Abstract
This study quantifies the impact of individual attributes, the built environment, and travel characteristics on the use of bike-sharing and the willingness of shifting to bike-sharing-related travel modes (bike-sharing combined with other public transportation modes such as bus and subway) under different scenarios. The data are from an RP (Revealed Preference) survey and SP (Stated Preference) survey in Nanjing, China. Three mixed logit models are established: an individual attribute–travel characteristics model, a various-factor bike-sharing usage frequency model, and a mixed scenario–transfer willingness model. It is found that age and income are negatively associated with bike-sharing usage; the transfer distance (about 1 km), owning no car, students, and enterprises are positively associated with bike-sharing usage; both weather and travel distance have a significant negative impact on mode shifting. The sesearch conclusions can provide a reference for the formulation of urban transportation policies, the daily operation scheduling, and service optimization of bike-sharing.
Highlights
The development of technologies such as big data and mobile payments has led to new types of travel, including bike-sharing
The online survey was conducted in Nanjing, China, in September 2018, and two offline supplementary surveys were conducted in January 2019 and September 2019, which were implemented by Revealed Preference (RP) survey
This study explored the impact of bike-sharing on the transfer of residents’ travel modes by travel survey data in Nanjing, China
Summary
The development of technologies such as big data and mobile payments has led to new types of travel, including bike-sharing. Bike-sharing is where companies provide bicycle-sharing services in public service areas such as campuses and subway stations It is a time-sharing leasing model, which is in line with the concept of low-carbon travel, maximizes the use of public road passing rates, and is a new type of green environmental protection sharing economy. The paper establishes an individual attribute–travel feature model and analyzes the influence of the individual attributes on travel characteristics when using bike-sharing-related travel modes. We have established a mixed scenario–transfer willingness model to investigate the tendency of travelers to shift to bike-sharing-related travel modes in different scenarios. Based on the research findings, the degree of influence of various types of travelers is clearly identified, which provides a reference for urban traffic policy formulation and bike-sharing operation management, daily dispatch, and structural optimization, and promotes the organic integration of multi-modal transportation modes for efficient and green development of the comprehensive urban transportation system.
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