IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v12y2020i17p6944-d404423.html
   My bibliography  Save this article

Valuation of Water Resource Green Efficiency Based on SBM–TOBIT Panel Model: Case Study from Henan Province, China

Author

Listed:
  • Yiru Guo

    (School of Management, Wuhan University of Technology, Luoshi Road No. 122, Wuhan 430070, China)

  • Yan Hu

    (School of Management, Wuhan University of Technology, Luoshi Road No. 122, Wuhan 430070, China)

  • Ke Shi

    (School of Public Policy & Management, Zhengzhou University, Kexue Road NO. 101, Zhengzhou 450001, China)

  • Yuriy Bilan

    (Institute of Management, University of Social Sciences, 9 Sienkiewicza St., 90-113 Lodz, Poland)

Abstract

With progress in China’s industrialization and urbanization, the contradiction of social and economic development with water resource supply–demand and water environmental pollution becomes increasingly prominent. To cope with the dual constraints of resource shortage and environmental regulations, the concept of water resource green efficiency that considers economic, environmental, and ecological factors is highly involved to promote sustainable economic development. The theoretical and practice circle devote to scientific green efficiency assessment of water resources and effective recognition of relevant influencing factors. However, to an extent they neglect social benefits brought by sustainable development and possible influences of industrial restructuring on green efficiency. They also lack concern on green efficiency of water resources in inland arid areas. To offset the disadvantages of existing studies, the philosophy of sustainable development was integrated into the input–output assessment system of green efficiency of water resources, and an assessment model was constructed using the SBM–Tobit (slack-based measure and Tobit) method. Moreover, a case study based on Henan Province, China was carried out. The green efficiencies of water resources in 18 cities of Henan Province during 2011–2018 were calculated. The operation mechanism of relevant influencing factors was discussed, and the methods to improve green efficiency of water resources were determined. Results reveal that the sustainable green efficiency of water resources in Henan Province increased in fluctuation during 2011–2018. The mean green efficiency increased from 0.425 in 2011 to 0.498 in 2018. At present, green efficiency of water resources in Henan Province remains at a low level, with a mean of 0.504. Reducing water consumption intensity and increasing investment to water environmental pollution technologies can promote green efficiency of water resources significantly. Conclusions provide a new method for scientific measurement and green efficiency assessment of water resources in inland arid areas.

Suggested Citation

  • Yiru Guo & Yan Hu & Ke Shi & Yuriy Bilan, 2020. "Valuation of Water Resource Green Efficiency Based on SBM–TOBIT Panel Model: Case Study from Henan Province, China," Sustainability, MDPI, vol. 12(17), pages 1-17, August.
  • Handle: RePEc:gam:jsusta:v:12:y:2020:i:17:p:6944-:d:404423
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/12/17/6944/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/12/17/6944/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Yande Gong & Joe Zhu & Ya Chen & Wade D. Cook, 2018. "DEA as a tool for auditing: application to Chinese manufacturing industry with parallel network structures," Annals of Operations Research, Springer, vol. 263(1), pages 247-269, April.
    2. Ching‐Hsun Chang, 2018. "How to Enhance Green Service and Green Product Innovation Performance? The Roles of Inward and Outward Capabilities," Corporate Social Responsibility and Environmental Management, John Wiley & Sons, vol. 25(4), pages 411-425, July.
    3. Zhou, Yuanchun & Ma, Mengdie & Gao, Peiqi & Xu, Qiming & Bi, Jun & Naren, Tuya, 2019. "Managing water resources from the energy - water nexus perspective under a changing climate: A case study of Jiangsu province, China," Energy Policy, Elsevier, vol. 126(C), pages 380-390.
    4. Long, Kaisheng & Pijanowski, Bryan C., 2017. "Is there a relationship between water scarcity and water use efficiency in China? A national decadal assessment across spatial scales," Land Use Policy, Elsevier, vol. 69(C), pages 502-511.
    5. Zhihai Yang & Dong Wang & Tianyi Du & Anlu Zhang & Yixiao Zhou, 2018. "Total-Factor Energy Efficiency in China’s Agricultural Sector: Trends, Disparities and Potentials," Energies, MDPI, vol. 11(4), pages 1-16, April.
    6. Chuang-lin Fang & Chao Bao & Jin-chuan Huang, 2007. "Management Implications to Water Resources Constraint Force on Socio-economic System in Rapid Urbanization: A Case Study of the Hexi Corridor, NW China," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 21(9), pages 1613-1633, September.
    7. Bao, Chao & Fang, Chuang-lin, 2007. "Water resources constraint force on urbanization in water deficient regions: A case study of the Hexi Corridor, arid area of NW China," Ecological Economics, Elsevier, vol. 62(3-4), pages 508-517, May.
    8. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    9. Jintao Lu & Licheng Ren & Siqin Yao & Dan Rong & Marinko Skare & Justas Streimikis, 2020. "Renewable energy barriers and coping strategies: Evidence from the Baltic States," Sustainable Development, John Wiley & Sons, Ltd., vol. 28(1), pages 352-367, January.
    10. Tone, Kaoru & Tsutsui, Miki, 2010. "Dynamic DEA: A slacks-based measure approach," Omega, Elsevier, vol. 38(3-4), pages 145-156, June.
    11. Tone, Kaoru, 2001. "A slacks-based measure of efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 130(3), pages 498-509, May.
    12. F. Chemak & J.Ph Boussemart & F. Jacquet, 2010. "Farming system performance and water use efficiency in the Tunisian semi-arid region: data envelopment analysis approach," Post-Print hal-00570321, HAL.
    13. Omezzine, Abdallah & Zaibet, Lokman, 1998. "Management of modern irrigation systems in oman: allocative vs. irrigation efficiency," Agricultural Water Management, Elsevier, vol. 37(2), pages 99-107, July.
    14. Xianguo Li & Qian Zhang, 2015. "AHP-based resources and environment efficiency evaluation index system construction about the west side of Taiwan Straits," Annals of Operations Research, Springer, vol. 228(1), pages 97-111, 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. Xu Zhang & Huaping Sun & Taohong Wang, 2022. "Impact of Financial Inclusion on the Efficiency of Carbon Emissions: Evidence from 30 Provinces in China," Energies, MDPI, vol. 15(19), pages 1-15, October.
    2. Atalel Wubalem & Teshale Woldeamanuel & Zerihun Nigussie, 2023. "Economic Valuation of Lake Tana: A Recreational Use Value Estimation through the Travel Cost Method," Sustainability, MDPI, vol. 15(8), pages 1-20, April.
    3. Yuwen Lyu & Yuqing Peng & Hejian Liu & Ji-Jen Hwang, 2022. "Impact of Digital Economy on the Provision Efficiency for Public Health Services: Empirical Study of 31 Provinces in China," IJERPH, MDPI, vol. 19(10), pages 1-17, May.
    4. Chong Huang & Kedong Yin & Zhe Liu & Tonggang Cao, 2021. "Spatial and Temporal Differences in the Green Efficiency of Water Resources in the Yangtze River Economic Belt and Their Influencing Factors," IJERPH, MDPI, vol. 18(6), pages 1-18, March.

    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. Alperovych, Yan & Hübner, Georges & Lobet, Fabrice, 2015. "How does governmental versus private venture capital backing affect a firm's efficiency? Evidence from Belgium," Journal of Business Venturing, Elsevier, vol. 30(4), pages 508-525.
    2. Chen, Yufeng & Ni, Liangfu & Liu, Kelong, 2021. "Does China's new energy vehicle industry innovate efficiently? A three-stage dynamic network slacks-based measure approach," Technological Forecasting and Social Change, Elsevier, vol. 173(C).
    3. Yongqi Feng & Haolin Zhang & Yung-ho Chiu & Tzu-Han Chang, 2021. "Innovation efficiency and the impact of the institutional quality: a cross-country analysis using the two-stage meta-frontier dynamic network DEA model," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(4), pages 3091-3129, April.
    4. Yu-Chuan Chen & Yung-Ho Chiu & Tzu-Han Chang & Tai-Yu Lin, 2023. "Sustainable Development, Government Efficiency, and People’s Happiness," Journal of Happiness Studies, Springer, vol. 24(4), pages 1549-1578, April.
    5. Yung‐ho Chiu & Tai‐Yu Lin & Tzu‐Han Chang & Yi‐Nuo Lin & Shih‐Yung Chiu, 2021. "Prevaluating efficiency gains from potential mergers and acquisitions in the financial industry with the Resample Past–Present–Future data envelopment analysis approach," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 42(2), pages 369-384, March.
    6. Chen, Kuan-Chen & Lin, Sun-Yuan & Yu, Ming-Miin, 2022. "Exploring the efficiency of hospital and pharmacy utilizations in Taiwan: An application of dynamic network data envelopment analysis," Socio-Economic Planning Sciences, Elsevier, vol. 84(C).
    7. Zhen Shi & Fengping Wu & Huinan Huang & Xinrui Sun & Lina Zhang, 2019. "Comparing Economics, Environmental Pollution and Health Efficiency in China," IJERPH, MDPI, vol. 16(23), pages 1-30, December.
    8. Yu, Ming-Miin, 2010. "Assessment of airport performance using the SBM-NDEA model," Omega, Elsevier, vol. 38(6), pages 440-452, December.
    9. Aparicio, Juan & Kapelko, Magdalena, 2019. "Accounting for slacks to measure dynamic inefficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 278(2), pages 463-471.
    10. Huang, Shwu-Huei & Yu, Ming-Miin & Huang, Ya-Ling, 2022. "Evaluation of the efficiency of the local tax administration in Taiwan: Application of a dynamic network data envelopment analysis," Socio-Economic Planning Sciences, Elsevier, vol. 83(C).
    11. Alperovych, Yan & Amess, Kevin & Wright, Mike, 2013. "Private equity firm experience and buyout vendor source: What is their impact on efficiency?," European Journal of Operational Research, Elsevier, vol. 228(3), pages 601-611.
    12. Wang, Qian & Ren, Shuming, 2022. "Evaluation of green technology innovation efficiency in a regional context: A dynamic network slacks-based measuring approach," Technological Forecasting and Social Change, Elsevier, vol. 182(C).
    13. Zhen Shi & Shijiong Qin & Yung-ho Chiu & Xiaoying Tan & Xiaoli Miao, 2021. "The impact of gross domestic product on the financing and investment efficiency of China’s commercial banks," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-23, December.
    14. Plácido Moreno & Sebastián Lozano, 2014. "A network DEA assessment of team efficiency in the NBA," Annals of Operations Research, Springer, vol. 214(1), pages 99-124, March.
    15. Fang-Rong Ren & Ze Tian & Yu-Ting Shen & Yung-Ho Chiu & Tai-Yu Lin, 2019. "Energy, CO 2 , and AQI Efficiency and Improvement of the Yangtze River Economic Belt," Energies, MDPI, vol. 12(4), pages 1-17, February.
    16. Wei Yan & Changbiao Zhong, 2022. "The Coordination of Aquaculture Development with Environment and Resources: Based on Measurement of Provincial Eco-Efficiency in China," IJERPH, MDPI, vol. 19(13), pages 1-13, June.
    17. Min Wang & Meng Ji & Xiaofen Wu & Kexin Deng & Xiaodong Jing, 2023. "Analysis on Evaluation and Spatial-Temporal Evolution of Port Cluster Eco-Efficiency: Case Study from the Yangtze River Delta in China," Sustainability, MDPI, vol. 15(10), pages 1-16, May.
    18. 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).
    19. Zhen Shi & Huinan Huang & Yingju Wu & Yung-Ho Chiu & Shijiong Qin, 2020. "Climate Change Impacts on Agricultural Production and Crop Disaster Area in China," IJERPH, MDPI, vol. 17(13), pages 1-23, July.
    20. Iveta Repkova, 2013. "Estimation of Banking Efficiency in the Czech Republic: Dynamic Data Envelopment Analysis," DANUBE: Law and Economics Review, European Association Comenius - EACO, issue 4, pages 261-275, 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:12:y:2020:i:17:p:6944-:d:404423. 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.