Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor | Department of Land Surveying and Geo-Informatics | en_US |
| dc.contributor.advisor | Xu, Yang (LSGI) | en_US |
| dc.contributor.advisor | Wong, Man Sing Charles (LSGI) | en_US |
| dc.creator | Ren, Mengyao | - |
| dc.identifier.uri | https://theses.lib.polyu.edu.hk/handle/200/13851 | - |
| dc.language | English | en_US |
| dc.publisher | Hong Kong Polytechnic University | en_US |
| dc.rights | All rights reserved | en_US |
| dc.title | Utilizing crowdsourced data to characterize pandemic-induced behavior changes and tourist-resident interactions in tourism cities | en_US |
| dcterms.abstract | Pandemics profoundly affect urban economies and daily life, with tourism-dependent cities experiencing heightened economic vulnerability and complex public health challenges. During the global COVID-19 pandemic, strict safety protocols and heightened health concerns led to significant behavioral shifts, including travel disruptions and reduced consumer spending. These changes caused unprecedented disruptions across sectors closely tied to tourism, such as hospitality, restaurants, and air transportation, resulting in declining incomes and rising unemployment in tourism-dependent cities. Moreover, these cities face a higher risk of disease transmission as travelers from diverse regions increase the risks of importing and spreading infectious diseases. Interactions between residents and inbound travelers at activity venues further amplify transmission risks, posing threats to both groups. Balancing disease control with economic stability presents a critical challenge for tourism-dependent cities. Minimizing travel restrictions to mitigate economic losses while effectively managing disease spread risks requires a nuanced approach. It is essential to understand how pandemics and policy responses influence the travel and spending behavior of the two stakeholders in tourism cities, i.e., tourists and residents, as well as their potential interactions in urban areas. These insights are crucial for designing resilient crisis response measures and long-term strategies for sustainable development. | en_US |
| dcterms.abstract | This thesis comprehensively investigates pandemic-induced behavior changes and tourist-resident interactions in a tourism city, aiming to achieve the following objectives: (1) to assess the extent to which human behavior in tourism cities varies in response to the severity of the pandemic, both locally and remotely; (2) to assess the effects of policy responses, including social distancing and stimulus payments, on human behavior in tourism cities; (3) to assess the heterogeneous impacts of the pandemic and policy responses across various economic sectors; (4) to assess the extent to which the impacts of the pandemic and policy responses differ between residents and tourists; (5) to characterize the diverse interaction modes between tourists and residents across space, time, and activity venues, as well as variations in direct contact potential across different modes; (6) to construct indices to measure the potential for interactions between tourists and residents across various modes. | en_US |
| dcterms.abstract | This thesis addresses six research objectives through three data-driven case studies conducted in a tourism city. The first study utilizes car navigation data to model the dynamic effects of local and national COVID-19 conditions on the travel behavior of domestic inbound travelers in Jeju, Korea. The second study leverages a large-scale dataset of credit and debit card transactions to estimate the heterogeneous impacts of COVID-19 and policy responses on spending behavior of residents and domestic inbound travelers in Jeju. The third study presents an innovative analytical framework to uncover potential interactions between tourists and residents within a time-geographic lens. An empirical application of this framework in Jeju displays its effectiveness in revealing the complexity and dynamics of intergroup interactions across space, time, and activity venues. | en_US |
| dcterms.abstract | This thesis provides essential empirical evidence, offering alternative viewpoints on the dynamics and complexity of risk perception and behavioral responses. It enriches the field of time geography by deepening the understanding of space-time path relationships among individuals and introducing a robust tool for analyzing intergroup interactions. Through multiple data-driven case studies, the research underscores the value of spatiotemporal big data in policy evaluation, crisis management, and other practical applications. The findings make significant contributions to the fields of crisis management, tourism geography, and urban studies, delivering valuable insights and addressing fundamental issues within these domains. | en_US |
| dcterms.extent | xii, 130 pages : color illustrations | en_US |
| dcterms.isPartOf | PolyU Electronic Theses | en_US |
| dcterms.issued | 2025 | en_US |
| dcterms.educationalLevel | Ph.D. | en_US |
| dcterms.educationalLevel | All Doctorate | en_US |
| dcterms.accessRights | open access | en_US |
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