The Factors Influencing Resident’s Intentions on E-Bike Sharing Usage in China

Abstract

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.

A Comparison in Travel Characteristics of Bike-Sharing between College Students and Office Workers Based on Theory of Planned Behavior

“…Ransford found that for office workers who use bicycles for work, AT does not significantly affect behavioral intentions [ 41 ]. Research findings that in the E-bike-sharing travel model, the influence of AT on travel intentions is less significant than that of SN and PBC [ 42 ].…”

“…Subjective norm (SN) refers to the social pressure that individuals face when adopting a certain behavior, where support or approval from family and friends can increase willingness to adopt a certain behavior, and vice versa [ 19 ]. Regarding bicycle travel, parents may not recommend to their children to ride bicycles due to safety concerns, while friends and classmates may use the advantages of bike sharing to increase their willingness to travel [ 42 ]. Previous studies have demonstrated the positive impact of bike sharing on the willingness to travel by bicycle, with some scholars arguing that the influence of SN on the willingness to use bike sharing is most significant [ 42 , 43 , 44 ].…”

“…Regarding bicycle travel, parents may not recommend to their children to ride bicycles due to safety concerns, while friends and classmates may use the advantages of bike sharing to increase their willingness to travel [ 42 ]. Previous studies have demonstrated the positive impact of bike sharing on the willingness to travel by bicycle, with some scholars arguing that the influence of SN on the willingness to use bike sharing is most significant [ 42 , 43 , 44 ]. Measures such as policy guidance, environmental awareness, and price incentives can have a positive impact on bicycle travel through SN.…”

Aging Population Spatial Distribution Discrepancy and Impacting Factor

“…The marginal impact estimates the likelihood that a response level will change as the predicted changes occur. The estimated observation variable on the intention to use shared motorcycles, which claims to improve the variable with a higher average marginal effect value, will achieve a great benefit [33].…”

“…There was a rapid increase in medical beds between 2010 and 2020, reaching 62.3 in 2020 versus 30.59 in 2010; the most significant change is Xuzhou, where the number of beds grew eight times over the decade. The number of medical beds represents the necessary level of local healthcare facility for the elderly group [33]. The guide from China's National Health Commission suggests that the number of medical beds should reach 74-75/10,000 people by 2025.…”