Evaluation and influencing factors of the tourism industry efficiency under carbon emission constraints in China.

Abstract

A significant industrial transformation in China's tourism sector is currently taking place in response to carbon peak and carbon neutrality targets. This paper applies the data envelopment analysis (DEA) model to calculate the efficiency of the tourism industry under carbon emission constraints and further investigates its influencing factors through the Tobit regression. The results are as follows: (1) The tourism efficiency under carbon emission constraints of China from 2000 to 2019 showed a trend of first rising and then declining, and there were obvious regional differences; (2) from 2000 to 2019, the total factor productivity of tourism in China increased significantly, while the contributions of technical progress, pure technical efficiency, and scale efficiency decreased sequentially; (3) the factors of industrial structure, transportation convenience, economic development level, degree of opening to the outside world, and the level of scientific and technological development have varying degrees of influence on tourism efficiency. Based on the analysis results, this paper puts forward several policy suggestions on tourism efficiency and low-carbon development. The findings of this paper have some bearing on developing nations' efforts to boost tourism efficiency and realize high-quality industry growth within the framework of sustainable development.