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                <text>A case study on a beacon of hope transition: India's renewable energy integration and the Ujwal DISCOM assurance Yojana (UDAY)</text>
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                <text>This case study examines the transformative impact of the Ujwal DISCOM Assurance Yojana (UDAY) on India's energy landscape, focusing on its role in facilitating renewable energy integration. India's energy sector faced daunting challenges, including financially distressed power distribution companies (DISCOMs) and high aggregate technical and commercial (AT&amp;amp;C) losses. UDAY's financial restructuring and operational efficiency improvements led to remarkable reductions in DISCOMs' debt burdens and AT&amp;amp;C losses, respectively. The policy aligned with India's renewable energy goals, driving DISCOMs to procure renewable energy sources. Consequently, India witnessed significant growth in its renewable energy capacity, environmental benefits through reduced emissions, and economic growth via job creation. This case study offers insights into the challenges faced, technological advancements incentivized, and the long-term sustainability of these reforms. Moreover, it presents broader lessons for energy sector reform and renewable energy integration, both within India and globally.  2024, IGI Global. All rights reserved.</text>
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                <text>Baranidharan S.; Mallika B.K.; Thilaga N.</text>
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                <text>Green Economy and Renewable Energy Transitions for Sustainable Development, pp. 255-271.</text>
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                <text>Baranidharan S., Christ University, India; Mallika B.K., Christ University, India; Thilaga N., Kavery Arts and Science College, India</text>
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                <text>Mapping the AI landscape in healthcare quality: A bibliometrics analysis</text>
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                <text>This study explores the application of Artificial Intelligence (AI) in healthcare quality improvement through a bibliometric analysis of 222 documents retrieved from the Scopus database using the keywords "healthcare," "quality," and "AI." By examining bibliographic coupling, citations, co-citations, author keywords, and co-occurrence networks, the research unveils the key themes, prominent authors, and emerging trends in this field. The analysis reveals a focus on areas like machine learning for disease prediction, clinical decision support systems, and patient safety improvement. Leading authors and research groups are identified, and promising future directions such as explainable AI and integration with electronic health records are highlighted. This study contributes to understanding the current landscape of AI in healthcare quality improvement and guiding future research for maximizing its impact.  2024, IGI Global. All rights reserved.</text>
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                <text>Baranidharan S.; Narayanan R.</text>
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                <text>Revolutionizing the Healthcare Sector with AI, pp. 207-228.</text>
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                <text>ISBN: 979-836933732-5; 979-836933731-8</text>
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                <text>Baranidharan S., Christ University, India; Narayanan R., Dayananda Sagar University, India</text>
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                <text>Predicting cryptocurrency prices model using a stacked sparse autoencoder and Bayesian optimization</text>
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                <text>In recent years, digital currencies, also known as cybercash, digital money, and electronic money, have gained significant attention from researchers and investors alike. Cryptocurrency has emerged as a result of advancements in financial technology and has presented a unique opening for research in the field. However, predicting the prices of cryptocurrencies is a challenging task due to their dynamic and volatile nature. This study aims to address this challenge by introducing a new prediction model called Bayesian optimization with stacked sparse autoencoder-based cryptocurrency price prediction (BOSSAE-CPP). The main objective of this model is to effectively predict the prices of cryptocurrencies. To achieve this goal, the BOSSAE-CPP model employs a stacked sparse autoencoder (SSAE) for the prediction process and resulting in improved predictive outcomes. The results were compared to other models, and it was found that the BOSSAE-CPP model performed significantly better.  2023, IGI Global.</text>
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                <text>Baranidharan S.; Narayanan R.; Geetha V.</text>
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                <text>Revolutionizing Financial Services and Markets Through FinTech and Blockchain, pp. 60-77.</text>
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                <text>Baranidharan S., CHRIST University (Deemed), India; Narayanan R., Dayananda Sagar University, India; Geetha V., Seshadripuram Evening College, India</text>
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                <text>Prediction and analysis of financial crises using machine learning</text>
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                <text>This study presents a comparative analysis of various machine learning algorithms for credit risk assessment. The algorithms were tested on two credit datasets: German Credit Dataset and Australian Credit Dataset. The performance of the algorithms was evaluated based on several metrics, including sensitivity, specificity, accuracy, F-score, and Kappa. The results showed that the FCPFS-QDNN algorithm outperformed other algorithms in both datasets, achieving high accuracy, sensitivity, specificity, and F-score. On the other hand, the ACO Algorithm and Multilayer Perceptron algorithms were found to perform poorly in both datasets. The findings of this study have significant implications for credit risk assessment in banking and financial institutions. The study recommends the use of the FCPFS-QDNN algorithm for credit risk assessment due to its superior performance compared to other algorithms.  2023, IGI Global. All rights reserved.</text>
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                <text>Baranidharan S.; Rathod H.S.</text>
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                <text>Advancement in Business Analytics Tools for Higher Financial Performance, pp. 200-214.</text>
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                <text>Baranidharan S., School of Business and Management, CHRIST University, Bengaluru, India; Bhat S.R., College of Banking and Financial Studies, Muscat, Oman; Devesh S., School of Business and Management, CHRIST University, Bengaluru, India; Warrier G.S., Department of Computer Science, CHRIST University, Bengaluru, India</text>
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                <text>Baranidharan S., Christ University, India; Krishnaveni N., Nirmala College for Women, India; George P.A., Mangalam College of Engineering, India; Pradeep Kumar S.V., Christ University, India; Mohan C., Christ University, India; Sandhya D., Christ University, India; Vinod P., Christ University, India</text>
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                <text>This chapter presents a systematic review of contemporary trends and strategies in AML through the PRISMA framework. The study identifies emerging threats, evolving typologies, and technological innovations reshaping AML practices in the digital era. The review emphasizes the growing significance of regulatory technology (RegTech), AI, and public-private information-sharing platforms in enhancing detection, reporting, and compliance. Findings suggest a shift from traditional rule-based approaches toward adaptive, data-driven frameworks, although implementation gaps persist across jurisdictions. A critical insight emerging from the analysis is the imbalance between technological advancement and regulatory harmonization, particularly in developing economies. The chapter offers policymakers, scholars, and financial institutions 1) a consolidated foundation to better understand and address the multifaceted challenges of money laundering in a rapidly digitizing global economy and 2) a proposed roadmap for future AML initiatives to align institutional accountability.  2026, IGI Global Scientific Publishing.</text>
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                <text>Baranidharan S., Christ University, India; Kulkarni S., Christ University, India</text>
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                <text>In an increasingly competitive streaming landscape, Netflix faces the imperative to adapt its digital marketing strategy for long- term success beyond binge- watching. Challenges include fragmented audience attention, differentiation amidst competition, optimizing marketing ROI, and evolving consumer behavior. To thrive, Netflix must invest in original content, harness data- driven insights, cultivate strategic partnerships, and adapt to changing consumer preferences. By prioritizing subscriber engagement and retention, balancing acquisition efforts, and leveraging emerging technologies, Netflix can maintain its market leadership position and sustain growth. This case study explores key challenges and strategies for Netflix's digital marketing evolution, providing insights for marketing professionals and industry observers navigating the dynamic streaming landscape.  2025, IGI Global Scientific Publishing. All rights reserved.</text>
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                <text>The Impact of Carbon Pricing on Green Investment in Manufacturing;pp.163-185</text>
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                <text>Baranidharan S.; Muralidharan P., Christ University, India; Durgarani M., School of Business and Management, Christ University, India; Sakeerthi S., JAIN Deemed- to- be University, India; Rameshkumaar V.P., Sona College of Technology, India</text>
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                <text>This case study examines the Perform, Achieve, and Trade (PAT) scheme under Indias National Action Plan on Climate Change (NAPCC), a market- based initiative aimed at reducing industrial carbon emissions. PAT sets energy- efficiency targets for energy- intensive sectors and rewarding units that surpass their mandated goals. Through policy analysis and secondary data review across designated consumer industries, the study assesses scheme operations, compliance, and credit market performance. The notable improvements in energy efficiency, greater adoption of low- carbon technologies, and the formation of Indias early energy- credit market. However, issues such as uneven sector engagement, limited trading volumes, and institutional capacity constraints reveal challenges in implementing such mechanisms in emerging economic contexts. Overall, the case spotlights how regulatory mandates combined with trading incentives can deliver measurable climate benefits while underlining the need for stronger market design and governance to drive long- term industrial decarbonization.  2026 by IGI Global Scientific Publishing. All rights reserved.</text>
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                <text>Baranidharan, S.; Praveenraj, David Winster; Dhanalakshmi, K.; Chandran, Joji; Sandhya, D.; Kurup, Rahul R.; Mohan, Chippy</text>
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                <text>Baranidharan S., Christ University, India; Praveenraj D.W., Christ University, India; Dhanalakshmi K., Christ University, India; Chandran J., Christ University, India; Sandhya D., Christ University, India; Kurup R.R., Christ University, India; Mohan C., Christ University, India</text>
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                <text>It presents an important shift in the food service industry, most of which was accelerated during the COVID-19 pandemic: ghost kitchens, or virtual or cloud kitchens. This research discusses the operational mechanisms, workforce consequences, and consumer attitudes toward ghost kitchens, which operate strictly for delivery purposes without having a traditional dining area, as well as the literature used between the years 2007 to 2024. The labor standards and compliance, as most ghost kitchens are built upon gig economy workers who toil in challenging circumstances. Additionally, the study examines consumer perception of this new phenomenon of dining and its potential for transforming culinary careers. Its findings indicate that while ghost kitchens open avenues for creativity in culinary arts and expansion of the marketplace, it simultaneously necessitates a readjustment in labor norms and consumer awareness. Given the anticipated high growth rate for the ghost kitchen market in the next years, it is significant that food service sector stakeholders grasp these dynamics.  2025 by IGI Global Scientific Publishing. All rights reserved.</text>
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                <text>Baranidharan S., School of Business and Management, Christ University, Karnataka, Bangalore, India; Rajkumar R., PG and Research Department of Commerce, St. Josephs College of Arts and Science (Autonomous), Tamil Nadu, India; Devesh S., School of Business and Management, Christ University, Karnataka, Bangalore, India; Mallika B.K., School of Business and Management, Christ University, Karnataka, Bangalore, India</text>
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                <text>Baranidharan S., Christ University, Bangalore, India; Sankarkumar A.V., St. Francis College, India; Chandrakala G., Dayananda Sagar University, India; Dhanalakshmi K., Christ University, Bangalore, India; Mohan C., Christ University, Bangalore, India; Victor M., Christ University, Bangalore, India; Rindavanam R.V., Christ University, Bangalore, India; Sembiyan R., St. Josephs College of Arts and Science, Cuddalore, India</text>
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                <text>This study examines the multifaceted societal impact of 5G and 6G mobile communication technologies. Employing a systematic literature review (SLR) of recent scholarly literature (2022-2024), A comprehensive search strategy was implemented across reputable academic databases (Scopus, Web of Science, IEEE Xplore) to identify relevant publications. Selected articles underwent rigorous critical appraisal and thematic analysis to synthesize key findings and recurring themes. The review reveals the potential of 5G/6G to bridge the digital divide, particularly in underserved regions, through strategic infrastructure development. Social transformation can be achieved by fostering equitable access to communication services and deploying transformative applications in critical sectors like agriculture and healthcare. However, challenges persist regarding infrastructure limitations, equitable access, and sustainable development. Effective policy frameworks and robust managerial strategies for responsible deployment are crucial to maximize the positive impact of 5G/6G technologies.  2025 by IGI Global Scientific Publishing. All rights reserved.</text>
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                <text>Baranidharan S., Christ University, Bangalore, India; Sridevi M., Christ Academy Institute for Advanced Studies, India; Krishnaveni N., Nirmala College for Women, India; Mohan C., Christ University, Bangalore, India; Pradeep Kumar S.V., Christ University, Bangalore, India; Sandhya D., Christ University, Bangalore, India; Vinod P., Christ University, Bangalore, India; Kurup R.R., Christ University, Bangalore, India</text>
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