Analysis of spatial patterns and driving factors of provincial tourism demand in China

Modeling and forecasting tourism demand across destinations has become a priority in tourism research. Most tourism demand studies rely on annual statistics with small sample sizes and lack research on spatial heterogeneity and drivers of tourism demand. This study proposes a new framework for measuring inter-provincial tourism demand's spatiotemporal distribution using search engine indices based on a geographic perspective. A combination of spatial autocorrelation and Geodetector is utilized to recognize the spatiotemporal distribution patterns of tourism demand in 2011 and 2018 in 31 provinces of mainland China and detect its driving mechanisms. The results reveal that the spatial distribution of tourism demand manifests a vital stratification phenomenon with significant spatial aggregation in the southwest and northeast of China. Traffic conditions, social-economic development level, and physical conditions compose a constant and robust interaction network, which dominates the spatial distribution of tourism demand in different development stages through different interactions.

Automated summary

Modeling and forecasting tourism demand is crucial in tourism research. This study proposes a new framework to measure the spatiotemporal distribution of inter-provincial tourism demand in mainland China, using search engine indices. The results reveal a stratification phenomenon in the spatial distribution of tourism demand, with significant clusters in southwestern and northeastern China. Factors such as traffic conditions, socio-economic development, and physical conditions play a crucial role in shaping the spatial distribution of tourism demand.