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Resilience of ride-hailing services in response to air pollution and its association with built-environment and socioeconomic characteristics

Datos Bibliográficos

ID12295100
AutoresYisheng Peng (0000-0003-2994-1448, Southwest Jiaotong University), Jiahui Liu (0009-0001-8829-4490, University of Hong Kong), F Li (0000-0001-9835-375X, Chengdu University of Technology), Jianqiang Cui (Griffith University), Yi Lü (0000-0001-7614-6661, City University of Hong Kong), Linchuan Yang (0000-0001-6070-9044, Southwest Jiaotong University, autor de correspondencia)
Año2024
Volumen120
Páginas103971-103971
Fecha de publicación2024-08-20
Peer ReviewedSí
Open AccessSí
TipoARTICLE
RevistaJournal of Transport Geography (JOURNAL)
Identificadores de la revistaISSN: 0966-6923 • E-ISSN: 1873-1236
EditorialElsevier BV (PUBLISHER)
DOI10.1016/j.jtrangeo.2024.103971
OpenAlexW4402162541
IdiomaEN
Citas recibidas8
Referencias citadas59

Air pollution, an unexpected event, poses a significant threat to public health and affects human mobility. Ride-hailing provides an effective way to understand how human mobility adapts to air pollution. This study examines a week-long ride-hailing demand dataset from Chengdu, China, to evaluate the resilience of ride-hailing services (or ride-hailing resilience) in the face of poor air quality. A gradient boosting decision tree model is developed to explore the non-linear and interaction effects of air pollution, the built environment, and socioeconomic characteristics on ride-hailing demand and resilience. The results show that the relative importance and impact of independent factors on ride-hailing demand and resilience vary. Specifically, the density of residence facilities and air pollution are the most important predictors of ride-hailing demand and resilience, respectively. The non-linear and interaction effects of air pollution and selected built-environment and socioeconomic characteristics on ride-hailing resilience are presented. We recommend that urban planners and policymakers address the vulnerability of regions to air pollution, optimize the allocation of ride-hailing resources, and develop strategies to improve regional resilience

Air pollution · Association (psychology · Built environment · Business · Civil engineering · Environmental health · Environmental planning · Geography · Poison control · Psychological resilience · Resilience (materials science · Socioeconomic status · Engineering · Medicine · Psychology · Social Psychology · Traffic and Road Safety · Transportation Planning and Optimization · Urban Transport and Accessibility · Ecology

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Obras citantes distintas8
Citas por año8
Intervalo de citas2025 - 2026 (2)
Velocidad de citacióncurrent
Altamente citadoNo
Tipos de citaNeutras: 8
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