Category Archives: Uncategorized

Impact Of Agro Tourism On Farmers Economic Empowerment: An Empirical Study

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Authors: Amit Kumar, Raj Kumar

Abstract: Agriculture has long been the backbone of rural economies and continues to serve as the primary source of livelihood for a large segment of the population. However, declining farm profitability, unpredictable climatic conditions, and increasing production costs have created significant challenges for farmers. In response to these challenges, agro-tourism has emerged as an innovative approach that enables farmers to diversify their income sources while promoting rural culture and agricultural heritage. The present study investigates the impact of agro-tourism on the economic empowerment of farmers. The study is based on primary data collected from 150 farmers engaged in agro-tourism activities through a structured questionnaire. A quantitative research approach was employed to analyze the relationship between agro-tourism participation and various dimensions of economic empowerment, including income enhancement, employment generation, entrepreneurial development, and financial independence. The findings indicate that agro-tourism has contributed significantly to improving farmers' economic conditions by generating additional income opportunities, creating local employment, and encouraging entrepreneurial initiatives. Furthermore, agro-tourism has enhanced the financial security and self-reliance of farming households. The study concludes that agro-tourism can serve as an effective strategy for promoting sustainable rural development and strengthening the economic position of farmers. Therefore, greater support in terms of infrastructure development, training programs, marketing assistance, and policy initiatives is essential to unlock the full potential of agro-tourism in rural areas.

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Impact Of UPI Adoption On Consumer Spending Patterns In India

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Authors: Gulshan Kumar, Meentu Grover

Abstract: The rapid growth of Unified Payments Interface (UPI) has transformed the way people conduct financial transactions in India. With the widespread availability of smartphones, internet connectivity, and government initiatives promoting a cashless economy, UPI has become one of the most preferred digital payment methods among consumers. This study examines the impact of UPI adoption on consumer spending patterns in India and explores how digital payment convenience influences purchasing behavior. The research investigates key aspects such as transaction frequency, spending habits, impulse buying tendencies, budgeting practices, and consumer preferences for digital payments over traditional cash transactions. Primary data were collected through a structured questionnaire administered to UPI users from diverse demographic backgrounds. The findings indicate that UPI adoption has significantly increased the ease and speed of transactions, encouraging more frequent purchases and reducing dependence on cash. Consumers reported greater convenience in managing daily expenses, while businesses benefited from faster and more transparent payment processes. The study further reveals that although UPI promotes financial accessibility and convenience, it may also contribute to increased discretionary spending due to the ease of making instant payments. The findings highlight the growing role of digital payment systems in shaping consumer financial behavior and supporting India's digital economy. The study offers valuable insights for policymakers, financial institutions, and digital payment service providers seeking to enhance consumer engagement and promote responsible digital financial practices.

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A Comparative Financial Performance Analysis Of Public And Private Sector Banks In India

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Authors: Dr. Sahil Nazir, Natasha

Abstract: The banking sector plays a vital role in the economic development of India by mobilizing savings and channelizing funds into productive investments. The present study aims to compare the financial performance of public and private sector banks operating in India. The study evaluates the performance of five public sector banks and five private sector banks using financial indicators such as profitability, asset quality, liquidity, customer satisfaction, and operational efficiency. Primary data were collected from 200 respondents comprising customers of selected banks through a structured questionnaire. Secondary financial indicators were used to support the comparative analysis. Statistical tools such as percentage analysis, mean score analysis, and independent sample t-test were employed for data interpretation. The findings reveal that private sector banks outperform public sector banks in terms of customer satisfaction, service quality, digital banking facilities, and profitability. Public sector banks, however, enjoy higher customer trust, wider geographical coverage, and greater government support. The study concludes that while private banks exhibit superior financial efficiency, public sector banks continue to maintain a significant presence due to their reliability and extensive branch network. The research provides valuable insights for policymakers, banking professionals, and investors.

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QuantumTrust: Blockchain And Quantum Cryptography Framework For Secure Data Sharing

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Authors: Narendrababu T, V Kiran Kumar

Abstract: As a result, the competition for consumers' attention has been increased because of the rapid development of digital marketplaces. At the same time, the current approaches to consumer analytics are based on the use of self-reported measures and do not reflect subconscious processes. Neuromarketing or neuroscience marketing can be described as the application of neuroscientific methods to understanding consumer behavior. In other words, neuromarketing can be used to investigate the mechanisms of making purchasing decisions. This paper introduces the neuromarketing analytics framework based on EEG, ET, and GSR technologies to predict purchase intent in digital marketplaces. Based on data collected from 120 participants who were shown e-commerce product listings, spectral EEG features (theta, alpha, beta, and gamma bands), ET measures (fixation duration, saccade amplitude, and pupil dilation), and GSR phasic responses have been extracted. The proposed deep learning model combines TCN and multi-head attention architecture and achieves 89.2% accuracy in predicting purchase intent. The performance of the proposed model significantly outperforms unimodal baseline models (EEG-based: 76.4%; ET-based: 78.1%; GSR-based: 71.2%). The most significant predictors of purchase intent are found to be gamma band power (30-45 Hz) during product exposure and pupil dilation change.

DOI: http://doi.org/10.5281/zenodo.20666451

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Leveraging AI-Driven Data Ecosystems For Commercial Excellence In Life Sciences A Unified Framework Integrating Predictive, Prescriptive, And Cognitive Analytics

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Authors: Shilpa Hiwale, Dr B V V Siva Prasa

Abstract: The rapid growth in both the volume and complexity of enterprise data has significantly accelerated the adoption of Artificial Intelligence (AI), particularly within the life sciences industry. This paper explores how AI-driven data ecosystems can enable commercial excellence by integrating predictive, prescriptive, and cognitive analytics within a unified framework. The study combines quantitative analysis of customer, sales, and operational datasets with insights from academic research and real-world industry practices. The findings suggest that organizations adopting integrated AI ecosystems are better positioned to enhance forecasting accuracy, improve customer engagement, and enable faster, more informed decision-making. The data used were business-related datasets sourced from Kaggle and data were gathered using a quantitative and analytical research approach. Using Python-based machine learning frameworks, about 50,000 records of customer, sales, demand, churn and operational data were analyzed. Different analytical models such as Logistic Regression, Decision Tree, Random Forest, Support Vector Machine, and Artificial Neural Networks were used to discover the customer behavior, sales forecasting, customer segmentation, and prediction of risk. The results show that AI-powered analytics have a significant impact on improving the accuracy of predictions, customer retention, business intelligence, and operational efficiency. The most significant factors influencing customer churn were the customers' satisfaction and the customer segmentation and demand forecasting for marketing targeting and resource optimization. The study also shows that AI-powered analytical systems can aid in intelligent decision-making by converting vast amounts of business information into commercial intelligence that is useful for business decisions. The proposed data ecosystem framework will leverage AI to provide predictive, prescriptive and cognitive analytics that will enhance the performance and competitiveness of organizations. The study adds to the body of literature on AI-powered business transformation and offers valuable insights for organizations aiming to adopt data-driven approaches for sustainable commercial success.

DOI: https://doi.org/10.5281/zenodo.20666345

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IoT-Enabled Energy Monitoring And Adaptive Load Control For Intelligent Electrical Distribution Systems

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Authors: Dr Yaganti Krishnapriya, Talari Manohar

Abstract: The increasing demand for energy worldwide and the introduction of renewable energy sources make it necessary to move from conventional electrical distribution systems to smart electrical distribution systems. This study proposes an Internet of Things (IoT)-based framework for continuous real-time monitoring of electrical distribution systems. It employs IoT sensors, edge computing nodes, and a cloud-based analytical system for the continuous monitoring of electrical distribution systems. Moreover, the system uses a novel adaptive load scheduling (ALS) algorithm that is based on a hybrid LSTM-XGBoost model to accurately forecast future consumer loads. With the ALS algorithm, the system can predict consumer loads with an accuracy of 96.2% (RMSE = 0.034). Finally, the Model Predictive Control (MPC)-based load control system lowers peak demand and energy expenses by 27.4% and 19.8%, respectively, in a testbed with 200 residential customers.

DOI: http://doi.org/10.5281/zenodo.20666042

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Employee Motivation And Its Impact On Workplace Productivity: An Empirical Study

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Authors: Gurpreet Singh, Dr. Sahil Nazir

Abstract: Employee motivation is one of the most important determinants of workplace productivity and organizational success. Motivated employees demonstrate greater commitment, efficiency, creativity, and job satisfaction, which ultimately contribute to improved organizational performance. In today's competitive business environment, organizations continuously strive to develop motivational strategies that encourage employees to perform at their best. The present study examines the impact of employee motivation on workplace productivity using primary data collected from 200 employees working in different organizations. The study investigates various motivational factors such as salary and incentives, recognition and rewards, career advancement opportunities, work environment, leadership support, and training and development programs. Data were collected through a structured questionnaire and analyzed using percentage analysis, mean score analysis, correlation analysis, and chi-square testing. The findings reveal that employee motivation significantly influences workplace productivity. Salary and incentives emerged as the most important motivational factor, followed by career growth opportunities and recognition programs. The study also found a strong positive relationship between employee motivation and productivity. Employees who reported higher motivation levels demonstrated better performance, increased efficiency, and greater organizational commitment. The study concludes that organizations should implement comprehensive motivational strategies to enhance employee productivity and achieve long-term success.

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Courtyard as Timeless Architectural Typology: Past. Present. Furure

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Authors: Ar. Sameer Sharma, Khushi Gupta

Abstract: The courtyard has traditionally played the role of climate mediator, social interaction facilitator, and spatial hierarchy structure in Indian built environments. However, this ancient typology has been carefully sidelined in mainstream Indian urban housing in the last 50 years despite its demonstrated environmental and social advantages. The present paper follows a socio-spatial path of the courtyard in Indian architecture in three climatic regions, such as hot-dry, warm-humid and temperate. The study, through the comparative analysis of the traditional precedents, patterns of decline documented, and the current reinterpretations, demonstrates that the loss of the courtyard is due to the overlapping forces: the floor area ratio regulations that punish the open-to-sky spaces, the economic pressures that prefer to maximize the built area, the ideological hegemony of the modernist planning models, and changing household patterns. Still, as the paper also reveals, the underlying principles of the courtyard, which include shallow plans, transitional spaces, hierarchical organization, and climate-responsive geometry are actively being reclaimed and modified by modern practice. Other projects such as House of Secret Gardens (Ahmedabad), Narsighar House (Nakhomah), House of Voids (Vijayawada), Pirouette House (Thiruvananthapuram), House of Memories (Karnataka), and The Earth House (Mukteshwar) represent various approaches to the re-use of courtyard logic. The paper contends that the courtyard is not a nostalgic artefact but a resistant, flexible spatial tool whose logic is urgently needed to tackle the twin challenges of increasing urban density and the accelerating climate change. At the end of the paper, there are design principles and regulatory recommendations on how to integrate courtyard strategies into the future urban development.

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Revenue Generate and Smart Village Devleopment

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Authors: Ar. Arjun Sharma, Zuneid Khan

Abstract: Smart village development integrates modern infrastructure, digital connectivity, smart agriculture, eco-friendly practices, quality education, healthcare, and skill-based livelihood opportunities to enhance the standard of living for rural populations. This research explores revenue generation strategies as a cornerstone for the successful implementation and sustainability of smart village projects. It examines various models of income generation, including Agri-tech innovations, digital entrepreneurship, renewable energy solutions, eco-tourism, and public-private partnerships. Through a combination of case studies, policy analysis, and stakeholder interviews, the study identifies key enablers and barriers to effective revenue generation in rural contexts. The findings highlight the importance of local capacity-building, infrastructure investment, and inclusive governance in fostering resilient rural economies. This paper contributes to the understanding of how smart village frameworks can be financially sustainable while enhancing quality of life, economic opportunities, and social equity in rural regions.

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Construction Methodology Of Rotating Building Using Prefabricated Modules

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Authors: Ar. Sameer Sharma, Sanskar Gupta

Abstract: Rotating buildings form a novel class of dynamic architecture in which each floor rotates independently around a fixed central core, enabling continuously changing façades, customizable views, and adaptive daylighting. This paper investigates the construction methodology of such buildings using prefabricated modular units, with emphasis on the structural system, sequence of assembly, integration of renewable energy, and practical feasibility. The analysis is based on secondary data from case‑study papers on the Dubai Rotating Tower (Dynamic Architecture) and related literature on kinetic and modular high‑rise construction. The typical configuration features a central reinforced‑concrete core to which prefabricated steel‑floor modules are attached, allowing independent rotation via bearing‑based or air‑cushion systems. Vertical‑axis wind turbines are integrated between floors, and solar panels are mounted on the roof, contributing to partial or full energy self‑sufficiency. The prefabricated approach reduces on‑site labour by 70–80%, accelerates construction by 30–50%, and improves quality control. Despite these advantages, the system faces challenges in maintenance, logistics, and economic feasibility, especially in emerging markets such as India. The paper concludes that rotating buildings using prefabricated modules are technically feasible and conceptually suitable for contemporary high‑rise design, but require detailed structural, mechanical, and economic studies before large‑scale implementation.

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