Evaluating the tourism green productivity and its driving factors in the context of climate change

Abstract

In the context of global climate changes, the green transformation of tourism industry has become a general trend. This study constructed a comprehensive evaluation model (Super SBM-GML) to measure the tourism green productivity (TGP) and used methods including kernel density estimation, spatiotemporal transition, and quantile regression to analyze the evolutionary characteristics and driving factors of province-level TGP in China between 2009 and 2019. The results showed the following: (1) China’s TGP exhibited a two-stage growth trend, maintaining steady growth before 2014 and accelerating thereafter. (2) Regarding the dynamic evolutionary characteristics, the local spatial structure of provincial TGP remains unstable, and the provinces themselves can change their relative positions relatively easily, showing certain characteristics of spatial agglomeration and dynamic interaction. (3) The spatiotemporal network pattern of provincial tourism green productivity was dominated by positive correlations, indicating that the overall collaborative dynamics between provinces were stronger than the competition. However, a certain degree of spatiotemporal competition could be found between some neighboring provinces. (4) The TGP is affected by various driving factors such as tourism economic scale, industrial structure, scientific and technological innovation and environmental regulations, but the driving intensity and direction of each factor differ significantly across the TGP developmental stages.