Editorial: Emerging on-demand passenger and logistics systems: Modelling, optimization, and data analytics

• Main Authors: KE, Jintao, WANG, Hai, MASOUD, Neda, SCHIFFER, Maximilian, CORREIA, Goncalo H. A.
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2024
• Subjects: Numerical Analysis and Scientific Computing; Operations Research, Systems Engineering and Industrial Engineering; Transportation
• Online Access: https://ink.library.smu.edu.sg/sis_research/8715; https://ink.library.smu.edu.sg/context/sis_research/article/9718/viewcontent/EmergingOn_DemandPassenger_av.pdf
• Institution: Singapore Management University

The proliferation of smart personal devices and mobile internet access has fueled numerous advancements in on-demand transportation services. These services are facilitated by online digital platforms and range from providing rides to delivering products. Their influence is transforming transportation systems and leaving a mark on changing individual mobility, activity patterns, and consumption behaviors. For instance, on-demand transportation companies such as Uber, Lyft, Grab, and DiDi have become increasingly vital for meeting urban transportation needs by connecting available drivers with passengers in real time. The recent surge in door-to-door food delivery (e.g., Uber Eats, DoorDash, Meituan); grocery delivery (e.g., Amazon Fresh, Picnik); and same-day courier services (e.g., Amazon Same-Day Delivery) has significantly enhanced both convenience and safety for customers, particularly during the COVID-19 pandemic.