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- Publisher Website: 10.1016/j.apgeog.2021.102504
- Scopus: eid_2-s2.0-85109774013
- WOS: WOS:000686900300006
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Article: Abrupt changes, institutional reactions, and adaptive behaviors: An exploratory study of COVID-19 and related events' impacts on Hong Kong's metro riders
Title | Abrupt changes, institutional reactions, and adaptive behaviors: An exploratory study of COVID-19 and related events' impacts on Hong Kong's metro riders |
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Authors | |
Keywords | COVID-19 Adaptive travel behaviors Measurement Geovisualization Predictor |
Issue Date | 2021 |
Publisher | Pergamon. The Journal's web site is located at http://www.elsevier.com/locate/apgeog |
Citation | Applied Geography, 2021, v. 134, article no. 102504 How to Cite? |
Abstract | Abrupt socioeconomic changes have become increasingly commonplace. In face of these, both institutions and individuals must adapt. Against the backdrop of the COVID-19 pandemic, suddenness, scale, and impacts of which are unprecedented as compared to its counterparts in history, we first propose transferable measures and methods that can be used to quantify and geovisualize COVID-19 and subsequent events' impacts on metro riders' travel behaviors. Then we operationalize and implement those measures and methods with empirical data from Hong Kong, a metropolis heavily reliant on transit/metro services. We map out where those impacts were the largest and explores its correlates. We exploit the best publicly available data to assemble probable explanatory variables and to examine quantitatively whether those variables are correlated to the impacts and if so, to what degree. We find that both macro- and meso-level external/internal events following the COVID-19 outbreak significantly influenced of metro riders' behaviors. The numbers of public rental housing residents, public and medical facilities, students' school locations, residents’ occupation, and household income significantly predict the impacts. Also, the impacts differ across social groups and locales with different built-environment attributes. This means that to effectively manage those impacts, locale- and group-sensitive interventions are warranted. |
Persistent Identifier | http://hdl.handle.net/10722/304847 |
ISSN | 2023 Impact Factor: 4.0 2023 SCImago Journal Rankings: 1.204 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Zhou, J | - |
dc.contributor.author | Wu, J | - |
dc.contributor.author | Ma, H | - |
dc.date.accessioned | 2021-10-05T02:36:03Z | - |
dc.date.available | 2021-10-05T02:36:03Z | - |
dc.date.issued | 2021 | - |
dc.identifier.citation | Applied Geography, 2021, v. 134, article no. 102504 | - |
dc.identifier.issn | 0143-6228 | - |
dc.identifier.uri | http://hdl.handle.net/10722/304847 | - |
dc.description.abstract | Abrupt socioeconomic changes have become increasingly commonplace. In face of these, both institutions and individuals must adapt. Against the backdrop of the COVID-19 pandemic, suddenness, scale, and impacts of which are unprecedented as compared to its counterparts in history, we first propose transferable measures and methods that can be used to quantify and geovisualize COVID-19 and subsequent events' impacts on metro riders' travel behaviors. Then we operationalize and implement those measures and methods with empirical data from Hong Kong, a metropolis heavily reliant on transit/metro services. We map out where those impacts were the largest and explores its correlates. We exploit the best publicly available data to assemble probable explanatory variables and to examine quantitatively whether those variables are correlated to the impacts and if so, to what degree. We find that both macro- and meso-level external/internal events following the COVID-19 outbreak significantly influenced of metro riders' behaviors. The numbers of public rental housing residents, public and medical facilities, students' school locations, residents’ occupation, and household income significantly predict the impacts. Also, the impacts differ across social groups and locales with different built-environment attributes. This means that to effectively manage those impacts, locale- and group-sensitive interventions are warranted. | - |
dc.language | eng | - |
dc.publisher | Pergamon. The Journal's web site is located at http://www.elsevier.com/locate/apgeog | - |
dc.relation.ispartof | Applied Geography | - |
dc.subject | COVID-19 | - |
dc.subject | Adaptive travel behaviors | - |
dc.subject | Measurement | - |
dc.subject | Geovisualization | - |
dc.subject | Predictor | - |
dc.title | Abrupt changes, institutional reactions, and adaptive behaviors: An exploratory study of COVID-19 and related events' impacts on Hong Kong's metro riders | - |
dc.type | Article | - |
dc.identifier.email | Zhou, J: zhoujp@hku.hk | - |
dc.identifier.email | Wu, J: jiangyue@connect.hku.hk | - |
dc.identifier.email | Ma, H: mhx18@connect.hku.hk | - |
dc.identifier.authority | Zhou, J=rp02236 | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1016/j.apgeog.2021.102504 | - |
dc.identifier.scopus | eid_2-s2.0-85109774013 | - |
dc.identifier.hkuros | 326036 | - |
dc.identifier.volume | 134 | - |
dc.identifier.spage | article no. 102504 | - |
dc.identifier.epage | article no. 102504 | - |
dc.identifier.isi | WOS:000686900300006 | - |
dc.publisher.place | United Kingdom | - |