Eric Tsui – författare

This book looks at generative artificial intelligence (GAI) and knowledge management systems (KMS). It explains the design considerations to implement generative AI in practice.The book looks at the evolving digital environment and discusses how organizations may effectively manage knowledge through emerging technologies. Chapters cover theory, design, and implementation and case studies from industry players. These case studies will focus on organization implementation experiences to draw out applicable frameworks, principles, and best practices. This provides readers with essential insights into future technology development trends.Providing a methodological approach to designing and deploying GAI-based KMS in business, this book will appeal to academic researchers, industrial practitioners, students, and anyone interested in GAI-based KMS.

This book looks at generative artificial intelligence (GAI) and knowledge management systems (KMS). It explains the design considerations to implement generative AI in practice.The book looks at the evolving digital environment and discusses how organizations may effectively manage knowledge through emerging technologies. Chapters cover theory, design, and implementation and case studies from industry players. These case studies will focus on organization implementation experiences to draw out applicable frameworks, principles, and best practices. This provides readers with essential insights into future technology development trends.Providing a methodological approach to designing and deploying GAI-based KMS in business, this book will appeal to academic researchers, industrial practitioners, students, and anyone interested in GAI-based KMS.

This book looks at generative artificial intelligence (GAI) and knowledge management systems (KMS). It explains the design considerations to implement generative AI in practice.The book looks at the evolving digital environment and discusses how organizations may effectively manage knowledge through emerging technologies. Chapters cover theory, design, and implementation and case studies from industry players. These case studies will focus on organization implementation experiences to draw out applicable frameworks, principles, and best practices. This provides readers with essential insights into future technology development trends.Providing a methodological approach to designing and deploying GAI-based KMS in business, this book will appeal to academic researchers, industrial practitioners, students, and anyone interested in GAI-based KMS.

This book presents selected papers from the 2025 3rd International Conference on Management Information System which was held on Yokohama, Japan during September 27-29. The chapters collectively offer a rich and diverse exploration of contemporary issues in management information systems, reflecting cutting-edge research and practical applications. These chapters address critical topics such as technological innovation, sales management, government incentives for sustainable transportation, and the paradoxes of technology adoption. By reframing technological pathways and examining effective sales strategies, the book provides fresh perspectives and practical solutions for both academia and industry.The integration of advanced methodologies, such as data mining for predicting fire incidents and machine learning models for financial predictions, showcases the innovative use of technology in risk management and decision-making processes. Additionally, the exploration of AI's impact on individual investors and the enhancement of management information systems with large language models highlight the transformative potential of artificial intelligence in various sectors.Overall, the book's comprehensive approach and interdisciplinary focus make it a valuable contribution to the fields of management information systems, finance, and technology, offering theoretical and practical insights that can drive innovation and efficiency across multiple domains.

This book presents selected papers from the 2025 3rd International Conference on Management Information System which was held on Yokohama, Japan during September 27-29. The chapters collectively offer a rich and diverse exploration of contemporary issues in management information systems, reflecting cutting-edge research and practical applications. These chapters address critical topics such as technological innovation, sales management, government incentives for sustainable transportation, and the paradoxes of technology adoption. By reframing technological pathways and examining effective sales strategies, the book provides fresh perspectives and practical solutions for both academia and industry.The integration of advanced methodologies, such as data mining for predicting fire incidents and machine learning models for financial predictions, showcases the innovative use of technology in risk management and decision-making processes. Additionally, the exploration of AI's impact on individual investors and the enhancement of management information systems with large language models highlight the transformative potential of artificial intelligence in various sectors.Overall, the book's comprehensive approach and interdisciplinary focus make it a valuable contribution to the fields of management information systems, finance, and technology, offering theoretical and practical insights that can drive innovation and efficiency across multiple domains.

This proceedings volume covers peer-reviewed papers of the 2nd International Conference on Management Information System which is held on Sept 28–30, 2024, in Tokyo, Japan. In an increasingly digitalized and connected world, management information systems are no longer serving resource planning, monitoring and reporting purposes. Indeed with the increasing availability of data from new sources, machine learning and artificial intelligence software can enable more automations involving less human decision-making and interventions, as well as generate predictions which can, among others, enhance risk prevention and astuteness in crisis management. This volume is valuable in introducing and explaining the impact of Industry 4.0, generative artificial intelligence, metaverse and others on organizational management information systems. Latest research and case studies are covered.

This proceedings volume covers peer-reviewed papers of the 2nd International Conference on Management Information System which is held on Sept 28–30, 2024, in Tokyo, Japan. In an increasingly digitalized and connected world, management information systems are no longer serving resource planning, monitoring and reporting purposes. Indeed with the increasing availability of data from new sources, machine learning and artificial intelligence software can enable more automations involving less human decision-making and interventions, as well as generate predictions which can, among others, enhance risk prevention and astuteness in crisis management. This volume is valuable in introducing and explaining the impact of Industry 4.0, generative artificial intelligence, metaverse and others on organizational management information systems. Latest research and case studies are covered.