A statistical analysis of bike sharing usage and its potential as an auto-trip substitute. (March 2019)

• Record Type: Journal Article
• Authors: Barbour, Natalia; Zhang, Yu; Mannering, Fred
• Is Part Of: Journal of transport & health. Volume 12(2019)
• Page Start: 253
• Page End: 262
• Publication Date: 2019-03
• Subjects: Travel behavior -- Random-parameter logit models -- Shared mobility -- Health indicator -- Mode shift; Transportation -- Health aspects -- Periodicals; Transportation -- Periodicals; Public Health -- Periodicals; Noise, Transportation -- Periodicals; Air Pollutants -- Periodicals; 388
• DOI: 10.1016/j.jth.2019.02.004
• Languages: English
• ISSNs: 2214-1405

Abstract

Abstract: Introduction: Bikesharing has become increasingly popular in urban areas as an alternative active transportation mode that can help relieve congestion, mitigate negative environmental impacts, and improve public health through increased physical activity. To understand the benefit of bikesharing, it is important to identify the factors influencing how often registered users use bikesharing, and assess whether and how much their bikesharing use is displacing an auto trip. Methods: A survey was conducted, and random parameters logit models were estimated to study individuals' bikesharing usage rates and modal substitution. In addition to standard socio-demographic and travel behavior characteristics of the survey respondents, health-related questions were also included in the survey and health-related indicators were considered as explanatory variables in the estimated models. Results: It was found that gender, age, income, household size, commute type and length, and vehicle ownership all played significant roles in bikesharing usage and modal substitution decisions. Regarding health measures, respondents' body mass index (BMI), one of the health-related indicators, was also a significant predictor of bikesharing usage. Conclusions: The outcomes of this research provide some initial insights into the bikesharing decision-making process that can help in the development of policies to improve the performance of bikesharing systems and making them a more viable transportation option. Highlights: Introduced height, weight, and other health-related indicators in the questionnaire of bikesharing. Studied both the use frequency of bikesharing and the function of bikesharing as auto mode substitute. Used random parameters logit model to study the heterogeneity of explanatory variables. Extended the existing literature in bikesharing to help in the development of policies to improve the performance of bikesharing systems.