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Assessment of AI Companies Operational Performance in India
The article has delved into understanding the importance and performance of Artificial Intelligence companies in India with the data of the past five years. It scrutinizes the performance and significance of Artificial Intelligence (AI) companies in India over the past five years. It delves into the financial data, specifically examining Profit After Tax as an independent variable and its relation to net cash flows in these companies. The analysis involves nine prominent AI companies in India and employs statistical tools such as correlation, regression, standard deviation, and one-way ANOVA. The findings indicate varying relationships between Profit After Tax and net cash flows across different companies, underscoring the complexities within their financial dynamics. While some companies exhibit a positive correlation, others show no direct relationship. Additionally, the article explores government guidelines and existing laws that impact AI companies in India, emphasizing ethical and responsible AI usage. Despite the evolving market, the article suggests a promising future for AI companies in India, contingent upon their ability to tailor solutions to the unique challenges and opportunities in the Indian landscape. 2025 Author(s). -
A Computational Data-Granular Model Highlighting the Evolving Fintech Landscape in India
The Fintech sector in India has undergone remarkable development, complementing the significant progress in financial technology designed to simplify financial services and provide innovative solutions. This study aims to discover and analyze two significant knowledge gaps in the Indian Fintech sector. It seeks to identify and examine the evolving patterns in web searches for potential career opportunities in the Fintech sector, providing perspectives into the trendline data from the country. Secondly, the study will assess employment in the Fintech Sector in India, emphasizing Position Titles, the geographical distribution of opportunities, and market trends from 2015 to 2023. Furthermore, it will examine the motivation and strategies essential for supporting and developing the Fintech sector in India. It performs a trend analysis on Fintech, Finance, and Accountancy searches and how they have changed over the years. By addressing these gaps, the research aims to provide valuable insights into the Fintech industry's dynamics and development in the Fintech job market over the years in the Indian context. To complement the trend analysis conducted in the paper, a computational modeling approach is used to predict future job trends in the Indian Fintech sector. The model relies on data from the years 2015 to 2023 on job openings, web searches, and geographical distribution. Therefore, the Autoregressive Integrated Moving Average (ARIMA) model has been used to understand the future patterns of job opportunities and skill requirements accordingly. This research will be helpful for companies and business owners to improve their financial operations in the long run. 2025, Bentham Books imprint. -
Chatbots in Banking: Transforming Customer Interaction and Service Efficiency Through AI
The advent of Artificial Intelligence (AI) and chatbot technologies has brought drastic transformative changes to the banking sector which has reshaped customer engagement, enhanced efficiency and provided 24/7 assistance to the customers. The paper investigates the usage and impact of AI-powered chatbots on the customer experience and overall performance of the banking institutions through thorough analysis of recent advancements in technology, the study explores how chatbots which are leveraging machine learning (ML) and natural language processing (NLP) are used to address customer enquiries, facilitate transactions and offer customized financial guidance. Additionally, the current study also examines the influence of chatbots on customer satisfaction, regulatory compliance and measures of security highlighting both the advantages and challenges of such systems. Hence, the aim is to contribute to a comprehensive understanding of chatbots' role in banking providing insights into their effectiveness and potential for the future refinement to meet evolving customer expectations. 2025 by IGI Global Scientific Publishing. All rights reserved. -
A Multi-Dimensional Analysis of NIFTY50's Strategic Integration and Performance on the United Nations' Sustainable Development Goals
In 2015, the United Nations introduced 2030 agenda for Sustainable Development focusing on Sustainable Development Goals (SDGs) and 167 specific targets which are adopted by 193 member countries. The goals serve as a global blueprint for achieving inclusive, equitable and sustainable growth. The present study evaluates the sustainability performance of leading companies listed on the NIFTY50 index to assess how effectively for top performing firms have integrated SDG principles into their strategic planning, disclosure practices and operational frameworks. The resulting scores provide a quantifiable measure of companys alignment with global SDG agenda. Also, the study analyzes the financial performance indicators specifically for stock returns and volatility using NIFTY50 as benchmark. It reveals a positive relationship between higher SDG scores and improved stock performance as well as a negative correlation for volatility suggesting that companies with stronger sustainability engagement tend to offer better risk- adjusted returns. Copyright 2026, IGI Global Scientific Publishing. Copying or distributing in print or electronic forms without written permission of IGI Global Scientific Publishing is prohibited. Use of this chapter to train generative artificial intelligence (AI) technologies is expressly prohibited. The publisher reserves all rights to license its use for generative AI training and machine learning model development. -
Greening the Portfolio: Investor Insights into Sustainable Development Opportunities in India
Using an investor-centric approach, the present study examines investors' investment patterns toward green financing and factors influencing investor preferences, motivations regarding green investments, decision-making processes, and the development of green finance in the Indian financial sector. The objectives of the paper are twofold: first, using the bibliometric coupling, we identified the thematic clusters within green finance literature, revealing emerging trends and gaps and second, the impact of investors awareness and engrossment levels on their participation in green investments, especially in the Indian financial sector. The quantitative and qualitative methods employed in this study offered insights into how green finance is changing in India and what it means for sustainable development. The findings highlighted an intriguing pattern: youth investors, who have greater engagement and are more inclined toward green finance than their older counterparts. This tendency among the younger generation is not just a one-off event but reflects more significant changes in socioeconomic conditions and a growing awareness of environmental issues. It becomes clear that younger investors are aware of the need to protect the environment and are skilled at assessing the long-term sustainability and financial strength of green investment portfolios. The managerial implications of the study are relevant for academic researchers, practitioners, policymakers, financial regulators, issuers, and investors engaged in green finance. 2025 The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Identification of Brain Tumors Using CNN and ML with Diverse Feature Selection Techniques
Early diagnosis and treatment is very essential in monitoring Brain tumor using MRI images. Convolutional Neural Networks (CNN) and Machine Learning (ML) classifiers have been widely used but there is not much work on how feature selection techniques would affect the performance of the CNN. Secondly, there is a need for investigation concerning small dataset adaptability and ML-CNN comparisons. To improve the classification accuracy, we integrate Univariate, Recursive Feature Elimination (RFE), Recursive Feature Elimination with Cross Validation (RFECV) with CNN in this study. Preprocessing, feature extraction & selection was carried out on the dataset consisting of 253 MRI images and they are classified using CNN and ML models (Logistic Regression, Decision Tree, Random Forest, Nae Bayes). With the results 96%, CNN with Univariate Feature Selection performed better than ML classifiers, and other selection techniques. The results demonstrate that feature selection is necessary to get the best performance out of CNN models operating on small datasets. Future studies should be based on different deep learning architectures to improve classification and application i n other datasets. 2025, Interdisciplinary Publishing Academia. All rights reserved. -
Data-Driven Sustainability: Revolutionizing Hospital Supply Chains through Big Data Analytics
Purpose: Despite the growing interest in Big Data Analytics Capabilities (BDAC), its significant impact on hospital operations and supply chains in shaping hospital performance remains elusive. The study investigates the pivotal role of BDAC within the framework of hospital supply chains across India. Drawing upon the Resource-Based View, Dynamic Capability View, and Organisation Information Processing Theory, this research explores the intricate relationships among the organization's capability factors, BDAC, and hospital performance indicators. Design/Methodology/Approach: A conceptual model was developed and empirically tested using survey data collected from 446 hospital managers. The analysis was carried out by using partial least square-structural equation modeling (PLS-SEM). Findings: The results of this study support the significant mediating impact of BDAC on Operational Flexibility, Supply Chain Sustainability, and Organisation Revenue leading to the enhancement of organizational performance. The findings highlight the strategic importance of cultivating BDAC to improve operational efficiency and overall effectiveness in the context of Indian multispeciality hospitals. Originality/Value: This research contributes to the existing knowledge by highlighting the relationship between organization capability factors, BDAC, and performance indicators in the different settings of Indian multispeciality hospitals. The Author(s), under exclusive licence to Springer Nature Switzerland AG 2025. -
Redefining digital transformation in service supply chain: the missing piece of big data analytics
The study delves into the transformative role of big data analytics (BDA) in supply chain management within the service industry, employing the PRISMA framework to systematically review literature published between 2011 and 2024. A comprehensive search across multiple databases identified 286 relevant studies, which were meticulously analysed through bibliometric techniques. Keyword and network analyses, conducted using VOSViewer, revealed critical research linkages, prominent technologies, and thematic patterns within the domain. The findings underscore the pivotal role of technology integration in enhancing the efficiency of service supply chains, with a particular emphasis on emerging technologies such as blockchain, artificial intelligence, and machine learning. By highlighting the interconnectedness of authors, identifying key themes through keyword analysis, and uncovering research patterns through frequency analysis, the study provides valuable insights into the integration of BDA, ultimately contributing to the advancement of supply chain management in the service industry. Copyright 2025 Inderscience Enterprises Ltd. -
An Optimized Convolutional Neural Network Model for Real-Time Object Detection in Drones
The capacity of drones to perform item detection in actual-time is crucial for applications inclusive of surveillance, seek and rescue, and environmental tracking. This look at investigates how convolutional neural networks (CNNs) can beautify object detection in aerial imagery by enhancing both accuracy and speed. CNNs excel at extracting spatial info, permitting drones to apprehend objects even in relatively complicated environments. by adopting light-weight CNN architectures and optimization strategies, we acquire advanced performance with minimum computational requirements, ensuring green operation on embedded drone platforms. Our findings verify that CNN-based fashions considerably decorate detection accuracy and responsiveness, allowing the improvement of smarter and more self reliant drones. 2025 IEEE. -
An Optimized Convolutional Neural Network Model for Real-Time Object Detection in Drones
The capacity of drones to perform item detection in actual-time is crucial for applications inclusive of surveillance, seek and rescue, and environmental tracking. This look at investigates how convolutional neural networks (CNNs) can beautify object detection in aerial imagery by enhancing both accuracy and speed. CNNs excel at extracting spatial info, permitting drones to apprehend objects even in relatively complicated environments. by adopting light-weight CNN architectures and optimization strategies, we acquire advanced performance with minimum computational requirements, ensuring green operation on embedded drone platforms. Our findings verify that CNN-based fashions considerably decorate detection accuracy and responsiveness, allowing the improvement of smarter and more self reliant drones. 2025 IEEE. -
How tourist motivations shape perceptions of service quality at pilgrimage sites
Previous research has not adequately examined how various tourist motivations affect perceived service quality at pilgrimage destinations. This study seeks to investigate the effect of various motives religious pilgrimage, votive offerings, leisure, and meditation on service quality perceptions at seven Jyotirlinga pilgrimage destinations in North India. A cross-sectional survey of 1047 visitors was carried out, and data were analysed through one-way ANOVA to determine significant differences between visitor groups. For multiple comparisons, Bonferroni and Games-Howell post hoc tests were used depending on the homogeneity of variances. The results show differences in service quality perceptions, specifically in desired facilities, safety and security, and transportation. Pilgrims interested in religious devotion emphasised safety, whereas leisure travellers gave more importance to the quality of facilities available and transportation. These findings have practical implications for pilgrimage site management, highlighting the importance of making targeted improvements in service delivery to meet the expectations of various visitor segments. Copyright 2025 Inderscience Enterprises Ltd. -
Fragile foundation: Tourism, culture, and environmental stability in Joshimath and Kedarnath
This study aims to explore the ecological and cultural challenges in the delicate ecosystems of Joshimath and Kedarnath. A mixed method approach was adopted. Primary data was collected through semi-structured interviews with 35 tourists to look at the perception of environmental degradation and cultural influences. Content analysis of secondary data, including media reports and academic articles add contextual insights to the issue. The findings suggest that overcrowding and rapid construction works are increasing the environmental instability in both the sites; leading to natural disasters like floods, landslides, avalanches, etc. The tourists are disappointed due to overcrowding, and the threats it brings to the cultural and natural heritage. The study, thus highlights the urgent need for responsible tourism and much stricter developmental control measures. This study highlights that without immediate interventions, these fragile ecosystems are left with the threat of suffering from irreversible damages infringing upon their environmental significance and cultural values. 2025, IGI Global Scientific Publishing. All rights reserved. -
Service Quality in Tourism and Hospitality: A Review of Literature
The study aims to explore the literature on service quality research within the Indian tourism and hospitality sectors. It synthesizes key insights by analyzing dimensions used to measure service quality, identifying sector-specific trends, and highlighting future research opportunities relevant to enhancing human resource practices. The review is based on 255 articles (1999-2024) based on a systematic approach, retrieved from Web of Science and Scopus. The literature review identified that the banking sector, education sector, healthcare sector, and tourism and hospitality sector are the popular sectors of Service quality research in India. Other sectors like the Airline sector, Insurance sector and automotive sector are slowly gaining momentum in this area of research. The scope of future research Service Quality research in India is identified and stated. The study offers insights into the sector wise dimensions of service quality and its future potential, particularly for academicians conducting research in a niche area. 2026, IGI Global Scientific Publishing. All rights reserved. -
HIV-related stigma as a mediator between perceived social support and reasons for non-disclosure of self-HIV status among children and adolescents living with HIV
Children and adolescents living with HIV face complex decisions about disclosing their HIV status, influenced by social, emotional and contextual factors, including perceived support and experiences of stigma. This study examined the relationship between perceived social support, HIV-related stigma and motivations for non-disclosure, and assessed whether stigma mediates the link between social support and non-disclosure among young people living with HIV. A cross-sectional study was conducted with 90 participants aged 1018 years receiving antiretroviral therapy at a tertiary hospital in northern India. Participants completed standardized measures of perceived social support, HIV-related stigma and non-disclosure motivations. Higher social support was associated with lower stigma, and greater stigma predicted stronger non-disclosure motivation. Mediation analysis showed a significant indirect effect of social support on non-disclosure through stigma, indicating partial mediation. Findings underscore the central role of stigma in disclosure decision-making. Interventions that enhance supportive relationships and reduce stigmatizing attitudes in families, schools and healthcare settings may promote healthier coping and developmentally appropriate disclosure. 2026 Informa UK Limited, trading as Taylor & Francis Group. -
Evolving CSR: Ethical Leadership in Environmental Challenges and Sustainable Consumption
This chapter explores the evolution of CSR from simple philanthropy to strategic core in modern business. The best way to incorporate them is within the strategies of a corporation so that their effects are both effective and sustainable. This Chapter give more inputs on Ethical leadership in context of modern CSR; otherwise, firms are drawn toward a superficial greenwashing rather than an authentic stewardship for society and the environment. There are two basic CSR models discussed in this chapter. One, Carroll's CSR Pyramid, and the second one is the Triple Bottom Line model, where the organization frames CSR as three- dimensional responsibility toward people, profit, and planet. Chapter also include CSR Supporting Governance and responsibility. The Chapter also include example by Patagonia, for instance, tangible benefits through CSR would be the building up of brand reputation. Further, the chapter extends environmental impacts of CSR on Consumer Consumption regarding carbon reduction, renewable energy & Others. 2025, IGI Global Scientific Publishing. -
Analyzing the Diagnosis and Treatment of Astrocytoma, Oligodendroglioma, and Glioblastoma: A Systematic Review
Artificial intelligence (AI), particularly machine learning (ML) and deep learning (DL), has had a substantial impact on a variety of fields, including healthcare, neuro-oncology, and precision medicine. In recent years, the availability of large-scale labeled datasets has allowed AI-driven advances in glioma detection, classification, and prognosis prediction. However, issues remain in assuring model generalizability, interpretability, and real-world clinical application. One of the most significant disadvantages is the underrepresentation of rare glioma subtypes, which prevents appropriate classification and therapy optimization. This study thoroughly assesses AI-based approaches for glioma classification, survival prediction, and biomarker discovery. A comprehensive survey of ML and DL models published between 2015 and 2024 has been conducted, evaluating radiomics-based tumor detection, multi-omics data integration, and AI-assisted decision-making frameworks. The review investigates the usefulness of convolutional neural networks CNNs, support vector machines SVMs, ensemble learning, and hybrid AI architectures, focusing on classification accuracy, sensitivity, and clinical applicability. Despite these advances, AI-driven glioma research faces challenges such as dataset consistency, clinical validation gaps, and a scarcity of explainable AI (XAI) frameworks. This paper offers a comparative analysis of artificial intelligence approaches assessing their strengths, constraints, and clinical relevance in glioma diagnosis and prognosis prediction in order to solve these challenges. The results underscore artificial intelligences revolutionary capacity in redefining glioma diagnosis, enhancing accuracy, and shaping the future of personalized treatment, thereby integrating computational progress with clinical neuro-oncology. Glioma diagnosis, deep learning, astrocytoma, oligodendroglioma, glioblastoma. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2026. -
Navigating parental drug addiction and psychopathology: Impact on children's educational success and well-being
This chapter examines the anthologies of children who have demonstrated resilience in the face of adversity linked to their parents' problems, such as substance abuse and psychopathology. In navigating the complexities of the family unit, personal coping mechanisms and community and peer support arise as critical components. These anecdotes emphasize the capacity for favourable consequences resulting from providing individuals with educational and social support networks. This underscores resilience's profound complexity when confronted with difficulties within the family unit. 2024 by IGI Global. All Rights Reserved. -
Navigating parenting challenges: Supporting adolescents struggling with addiction in achieving educational success and well-being
A comprehensive and collaborative approach involving institutions, mental health professionals, parents, and educators is imperative in addressing adolescent addiction. Stakeholders make valuable contributions to the recovery process by engaging in coordinated treatment, fostering open communication, providing family counselling, addressing educational and emotional needs, and cultivating supportive environments. The collective endeavour promotes resilience, thereby guaranteeing immediate and enduring achievements. The convergence of shared responsibilities, ongoing support, and comprehension of the intricate nature of adolescent addiction generates a formidable catalyst for constructive transformation. The collective endeavour provides families and adolescents with optimism, restoration, and a more promising trajectory. 2024 by IGI Global. All Rights Reserved. -
Stress, resilience, and brain performance
The chapter explores the complex interplay among stress, resilience, and optimal cognitive functioning within the context of leadership. It researches the neuroscience of stress, chronic stress's neurobiological effects, and resilience's buffering function. This chapter examines evidence-based stress management techniques and provides practical strategies for developing resilience. The chapter elucidates the neuroscientific underpinnings that support the notion that resilience influences problem-solving, creativity, and decision-making. Real-world illustrations serve to demonstrate the adept navigation of challenges by resilient leaders. Case studies illustrate the integration of resilience practices by organizations. Furthermore, the text covers practical leadership advice and the overarching concept of organizational resilience concerning neuroleadership. 2024, IGI Global. All rights reserved. -
Empathy and compassion as fundamental elements of social cognition
This investigation into compassion and empathy highlights their crucial functions in social cognition, which influence engagements in various settings. Cultural dimensions underscore the significance of human connection by highlighting the societal influences that shape empathetic behaviours. The correlation between compassion, empathy, and mental health underscores their capacity to cultivate resilience. They make valuable contributions to communication and conflict resolution within interpersonal relationships. Efficacious interventions provide opportunities for individual development. Ethical considerations emphasize the importance of maintaining a delicate equilibrium between self-care and empathy. Ongoing technological and neurological research promises an expansion of applications. Cultivating kindness and compassion revolutionizes societies, ushering in an era of more significant global interdependence where mutual comprehension underpins all human engagements. 2024, IGI Global.