AI, Society and Digital Transformation

Proceedings of 2025 INFORMS Conference on Service Science, Oxford, UK, July 1-3, 2025
Erscheinungsjahr 2026
ISBN: 978-3-032-13115-7
Verlag: Springer

Buch, Englisch, 316 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 651 g

Reihe: Lecture Notes in Operations Research

This book presents recent research and practice advances in the field of Service Science. It contains selected papers from the 2025 INFORMS International Conference on Service Science, held in Oxford, UK from July 1-3, 2025. The book explores how AI, data, and digital technologies are driving sustainable transformation across industries and society at both national and international levels. It presents new theoretical frameworks, empirical research, and practical applications in the interdisciplinary fields of AI, digital transformation, and service science. The content includes empirical studies, modeling, and theoretical research that examine how AI and data are advancing sustainability across service systems. Topics covered include AI-driven smart cities, sustainable systems, the digital economy, AI ethics and governance, public health and AI, human-AI collaboration, machine learning and data-driven decision-making, quantum computing in service science, and the digital transformation of traditional industries.

Zielgruppe

Research

Autoren/Hrsg.

Xie, Xiaolei

Hu, Kejia

Hu, Guiping

Chen, Weiwei

Qiu, Robin

Fachgebiete

• Mathematik | Informatik EDV | Informatik Professionelle Anwendung
• Wirtschaftswissenschaften Wirtschaftssektoren & Branchen Dienstleistungssektor & Branchen
• Wirtschaftswissenschaften Betriebswirtschaft Wirtschaftsmathematik und -statistik
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz
• Wirtschaftswissenschaften Betriebswirtschaft Unternehmensforschung
• Wirtschaftswissenschaften Betriebswirtschaft Management Entscheidungsfindung
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken

Inhaltsverzeichnis

Inverse optimization in finite state continuous-time Markov decision processes.- Predicting Instability at Home and in Foster Care, Challenges and Opportunities.- Shaping the Future of Work in the AI Era: Business Model Innovation in Digitalisation for Decent Work and Economic Growth.- Research on Dynamic Risk Avoidance Route Planning for Multi Drone Collaborative Delivery in Complex Urban Environments.- Balancing Innovation and Values: How Culture Shapes AI Regulation.- From Proposals to Outcomes: Concept Aligned Chunking for Cross Document Relevance Assessment in Research Funding Review.- Design Of Intelligent Traffic Signal Control Using Reinforcement Learning.- DP UOTM: A Differentially Private Unbalanced Optimal Transport based Approach for High Quality Medical Image Synthesis.- Analysis of Changes in Grey White Matter Contrast in Healthy Older Adults.- Theorizing Generative AI’s Role in Strategic Decision Making: From Automation to Augmentation.- Static vs Dynamic Scheduling in Teleconsultation Systems: Managing Uncertainty and Walk ins in Teleconsultation.- The Impact of AI on Job Polarization in Egyptian Banking: Patterns, Implications and Associated Risks.- MSIO DLD Algorithm: Multi Objective Optimization for Health Science Short Video Recommendation.- Health Literacy in Online Health Platforms: A Markov Chain Analysis of User Behavioral Transitions.- Clustering Analysis of Cecal Microbiota Dynamics in Eimeria Maxima Infected Chickens.- Enhancing Logistics Management Education for Non STEM Students in the AI Era: Evaluating the Role of Industry Experts in Logistics Education.- Mathematical Foundations of AI Augmented Leadership: The NOVA Framework for Multi Agent AI Optimization.- Packages Design for Comorbid Psychiatric Disorders Based on Optimization of Disease Burden.- Optimizing Bus Fleet Energy Composition: Balancing Operator Costs and Carbon Emissions in Transit Network.- The Algorithmic Reconfiguration of Qualitative Inquiry: Navigating AI Driven Efficiency and Interpretive Richness.- Persuading AI Agents in a Queueing Game of Socially Scarce Resources Acquisition.- Comorbidity Patterns Before and After Juvenile Idiopathic Arthritis Diagnosis.- Validation of Survey Measures for Behavioral Customer Engagement with Textual Content from Customer Reviews.- RGP: Robust Goal Programming for Healthy Nutrition Tracking Using Patients  Dietary Image Predicted Data.

Über Autor(innen)

Xiaolei Xie is an Associate Professor in the Department of Industrial Engineering, Tsinghua University. His research focuses on the intersection of data science, operations research, simulation, and healthcare management. He has published over 30 international academic papers, with some of his work highlighted by academic organizations as outstanding contributions and selected as best papers of the year. He has received the Tsinghua University Outstanding Performance Award and the Annual Teaching Excellence Award.

Kejia Hu is an Associate Professor of management science at Saïd Business School, University of Oxford, UK and a Governing Body Fellow at Exeter College. Her research focuses on the integration of artificial intelligence (AI) with human decision-making in operations, aiming to transform real-world practice. By leveraging AI-driven data analytics, she develops innovative solutions to enhance resilience, operational efficiency, and service delivery in complex systems. Her work is widely published in leading academic journals and recognized for advancing the role of AI in practical, data-informed decision-making.

Guiping Hu is a Professor and the Head of School of Industrial Engineering and Management at Oklahoma State University, USA. She is also an IISE Fellow and the Donald & Cathey Humphreys Chair. Her research focuses on operations research and data analytics with applications in supply chain design, manufacturing production, renewable energy systems, and sustainable agriculture. Dr. Hu’s research has been supported by NSF, USDA, DOE, and DOD with over $11.9M funding. She has published about 100 journal articles and 50 conference proceedings with 4800+ citations. She is an ELATES fellow and an NSF IAspire Leadership Academy Fellow.

Weiwei Chen is a Professor at Rutgers University, USA. His research interests lie in operations and finance interface, as well as supply chain operations planning and scheduling. He also works on simulation and randomized global optimization methodologies. He has extensive experience working with businesses and the public sector, especially in energy and healthcare, to improve strategic decisions and operational efficiency using data analytics.

Robin Qiu is a tenured Professor of information science at Pennsylvania State University, USA. He teaches a variety of information and computing science courses, such as predictive analytics, management science, business process management, decision support systems, project management, enterprise integration, enterprise service computing, software engineering, Web-based systems, distributed systems, computer architecture/SOA, computer security, Web security, operations research, and system engineering. His research interests include big data, data/business analytics, smart service systems, service science, service operations and management, information systems, cybersecurity, blockchain, and manufacturing and supply chain management.