, economic democracy connotes the control of the means of production and social democracy means the abolition of social Privileges.
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.
Abstract: Artificial Intelligence (AI) has emerged as a transformative force that is redefining the way organizations approach digital transformation. By enabling intelligent automation, advanced data analysis, predictive decision-making, and personalized customer experiences, AI has become a key driver of innovation and organizational competitiveness. Despite its growing adoption, organizations continue to face several challenges, including ethical concerns, data privacy issues, cybersecurity risks, workforce adaptation, and implementation costs. This study examines the role of Artificial Intelligence in digital transformation by synthesizing evidence from recent academic literature, industry reports, and credible institutional publications. The paper adopts a qualitative approach based on secondary sources to explore how AI contributes to organizational transformation across different sectors. The analysis highlights that successful digital transformation depends not only on technological adoption but also on organizational readiness, effective leadership, employee capabilities, and responsible governance. The study further discusses the opportunities created by AI, the barriers affecting its implementation, and the future directions that can support sustainable digital transformation. The findings provide valuable insights for researchers, business leaders, and policymakers seeking to understand the evolving relationship between Artificial Intelligence and digital transformation in the modern business environment.
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.