
Emerging Frontiers in Interdisciplinary Research: Artificial Intelligence, Innovation, and Sustainable Transformation explores the dynamic convergence of technology, creativity, and sustainability in shaping the future of global development. This volume brings together diverse perspectives from scholars, researchers, and practitioners who examine how artificial intelligence and innovative methodologies are transforming traditional disciplines and creating new pathways for collaborative progress. The book highlights the role of AI as a catalyst for change across sectors such as education, healthcare, environmental management, industry, and public policy. It demonstrates how interdisciplinary approaches foster holistic solutions to complex global challenges, including climate change, resource management, digital transformation, and social equity. By integrating technological advancement with sustainable thinking, the contributors emphasize responsible innovation that balances economic growth with environmental and social well-being. Through theoretical insights, empirical studies, and practical case analyses, the book provides readers with a comprehensive understanding of emerging research trends and their real-world applications. It encourages dialogue between disciplines, bridging gaps between science, technology, humanities, and management to promote inclusive and sustainable progress. Designed for academicians, researchers, policymakers, and industry professionals, this volume serves as both a scholarly resource and a strategic guide. It underscores the importance of collaborative intelligence in navigating the complexities of the modern world and inspires forward-thinking solutions for a sustainable and innovation-driven future.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
