Poornaprajna International Journal of Emerging Technologies (PIJET)
Country of Publication: India Publisher: Poornaprajna Publication, Udupi, Karnataka, India Format: Open Access ISSN: 3107-8486 Year of Start: 2024 Available from: Crossref, Indian Citation Index, Zenodo, OpenAir Frequency: 2 Issues per year Language: English Scope: Multidisciplinary in Emerging Technologies Article Processing Charge: 2000 £ (Pounds) but currently free publication for first 10 years (till year 2030) Types of Journal: Academic/ Scholarly Journals Open Access: Yes Indexed & Abstracted: Yes Policy: Double blinded Peer Review Publication Ethics: Editorial Ethics Policy Review Time: Six to Eight Weeks Approximately Contact & Submission Email: pijet@poornaprajnapublication.com Poornaprajna International Journal of Emerging Technologies (PIJET) is an online, not-for-profit, Poornaprajna Group, Udupi sponsored free publication, blind peer-reviewed, open-access, quarterly but continuous weekly uploading of accepted papers, plagiarism free, refereed research journal published by Poornaprajna Publication, Udupi, India. PIJET offers free publication opportunity to its authors, allows to keep Copyright of the scholarly paper with the authors. It provides a global author-centric publishing platform for Professors, Research scholars, academicians, professionals, and students engaged in Research. The main aim of PIJET is to become the world’s leading Author-Centred fast publication journal that is preferred and trusted by the research community through publishing authentic, peer-reviewed, and scientifically developed research articles of international calibre. PIJET publishes research papers in the field of Emerging Technologies including Information Technology and Nanotechnology. The Journal publishes scholarly articles in English. PIJET accepts exceptional research contribution from the authors in the form of original papers, review papers, conceptual framework, analytical and simulation models, case studies, empirical research, and technical notes. All submissions are also checked for plagiarism. The length of the manuscript must be between five (5) to twenty (50) journal pages excluding references. The journal follows the |C|O|P|E| (Committee on Publication Ethics) guidance while accepting scholarly papers for publication. The Article Processing Charge (APC) subsidized for Faculty Members, Students and Research Scholars of Poornaprajna Group by its Research Fund.
Redefining the Goal and Building the Personality through Controlling the Environment – A Conceptual Study
Purpose: Investigating and shedding light on how environmental control can greatly improve goal achievement, leadership efficacy, and personal growth is the aim of this study. Conventional leadership models tend to disregard the impact of the external environment and instead place a strong emphasis on internal qualities like vision and resilience. The goal of this study is to close this gap by examining how making deliberate changes to one's social and physical environment might improve important leadership traits like self-efficacy, discipline, and flexibility. This study aims to provide a more comprehensive approach to leadership theory by combining frameworks for analysis, comparison, and interpretation. Methodology: Conceptual exploratory research method is used. This method incorporates both internal strengths and external flexibility. In addition to offering useful insights and doable tactics, the study gives prospective leaders the means to organize their surroundings for both professional and personal development, which eventually encourages ongoing self-improvement and long-term leadership success. Results/Analysis: In order to broaden the scope of current leadership theories, this exploratory study examines how environmental control can improve goal alignment, personality development, and leadership efficacy. This study shows how controlled surroundings are important for goal formulation and achievement by examining how changes to social and physical contexts might enhance motivation, focus, and decision-making. By using a comparative framework, the study compares environment-centered methods to traditional leadership theories that emphasize intrinsic qualities. It concludes that leaders who proactively manage their environment are more likely to be effective and flexible. Furthermore, the research employs an assessment methodology to investigate how environmental control enhances critical leadership attributes including self-efficacy, discipline, and resilience. The application of an interpretative framework yields findings that indicate environmental adaptation may be a useful supplement to contemporary leadership theory, promoting ongoing self-improvement and long-term success. Actionable ideas for creating conditions that support growth and goal attainment are presented in practical applications for emerging leaders. Finally, the study suggests a comprehensive model that enhances leadership effectiveness and increases the possibility of self-directed growth by striking a balance between internal attributes and external adaptation. Originality/Values: With its emphasis on the environment's transformative power as a tool for both professional and personal success, this study adds a comprehensive viewpoint to leadership theory. Type of Research: Exploratory Analysis.
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Redefining Experimental, Empirical, and Exploratory Research in AI Era
Purpose: To critically assess and enhance the integration of Artificial Intelligence (AI) in contemporary research methodologies. This study aims to evaluate the current use of AI across major research methods, identify gaps and opportunities, and establish comprehensive procedures for conducting and documenting AI-driven experimental, empirical, and exploratory research. By analyzing the advantages, benefits, constraints, and disadvantages using the ABCD framework, the research seeks to compare findings across different methods and assess their impact on AI-based research methodologies. Ultimately, the study aims to provide actionable insights and recommendations for advancing research practices in the AI era, ensuring that the methodologies evolve in line with technological advancements. Methodology: Exploratory method is used. The required information is searched using suitable keywords using Google search engine, Google Scholar search engine, and AI-driven GPTs and analysed using suitable analysis frameworks. Results & Analysis: The major research methods and scholarly publication formats of Experimental, Empirical, and Exploratory Research in AI Era are redefined, discussed, analysed, and interpreted with suitable suggestions. Outcome/Value Addition: The study aims to provide actionable insights and recommendations for advancing research practices in the AI era, ensuring that the methodologies evolve in line with technological advancements. Type of Research: Conceptual & Policy Research.
New Job Opportunities due to Integration of AI-driven GPTs across Four Industry Sectors - A Futuristic Analysis
Purpose: The purpose of this research paper is to explore and analyze the potential job opportunities emerging from the integration of AI-driven Generative Pre-trained Transformers (GPTs) across four key industry sectors: Primary, Secondary, Tertiary, and Quaternary. By examining the transformative impact of these advanced AI technologies, the study aims to provide insights into how AI-driven GPTs can create new roles, reshape existing job functions, and drive innovation within these sectors. This analysis is intended to guide industry stakeholders and policymakers in preparing for and capitalizing on the opportunities presented by AI advancements, ensuring a strategic and inclusive approach to workforce development and economic growth. Methodology: Exploratory research method is by collecting information using various search engines, AI-driven GPTs, and focus groups interactions and new interpretations are developed by analysing, comparing, and evaluating using various analysis frameworks. Key-findings: The integration of AI-driven Generative Pre-trained Transformers (GPTs) across various industry sectors, including Primary, Secondary, Tertiary, and Quaternary sectors, is poised to bring about transformative changes in workforce planning, skill requirements, and training. These changes will have far-reaching implications for businesses, employees, and educational institutions. Implications: The integration of AI-driven GPTs in the four industry sectors is unlocking new job opportunities that bridge traditional industry knowledge with cutting-edge AI capabilities. Originality/Value: New interpretations are developed by analysing, comparing, and evaluating using various analysis frameworks. Type of Paper: Exploratory research analysis.
An Overview of the Use of ICCT and Nanotechnology in Yellow Economy: Current Status and Future Opportunities
Purpose: To explore the use of Information Communication and Computation Technology and nanotechnology in promoting global yellow economy across the industries. Methodology: The exploratory research method is used where the relevant information on Yellow economy, ICCT and Nanotechnology are collected through keyword-based search using search engines like Google, Google Scholar, and AI-driven GPTs and analysed, compared, and evaluated using suitable analysing frameworks. The results are interpreted as new knowledge obtained from this research and suggested in the form of outcome postulates. Analysis: A thorough analysis of the Yellow Economy's background, significance, and technological requirements including the definition, components, applications, adoption trends, and challenges associated with ICCT and Nanotechnology, drawing insights from various sources to provide a holistic perspective. Case studies and examples are examined to explore successful integration scenarios and potential future developments. Additionally, a systematic analysis called ABCD analysis is presented to evaluate the potential advantages, benefits, constraints, and disadvantages of yellow economy driven by ICCT and Nanotechnology across industries. Results/Outcome: The impact of external factors like economic, environmental, social-cultural as well as technological, regulatory, and ethical considerations, are assessed through this exploratory research. Based on the findings, we propose future opportunities, policy recommendations, and research priorities aimed at maximizing benefits and mitigating risks associated with the adoption of ICCT and Nanotechnology in the Yellow Economy. The results of the outcome are interpreted as new knowledge and suggestions are given in the form of outcome postulates. Originality/Value: The paper provides valuable insights into the role of technology in optimizing industry operations and fostering sustainable economic growth in the Yellow Economy.
Tech-business Analytics in Digital Cashless Economy
Purpose: In the digital cashless economy, the main goal of tech-business analytics (TBA) is to use cutting-edge data analytics methods and tools to help companies that operate in cashless digital environments become more innovative, efficient, and successful. Design/Methodology/Approach: Clearly state the business goals that the analytics programme is intended to achieve. This can involve raising income, decreasing fraud, strengthening customer satisfaction, or optimising operational effectiveness. Findings/Result: Using tech-business analytics to streamline procedures, shorten transaction times, and allocate resources more efficiently is how businesses operating in the digital cashless economy are able to achieve increased operational efficiency. Originality/Value: In the fast-paced, dynamic digital cashless economy, firms may stay ahead of the competition, open up new opportunities, and foster innovation by embracing creativity in tech-business analytics. Paper Type: Exploratory Research on Technology Management.
Blockchain-Based Attendance System Using Hyperledger Fabric 2.5 And Ubuntu 24.04
Purpose: The purpose of this research is to design and implement a secure, transparent, and tamper-proof attendance management system using blockchain technology, specifically leveraging Hyperledger Fabric 2.5 deployed on Ubuntu 24.04. The paper aims to demonstrate how blockchain can efficiently replace traditional attendance systems by providing enhanced reliability, integrity, and auditability. Through practical implementation, the study evaluates performance, ease of use, and scalability, offering insights into blockchain's applicability in educational institutions and workplaces to mitigate common issues associated with traditional attendance tracking methods, such as data tampering, inefficiency, and lack of trust. Methodology: The methodology involves deploying a blockchain-based attendance system using Hyperledger Fabric 2.5 on Ubuntu 24.04. It includes requirements analysis, blockchain network setup, smart contract (chain code) development, and frontend-backend integration using React.js and Node.js. This is followed by rigorous functional and performance testing to ensure transparency, security, scalability, and overall system robustness. Result/Analysis: The analysis of the blockchain-based attendance system demonstrated significant improvements in data security, transparency, and efficiency compared to traditional attendance methods. Transactions executed reliably, achieving an average throughput of approximately 200 transactions per second with minimal latency, validating the scalability of Hyperledger Fabric 2.5 on Ubuntu 24.04. The use of cryptographic certificates ensured robust security, preventing unauthorized access and data manipulation. Additionally, integration of a React.js frontend provided user-friendly interaction, enhancing usability. Performance tests confirmed efficient resource utilization, maintaining stable CPU and memory consumption under varying workloads. Overall, results indicate the system's feasibility for reliable, secure, and scalable attendance management. Originality/Values: This study uniquely integrates Hyperledger Fabric 2.5 with Ubuntu 24.04, creating a practical, secure, and transparent blockchain-based attendance solution. Its originality lies in demonstrating real-world applicability, comprehensive performance evaluation, and detailed system integration insights, contributing valuable knowledge for institutions seeking innovative, decentralized, and efficient alternatives to traditional attendance tracking systems. Type of Research: Experimental-based Research.
Company Analysis of OpenAI with Special Emphasis on its Future Strategies
Purpose: This company analysis paper aims to provide a comprehensive, research-driven evaluation of OpenAI as a pioneering artificial intelligence company influencing the global IT and ITES sectors. Through applying analytical frameworks like SWOC, ABCD, and PESTLE, the paper critically examines OpenAI’s strategic strengths, industry challenges, and innovation-driven growth. It aims to inform and guide stakeholders—including policymakers, investors, and researchers—by offering insights into OpenAI’s current positioning, ethical implications, and future directions for sustainable and inclusive technological advancement. Methodology: This study employs an exploratory qualitative research approach to gather and analyze relevant information sourced through keyword-based searches using Google Search, Google Scholar, and AI-driven GPT models. The collected data is then systematically analyzed and interpreted in alignment with the study's objectives. Results/Analysis: This comprehensive analysis offers insights into OpenAI’s product ecosystem, emphasizing ChatGPT’s capabilities, applications, ethical implications, and societal contributions. The detailed analysis highlights critical aspects of OpenAI’s financial performance, revenue strategies, funding sources, and economic sustainability, presenting a nuanced view of its current market position and future strategic challenges. Further, a detailed analysis of financial performance indicators, revenue streams, funding sources, and economic viability of OpenAI’s business model are presented. The analysis also provides an in-depth understanding of OpenAI’s human resource development and retention strategies, highlighting scholarly insights and industry practices shaping the company's talent management approach. The analysis of OpenAI’s technology development and adoption strategies provides a comprehensive view of its innovation methodologies, market penetration tactics, and scholarly perspectives on its strategic initiatives. OpenAI’s significant ethical and regulatory challenges illustrate the importance of responsible governance, compliance management, and societal accountability in AI development and deployment. A comprehensive analysis of OpenAI, derived from SWOC, ABCD, and PESTLE frameworks, highlights critical insights and strategic implications for the company's future growth and sustainability. Originality/Value: The detailed SWOC analysis provides a balanced perspective on OpenAI’s ChatGPT, highlighting critical strengths contributing to its market leadership and notable weaknesses requiring strategic attention along with opportunities and Challenges. Results of ABCD stakeholders’ analysis and PESTL analysis for a Company from business expansion & strategic investment points of view are presented along with few suggestions for future actions. Type of Paper: Exploratory Research Case Study.
Digital Dharma: Translating Upanishadic Wisdom for the Age of Social Media
Purpose: In an era dominated by social media, digital distractions, and information overload, the ancient teachings of the Upanishads offer timeless wisdom for cultivating self-awareness, detachment, and inner peace. This paper explores how core Upanishadic concepts such as Ātman (self-realization), Vairagya (detachment), and Shanti (inner tranquillity) can be adapted to address the mental health challenges and identity crises exacerbated by the digital age. By examining the psychological impacts of constant connectivity, comparison culture, and digital addiction, the study investigates how Upanishadic practices like mindfulness, introspection, and self-inquiry (Atma Vichara) can foster mental well-being and authentic living in the modern world. Methodology: In this paper, the exploratory qualitative research method is used. The relevant information is collected using keyword-based search in Google search engine, Google Scholar search engine, and AI-driven GPTs. This information is analysed and interpreted as per the objectives of the paper. Analysis/ Results: Ultimately, by integrating ancient wisdom with contemporary digital lifestyles, we can create a balanced path that nurtures both technological progress and spiritual well-being, paving the way for a more mindful, compassionate, and connected world. Originality/ Values: Through this interdisciplinary approach, the paper aims to present a framework for “Digital Dharma,” integrating ancient wisdom with contemporary strategies for balanced, mindful engagement in the digital landscape
Transforming Customer Experience through Artificial Intelligence: Exploring Opportunities and Challenges
Purpose: This study examines the transformative role of Artificial Intelligence (AI) in improving the experience of customers, with a focus on its benefits, challenges, and future implications. As businesses increasingly adopt AI-driven solutions such as chatbots, virtual assistants, and personalized recommendation systems, understanding their impact on customer satisfaction, loyalty, and engagement becomes essential. The study explores how AI processes live data analysis, automation, and personalized interactions while addressing ethical concerns, issues related to the privacy of the data, and the potential loss of human touch. By analyzing the above, the study aims to provide important contributions for businesses, policymakers, and researchers on optimizing AI adoption to balance technological innovation with customer-centric values, ultimately fostering sustainable business growth and long-term customer relationships. Design/Methodology/Approach: This study employs a combination of both qualitative and quantitative analysis to evaluate the impact of AI-pushed solutions on customer revel in primary information is accrued through surveys and interviews with consumers and industry experts, whilst secondary information from present literature and case research provides contextual insights. Findings/Result: The findings of the study reveal that AI-driven solutions significantly enhance customer experience by improving service efficiency, personalization, and real-time engagement. Customers express higher satisfaction and loyalty when interacting with AI-powered chatbots and recommendation systems, particularly in areas like electronic commerce and banking. But, challenges of data privacy, ethical considerations, and no-human empathy in AI involvement remain key barriers to widespread acceptance. The study also highlights that businesses optimizing AI implementation with a balance of automation and human intervention achieve better customer retention and trust. these insights offer precious guidance for organizations trying to enhance AI adoption while maintaining a customer-centric approach. Originality/Value: This research paper contributes to the prevailing literature by giving a complete analysis of AI's impact on customer experience, offering actionable insights for businesses to optimize AI adoption while addressing ethical and human-centric challenges. Paper Type: Conceptual Research.
Disruptive Innovations Using Tech-Business Analytics in the Tertiary Industry Sector
Purpose: Disruptive Innovations Using Tech-Business Analytics in the Tertiary Industry Sector aims to transform service-based businesses through the use of cutting-edge technologies and insight-based decision-making. By increasing productivity, customization, and scalability, this strategy produces better client experiences, more efficient operations, and innovative business models that go against established market structures. Methodology: Combining both structured and unstructured information from multiple sources, such as market trends, consumer interactions, and the Internet of Things. employing big data analytics, predictive modeling, and machine learning to glean insights and spot possibilities. using cutting-edge technology to improve service delivery, such as cloud computing, blockchain, automation, and artificial intelligence. using platform-based economies, rethinking procedures, and developing new sources of income. Enhancing client happiness and strategy refinement through real-time analytics and feedback loops. In the tertiary sector, this model guarantees competitive advantage and sustainable growth. Analysis: In the tertiary sector, disruptive technologies powered by tech-business analytics are revolutionizing established service models through increased customer satisfaction, cost savings, and efficiency. As a result, tech-business analytics shift the tertiary industrial landscape and promote sustainable growth by acting as a catalyst for disruptive ideas. Originality/Value: An explanation of how traditional business analytics in the tertiary sector is different from tech business analytics. In addition, it looks at thirty recently submitted study recommendations about Tech Business Analytics in Tertiary industries and contains a generic design that can be used for technical purposes. Type of Paper: Exploratory Research.
The Future of Public Financial Management in the Digital Era: How AI and Blockchain Are Reshaping Government Accountability and Transparency
Purpose: This study examines how artificial intelligence (AI) and blockchain technologies transform public financial management (PFM) by enhancing government accountability, transparency, fraud detection, fiscal efficiency, and real-time financial oversight. Methods: A systematic literature review, secondary data analysis, and statistical modeling were utilized to evaluate global AI and blockchain adoption trends from 2020 to 2024. Regression analysis, chi-square tests, and ANOVA were applied to assess the impact of these technologies on fraud reduction, financial transparency, and cost savings. Findings: Regression analysis revealed a strong correlation (R² = 0.999) between AI adoption and fraud reduction, with approximately 500 fewer fraud cases per 10% increase in AI use. Blockchain significantly improved transparency (χ² = 18.72, p < 0.05), reducing financial mismanagement by 30%. ANOVA confirmed that AI and blockchain implementations increased public sector savings from $0.5 billion in 2020 to $3.2 billion in 2024. Value: The study highlights the critical role of clear regulatory frameworks, digital infrastructure investment, and workforce training in overcoming implementation challenges. It provides a strategic roadmap for policymakers, underscoring the importance of phased AI-blockchain integration and stakeholder engagement to modernize PFM systems effectively. Type of Paper: Empirical Research using secondary data.
Confluence of Mind and Machine: Exploratory Analysis of Human Agency and Ethical Governance at Nexus of Brain-Computer Interface and Superintelligent AI-Machines
Purpose: The parallel advancements in Brain-Computer Interfaces (BCIs) and Artificial Intelligence (AI) are rapidly creating a new paradigm of human-technology interaction. While much scholarship exists on the technological singularity and superintelligent machines in isolation, and on BCIs as medical devices, a significant gap exists in understanding their convergent impact. This research seeks to address this gap by qualitatively exploring a critical question: As BCIs become the primary interface between human cognition and a potentially superintelligent digital ecosystem, how will human agency, identity, and social structure be transformed, and what novel frameworks of ethical governance will be required? Methodology: This topic moves beyond purely technological forecasting to investigate the profound socio-philosophical implications of this convergence, making it ideal for a qualitative, scholarly inquiry. Using the exploratory research method, the relevant information is collected using keywords through search engines like Google, Google Scholar, AI-driven GPTs, and the collected information is analysed as per the objectives of the paper. Analysis: Based on a structured SWOC and ABCD analysis, the convergence of BCI and superintelligent AI presents a dual-edged future of immense potential benefits, such as eradicating disease and augmenting human cognition, alongside profound risks like existential threats from misaligned AI and the erosion of human autonomy. The analysis identifies key challenges, including irreversible social inequality, loss of mental privacy, and the potential devaluation of human purpose. Predictive scenario building outlines three plausible futures—Symbiotic Harmony, Gilded Cage, and Volatile Partnership—highlighting that the ultimate outcome depends on solving critical issues of AI alignment and establishing robust ethical governance. Originality/Value: This paper provides a novel integrated analysis of the convergent impacts of Brain-Computer Interfaces (BCI) and superintelligent AI, a topic previously examined only in isolated disciplinary silos. Its originality lies in applying structured qualitative frameworks (SWOC and ABCD) to systematically explore emergent risks to human agency and identity, while proposing proactive ethical governance models tailored to this hybrid technological future. Type of Paper: Review & Analysis-based exploratory Research.
Ubiquitous Digital University as an Alternative to the Traditional Higher Education Model to Develop an Ideal Education System
Purpose: The paper aims to explore and advocate for the transformative potential of ubiquitous digital universities in reshaping the landscape of higher education. By meticulously examining the features, functions, and business models of digital universities alongside an in-depth evaluation of their potential as an alternative to traditional education models, this research endeavours to offer insights into the development of an ideal education system. Through comprehensive analysis, it is essential to highlight the advantages, challenges, and opportunities inherent in ubiquitous digital universities, aiming to pave the way for a more accessible, flexible, and inclusive approach to education in the digital age. Methodology: Exploratory research method is used to analyse and evaluate the collected information from various sources, including Google, Google Scholar, HEIs websites, and AI-driven GPTs using identified keywords. Results & Findings: The results of these analyses are interpreted as new knowledge and presented in the form of postulates for future reference. Originality/Value: The paper compares conventional campus-based universities with digital universities and ubiquitous digital universities. The features of the ubiquitous digital university are also compared with the characteristics of an ideal education system. Both SWOC and ABCD analysis frameworks are used to analyse and evaluate these systems. The findings are summarized in the form of postulates for future reference. It is found that the technology-based progress in the university system takes it toward a hypothetical ideal education system. Type of Paper: Exploratory Research.
Mandala Principle in Artificial Intelligence: A Framework for Social Knowledge Preservation, Management, and Transfer in Learning Systems
Purpose: This study explores the Mandala principle as a philosophical and structural framework for knowledge transformation and transfer in social learning systems. It aims to investigate how ancient Mandala philosophy can inform the design of Artificial Intelligence-based Social Learning Management Systems (SLMS) to preserve, manage, and transfer social knowledge across generations and cultures. Methods: The research involves a conceptual analysis of the Mandala philosophy, rooted in social customs, traditions, and Vedic scriptures, examining its applicability to modern learning ecosystems. It synthesizes the philosophy’s principles with AI-driven social knowledge frameworks, proposing a Mandala-based SLMS model to organize knowledge, facilitate learning, and enhance social connectivity. Findings: The Mandala, beyond being a cultural or religious symbol, serves as a philosophical tool and "Resource Tank" for the transfer of social values, knowledge, consciousness, and behavior. The fundamental Mandala shapes individual thought and worldview from birth, dynamically evolving through experiences, technology, and social inputs in a structured, meaningful space. Utilizing this framework in AI systems fosters holistic knowledge preservation and effective social learning processes. Conclusion: Integrating the Mandala principle with AI-driven social learning platforms creates a novel framework for sustaining and transferring social knowledge and values. This approach provides a culturally grounded, dynamic system adaptable to evolving learning needs and societal contexts, supporting lifelong learning and social cohesion. Originality: This study uniquely bridges ancient Mandala philosophy with contemporary Artificial Intelligence applications in social learning management. It introduces the concept of a Mandala-based Social Learning Management System that emphasizes cultural philosophy and knowledge ecosystems as integral to AI-driven learning technologies, a perspective not extensively explored in existing literature. Type of Paper: Exploratory research.
Disruptive Innovations using Tech-Business Analytics in the Quaternary Industry Sector
Purpose: Tech-business analytics are used in the quaternary industry sector for disruptive innovations for a number of reasons. In essence, disruptive innovations in the quaternary industry sector that make use of tech-business analytics aim to alter how companies operate, compete, and deliver value; this will eventually lead to improved results and long-term success. Design/Methodology/Approach: Companies operating in the quaternary sector can create new value propositions, challenge established processes, and obtain a long-term competitive edge by utilizing tech-business analytics. In this industry, disruptive ideas that use tech-business analytics are usually executed in this way. Findings/Result: When tech-business analytics are used in the quaternary industry, disruptive breakthroughs typically have a number of notable repercussions. According to these findings, disruptive innovations that use tech-business analytics have a considerable positive impact on the overall company performance, customer happiness, and operational efficiency of the quaternary industry sector. Originality/Value: The disruptive developments in the quaternary industry sector that use tech-business analytics are distinctive due to a number of significant features. These characteristics show that disruptive innovations that use tech-business analytics are not just improvements on existing practices, but are more like new techniques that create value and establish new industry standards.
Disruptive Innovations using Tech-Business Analytics in the Secondary Industry Sector
Purpose: The principal objective is to revolutionize conventional manufacturing and production procedures by utilizing cutting-edge technologies and insights derived from data. In the secondary sector, the incorporation of tech-business analytics promotes competitive advantage, long-term sustainability, and more intelligent decision-making. Design/Methodology/Approach: Collect information from a range of sources, including sensors, IoT devices, ERP systems, and consumer reviews in production processes. Combine information from several systems and departments into a single platform to guarantee consistency and accuracy in analysis. Utilize methods like AIML, predictive analytics etc. monitoring to spot trends, inefficiencies, and opportunities. Utilize insights to create innovative solutions that go against the grain, such automated processes, smart factories, or customized production lines. Prior to full implementation, test new models or technologies on a small scale to assess their viability, performance, and return on investment. Successful innovations should be expanded throughout operations, integrated with current systems, and staff members should be trained for adoption. Create feedback loops with analytics to track results and keep improving procedures and inventions. This methodology aligns technology with secondary sector business objectives and guarantees that disruption is data-driven, strategic, and sustained. Findings/Result: Predictive maintenance and automation greatly cut down on resource waste and downtime. Budget allocation is enhanced and production expenses are reduced through data-driven decision-making. Faster defect detection and repair are made possible by real-time analytics. Agile manufacturing techniques provide more rapid reaction to market demands. Businesses that use tech-business analytics do better in terms of innovation and agility than traditional players. Energy-efficient and environmentally friendly activities are enhanced by intelligent resource management. Originality/Value: Tech-business analytics-based disruptive developments in the secondary industrial sector are distinctive due to a number of significant variables. These characteristics show that disruptive innovations that use tech-business analytics are not just improvements on existing practices, but are, in fact, new techniques that create value and establish new industry norms. Type of Paper: Exploratory Research.
Cloud Accounting Adoption in FMCG Sector: Employee Perceptions in Local vs. National Organizations
Purpose: Cloud accounting is increasingly adopted by organizations to enhance financial management efficiency. In the FMCG sector, employee perception, management support, and system integration are critical to successful adoption. However, limited research exists on how adoption differs between local and national organizations in emerging economies like Nepal. Methodology: A quantitative, cross-sectional study was conducted among 40 FMCG employees in Kathmandu Valley using a structured questionnaire. Descriptive statistics summarized perceptions across seven cloud accounting dimensions, while independent samples t-tests examined differences between local and national organizations. Results & Analysis: Findings indicate high acceptance of cloud accounting, with employees reporting ease of use, regular usage, security trust, and integration with other software. No significant differences were found between local (M = 3.98) and national (M = 4.01) organizations (p = 0.895). Training adequacy showed minor gaps but did not hinder adoption. FMCG employees demonstrate a positive perception of cloud accounting, regardless of organizational scale. Successful adoption is influenced more by management support, system usability, and training than by company size. Originality / Value: This study provides empirical evidence on cloud accounting adoption in Nepal’s FMCG sector and highlights that local firms can achieve adoption levels comparable to national companies, offering insights for managers and policymakers to enhance digital financial practices. Type of Paper: Empirical Research Paper.
Industry Analysis of the Nanotechnology Industry in India
Purpose: The purpose of this research case study is to provide a systematic examination of the competitive forces, market dynamics, and structural factors defining the nanotechnology sector in India. It aims to evaluate the industry's transformative potential across critical sectors like healthcare, agriculture, and energy while identifying the strategic challenges involved in bridging the gap between fundamental research and commercial manufacturing. Ultimately, the study seeks to inform critical decisions on resource allocation and long-term positioning, providing a foundation for sustainable competitive advantage in the global knowledge economy. Methodology: This study employs an exploratory case study research design that synthesizes data gathered from diverse, credible secondary sources such as Google Scholar, academic websites, and AI-driven large language models. The information collected is rigorously examined through specialized strategic frameworks—including SWOC, PESTLE, Porter’s Five Forces, and ABCD analysis—to ensure a comprehensive evaluation aligned with the paper's core objectives. By utilizing these multi-dimensional analytical tools, the research transforms raw data into actionable insights regarding the current status and future trajectory of the industry. Results/Analysis: The results and analysis of the industry analysis research case study reveal that the nanotechnology sector in India is a high-growth "knowledge economy" driver, currently undergoing a strategic shift from foundational research to application-oriented commercialization. Strategic frameworks like SWOC and ABCD highlight that while India ranks third globally in scientific publications, it faces a significant "Valley of Death" where laboratory innovations struggle to scale due to funding gaps and fragmented industry-academia linkages. Ultimately, the analysis identifies critical success factors in "frugal innovation," such as nano-fertilizers and low-cost water purification, which position India to address systemic societal challenges while needing a more consolidated regulatory framework to sustain global competitiveness. Originality/Value: The originality of this research case study lies in its comprehensive application of multiple strategic frameworks, such as SWOC, PESTLE, and ABCD analysis, to evaluate the multi-sectoral impact of nanotechnology within the specific socio-economic context of India. It provides unique value by identifying critical "lab-to-market" gaps and proposing a service-oriented operational model to accelerate the commercialization of deep-tech innovations for national developmental needs. Type of Paper: Exploratory Research Case study.
Digital Public Infrastructure (DPI) - AgriStack for Inclusive Development and Achieving Sustainability Goals
Purpose: The Government of India is promoting digital transformation in agriculture through initiatives such as e-NAM, NeGP-A, the Digital Agriculture Mission, and AgriStack, integrating technologies like AI, IoT, drones, and data analytics to enhance productivity, sustainability, and farmer livelihoods. With nearly 70% of rural households dependent on agriculture, Agriculture 4.0 and the 5C approach aim to strengthen collaboration, improve credit access, reduce costs, address climate change, and support inclusive growth while contributing significantly to India’s economy and UN Sustainable Development Goals. Methodology/Approach: The study typically uses a combination of case studies, policy analysis, and data-driven assessments to explore how AgriStack, a part of Digital Public Infrastructure (DPI), is applied in agriculture to promote inclusivity and sustainability. The approach might involve evaluating technological implementations and their impact on agricultural practices. The authors presented the DPI on Agristack in agriculture eco system and instrumental for the achieving sustainability. Findings/Results: The research indicates that leveraging digital infrastructure like AgriStack can significantly enhance the productivity of farmers, improve access to information, and drive progress towards achieving the UN's Sustainable Development Goals (SDGs). It demonstrates the potential for technology to bridge gaps in agricultural services and support environmental sustainability. Originality/Value: This paper provides unique insights into the role of digital frameworks in transforming the agricultural sector, particularly in emerging economies like India. 5C approach model and ABCD analysis gives more clarity on the DPI on Agristack. Paper Type: Review based Research Analysis.
Revolutionizing Entertainment: The AI-Generated Tools and Their Impact on Mass Media and Entertainment
Purpose: The purpose of the research paper is to explore and analyse the multifaceted influence of AI generate tool multimedia and entertainment industry. This research mainly focuses on redefining traditional practices in content creation, distribution, and audience engagement. Also provides a comprehensive analysis of the benefits and challenges presented by the advent of AI in this field. And delve in to the specific implications for various stakeholders, including content creators, consumers, and the broader media ecosystem. Design/Methodology/Approach: Develops the theoretical concepts based on literature review and case study on Entertainment Company and analysis on the model based on ABCD listing framework. Findings/Result: The various factors that effects mass media and entertainment industry are effectively listed and analyzed. The both positive and negative impacts of AI in this field is found in different aspect. So, challenge here is to retainment of positive impacts and need to find solution to overcome the negative impacts. Originality/Value: This research is mainly focused on how the artificial intelligence booms the mass media and entertainment industry with positive and negative imputation. Paper Type: Conceptual Research.