Shared mobility choices in metro connectivity: shared bikes versus shared e-bikes

The concurrent availability of shared bikes (DBS) and emerging shared e-bikes (EBS) systems offers new opportunities for sustainable urban mobility, particularly in enhancing first/last-mile connectivity with metro systems. However, a significant gap exists in understanding user choice behavior between DBS and EBS for metro connectivity. As shared micromobility options, DBS and EBS exhibit more competitive and complementary relationships compared to other transport modes when integrated with metro services. This study aims to bridge this gap by exploring the factors that influence the choice of DBS and EBS as metro connection modes. Taking Kunming—a Chinese city where both modes coexist—as a case study, the study identifies DBS and EBS trips connecting to the metro using operational data analyzed through the K-dimensional tree method (KDTree) along with Kernel Density Estimation analysis (KDE) methods. A Light Gradient Boosting Machine (LightGBM) model analyzes nonlinear effects in both to-metro and from-metro scenarios across four aspects: socioeconomic attributes, travel characteristics, the built environment, and transportation facilities. The results indicate that transportation facilities and the built environment significantly influence DBS and EBS user choices for metro connections, with notable nonlinear effects. For instance, cycling distance significantly influences mode choices. Initially, the probability of selecting EBS increases with cycling distance, then stabilizes. The likelihood of choosing EBS initially decreases and then increases as road non-linear coefficients rise in two modes. These insights deepen our understanding of DBS and EBS user choices for metro connections, improving the integration of these modes for first/last-mile journeys.