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Article: Synergistic role of audio-visual perceptions in promoting bikeshare for active travel

TitleSynergistic role of audio-visual perceptions in promoting bikeshare for active travel
Authors
KeywordsBikeshare
Nonlinear
Soundscape
Spatial analysis
Streetscape
Urban perception
Issue Date1-Aug-2025
PublisherElsevier
Citation
Transportation Research Part D: Transport and Environment, 2025, v. 145 How to Cite?
Abstract

This study examines factors beyond macroscale built environments (BE) influencing cycling behavior, integrating both microscale visual and auditory perceptions, especially soundscapes, while their impacts on cycling have not been explicitly investigated. Leveraging massive bikeshare trip data in Shenzhen, China, this study employs spatial explainable machine learning to uncover the associations among these three dimensions and cycling behavior using a multi-scale analytical framework. The results show that: (1) Macroscale BE remains dominant, while micro-scale soundscapes outweigh visual perceptions in explaining cycling usage. (2) Both perceived streetscape and soundscape indicators exhibit significant nonlinear effects on cycling behavior. (3) Synergistic interactions between visual streetscape and soundscape are observed, where maintaining audio-visual consistency (e.g., high perceived safety with high natural sounds perception) can positively affect cycling more substantially. Our findings encourage planners to prioritize strategic micro-level modifications targeting perceived street visual and auditory aspects over conventional macroscale BE interventions as cost-effective alternatives.


Persistent Identifierhttp://hdl.handle.net/10722/356536
ISSN
2023 Impact Factor: 7.3
2023 SCImago Journal Rankings: 2.328
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorZhang, Kaihan-
dc.contributor.authorSong, Qiwei-
dc.contributor.authorMa, Haoran-
dc.contributor.authorQiu, Waishan-
dc.contributor.authorLi, Meikang-
dc.contributor.authorKim, Inhi-
dc.date.accessioned2025-06-04T00:40:18Z-
dc.date.available2025-06-04T00:40:18Z-
dc.date.issued2025-08-01-
dc.identifier.citationTransportation Research Part D: Transport and Environment, 2025, v. 145-
dc.identifier.issn1361-9209-
dc.identifier.urihttp://hdl.handle.net/10722/356536-
dc.description.abstract<p>This study examines factors beyond macroscale built environments (BE) influencing cycling behavior, integrating both microscale visual and auditory perceptions, especially soundscapes, while their impacts on cycling have not been explicitly investigated. Leveraging massive bikeshare trip data in Shenzhen, China, this study employs spatial explainable machine learning to uncover the associations among these three dimensions and cycling behavior using a multi-scale analytical framework. The results show that: (1) Macroscale BE remains dominant, while micro-scale soundscapes outweigh visual perceptions in explaining cycling usage. (2) Both perceived streetscape and soundscape indicators exhibit significant nonlinear effects on cycling behavior. (3) Synergistic interactions between visual streetscape and soundscape are observed, where maintaining audio-visual consistency (e.g., high perceived safety with high natural sounds perception) can positively affect cycling more substantially. Our findings encourage planners to prioritize strategic micro-level modifications targeting perceived street visual and auditory aspects over conventional macroscale BE interventions as cost-effective alternatives.</p>-
dc.languageeng-
dc.publisherElsevier-
dc.relation.ispartofTransportation Research Part D: Transport and Environment-
dc.subjectBikeshare-
dc.subjectNonlinear-
dc.subjectSoundscape-
dc.subjectSpatial analysis-
dc.subjectStreetscape-
dc.subjectUrban perception-
dc.titleSynergistic role of audio-visual perceptions in promoting bikeshare for active travel-
dc.typeArticle-
dc.identifier.doi10.1016/j.trd.2025.104806-
dc.identifier.scopuseid_2-s2.0-105005497820-
dc.identifier.volume145-
dc.identifier.eissn1879-2340-
dc.identifier.isiWOS:001498361600002-
dc.identifier.issnl1361-9209-

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