E-bike sharing is considered a new mode of transport that is rapidly developing in China. In order to better understand the factors affecting the intention to use e-bike sharing, this study is based on the theory of planned behavior (TPB) and the technology acceptance model (TAM) and added the variable of policy support. A sample of 441 respondents in a small city in China was collected to analyze residents’ intention on e-bike sharing usage. The results show that the research model can explain well residents’ intention to use shared e-bikes. Perceived ease of use, perceived usefulness, attitude, subjective norms, and perceived behavioral control have direct positive effects on the intention to use shared e-bikes. Among them, the perceived ease of use has the greatest impact on the intention to use shared e-bikes. Moreover, policy support has an indirect positive influence on the intention to use shared e-bikes through partial mediation of attitude and subjective norms. Finally, some strategies to promote e-bike sharing are proposed. This study can provide a better understanding of the acceptance of e-bike sharing and the strategy for promoting e-bike sharing in urban transportation.

The phenomenon of population aging is gradually spreading around the world. Consequently, it is leading to unsustainable economic development due to the decline of the labor force. Therefore, many people identify the aging population from national and intercontinental levels, as it would not be possible to recognize specific population spatial distribution characteristics and impacting factors in a province or state because of the spatial and temporal differences. In this paper, Jiangsu Province was selected as the study area to represent its aging population’s spatial characteristics and to identify the spatial heterogeneity with impacting factor by Geographically Weighted Regression (GWR), as well as to determine the impacting situation by marginal effect. The results show the following: (1) The impact factor’s spatial heterogeneity from the cities in Jiangsu Province is small but occurs in the city groups, while the impacting situation is the same in the north, central and south city groups, showing a disparity among them. (2) There is a significant change in the impact factor’s influence from 2010 to 2020. (3) The social–economic factor negatively relates to the aging population in 2020, with an interval value of [−1.0585, −1.0632]. This finding indicates that the spatial heterogeneity of the aging population at the province level is not the same as that at the national level. Therefore, we need to consider the local situation more. These findings further provide an empirical basis for the province-level study of the aging population, which differs from the national level.

As a form of rapid mass transportation, urban rail systems have always been widely used to alleviate urban traffic congestion and reconstruct urban structures. Land use characteristics are indispensable to this system and correlate with urban ridership. Dock-less bicycle-sharing expands the station service coverage range because it integrates public transportation with an urban rail system to create a convenient travel model. Consequently, the land use pattern with dock-less bicycle-sharing is associated with urban rail ridership. This paper measures the correlation between land use and urban rail ridership based on the trajectory of dock-less bicycle-sharing, which precisely reflects the travel behavior of passengers along the trip chain. The specific relationship has been determined using the random forest model. This paper found that the land use pattern could better explain the egress ridership during morning peak hours. In particular, it could explain 48.46% of the urban rail ridership in terms of egress, but the explicability for the ingress ridership slightly decreased to 36.88%. This suggests that the land use pattern is related to urban rail ridership. However, the impact situation varies, so we should understand this relationship with greater care.