IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v11y2019i17p4556-d259818.html
   My bibliography  Save this article

Evaluation of Water Use Efficiency of 31 Provinces and Municipalities in China Using Multi-Level Entropy Weight Method Synthesized Indexes and Data Envelopment Analysis

Author

Listed:
  • Boyang Sun

    (School of Environment, Beijing Normal University, Beijing 100875, China)

  • Xiaohua Yang

    (School of Environment, Beijing Normal University, Beijing 100875, China)

  • Yipeng Zhang

    (School of Economics and Resources Management, Beijing Normal University, Beijing 100875, China)

  • Xiaojuan Chen

    (Changjiang Water Resources Protection Institute, Wuhan 430051, China)

Abstract

China’s water shortage problem is becoming increasingly severe. Improving water use efficiency is crucial to alleviating China’s water crisis. This paper evaluates the water use efficiency of 31 provinces and municipalities in China by using the data envelopment analysis (DEA) method. When the usual DEA model has too many indexes selected, it will cause the majority of the decision making units (DMUs) efficiency values be one, which leads to invalid evaluation results. Therefore, by using the entropy weight method, a new synthetic set of indexes is constructed based on the original indexes. The new synthetic set of indexes retains the full information of the original indexes, and the goal of simplifying the number of indexes is achieved. Simultaneously, by empowering the original indexes, the evaluation using synthetic indexes can also avoid the impact of industrial structure and labor division on water use efficiency. The results show that in China’s northeastern grain producing areas, water use efficiency is higher due to the high level of agricultural modernization. The provinces in the middle reaches of the Yangtze River have the lowest water use efficiency due to water pollution and water waste. In general, China’s overall water use efficiency is low, and there is still much room for improvement.

Suggested Citation

  • Boyang Sun & Xiaohua Yang & Yipeng Zhang & Xiaojuan Chen, 2019. "Evaluation of Water Use Efficiency of 31 Provinces and Municipalities in China Using Multi-Level Entropy Weight Method Synthesized Indexes and Data Envelopment Analysis," Sustainability, MDPI, vol. 11(17), pages 1-11, August.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:17:p:4556-:d:259818
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/11/17/4556/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/11/17/4556/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Xiao-Hua Yang & Bo-Yang Sun & Jian Zhang & Mei-Shui Li & Jun He & Yi-Ming Wei & Yu-Qi Li, 2016. "Hierarchy evaluation of water resources vulnerability under climate change in Beijing, China," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 84(1), pages 63-76, November.
    2. Longyu Shi & Xueqin Xiang & Wei Zhu & Lijie Gao, 2018. "Standardization of the Evaluation Index System for Low-Carbon Cities in China: A Case Study of Xiamen," Sustainability, MDPI, vol. 10(10), pages 1-20, October.
    3. Yuanjie Li & Zhuoying Zhang & Minjun Shi, 2019. "Restrictive Effects of Water Scarcity on Urban Economic Development in the Beijing-Tianjin-Hebei City Region," Sustainability, MDPI, vol. 11(8), pages 1-23, April.
    4. Conglin Zhang & Leihua Dong & Yu Liu & Haijuan Qiao, 2016. "Analysis on Impact Factors of Water Utilization Structure in Tianjin, China," Sustainability, MDPI, vol. 8(3), pages 1-11, March.
    5. Dariush Khezrimotlagh & Yao Chen, 2018. "Data Envelopment Analysis," International Series in Operations Research & Management Science, in: Decision Making and Performance Evaluation Using Data Envelopment Analysis, chapter 0, pages 217-234, Springer.
    6. Xifeng WANG, 2018. "Study on Water Resources Efficiency with the Regional Water Resources Carrying Capacity into Consideration," Chinese Journal of Urban and Environmental Studies (CJUES), World Scientific Publishing Co. Pte. Ltd., vol. 6(04), pages 1-16, December.
    7. Nathaniel D. Mueller & James S. Gerber & Matt Johnston & Deepak K. Ray & Navin Ramankutty & Jonathan A. Foley, 2012. "Closing yield gaps through nutrient and water management," Nature, Nature, vol. 490(7419), pages 254-257, October.
    8. Mardani, Abbas & Zavadskas, Edmundas Kazimieras & Streimikiene, Dalia & Jusoh, Ahmad & Khoshnoudi, Masoumeh, 2017. "A comprehensive review of data envelopment analysis (DEA) approach in energy efficiency," Renewable and Sustainable Energy Reviews, Elsevier, vol. 70(C), pages 1298-1322.
    9. Sueyoshi, Toshiyuki & Yuan, Yan & Goto, Mika, 2017. "A literature study for DEA applied to energy and environment," Energy Economics, Elsevier, vol. 62(C), pages 104-124.
    10. K. Cheng & Q. Fu & J. Meng & T. X. Li & W. Pei, 2018. "Analysis of the Spatial Variation and Identification of Factors Affecting the Water Resources Carrying Capacity Based on the Cloud Model," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(8), pages 2767-2781, June.
    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. Wei Qian & Chun Fu & Zhongzheng He, 2023. "Study on Evaluation of Order Degree of Water Resources Coupling System Considering Time Series Characteristics—Take Jiangxi Province as an Example," Sustainability, MDPI, vol. 15(19), pages 1-17, September.
    2. Angel Higuerey & Christian Viñan-Merecí & Zulema Malo-Montoya & Valentín-Alejandro Martínez-Fernández, 2020. "Data Envelopment Analysis (DEA) for Measuring the Efficiency of the Hotel Industry in Ecuador," Sustainability, MDPI, vol. 12(4), pages 1-18, February.
    3. Heng Zhang & Qian Chang & Sui Li & Jiandong Huang, 2022. "Determining the Efficiency of the Sponge City Construction Pilots in China Based on the DEA-Malmquist Model," IJERPH, MDPI, vol. 19(18), pages 1-17, September.
    4. Muchen Luo & Yimin Wu, 2022. "Data-Driven Evaluation and Optimisation of Livelihood Improvement Efficiency," Sustainability, MDPI, vol. 14(13), pages 1-24, July.
    5. Xiaoxiao Ye & Yong Fan & Jing Miao & Zongyi He, 2022. "The Competitiveness of Regional Urban System in Hubei Province of China," Land, MDPI, vol. 11(6), pages 1-18, June.
    6. Wasi Ul Hassan Shah & Yuting Lu & Gang Hao & Hong Yan & Rizwana Yasmeen, 2022. "Impact of “Three Red Lines” Water Policy (2011) on Water Usage Efficiency, Production Technology Heterogeneity, and Determinant of Water Productivity Change in China," IJERPH, MDPI, vol. 19(24), pages 1-23, December.
    7. Shaoxiong Yang & Jinfu Xu & Ruoyu Yang, 2020. "Research on Coordination and Driving Factors of Sports Industry and Regional Sustainable Development—Empirical Research Based on Panel Data of Provinces and Cities in Eastern China," Sustainability, MDPI, vol. 12(3), pages 1-21, January.

    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. Hongli Liu & Xiaoyu Yan & Jinhua Cheng & Jun Zhang & Yan Bu, 2021. "Driving Factors for the Spatiotemporal Heterogeneity in Technical Efficiency of China’s New Energy Industry," Energies, MDPI, vol. 14(14), pages 1-21, July.
    2. Haitao Li & Jie Xiong & Jianhui Xie & Zhongbao Zhou & Jinlong Zhang, 2019. "A Unified Approach to Efficiency Decomposition for a Two-Stage Network DEA Model with Application of Performance Evaluation in Banks and Sustainable Product Design," Sustainability, MDPI, vol. 11(16), pages 1-18, August.
    3. Laura Calzada-Infante & Ana María López-Narbona & Alberto Núñez-Elvira & Javier Orozco-Messana, 2020. "Assessing the Efficiency of Sustainable Cities Using an Empirical Approach," Sustainability, MDPI, vol. 12(7), pages 1-13, March.
    4. Feng, Xuesong & Tao, Zhibin & Shi, Ruolin, 2024. "The Spatiotemporal exploration of intercity transport energy efficiency in the mainland of China on the basis of improved stochastic frontier modelling," Renewable Energy, Elsevier, vol. 224(C).
    5. Ghodeswar, Archana & Oliver, Matthew E., 2022. "Trading one waste for another? Unintended consequences of fly ash reuse in the Indian electric power sector," Energy Policy, Elsevier, vol. 165(C).
    6. Fernández, David & Pozo, Carlos & Folgado, Rubén & Jiménez, Laureano & Guillén-Gosálbez, Gonzalo, 2018. "Productivity and energy efficiency assessment of existing industrial gases facilities via data envelopment analysis and the Malmquist index," Applied Energy, Elsevier, vol. 212(C), pages 1563-1577.
    7. Filip Fidanoski & Kiril Simeonovski & Violeta Cvetkoska, 2021. "Energy Efficiency in OECD Countries: A DEA Approach," Energies, MDPI, vol. 14(4), pages 1-21, February.
    8. Ding, Li-Li & Lei, Liang & Zhao, Xin & Calin, Adrian Cantemir, 2020. "Modelling energy and carbon emission performance: A constrained performance index measure," Energy, Elsevier, vol. 197(C).
    9. De Clercq, Djavan & Wen, Zongguo & Caicedo, Luis & Cao, Xin & Fan, Fei & Xu, Ruifei, 2017. "Application of DEA and statistical inference to model the determinants of biomethane production efficiency: A case study in south China," Applied Energy, Elsevier, vol. 205(C), pages 1231-1243.
    10. Hosseini, Keyvan & Stefaniec, Agnieszka, 2019. "Efficiency assessment of Iran's petroleum refining industry in the presence of unprofitable output: A dynamic two-stage slacks-based measure," Energy, Elsevier, vol. 189(C).
    11. Jindal, Abhinav & Nilakantan, Rahul, 2021. "Falling efficiency levels of Indian coal-fired power plants: A slacks-based analysis," Energy Economics, Elsevier, vol. 93(C).
    12. Liang-Han Ma & Jin-Chi Hsieh & Yung-Ho Chiu, 2020. "Comparing regional differences in global energy performance," Energy & Environment, , vol. 31(6), pages 943-960, September.
    13. Zhou, Anhua & Li, Jun, 2021. "Investigate the impact of market reforms on the improvement of manufacturing energy efficiency under China’s provincial-level data," Energy, Elsevier, vol. 228(C).
    14. Abbas Mardani & Dalia Streimikiene & Tomas Balezentis & Muhamad Zameri Mat Saman & Khalil Md Nor & Seyed Meysam Khoshnava, 2018. "Data Envelopment Analysis in Energy and Environmental Economics: An Overview of the State-of-the-Art and Recent Development Trends," Energies, MDPI, vol. 11(8), pages 1-21, August.
    15. Haider, Salman & Danish, Mohd Shadab & Sharma, Ruchi, 2019. "Assessing energy efficiency of Indian paper industry and influencing factors: A slack-based firm-level analysis," Energy Economics, Elsevier, vol. 81(C), pages 454-464.
    16. Mohd Chachuli, Fairuz Suzana & Ahmad Ludin, Norasikin & Md Jedi, Muhamad Alias & Hamid, Norul Hisham, 2021. "Transition of renewable energy policies in Malaysia: Benchmarking with data envelopment analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 150(C).
    17. Qingwei Shi & Hong Ren & Weiguang Cai & Jingxin Gao, 2020. "How to Set the Proper CO 2 Reduction Targets for the Provincial Building Sector of China?," Sustainability, MDPI, vol. 12(24), pages 1-22, December.
    18. Yongrok Choi & Fan Yang & Hyoungsuk Lee, 2020. "On the Unbalanced Atmospheric Environmental Performance of Major Cities in China," Sustainability, MDPI, vol. 12(13), pages 1-14, July.
    19. Kassoum Ayouba, 2023. "Spatial dependence in production frontier models," Journal of Productivity Analysis, Springer, vol. 60(1), pages 21-36, August.
    20. Kai Xu & Bart Bossink & Qiang Chen, 2019. "Efficiency Evaluation of Regional Sustainable Innovation in China: A Slack-Based Measure (SBM) Model with Undesirable Outputs," Sustainability, MDPI, vol. 12(1), pages 1-21, December.

    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:jsusta:v:11:y:2019:i:17:p:4556-:d:259818. 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.