Spatial network analysis of tourism carbon efficiency: A study in Chinese prefecture-level cities

Reducing carbon emissions and improving carbon efficiency are crucial for sustainable tourism development. Effective measurement of tourism carbon efficiency and the accuracy of its spatial relationship can considerably pursue this target. Therefore, this study focuses on 271 prefecture-level cities in China and utilizes super-efficiency SBM-DEA to measure their tourism carbon efficiency. Furthermore, exploring the spatial association networks of these cities by using an improved gravity model and social network analysis. Finally, the QAP model was used to investigate network drivers. The results reveal that: (1) China's tourism carbon efficiency shows an upward trend. However, considerable spatial heterogeneity exists, higher in eastern cities, lower in central and western cities. (2) The spatial association network of tourism carbon efficiency(SANTCE) has a strong overall correlation, the network structure is relatively stable and insignificant hierarchical structure. (3) SANTCE is characterized by a “core–edge” feature, the cities in the developed eastern regions occupy a dominant position and play an important role as controllers and bridges, whereas the central and western cities are the peripheral regions. (4) Different blocks in SANTCE show evident spatial polarization and diffusion effects. As the net inflow block, the Yangtze River Delta, Pearl River Delta, and Beijing can effectively attract and integrate the relevant factors and resources in net spillover blocks. They can also generate spillover effects to drive overall efficiency improvement. (5) Differences in industry structure, economic development, education level, and tourism market size have a positive effect on the formation of TCEAN, whereas differences in government intervention have a reverse effect.