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Spatial-Temporal Variation and Influencing Factors of Regional Tourism Carbon Emission Efficiency in China Based on Calculating Tourism Value Added

Author

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  • Jun Liu

    (School of Tourism, Hubei University, Wuhan 430062, China
    Tourism Development and Management Research Center, Hubei Key Research Base of Humanities and Social Sciences, Wuhan 430062, China)

  • Fanfan Deng

    (School of Tourism, Hubei University, Wuhan 430062, China
    Tourism Development and Management Research Center, Hubei Key Research Base of Humanities and Social Sciences, Wuhan 430062, China)

  • Ding Wen

    (South China Institute of Environmental Sciences, Ministry of Ecology and Environment, Guangzhou 510530, China)

  • Qian Zhang

    (School of Tourism, Hubei University, Wuhan 430062, China)

  • Ye Lin

    (School of Business, Hubei University, Wuhan 430062, China)

Abstract

Tourism-related carbon emission efficiency is an important indicator that reflects the sustainable development of tourism and can better balance the relationship between negative environmental impact and economic value. According to panel data of 30 provincial regions, “the tourism value added coefficient” (not including the Tibet Autonomous Region) in mainland China from 2000 to 2019, we estimate the tourism of each provincial administrative unit carbon emissions, measure the tourism carbon efficiency value, and analyze the measurement results of the change trend, spatial differentiation characteristics, and influencing factors. The results show that (1) the carbon emission efficiency of regional tourism in China increased significantly from 2000 to 2019, but there was a significant difference in the carbon emission efficiency of tourism among regions, and the sustainable development level of regional tourism was still unbalanced. (2) The spatial pattern of provincial administrative units in China has the adjacent characteristics of High-High agglomeration and Low-Low agglomeration, the difference in the tourism eco-efficiency development level among regions gradually decreases with time, and there is a dynamic convergence characteristic. (3) The q value represents the intensity of the impact factor on tourism carbon emission efficiency. According to the q value, the factors affecting tourism carbon emission efficiency were divided into dominant factors (0.5 ≤ q ≤ 1), inducing factors (0.2 ≤ q < 0.5) and driving factors (0 ≤ q < 0.2), among which the level of technological development was the dominant factor. The level of opening-up to the outside world is the inducing factor; environmental regulation intensity, urbanization level, regional economic development level, tourism industry environment, and tourism infrastructure are the driving factors. (4) The influence degree of influencing factors on the spatial differentiation of tourism carbon emission efficiency is significantly different in different periods. The degree of influence of the urbanization level and tourism industry environment shows an upward trend over time, and the influence degree of other factors shows a “V-shaped” trend. (5) The two-factor interaction will significantly enhance the spatial differentiation of regional tourism carbon emission efficiency, and the interaction between the level of scientific and technological innovation and other influencing factors has a deeper impact on tourism carbon emission efficiency.

Suggested Citation

  • Jun Liu & Fanfan Deng & Ding Wen & Qian Zhang & Ye Lin, 2023. "Spatial-Temporal Variation and Influencing Factors of Regional Tourism Carbon Emission Efficiency in China Based on Calculating Tourism Value Added," IJERPH, MDPI, vol. 20(3), pages 1-20, January.
    • Handle: RePEc:gam:jijerp:v:20:y:2023:i:3:p:1898-:d:1041912
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    References listed on IDEAS

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    1. Liguo Wang & Guodong Jia, 2023. "Spatial Spillover and Threshold Effects of High-Quality Tourism Development on Carbon Emission Efficiency of Tourism under the “Double Carbon” Target: Case Study of Jiangxi, China," Sustainability, MDPI, vol. 15(6), pages 1-21, March.

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