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Impact of High-Speed Rail on the Development Efficiency of Low-Carbon Tourism: A Case Study of an Agglomeration in China

Author

Listed:
  • Mingwei Li

    (School of Tourism, Xinyang Normal University, Xinyang 464000, China)

  • Bingxue Shao

    (School of Tourism, Xinyang Normal University, Xinyang 464000, China)

  • Xiasheng Shi

    (Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education, Dalian University of Technology, Dalian 116024, China
    School of Information and Control Engineering, China University of Mining and Technology, Xuzhou 221116, China)

Abstract

As an important indicator for measuring the development level of low-carbon tourism, reducing the carbon emissions of tourism transportation has become an essential strategic goal and task for the sustainable development of tourism. Among many tourism vehicles, high-speed rails have a significant role in reducing the carbon emissions of tourism transportation. To clarify the impact of high-speed rails on the development efficiency of low-carbon tourism, using the relevant data of Zhengzhou urban agglomeration from 2010 to 2020, the DEA-BCC model and the Malmquist index method were used to measure these data. The results show the following: (1) the average comprehensive development efficiency of the Zhengzhou metropolitan high-speed rail for low-carbon tourism is low, and the comprehensive development efficiency of each city varies greatly; (2) the impact of high-speed rails on the development efficiency of low-carbon tourism in some underdeveloped areas is increasing. The impact on the development efficiency of low-carbon tourism in more developed areas is declining; (3) affected by COVID-19, tourism carbon emissions have shown a downward trend, reflecting the importance of low-carbon travel to low-carbon tourism to a certain extent. The research results not only verify the existing research conclusions but also verify the role of high-speed rails in the development of low-carbon tourism, and have practical value with respect to targeted guidance for the development of low-carbon tourism.

Suggested Citation

  • Mingwei Li & Bingxue Shao & Xiasheng Shi, 2022. "Impact of High-Speed Rail on the Development Efficiency of Low-Carbon Tourism: A Case Study of an Agglomeration in China," Sustainability, MDPI, vol. 14(16), pages 1-16, August.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:16:p:9879-:d:884924
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    References listed on IDEAS

    as
    1. Ji Wu & Xian Cheng & Stephen Shaoyi Liao, 2020. "Tourism forecast combination using the stochastic frontier analysis technique," Tourism Economics, , vol. 26(7), pages 1086-1107, November.
    2. Jianping Zha & Zhiyong Li, 2017. "Drivers of tourism growth," Tourism Economics, , vol. 23(5), pages 941-962, August.
    3. Strauss, Jack & Li, Hongchang & Cui, Jinli, 2021. "High-speed Rail's impact on airline demand and air carbon emissions in China," Transport Policy, Elsevier, vol. 109(C), pages 85-97.
    4. Yong-bae Ji & Choonjoo Lee, 2010. "Data envelopment analysis," Stata Journal, StataCorp LP, vol. 10(2), pages 267-280, June.
    5. Yuanyuan Lin & Nianqi Deng & Hailian Gao, 2018. "Research on Technological Innovation Efficiency of Tourist Equipment Manufacturing Enterprises," Sustainability, MDPI, vol. 10(12), pages 1-17, December.
    6. Shekhar Mishra & Avik Sinha & Arshian Sharif & Norazah Mohd Suki, 2020. "Dynamic linkages between tourism, transportation, growth and carbon emission in the USA: evidence from partial and multiple wavelet coherence," Current Issues in Tourism, Taylor & Francis Journals, vol. 23(21), pages 2733-2755, November.
    7. Yue Pan & Gangmin Weng & Conghui Li & Jianpu Li, 2021. "Coupling Coordination and Influencing Factors among Tourism Carbon Emission, Tourism Economic and Tourism Innovation," IJERPH, MDPI, vol. 18(4), pages 1-17, February.
    8. Xueqiao Yu & Maoxiang Lang & Yang Gao & Kai Wang & Ching-Hsia Su & Sang-Bing Tsai & Mingkun Huo & Xiao Yu & Shiqi Li, 2018. "An Empirical Study on the Design of China High-Speed Rail Express Train Operation Plan—From a Sustainable Transport Perspective," Sustainability, MDPI, vol. 10(7), pages 1-19, July.
    9. Ana-Maria Dinu, 2018. "The Importance of Transportation to Tourism Development," Academic Journal of Economic Studies, Faculty of Finance, Banking and Accountancy Bucharest,"Dimitrie Cantemir" Christian University Bucharest, vol. 4(4), pages 183-187, December.
    10. Fumin Deng & Yuan Fang & Lin Xu & Zhi Li, 2020. "Tourism, Transportation and Low-Carbon City System Coupling Coordination Degree: A Case Study in Chongqing Municipality, China," IJERPH, MDPI, vol. 17(3), pages 1-17, January.
    11. Jia, Ruining & Shao, Shuai & Yang, Lili, 2021. "High-speed rail and CO2 emissions in urban China: A spatial difference-in-differences approach," Energy Economics, Elsevier, vol. 99(C).
    12. (Ato) Xu, Wangtu & Zhou, Jiangping & Yang, Linchuan & Li, Ling, 2018. "The implications of high-speed rail for Chinese cities: Connectivity and accessibility," Transportation Research Part A: Policy and Practice, Elsevier, vol. 116(C), pages 308-326.
    13. Fernández, Xosé Luis & Coto-Millán, Pablo & Díaz-Medina, Benito, 2018. "The impact of tourism on airport efficiency: The Spanish case," Utilities Policy, Elsevier, vol. 55(C), pages 52-58.
    14. Chen, Jun, 2021. "High-speed rail and energy consumption in China: The intermediary roles of industry and technology," Energy, Elsevier, vol. 230(C).
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