IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v17y2020i4p1159-d319837.html
   My bibliography  Save this article

Measurement and Spatial Variation of Green Total Factor Productivity of the Tourism Industry in China

Author

Listed:
  • Xingming Li

    (Key Laboratory for Geographical Process Analysis & Simulation Hubei Province, Central China Normal University, Wuhan 430079, China)

  • Pengfei Shi

    (School of Economics and Management, Southwest University, Chongqing 400715, China)

  • Yazhi Han

    (Key Laboratory for Geographical Process Analysis & Simulation Hubei Province, Central China Normal University, Wuhan 430079, China)

  • Aimin Deng

    (School of Business Administration, Zhongnan University of Economics and Law, Wuhan 430073, China)

  • Duan Liu

    (School of Business Administration, Zhongnan University of Economics and Law, Wuhan 430073, China)

Abstract

Promoting tourism in China using sustainable practices has become a very important issue. In order to analyze temporal characteristics and spatial regularities of green total factor productivity (GTFP), carbon emissions and the consumption of energy related to tourism in China were estimated using a "bottom-up" method. The construction of a measurement framework (including carbon emissions and energy consumption) of GTFP for the tourism industry was also undertaken. The data envelopment analysis (DEA) model and the Malmquist–Luenberger (ML) index were used to measure and calculate tourism GTFP in China between 2007 and 2018, as well as analyze spatio-temporal differences. Results indicate that: (1) carbon emissions and the consumption of energy are increasing, and they have not yet peaked, with traffic associated with tourism accounting for the largest proportion among tourism sectors; the spatial distribution of carbon emissions and the consumption of energy is not balanced; (2) green development of tourism in China has achieved a good level of performance during the study period, driven by technical efficiency. Since 2014, pure technical efficiency (PE) has been >1, indicating that the tourism industry in China has entered a stage of change and promotion; (3) significant spatial differences exist in tourism GTFP in China. For example, the overall pattern of being strongest in the east and weakest in the west has not changed. Currently, eastern, central, and western regions in China rely on different dynamic mechanisms to promote tourism green development. In addition, some provinces have become the core or secondary growth poles of tourism green development in China.

Suggested Citation

  • Xingming Li & Pengfei Shi & Yazhi Han & Aimin Deng & Duan Liu, 2020. "Measurement and Spatial Variation of Green Total Factor Productivity of the Tourism Industry in China," IJERPH, MDPI, vol. 17(4), pages 1-14, February.
    • Handle: RePEc:gam:jijerp:v:17:y:2020:i:4:p:1159-:d:319837
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/17/4/1159/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/17/4/1159/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Guoqing Zhao & Zhongyuan Zhang, 2010. "Uncovering the Relationship between FDI, Human Capital and Technological Progress in Chinese High‐technology Industries," China & World Economy, Institute of World Economics and Politics, Chinese Academy of Social Sciences, vol. 18(1), pages 82-98, January.
    2. Long, Xingle & Zhao, Xicang & Cheng, Faxin, 2015. "The comparison analysis of total factor productivity and eco-efficiency in China's cement manufactures," Energy Policy, Elsevier, vol. 81(C), pages 61-66.
    3. Mai Huong Giang & Tran Dang Xuan & Bui Huy Trung & Mai Thanh Que & Yuichiro Yoshida, 2018. "Impact of Investment Climate on Total Factor Productivity of Manufacturing Firms in Vietnam," Sustainability, MDPI, vol. 10(12), pages 1-18, December.
    4. Yangho Chung & Rolf Fare, 1995. "Productivity and Undesirable Outputs: A Directional Distance Function Approach," Microeconomics 9511002, University Library of Munich, Germany, revised 09 Nov 1995.
    5. Kumar, Surender, 2006. "Environmentally sensitive productivity growth: A global analysis using Malmquist-Luenberger index," Ecological Economics, Elsevier, vol. 56(2), pages 280-293, February.
    6. Ramon Fuentes & Alberto Alvarez-Suarez, 2012. "Productivity of travel agencies in Spain: the case of Alicante," The Service Industries Journal, Taylor & Francis Journals, vol. 32(16), pages 2623-2640, December.
    7. Zhang, Ning & Wang, Bing, 2015. "A deterministic parametric metafrontier Luenberger indicator for measuring environmentally-sensitive productivity growth: A Korean fossil-fuel power case," Energy Economics, Elsevier, vol. 51(C), pages 88-98.
    8. Wanke, Peter & Barros, C.P. & Nwaogbe, Obioma R., 2016. "Assessing productive efficiency in Nigerian airports using Fuzzy-DEA," Transport Policy, Elsevier, vol. 49(C), pages 9-19.
    9. Howitt, Oliver J.A. & Revol, Vincent G.N. & Smith, Inga J. & Rodger, Craig J., 2010. "Carbon emissions from international cruise ship passengers' travel to and from New Zealand," Energy Policy, Elsevier, vol. 38(5), pages 2552-2560, May.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Wenhan Ren & Yu Chen, 2022. "Realizing the Improvement of Green Total Factor Productivity of the Marine Economy—New Evidence from China’s Coastal Areas," IJERPH, MDPI, vol. 19(14), pages 1-22, July.
    2. Yan Gu & Junfei Chen & Juan Ji & Menghua Deng, 2024. "The Impacts of Water Ecological Carrying Capacity on Green Total Factor Productivity: The Case of Chemical Industry in Jiangsu, China," SAGE Open, , vol. 14(2), pages 21582440241, April.
    3. Yiyang Sun & Guolin Hou, 2021. "Analysis on the Spatial-Temporal Evolution Characteristics and Spatial Network Structure of Tourism Eco-Efficiency in the Yangtze River Delta Urban Agglomeration," IJERPH, MDPI, vol. 18(5), pages 1-29, March.
    4. Haisheng Chen & Dingqing Ni & Shuiping Zhu & Ying Ying & Manhong Shen, 2022. "Does the National Credit Demonstration Policy Affect Urban Green Economy Efficiency? Evidence from the Yangtze River Delta Region of China," IJERPH, MDPI, vol. 19(16), pages 1-20, August.
    5. Ruomeng Zhou & Yunsheng Zhang, 2023. "Measurement of Urban Green Total Factor Productivity and Analysis of Its Temporal and Spatial Evolution in China," Sustainability, MDPI, vol. 15(12), pages 1-32, June.
    6. Liang Zhao & Liangyu Chen, 2022. "Research on the Impact of Government Environmental Information Disclosure on Green Total Factor Productivity: Empirical Experience from Chinese Province," IJERPH, MDPI, vol. 19(2), pages 1-20, January.
    7. Shangram Bahadur Shah & Jirakiattikul Sopin & Kua-Anan Techato & Bibek Kumar Mudbhari, 2023. "A Systematic Review on Nexus Between Green Finance and Climate Change: Evidence from China and India," International Journal of Energy Economics and Policy, Econjournals, vol. 13(4), pages 599-613, July.
    8. Zheng Wang & Jinhua Luo, 2024. "Evaluating the tourism green productivity and its driving factors in the context of climate change," Tourism Economics, , vol. 30(3), pages 655-679, May.
    9. Xiaopeng Si & Zi Tang, 2024. "Assessment of low-carbon tourism development from multi-aspect analysis: A case study of the Yellow River Basin, China," Papers 2402.11579, arXiv.org.
    10. Xiaoshu Xu & Airong Yue & Xuechen Meng, 2023. "Increase in Industrial Sulfur Dioxide Pollution Fee and Polluting Firms’ Green Total Factor Productivity: Evidence from China," Sustainability, MDPI, vol. 15(14), pages 1-12, July.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Chen, Xiang & Chen, Yong & Huang, Wenli & Zhang, Xuping, 2023. "A new Malmquist-type green total factor productivity measure: An application to China," Energy Economics, Elsevier, vol. 117(C).
    2. Long, Xingle & Wu, Chao & Zhang, Jijian & Zhang, Jing, 2018. "Environmental efficiency for 192 thermal power plants in the Yangtze River Delta considering heterogeneity: A metafrontier directional slacks-based measure approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 3962-3971.
    3. Wei, Yigang & Li, Yan & Wu, Meiyu & Li, Yingbo, 2019. "The decomposition of total-factor CO2 emission efficiency of 97 contracting countries in Paris Agreement," Energy Economics, Elsevier, vol. 78(C), pages 365-378.
    4. Chung, Yeimin & Heshmati, Almas, 2013. "Measurement of Environmentally Sensitive Productivity Growth in Korean Industries," IZA Discussion Papers 7235, Institute of Labor Economics (IZA).
    5. Yang, Zhenbing & Fan, Meiting & Shao, Shuai & Yang, Lili, 2017. "Does carbon intensity constraint policy improve industrial green production performance in China? A quasi-DID analysis," Energy Economics, Elsevier, vol. 68(C), pages 271-282.
    6. Subhash C. Ray & Kankana Mukherjee, 2007. "Efficiency in Managing the Environment and the Opportunity Cost of Pollution Abatement," Working papers 2007-09, University of Connecticut, Department of Economics.
    7. Yu, Yanni & Qian, Tao & Du, Limin, 2017. "Carbon productivity growth, technological innovation, and technology gap change of coal-fired power plants in China," Energy Policy, Elsevier, vol. 109(C), pages 479-487.
    8. Yu, Yantuan & Huang, Jianhuan & Zhang, Ning, 2019. "Modeling the eco-efficiency of Chinese prefecture-level cities with regional heterogeneities: A comparative perspective," Ecological Modelling, Elsevier, vol. 402(C), pages 1-17.
    9. Claudia García-García & Catalina B. García-García & Román Salmerón, 2021. "Confronting collinearity in environmental regression models: evidence from world data," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 30(3), pages 895-926, September.
    10. Aparicio, Juan & Pastor, Jesus T. & Zofio, Jose L., 2013. "On the inconsistency of the Malmquist–Luenberger index," European Journal of Operational Research, Elsevier, vol. 229(3), pages 738-742.
    11. Chen, Zhenling & Zhang, Xiaoling & Ni, Guohua, 2020. "Decomposing capacity utilization under carbon dioxide emissions reduction constraints in data envelopment analysis: An application to Chinese regions," Energy Policy, Elsevier, vol. 139(C).
    12. Blessing Atwine & Ibrahim Mike Okumu & John Bosco Nnyanzi, 2023. "What drives the dynamics of employment growth in firms? Evidence from East Africa," Journal of Innovation and Entrepreneurship, Springer, vol. 12(1), pages 1-25, December.
    13. Hongwei Liu & Ronglu Yang & Zhixiang Zhou & Dacheng Huang, 2020. "Regional Green Eco-Efficiency in China: Considering Energy Saving, Pollution Treatment, and External Environmental Heterogeneity," Sustainability, MDPI, vol. 12(17), pages 1-19, August.
    14. Zhuang Miao & Tomas Baležentis & Zhihua Tian & Shuai Shao & Yong Geng & Rui Wu, 2019. "Environmental Performance and Regulation Effect of China’s Atmospheric Pollutant Emissions: Evidence from “Three Regions and Ten Urban Agglomerations”," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 74(1), pages 211-242, September.
    15. Sueyoshi, Toshiyuki & Goto, Mika, 2012. "DEA environmental assessment of coal fired power plants: Methodological comparison between radial and non-radial models," Energy Economics, Elsevier, vol. 34(6), pages 1854-1863.
    16. Rongrong Xu & Yongxiang Wu & Ming Chen & Xuan Zhang & Wei Wu & Long Tan & Gaoxu Wang & Yi Xu & Bing Yan & Yuedong Xia, 2019. "Calculation of the contribution rate of China’s hydraulic science and technology based on a feedforward neural network," PLOS ONE, Public Library of Science, vol. 14(9), pages 1-22, September.
    17. Lisann Krautzberger & Heike Wetzel, 2012. "Transport and CO 2 : Productivity Growth and Carbon Dioxide Emissions in the European Commercial Transport Industry," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 53(3), pages 435-454, November.
    18. Greta Falavigna & Alessandro Manello & Sara Pavone, 2012. "The distribution of agricultural funds towards undeveloped areas: evidence from Italy," CERIS Working Paper 201219, CNR-IRCrES Research Institute on Sustainable Economic Growth - Torino (TO) ITALY - former Institute for Economic Research on Firms and Growth - Moncalieri (TO) ITALY.
    19. Managi, Shunsuke & Jena, Pradyot Ranjan, 2008. "Environmental productivity and Kuznets curve in India," Ecological Economics, Elsevier, vol. 65(2), pages 432-440, April.
    20. Yaozu Xue, 2022. "Evaluation analysis on industrial green total factor productivity and energy transition policy in resource-based region," Energy & Environment, , vol. 33(3), pages 419-434, May.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:17:y:2020:i:4:p:1159-:d:319837. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.