The Science of Flexibility in Mobility

This book presents a systematic approach to designing flexible structures for effective operations, bridging centralized planning with decentralized execution. With applications spanning supply chain management, service operations, and smart city logistics, the authors develop innovative approaches to resource allocation, workforce mobility, and transportation networks. Drawing on recent advances in process flexibility, the book examines how operational systems can adapt efficiently to changes in demand, resources, and external conditions. The authors bring together recent developments in flexibility design, including sparsity design in general networks and flexibility in decentralized systems. The book also introduces contemporary approaches to decision-making under uncertainty, including robust optimization and real-time analytics. As organizations face increasing uncertainty and rapid technological change, the ability to design flexible and adaptive operational systems has become increasingly important. This book provides a systematic framework for understanding, designing, and implementing flexibility in mobility, supply chain, and service operations and is a valuable resource for researchers, practitioners, and graduate students in operations research, industrial engineering, business analytics, and related fields.

Illustrates how flexibility can improve mobility systems, with applications including ride-sharing and urban planning Provides real-world case studies demonstrating how flexible operational structures can enhance efficiency and resilience Includes recent research on flexibility in decentralized operations and its implications for operational decision-making

Autorentext

Mabel C. Chou, Ph.D., is an Associate Professor in the Department of Analytics and Operations at National University of Singapore (NUS). Her research focuses on process flexibility, optimization, operations and supply chain management, and data-driven decision-making, with applications to complex systems under uncertainty. Her work addresses the design and management of flexible operational systems, resource allocation, and decision-making across supply chain and service operations and has been published in leading international journals. Dr. Chou has extensive experience working with industry, having consulted for organizations including GSK, Unilever, Caterpillar, P&G, SIA Engineering Company, National University Hospital, Lenovo, and Supreme Components International.

Jinjia Huang, Ph.D., is an Associate Professor at College of Management and Economics, Tianjin University. He was a senior research fellow of the Institute of Operations Research and Analytics (IORA) at the National University of Singapore. His research is driven by real-world challenges through global industry collaborations across China, Singapore, Japan, and the United States, working with companies such as SF Express, VariFlight, Guiyang Renmin Hospital, SBS Transit, Singapore Airlines, IDSC Consultancy, Komatsu, and Jerome's Furniture. He specializes in applying data-driven optimization, empirical analysis, and deep learning to address complex challenges in logistics, supply chain management, airline and airport operations, supply chain finance, healthcare, and retail operations. His work has been published in leading journals and has led to the development of the Joint Prediction and Optimization (JPO) system for demand forecasting and inventory control.

Chung Piaw Teo, Ph.D., is Dean and Stephen Riady Professor at NUS Business School, National University of Singapore (NUS). He is also Co-Director of the SIANUS Digital Aviation Corporate Laboratory. Prior to becoming Dean, he was executive director of the NUS Institute of Operations Research and Analytics (IORA). He has held several leadership positions at NUS Business School, including head of department, acting deputy dean, vice-dean of research and the Ph.D. program, and chair of the Ph.D. committee. Dr. Teo's research spans operations research and analytics, supply chain management, discrete optimization, service and manufacturing operations, and machine learning, with applications in areas including aviation, logistics, e-commerce, platform operations and urban systems. He was elected an INFORMS Fellow for his contributions to the optimization of business processes, particularly in inventory, logistics and supply chain management, as well as for his leadership and service to the profession.

Zhenzhen Yan, Ph.D., is an Associate Professor at the School of Physical and Mathematical Sciences, with a courtesy appointment at Nanyang Business School, Nanyang Technological University. Her research interests primarily focus on data-driven resource allocation. She has pioneered a series of robust and responsive methods, especially effective with moderate datasets. Her work has broad applications, spanning smart city operations, supply chain management, and e-commerce operations. Through the development of advanced models and analytical tools, she addresses real-world challenges, particularly in decentralized and dynamic environments, ensuring solutions are both scalable and practical. Her work has led to more than 10 publications in leading operations management journals, and her research excellence has garnered recognition through numerous accolades.

Inhalt

Introduction to Process Flexibility.- Foundations of Process Flexibility.- Designing Sparse yet Effective Structures.- Flexibility in Decentralized Systems: When Less Is More.