Promoting tourism in China using sustainable practices has become a very important issue. In order to analyze temporal characteristics and spatial regularities of green total factor productivity (GTFP), carbon emissions and the consumption of energy related to tourism in China were estimated using a "bottom-up" method. The construction of a measurement framework (including carbon emissions and energy consumption) of GTFP for the tourism industry was also undertaken. The data envelopment analysis (DEA) model and the Malmquist–Luenberger (ML) index were used to measure and calculate tourism GTFP in China between 2007 and 2018, as well as analyze spatio-temporal differences. Results indicate that: (1) carbon emissions and the consumption of energy are increasing, and they have not yet peaked, with traffic associated with tourism accounting for the largest proportion among tourism sectors; the spatial distribution of carbon emissions and the consumption of energy is not balanced; (2) green development of tourism in China has achieved a good level of performance during the study period, driven by technical efficiency. Since 2014, pure technical efficiency (PE) has been >1, indicating that the tourism industry in China has entered a stage of change and promotion; (3) significant spatial differences exist in tourism GTFP in China. For example, the overall pattern of being strongest in the east and weakest in the west has not changed. Currently, eastern, central, and western regions in China rely on different dynamic mechanisms to promote tourism green development. In addition, some provinces have become the core or secondary growth poles of tourism green development in China.

This paper introduces energy consumption and carbon emission into the analysis framework of the green productivity of tourism. By comparing and analyzing the two main methods used to evaluate the energy consumption and carbon emission estimations of tourism, namely, the “top-down” and “bottom-up” method, and considering the availability of data, the “bottom-up” method was adopted to evaluate the energy consumption and carbon emissions of tourism in the Yangtze River Economic Zone (YREZ). Then, using the Malmquist-Luenberger (ML) index in the super-efficiency data envelopment analysis (DEA) model, the green productivity of the tourism in 11 provinces and cities in the YREZ from 2006 to 2015 was measured. The empirical results show that: (1) The energy consumption and carbon emissions of tourism in the YREZ have increased steadily over the past 10 years, which has caused a certain degree of pollution to the environment, indicating that tourism is no longer a “smoke-free industry”; (2) there are significant provincial differences between the energy consumption and carbon emissions of tourism in the YREZ, with Shanghai always ranking first, while Guizhou and Yunnan ranks last, which represents that the tourism economic development level is positively correlated with the tourism energy consumption and carbon emissions; (3) the green productivity of tourism in the YREZ shows a fluctuating increasing trend in the past 10 years, and technological progress has become the main reason for its growth in green productivity; and (4) the green productivity of tourism in 11 provinces and cities in the YREZ can be divided into three types: Progressive type of tourism green development, stagnant type of tourism green development, and declining type of tourism green development. Consequently, different types of provinces should explore effective dependency paths based on their own conditions.

The sharing economy has become an important business model for China to promote energy conservation and emission reduction, improve the utilization efficiency of social resources, promote green and sustainable development, and achieve high-quality economic development. How to improve the willingness of individuals to share underutilized resources with others is becoming an urgent problem for enterprises and academia. Although current research on the sharing economy provides insights into users’ perspectives, little attention has been given to the comprehensive investigation of the sharing intention of individual service providers. Based on the motivation—opportunity—abilities (MOA) theory, we analyze the influencing factors and boundary conditions of individual resource sharing intention by taking new consumer groups as research samples. The results reveal that the sharing intention of individual service providers depends on their customized service capability, economic motivation, and perceived ease of use. Furthermore, the burden of ownership and fashion consciousness will further influence the sharing intention of individual service providers. This discovery provides theoretical basis for the development of an enterprise sharing economy and government guidance, and enriches the theoretical research on the sharing economy.