Estimation of the aggregation degree of public transport use among elderly people based on urban built environment

Xianchen Dou, Meiying Jian, Chen Guo and JinXin Cao

Journal of Transport Geography, 2023, vol. 112, issue C

Abstract: With the accelerated aging process, the increased willingness of elderly people to travel, and the concessionary bus travel policy implementation, public transport, especially buses, has become one of the important ways for China's elderly people to participate in social activities. Meanwhile, the increased use of public transport by elderly people results in serious conflicts with commuters. In order to understand details about when, where and why public transport trips of the elderly become large, this study investigates the aggregation degree of public transport use among the elderly as well as its determinants mainly from the viewpoint of spatial characteristics. Based on Smart card data and Baidu Map API, the aggregation degree of public transport use in elderly people is rated on a scale of 1 to 5. And then its correlation to the microscopic built environment is analyzed by using negative binomial regression. The results indicate that public transport use by elderly people is highly aggregative in both spatial and temporal dimensions. It is also found that the urban built environment has a significant effect on the aggregation degree of public transport use in the elderly and significant variables for four time periods on both weekdays and weekends are quite different. The proximity of housing estates, elderly activity centers, universities for the elderly, and medical and shopping facilities near bus stations increases the aggregation degree of public transport use by elderly people. This study will provide a reference basis for optimizing the public transport system in the aging society.

Keywords: Public transport use; Built environment; Elderly people; Smart card data; Negative binomial regression (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:eee:jotrge:v:112:y:2023:i:c:s0966692323001795

DOI: 10.1016/j.jtrangeo.2023.103707

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