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Towards a multidimensional big data index for urban tourism resilience

Towards a multidimensional big data index for urban tourism resilience

Zhong, Lina, Dong, Yingchao, Qi, Xiangchi, Li, Meiling, Wang, Yaojun and Coca-Stefaniak, J. Andres ORCID logoORCID: https://orcid.org/0000-0001-5711-519X (2025) Towards a multidimensional big data index for urban tourism resilience. International Journal of Tourism Cities. ISSN 2056-5607 (doi:10.1080/20565607.2025.2566410/)

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51074 COCA-STEFANIAK_Towards_A_Multidimensional_Big_Data_Index_For_Urban_Tourism_Resilience_(OA)_2025.pdf - Published Version
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Abstract

This study posits an index system based on multidimensional urban big data indicators to accurately portray city tourism development before, during and after a global public health crisis. As part of this process, index scores were calculated for cities and provinces in China using standard deviation ellipse, kernel density, and regression analyses to explore the impact of the COVID-19 pandemic on urban tourism and the resilience of tourism cities. The results show that regions with better tourism infrastructure and resources displayed higher levels of resilience. Similarly, post-pandemic recovery varied widely from one region to another. After the pandemic, the dissemination of tourism images shows a more balanced trend. Although the tourism sector was affected, niche urban destinations experienced growth. The focus of tourism resources changed towards the southwest of China. Overall, most tourism cities in the country’s eastern coastal regions displayed low levels of resilience, while other cities located in emerging tourism markets showed high levels of resilience. Cities in different quadrants exhibited very different resistance and recovery capabilities.

Item Type: Article
Uncontrolled Keywords: resilience, urban tourism, GIS, big data, indicator system
Subjects: G Geography. Anthropology. Recreation > GV Recreation Leisure
H Social Sciences > H Social Sciences (General)
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Faculty / School / Research Centre / Research Group: Greenwich Business School
Greenwich Business School > Networks and Urban Systems Centre (NUSC)
Greenwich Business School > School of Business, Operations and Strategy
Related URLs:
Last Modified: 03 Oct 2025 16:12
URI: https://gala.gre.ac.uk/id/eprint/51074

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