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

Chen，Zhiheng1; Li，Peiran1; Jin，Yan Xiu1; Bharule，Shreyas2; Jia，Ning4; Li，Wenjing1; Song，Xuan1,3; Shibasaki，Ryosuke1; Zhang，Haoran5

2023-03-01

10.1016/j.tranpol.2022.12.010

Transport Policy   Impact Factor & Quartile

0967-070X

1879-310X

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.

Aging society Big data Inequity Mobile phone TOD Urban planning

SSCI

English

Others

Business & Economics ; Transportation

Economics ; Transportation

WOS:000923190400001

ELSEVIER SCI LTD

2-s2.0-85144753230

Scopus

1.Center for Spatial Information Science,The University of Tokyo,Chiba,5-1-5 Kashiwanoha, Kashiwa-shi,277-8568,Japan
2.LocationMind Inc.,Chiyoda-ku,3-5-2 Iwamotocho, Tokyo,101-0032,Japan
3.SUSTech-UTokyo Joint Research Center on Super Smart City,Department of Computer Science and Engineering,Southern University of Science and Technology(SUSTech),Shenzhen,China
4.College of Management and Economics,Tianjin University,Tianjin,China
5.School of Urban Planning & Design,Peking University,Shenzhen,China

Chen，Zhiheng,Li，Peiran,Jin，Yan Xiu,et al. Using mobile phone big data to identify inequity of aging groups in transit-oriented development station usage: A case of Tokyo[J]. Transport Policy,2023,132:65-75.

Chen，Zhiheng.,Li，Peiran.,Jin，Yan Xiu.,Bharule，Shreyas.,Jia，Ning.,...&Zhang，Haoran.(2023).Using mobile phone big data to identify inequity of aging groups in transit-oriented development station usage: A case of Tokyo.Transport Policy,132,65-75.

Chen，Zhiheng,et al."Using mobile phone big data to identify inequity of aging groups in transit-oriented development station usage: A case of Tokyo".Transport Policy 132(2023):65-75.