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Title: Impact of Digital and Social Media Advertising on Millennial Consumers

Abstract: Generation Y, commonly identified as Millennials, comprises individuals born between 1981 and 1996. Characterized by profound digital immersion and technological proficiency, this cohort has been significantly influenced by the pervasive expansion of social media. Consequently, social media advertising has emerged as a formidable catalyst in shaping their purchase intentions, consumption patterns, and brand preferences. The present study investigates the multifaceted influence of social media advertising on the buying behaviour of Generation Y consumers within the contemporary digital marketplace. The findings unequivocally demonstrate that social media advertising exerts a profound influence on the lifestyle orientations, consumption behaviour, and purchase decision-making processes of Generation Y consumers. The ubiquitous proliferation of digital platforms such as Instagram, Facebook, YouTube, WhatsApp, and X (formerly Twitter) has fundamentally reconfigured the dynamics of consumer–brand interaction. By facilitating instantaneous access to comprehensive product information, authentic consumer reviews, algorithmically curated recommendations, and influencer-generated endorsements, social media advertising substantially shapes consumer perceptions, reinforces purchase intentions, and cultivates enduring brand predispositions within the contemporary digital ecosystem. The study further highlights that Generation Y consumers actively engage with digital content and rely heavily on online reviews and peer recommendations before making purchases. Businesses and marketers can therefore better understand consumer expectations and design effective advertising strategies to attract and retain this segment. The research concludes that social media advertising has become an essential marketing tool influencing Generation Y’s buying behaviour in the modern digital economy.

By Swati Agarwal
In Volume: 15,Issue: 1
Title: A Qualitative Analysis of 40 Case Studies on BUBT Students' Admission Experience and Satisfaction

Abstract: Based on in-depth case studies of forty students from all academic departments, this study offers a thorough qualitative examination of the admission experiences and satisfaction of students at Bangladesh University of Business and Technology (BUBT). This study finds important factors impacting admission decisions, student happiness, and retention intentions using NVivo 14 software for rigorous qualitative data analysis. The results show a complicated paradox: although 90% of students selected BUBT mainly because of its reasonably priced tuition (20,000–25,000 BDT per semester), they also voiced serious discontent with the qualifications of the instructors, classroom conduct, bullying on Facebook, and subpar housing. With 92.5% of female students satisfied, the proctorial system was found to be the most favorable element. Nonetheless, 65% of students said they had witnessed or experienced instructor annoyance in the form of yelling, canceling classes, or acting insultingly, and 85% of students desired senior teachers with PhDs. The fact that 80% of students said they would be willing to pay an additional 5,000–10,000 BDT per semester if BUBT hired internationally renowned PhD staff and addressed behavioral concerns with teachers is also remarkable. Additionally, 45% of students saw their institution rating as a direct advantage for their own careers, according to the report. Eight evidence-based recommendations, with projected implementation timescales ranging from immediate to two years, are included in the research's conclusion. These recommendations include urgent PhD faculty recruitment, teacher training programs, hostel expansion, and official Facebook group moderating.

By S.K.S. Yadav, Tasfiunnoor Pinky, Dhwani Gupta
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: The Role of Artificial Intelligence in Digital Transformation: opportunities, challenges and Future Directions

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.

By S.K.S. Yadav, Kavita
In Volume: 15,Issue: 1
Title: Technology as a Catalyst for Global Change: Innovation, Equity, and Sustainable Transformation

Abstract: Technology has emerged as a transformative force shaping global development, social equity, and environmental sustainability. From artificial intelligence and digital health systems to renewable energy and smart infrastructure, technological innovation is redefining economies, governance, and human well-being. However, unequal access to digital resources, infrastructural disparities, and ethical challenges continue to widen global inequalities. This chapter explores how technology functions as a catalyst for global change by examining its role in innovation ecosystems, social inclusion, and sustainable development. It critically analyzes digital transformation across sectors such as healthcare, education, industry, and environmental management, while addressing issues of digital divide, data governance, and ethical responsibility. The chapter further aligns technological advancements with the Sustainable Development Goals (SDGs), emphasizing inclusive innovation and policy-driven transformation. Through conceptual frameworks and global case illustrations, it proposes a balanced pathway that integrates innovation with equity and sustainability. Ultimately, the chapter argues that technology, when guided by ethical governance and inclusive policies, can serve as a powerful instrument for achieving resilient and sustainable global futures.

By Neha Soni
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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