Analysing the differential impact of the COVID-19 pandemic on the resilience of the tourism economy: A case study of the ChengduChongqing urban agglomeration in China

Abstract

The outbreak of the COVID-19 pandemic in 2019 had a profound impact on the tourism economy, underscoring the critical importance of assessing and analyzing tourism economic resilience. Traditionally, prior research predominantly focused on constructing evaluation systems based on three dimensions: Risk preparedness capability, Restoration capability, and Reorganization and modernization capacity. In this study, we take an innovative approach by incorporating urban network thinking and establishing a tourism economic network, while introducing the dimension of “The rationality of network structure.” To comprehensively understand the dynamics of tourism economic resilience, we divided the period from 2018 to 2021 into three distinct phases: Stable period, Pre-shock period, and Shock period. This division allowed us to conduct comparative research that highlights the variations in tourism economic resilience across these different time frames. Additionally, we employed advanced methods, such as kernel density estimation and the GTWR model, for empirical analysis of tourism economic resilience within the Chengdu-Chongqing city cluster. The results of our research unveiled that Chengdu and Chongqing both demonstrate a remarkable level of resilience within their tourism economies. However, given their status as the “dual core” of the Chengdu-Chongqing city agglomeration, they are inherently more susceptible to significant fluctuations when confronted with shocks. The spatial pattern of tourism economic resilience is characterized by prominent wings on both sides, a North-South balance, and a central region with vulnerabilities. The predominant evolutionary patterns are marked by multi-level stabilization, moderate growth, and moderate decline. Ziyang is an exceptional region within the broader growth zone, and its reduced risk preparedness capability has led to an overall decline in tourism economic resilience. Furthermore, key influencing factors, including the economy, infrastructure, and ecological environment, exhibit significant spatial heterogeneity. In conclusion, our study offers valuable insights into researching tourism economic resilience under external shocks, such as the COVID-19 pandemic. These findings can be instrumental in guiding policymakers as they develop effective strategies to bolster tourism economic resilience.