Applying machine learning approaches to model travel choice between micro-mobility services
Shared micro-mobility gradually becomes a crucial part of human daily transportation. To develop the shared micro-mobility, discovering the important influence factors of each travel mode is a key aspect. However, there are scarce studies that adopt machine learning methods to model travel choice between shared micro-mobility services and identify the crucial determinants for each mode. This study