Smart Digital Service Ecosystems A Research Roadmap from Service Computing and Engineering Perspectives - Badr, Youakim (Cham : Springer International Publishing : Imprint: Springer, 2023)
This book provides a holistic overview of the major advances that have been made in the context of Service Science with a focus on IT-enabled services. To address challenges in collaborative, social-centric, ad-hoc, dynamic and open environments, the book studies IT-enabled service systems from two distinct but complementary research perspectives: service engineering and service computing. From a service engineering view, the book shows how to apply a systemic approach to tackle social problems from holistic and multi-disciplinary perspectives by focusing on service systems and developing a service design framework, including socio-technical aspects, the service reference model, data-driven collaboration processes, the incremental design method, requirement propagation, and system adaptability with feedback loops. From a service computing view, the book introduces a service-oriented aided infrastructure to support IT-enabled service systems in ICT-facilitated environments and provide access to tangible and intangible resources in a trustworthy environment. The book offers a valuable companion and comprehensive reference guide for undergraduate and graduate students who want to learn about current concepts for designing and implementing service systems; and for researchers who want to identify future directions in build smart digital service ecosystems, integrating Internet of Things (IoT) and Artificial Intelligence (AI) and cyber-security. The book also appeals to developers who need to implement advanced services and want to capitalize on corresponding business models, customer-driven interaction, and scalable architectures.
Keywords: Service industries; Operations research; Quantitative research; Engineering mathematics; Engineering -- Data processing; Technological innovations; Electronic data processing -- Management; Services; Operations Research and Decision Theory; Data Analysis and Big Data; Mathematical and Computational Engineering Applications; Innovation and Technology Management; IT Operations