Accurate demand forecasting is a key success for mobility service businesses, especially
shared electric (e-) scooters, for their volatile demand, high operational costs, and strict …

The electric scooter (e-scooter) sharing service has attracted significant attention because of
its extensive usage and eco-friendliness. Since e-scooters are mostly accessed by foot, the …

This paper presents the findings on modeling the demand for shared e-scooter services
(SES); specifically, spatio-temporal variation of SES demand. A zero-inflated negative …

Dockless electric scooters (e-scooter) have emerged as a green alternative to automobiles
and a solution to the first-and last-mile problems. Demand anticipation, or being able to …

The shared electric scooter (E-scooter) is an emerging micro-mobility mode in sustainable
cities. Accurate hourly trip demand prediction is critical for effective service maintenance, but …

The goal of the current study is to identify and quantify the influence of various contributing
factors on dockless e‐scooter demand. Drawing on high‐resolution e‐scooter trip level data …

First-Mile/Last-Mile is one of the burdened urban transportation problems limiting the
effectiveness of public transit. Recently, the newly emerged shared micro-mobility, escooter …

Accurately forecasting the real-time travel demand for dockless scooter-sharing is crucial for
the planning and operations of transportation systems. Deep learning models provide …

The shared e-scooter is a popular and user-convenient mode of transportation, owing to the
free-floating manner of its service. The free-floating service has the advantage of offering …

Shared e-scooter programs were first implemented in 2017 to solve problems with the
current transportation landscape. Combining ideas from mobility as a service, micromobility …