How to Decouple Tourism Growth from Carbon Emissions? A Spatial Correlation Network Analysis in China

Zhaoming Deng, Meijing Zhou () and Qiong Xu ()
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Zhaoming Deng: Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
Meijing Zhou: Beijing Institute of Petrochemical Technology, Beijing 102617, China
Qiong Xu: Business School, Central South University, Changsha 410083, China

Sustainability, 2022, vol. 14, issue 19, 1-14

Abstract: This research aims to analyze the spatial correlation network of the decoupling between tourism growth and carbon emissions in China’s 31 provinces to promote the overall decoupling through regional cooperation. This study scientifically measures the decoupling index from 2009 to 2019 based on a “bottom-up” method and the Tapio decoupling model. It analyzes the spatial correlation network of the decoupling and its driving factors by using social network analysis. The conclusions show that the decoupling between China’s tourism economic growth and carbon emissions was dominated by an expansive connection, which indicates a nonideal decoupling state. Among the regions, decoupling was stronger in the eastern provinces and weaker in the middle and western districts. The spatial correlation outside the plates was more significant, while the internal correlation was weaker. Beijing and Shanghai were in the center of the network, and the eastern developed provinces were in the subcentral place, both of which had more muscular control over the network. In contrast, the middle and western regions were on edge positions, playing passive roles in the network. In addition, the economic development level was the most vital driving force behind the spatial correlation, followed by spatial adjacency and government policy. In contrast, the industrial structure and technological level were negative influencing factors. These research findings indicate potential interprovincial cooperation in terms of tourism decarbonization, which provide a profound reference for the whole sustainable development of China’s tourism industry.

Keywords: tourism economic growth; carbon emission; decoupling theory; spatial correlation network; influencing factor; social network analysis (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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