Understanding spatial tourism destination recovery in Iran based on a destination attribute recovery index for COVID‐19

Abstract

Throughout history, the tourism industry has encountered diverse crises, each with its distinct characteristics. While the nature of these crises may evolve, the inevitability of their occurrence persists. Given the unpredictability of such events, understanding recovery factors for tourism destinations becomes crucial for swift recuperation. This study employed a destination recovery measurement model, visualised through Geographic Information System and GeoDA, focusing on Iran's 31 provinces. Indicators including tourism density, capacity, investment, accommodation, employment rate and destination type, in conjunction with COVID‐19 cases, were utilised to gauge recovery status. The spatial distribution of the destination recovery index was analysed, revealing nonrandom cluster patterns, affirming that recovery is influenced by specific factors rather than occurring haphazardly. Provinces equipped with higher‐factor concentrations demonstrated swifter recovery, while others exhibited less tourism‐related prominence. These findings hold significance for stakeholders encompassing tourism managers, policymakers and governments vested in the sustainability of future tourism destinations.