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This book presents a comprehensive framework of scenarios engineering designed to guide and support services science in the era of modern AI. Offering a systematic overview of recent advancements, it explores key challenges and opportunities in both services science and scenarios engineering. The framework, grounded in parallel intelligence theory, addresses critical issues posed by emerging AI technologies in services systems, while providing tools for analysis, validation, and calibration. It also offers a platform for evaluating, analyzing, and comparing existing Scenarios Engineering for Services Science (SE4SS) projects, as well as guiding new research endeavors. By integrating core elements of services science, such as services systems, metrics, technology, automation, and ethics, through a multidimensional lens, the book enables researchers to explore foundational models, intelligent systems, domain-specific knowledge bases, datasets, and virtual systems. Case studies from various academic fields illustrate the application of standardized dimensions and metrics, fostering interdisciplinary insights and accelerating the development of the field.

The book is designed for researchers, practitioners, and students interested in the intersection of services science and artificial intelligence. It balances theoretical depth with practical application, offering valuable case studies and examples that clarify core concepts and make the material accessible. With its goal-oriented approach, the book is ideal for academics exploring advancements in services science and AI, data scientists applying AI to services systems, and students seeking to deepen their understanding of these rapidly evolving fields.