Bo Wang , Yuanyuan Guo , Fang Chen , Fengliang Tang
{"title":"The impact of the social-built environment on the inequity of bike-sharing use: A case study of Divvy system in Chicago","authors":"Bo Wang , Yuanyuan Guo , Fang Chen , Fengliang Tang","doi":"10.1016/j.tbs.2024.100873","DOIUrl":null,"url":null,"abstract":"<div><p>Bikeshare is increasingly recognized as a healthy travel behaviour worldwide. However, issues of inequity in bike-sharing usage exist and hinder the social benefits of bike-sharing system. This paper aims to unveil the spatiotemporal evolution of inequalities in bike-sharing usage and their social-built environment correlates, using Chicago’s Divvy system as a case study. Specifically, Gini coefficients and panel data regression models are applied to analyse equity concerns in bike-sharing uses and its social-built environmental factors. Thirty-two disadvantaged communities and forty-five non-disadvantaged communities are identified based on ethnicity, income, and education levels. The Gini index indicates a greater level of inequity and inconsistency in bike-sharing usage within disadvantaged communities compared to non-disadvantaged communities over time. Model results further reveal that built environment factors such as park space positively impact equitable bike-sharing uses in disadvantaged communities. In contrast, the social factor of educational levels in non-disadvantaged communities shows a negative relationship. These findings aim to promote essential, efficient, and equitable bike-sharing usage for Chicago, stakeholders and users.</p></div>","PeriodicalId":51534,"journal":{"name":"Travel Behaviour and Society","volume":"37 ","pages":"Article 100873"},"PeriodicalIF":5.1000,"publicationDate":"2024-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Travel Behaviour and Society","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2214367X24001364","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"TRANSPORTATION","Score":null,"Total":0}
引用次数: 0
Abstract
Bikeshare is increasingly recognized as a healthy travel behaviour worldwide. However, issues of inequity in bike-sharing usage exist and hinder the social benefits of bike-sharing system. This paper aims to unveil the spatiotemporal evolution of inequalities in bike-sharing usage and their social-built environment correlates, using Chicago’s Divvy system as a case study. Specifically, Gini coefficients and panel data regression models are applied to analyse equity concerns in bike-sharing uses and its social-built environmental factors. Thirty-two disadvantaged communities and forty-five non-disadvantaged communities are identified based on ethnicity, income, and education levels. The Gini index indicates a greater level of inequity and inconsistency in bike-sharing usage within disadvantaged communities compared to non-disadvantaged communities over time. Model results further reveal that built environment factors such as park space positively impact equitable bike-sharing uses in disadvantaged communities. In contrast, the social factor of educational levels in non-disadvantaged communities shows a negative relationship. These findings aim to promote essential, efficient, and equitable bike-sharing usage for Chicago, stakeholders and users.
期刊介绍:
Travel Behaviour and Society is an interdisciplinary journal publishing high-quality original papers which report leading edge research in theories, methodologies and applications concerning transportation issues and challenges which involve the social and spatial dimensions. In particular, it provides a discussion forum for major research in travel behaviour, transportation infrastructure, transportation and environmental issues, mobility and social sustainability, transportation geographic information systems (TGIS), transportation and quality of life, transportation data collection and analysis, etc.