A Study on Static and Dynamic Provincial-level Measurements of Tourism Industry Efficiency in China -Based on Malmquist-Luenberger Index and SBM-DEA models

Abstract

While existing studies have considered economic inputs and outputs into the industrial efficiency measurement models for eco-tourism industries in China, few of them have put environment inputs such as natural resources and outputs such as carbon emission into account. This study applies the tourism stripping factor method to measure provincial tourism carbon emissions and innovatively employs the Malmquist-Luenberger and SBM-DEA models with unfavorable outputs to evaluate the eco-efficiency of China's provincial tourism industry by adding input and output variables reflecting environmental factors. The study found that, unlike the results from traditional models without unfavorable outputs, which showed a slight downward trend in pure economic efficiency, the industrial efficiency including the environmental factors of 31 Chinese provinces showed an upward trend through the static analysis, representing an increase in the eco-efficiency of the tourism industry. The tourism industrial efficiency values in each region evaluated dynamically are less volatile than the results from traditional models, which may support the moderating effect of the technological upgrading of China's green industry on the efficiency of the tourism industry. Theoretical and empirical findings of this research are also illustrated.