Short- and long-term destination resilience in Wuhan, China under COVID-19: Differences in scenic spot type and origin market structure

Abstract

Analyzing changes in destination resilience can inform critical but under-explored linkages characterizing disaster events and recovery. Based on web search data from 2011 to 2021, this study applied Tourism Background Trend Line (TBTL) modeling to calculate tourism resilience of 41 scenic spots in Wuhan, China under COVID-19. Existing government classifications and market demand data informed scenic spot categorization into three groups based on attraction type (cultural, leisure, natural) or domestic origin market structure (high, moderate and low dependence on the local market). Two-way ANOVAs tested differences in short- and long-term resilience among these different groups. Results indicate that scenic spots with low dependence on the local market were most resilient in the short-term (Jan–April 2020), while scenic spots with high dependence on the local market and natural scenic spots were most resilient in the long-term (May 2020–Dec 2021). Findings highlight heterogeneities in destination resilience at the micro-scale within a single destination, encouraging managers to develop targeted marketing strategies for various scenic spots at different stages of crises like COVID-19. The study's novel framework and implications also inform short-versus long-term resilience theory while accentuating destination recovery strategies in post-pandemic contexts.