Tourism Eco-Efficiency Measurement, Characteristics, and Its Influence Factors in China

• Main Authors: Xiaoping Qiu, Yiping Fang, Xueting Yang, Fubiao Zhu
• Format: Article
• Language: English
• Published: MDPI AG 2017-09-01
• Series: Sustainability
• Subjects: tourism eco-efficiency; measurement; characteristics; influence factors; China
• Online Access: https://www.mdpi.com/2071-1050/9/9/1634

As an emerging field of eco-efficiency, tourism eco-efficiency is becoming an important way to measure the sustainable development of tourism. This study calculated and decomposed tourism CO2 emissions in China, explored its evolution and distribution characteristics by using the ratio method of tourism eco-efficiency, and analyzed the influencing factors by adopting a regression model. The results indicate that: (1) tourism CO2 emissions in China have increased significantly, their largest source is transportation. Its characteristics can be divided into carbon emission intensity factor, income structure factor, consumption level factor, and tourist scale factor through utilizing the Logarithmic Mean Divisia Index (LMDI) method, which also shows that the decisive factor of increased of tourism CO2 emissions has been the tourist scale factor. (2) Tourism eco-efficiency is marked by spectacular but unstable growth, which can be divided into three stages: inefficient stagnation stage, fluctuating growth stage, and efficient development stage. (3) Tourism eco-efficiency in China has shown that the remarkable high–high cluster and low–low cluster, and the 31 provinces, can be divided into four groups, namely: a high-efficiency high-growth group, a high-efficiency low-growth group, a low-efficiency high-growth group, and a low-efficiency low-growth group. (4) The main influencing factors of tourism eco-efficiency are the scale effect, the structural effect, the technical effect, and the environmental regulation. Since these four factors have different impacts on the tourism eco-efficiency of different groups according to panel data regression, more effective policies should be adopted for the improvement of tourism eco-efficiency in China. Finally, the significances and deficiencies of this study are discussed.