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Study on the Spatio–Temporal Evolution of China’s Smart Water Co-Governance in G–E–P Mode

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  • Ning Zhang

    (School of Management, Hangzhou Dianzi University, Hangzhou 310018, China)

  • Zichen Wang

    (School of Management, Hangzhou Dianzi University, Hangzhou 310018, China)

  • Hongkai Ru

    (School of Economics, Hangzhou Dianzi University, Hangzhou 310018, China)

  • Haiyang Li

    (School of Management, Hangzhou Dianzi University, Hangzhou 310018, China)

Abstract

Smart water co-governance (SWCG) is a fundamental driving force to reduce the water crisis and promote the sustainable development of water resources. To explore the applicability and development of SWCG in different regions, the authors of this paper took 31 provinces of China (with the exception Hong Kong, Macao, and Taiwan) as research districts and used the three-stage data envelopment analysis (DEA) method to measure and compare the efficiency of smart water governance (SWG) in the government–enterprise–public (G–E–P) mode and without public participation in the government–enterprise (G–E) mode in 2019. Then, the Malmquist model was used to measure the spatio–temporal evolution of the G–E–P mode from 2010 to 2019, focusing on the analysis of the top ten provinces of the China Internet Development Index in 2019. According to the empirical analysis, the following results were obtained: (1) the efficiency of SWCG in the G–E–P mode was significantly higher than that in G–E model, as 13 provinces showed a significant decline and 10 provinces had a small change. In addition, SWCG in the G–E–P mode showed a good development trend in the eastern and southern regions. (2) The governance efficiency, pure technical efficiency, and scale efficiency showed upward trends, but the technological progress index and total factor productivity were still low. Therefore, SWG should vigorously promote public participation and the independent implementation of enterprises under the guidance and restriction of the government. Meanwhile, the construction of an SWG infrastructure and the level of science and technology should be strengthened. In addition, each province should adjust the input–output structure according to its redundancy or deficiency, weigh the suitability of the input level and scale, and strengthen the matching and support of the ability of multi-subjects and factors to ensure that an appropriate input–output scale level is reached and the efficiency of SWCG is improved.

Suggested Citation

  • Ning Zhang & Zichen Wang & Hongkai Ru & Haiyang Li, 2021. "Study on the Spatio–Temporal Evolution of China’s Smart Water Co-Governance in G–E–P Mode," IJERPH, MDPI, vol. 18(23), pages 1-25, November.
    • Handle: RePEc:gam:jijerp:v:18:y:2021:i:23:p:12648-:d:692057
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    References listed on IDEAS

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    1. Jonathan Lautze & Sanjiv de Silva & Mark Giordano & Luke Sanford, 2011. "Putting the cart before the horse: Water governance and IWRM," Natural Resources Forum, Blackwell Publishing, vol. 35, pages 1-8, February.
    2. Jonathan Lautze & Sanjiv de Silva & Mark Giordano & Luke Sanford, 2011. "Putting the cart before the horse: Water governance and IWRM," Natural Resources Forum, Blackwell Publishing, vol. 35(1), pages 1-8, February.
    3. Claudia Pahl-Wostl, 2017. "An Evolutionary Perspective on Water Governance: From Understanding to Transformation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(10), pages 2917-2932, August.
    4. Claudia Pahl-Wostl, 2017. "Erratum to: An Evolutionary Perspective on Water Governance: From Understanding to Transformation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(13), pages 4369-4369, October.
    5. Geng Peng & Xiaodan Zhang & Fang Liu & Lijuan Ruan & Kaiyou Tian, 2021. "Spatial–temporal evolution and regional difference decomposition of urban environmental governance efficiency in China," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(6), pages 8974-8990, June.
    6. Harold Fried & Shelton Schmidt & Suthathip Yaisawarng, 1999. "Incorporating the Operating Environment Into a Nonparametric Measure of Technical Efficiency," Journal of Productivity Analysis, Springer, vol. 12(3), pages 249-267, November.
    7. Xiao-Ning Li & Ying Feng & Pei-Ying Wu & Yung-Ho Chiu, 2021. "An Analysis of Environmental Efficiency and Environmental Pollution Treatment Efficiency in China’s Industrial Sector," Sustainability, MDPI, vol. 13(5), pages 1-25, February.
    8. Neil S. Grigg, 2020. "Smart water management: can it improve accessibility and affordability of water for everyone?," Water International, Taylor & Francis Journals, vol. 45(6), pages 608-620, August.
    9. H. Fried & C. Lovell & S. Schmidt & S. Yaisawarng, 2002. "Accounting for Environmental Effects and Statistical Noise in Data Envelopment Analysis," Journal of Productivity Analysis, Springer, vol. 17(1), pages 157-174, January.
    10. Mallory Orme & Zoë Cuthbert & Francesco Sindico & Julie Gibson & Renice Bostic, 2015. "Good transboundary water governance in the 2015 Sustainable Development Goals: a legal perspective," Water International, Taylor & Francis Journals, vol. 40(7), pages 969-983, November.
    11. Sueyoshi, Toshiyuki & Sekitani, Kazuyuki, 2009. "An occurrence of multiple projections in DEA-based measurement of technical efficiency: Theoretical comparison among DEA models from desirable properties," European Journal of Operational Research, Elsevier, vol. 196(2), pages 764-794, July.
    12. Jia-Yin Yin & Yun-Fei Cao & Bao-Jun Tang, 2019. "Fairness of China’s provincial energy environment efficiency evaluation: empirical analysis using a three-stage data envelopment analysis model," 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. 95(1), pages 343-362, January.
    13. Li, Hai-ling & Zhu, Xue-hong & Chen, Jin-yu & Jiang, Fei-tao, 2019. "Environmental regulations, environmental governance efficiency and the green transformation of China's iron and steel enterprises," Ecological Economics, Elsevier, vol. 165(C), pages 1-1.
    14. Morten Graversgaard & Beatrice Hedelin & Laurence Smith & Flemming Gertz & Anker Lajer Højberg & John Langford & Grit Martinez & Erik Mostert & Emilia Ptak & Heidi Peterson & Nico Stelljes & Cors Van , 2018. "Opportunities and Barriers for Water Co-Governance—A Critical Analysis of Seven Cases of Diffuse Water Pollution from Agriculture in Europe, Australia and North America," Sustainability, MDPI, vol. 10(5), pages 1-39, May.
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    1. Cao, Xinghua & Chen, Hao, 2024. "The impact of public participation in environmental governance on the technical efficiency of enterprise," Finance Research Letters, Elsevier, vol. 62(PA).

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