Tourism plays a crucial role in alleviating poverty deprivations and achieving sustainable development. Nevertheless, there is a lack of literature regarding evaluating poor residents’ perceptions of the impacts of tourism on poverty alleviation from the perspective of multidimensional poverty. Taking Fenghuang County, China, as the study area, this study established an evaluation framework by using the Delphi method based on multidimensional poverty theory. Moreover, analytic hierarchy process (AHP) was employed to identify the weight of each indicator and assess poor residents’ perceptions of the impacts of tourism on poverty alleviation. The results indicate that tourism economic development has been a momentous contributor to alleviating multidimensional poverty in study locations to a certain extent (3.180). However, there is still room for improvement and promotion. With respect to various dimensions, the mean of economic level is the highest (1.125), whilst the means of education training (0.420) and health care (0.819) are relatively lower than the other dimensions.

The social network analysis has been actively applied in various tourist destinations, with a few studies on the tourism economic network structure of national parks. Taking the national parks in the Central Region of China as research objects, this study applies the modified gravity model to measure the strength of tourism economic connection. The social network analysis method (SNA) is used to analyze the network structure of tourism economic connection among national parks from the perspectives of overall network density, network centrality, and cohesive subgroups. The results show that the intensity of the tourism relationships among national parks in Central China is unbalanced in spatial distribution. The structure of tourism economic network presents a multi-core model. Lushan Mountain, Shaoshan, Wudang Mountain, and other national parks play a necessary role in the transmission of regional tourism economic elements. There are cohesive subgroups of connections among national parks, which are closely related to administrative divisions and regional cultural background. The subgroups of interior scenes in the same province are more closely related, and the degree of tourism integration still needs to be improved. The study advances the understanding of tourism economic network relationships among tourist attractions in a destination.

A low-carbon behaviour performance evaluation index system is designed by using a Delphi method in this study. The analytic hierarchy process (AHP) is applied to systematically measure the low-carbon behaviour performance of 32 scenic spots in Zhangjiajie, a world heritage site. The key driving factors that can significantly influence the low-carbon behaviour performance of the scenic spot are extracted by combining redundancy analysis (RDA). The results show that the scenic spots of Zhangjiajie performance well regarding low-carbon behaviour, however, there are still a great deal of room for improvement and promotion. Pressure from investors, the administration committees, tourists and local governments is the main driving factor for the low-carbon behaviour of scenic spot.