http://10.9.150.37:8080/dspace//handle/atmiyauni/252 Mon, 27 Apr 2026 18:44:25 GMT 2026-04-27T18:44:25Z http://10.9.150.37:8080/dspace//handle/atmiyauni/2338 Title: An Analytical Study on Customer Satisfaction Towards Online Banking Services for Selected Public Sector and Private Sector Banks Special Reference to Gujarat State Authors: Trivedi, Ishaben Aniruddhbhai; Dr. Kairvi, Rathod Wed, 01 Oct 2025 00:00:00 GMT http://10.9.150.37:8080/dspace//handle/atmiyauni/2338 2025-10-01T00:00:00Z http://10.9.150.37:8080/dspace//handle/atmiyauni/2337 Title: A Study on Factors Affecting Consumer Brand Switching Behavior in Prepaid Telecom with Special Reference to South Gujarat Zone Authors: Malek, Parvez Abdulhabib; Dr. Vishal, Khasgiwala Abstract: This research explores the factors affecting brand switching behaviour among prepaid newlinetelecom consumers in South Gujarat, focusing on understanding the key drivers that lead newlineconsumers to shift from one telecom provider to another. In the highly competitive prepaid newlinetelecom market, where multiple providers offer similar services, consumers frequently make newlinebrand-switching decisions based on various factors such as price sensitivity, network quality, newlinecustomer satisfaction, and promotional offers. The study identifies psychological factors, newlinesuch as trust, emotional attachment, and perceived value, as significant influencers of newlineconsumer decisions. newlineIt uses a descriptive research design that combines both qualitative and quantitative approach newlinees to collect data through structured questionnaires. The study involved 500 participants from newlinefour cities in South Gujarat. To analyze the data and check the hypotheses about how factors newlinelike demographics, service quality and brand loyalty are connected, statistical methods such newlineas descriptive statistics, regression analysis and actor analysis were used. newlineIt uses a descriptive research design, employing both qualitative and quantitative methods to newlinegather data through structured questionnaires, with a sample size of 500 respondents across newlinefour cities in South Gujarat. Statistical techniques, including descriptive statistics, regression newlineanalysis, and factor analysis, were used to analyze the data and test the hypotheses related to newlinethe relationships between demographic factors, service quality, pricing, and brand loyalty. newlineThe findings suggest that while price sensitivity and network quality are the primary drivers newlineof brand switching, factors such as customer satisfaction, trust, and promotional offers also newlineplay significant roles. Additionally, demographic factors like age, income, and education newlineinfluence the likelihood of consumers switching brands. The research concludes by providing newlineactionable insights for telecom operators to improve customer retention strategies Mon, 01 Sep 2025 00:00:00 GMT http://10.9.150.37:8080/dspace//handle/atmiyauni/2337 2025-09-01T00:00:00Z http://10.9.150.37:8080/dspace//handle/atmiyauni/2323 Title: Generative AI's Direct and Total Effect on Operational Excellence in Manufacturing: A Systematic Literature Review Authors: Singh, Rupali; Sankhi, Anil; Sikh, Gurmeetsingh H.; Nanavati, Kausumi Sun, 01 Jun 2025 00:00:00 GMT http://10.9.150.37:8080/dspace//handle/atmiyauni/2323 2025-06-01T00:00:00Z http://10.9.150.37:8080/dspace//handle/atmiyauni/2322 Title: Impact of Generative AI on Operational Excellence in Supply Chain Management: A Quantitative Analysis Authors: Singh, Rupali; Sankhi, Anil; Sikh, Gurmeetsingh H.; Nanavati, Kausumi Abstract: This study investigates the transformative impact of Generative Artificial Intelligence (GenAI) on operational excellence within supply chain management (SCM), particularly in manufacturing organizations. As supply chains face increasing complexity and volatility, GenAI offers powerful capabilities to enhance efficiency, agility, and decision-making. Using a quantitative research design, the study compares pre- and post-implementation performance metrics across 100 manufacturing firms. Key areas examined include cost reduction, inventory optimization, production scheduling, and risk mitigation. The analysis employs simple linear regression to test two hypotheses related to GenAI’s influence on operational cost and performance. Results reveal a statistically significant positive relationship between GenAI adoption and operational excellence, with an R-squared value of 0.838 indicating strong predictive power. Organizations that integrated GenAI experienced improvements in lead time reduction, on-time delivery rates, and inventory turnover. The findings support the resource-based view and dynamic capabilities theory, suggesting GenAI as a strategic asset that fosters competitive advantage through enhanced supply chain capabilities. This research contributes to both academic literature and managerial practice by offering empirical evidence on the benefits of GenAI in achieving supply chain excellence. The study also highlights critical success factors and suggests directions for future research in AI-driven supply chain transformation. Sun, 01 Jun 2025 00:00:00 GMT http://10.9.150.37:8080/dspace//handle/atmiyauni/2322 2025-06-01T00:00:00Z