Using mobile phone big data to identify inequity of aging groups in transit-oriented development station usage: A case of Tokyo

Zhiheng Chen, Peiran Li, YanXiu Jin, Shreyas Bharule, Ning Jia, Wenjing Li, Xuan Song, Ryosuke Shibasaki and Haoran Zhang

Transport Policy, 2023, vol. 132, issue C, 65-75

Abstract: With the coming of the aging society, the lives and travel of vulnerable groups, especially the elderly, have received unprecedented attention. This paper provides a framework for TOD age inequity research applicable to high-density and public-transport-oriented cities. Our research uses big mobile phone positioning data to extract the age information of TOD (Transit-Oriented Development) station users and uses geographic information and survey data to quantify the TOD service level. Then, we used the Gini coefficient, correlation coefficient analysis, and cluster analysis to explore the differences in TOD resource allocation across age groups on the JR Yamanote Line and part of the JR Chuo line in Tokyo. The results show that inequity exists at the TOD service level regarding user age, and there is a negative correlation between the average age of users and most indicators of TOD. In the clustering results, three unique TOD groups are formed: a) Residence-oriented aging TOD, b) Livable middle-aged TOD, and c) Commuter-oriented young TOD. Based on the research results, we made three suggestions for building an age-friendly TOD: a) More diverse land use, b) Better connectivity between transit nodes and multimodal transportation, and c) Affordable housing cost.

Keywords: TOD; Urban planning; Big data; Mobile phone; Inequity; Aging society (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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DOI: 10.1016/j.tranpol.2022.12.010

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