Towards a multidimensional big data index for urban tourism resilience

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.