Purpose - It is important to figure out the relationship between tourism carbon emissions and tourism economics for a healthy tourism development. Research design, data, and methodology - Data of this study are collected from 27 provinces (cities) of China. Tourist consumption stripping coefficient is used to calculate tourism carbon emissions. SBM-Undesirable model is used to measure the efficiency of tourism economics under the constraint of tourism carbon emissions. Results - The results show that: during the year of 2005-2015, there are obvious differences in totals and intensities of tourism carbon emissions among 27 provinces and cities which can be divided into three areas. There is a high possibility of underestimating the actual efficiency of tourism economics by leaving tourism carbon emissions out of account, and a high inefficiency caused by tourism carbon emissions will lead a low efficiency of tourism economics. Conclusions - The development of tourism should give consideration to both economic and environmental benefits, and reduce the inefficiency caused by tourism carbon emissions to improve efficiency of tourism economics by improving the level of technical efficiency and promoting technological progress.

Purpose - Performance appraisal has a significant influence on the development of low-carbon tourism distribution. Research design, data, and methodology - Data of this study are collected from 27 provinces (cities) of China. SBM-Malmquist model is used to measure the TFP and its dynamic changes of low-carbon tourism distribution; TOBIT model is used to discuss the factors of TFP of low-carbon tourism distribution. Results - The results show that, there are obvious differences among regional TFP of low-carbon tourism distribution, the average change tends to grow positively in general, and the western region grows fastest on average due to the improvement of technical efficiency and technical progress, while there are technical efficiency improvement but technical regresses in eastern and central regions. The economic scale, economic strength, structure of energy consumption, location quotient and government regulation have a significant positive effect on the TFP of low-carbon tourism; energy intensity, industrial structure and opening degree have a negative effect; investments in fixed assets, intensity of R&D fund and urbanization rate have no significant influence on the TFP of low-carbon tourism. Conclusions - Improving the productivity of low-carbon tourism and reducing regional differences are effective ways to develop low-carbon tourism and enhance tourism competitiveness.