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

Ning Zhang,Zichen Wang,Haiyang Li,Hongkai Ru

doi:10.3390/ijerph182312648

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.

Highlights

The term “water governance” first appeared in 2011 and became a research focus.Lautze (2000) defined it as an open, transparent, fair-participation, efficient, and sustainable governance that aligned water management objectives with local preferences [1]
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 Smart water co-governance (SWCG) is improved
Good water governance can effectively reduce the occurrence of the water resources crisis, promoting the coordinated and sustainable development of the economy, society, and ecosystem [3]

Summary

Introduction

The term “water governance” first appeared in 2011 and became a research focus.Lautze (2000) defined it as an open, transparent, fair-participation, efficient, and sustainable governance that aligned water management objectives with local preferences [1]. Good water governance can effectively reduce the occurrence of the water resources crisis, promoting the coordinated and sustainable development of the economy, society, and ecosystem [3]. If the governance issues in water resources, as a global public product, cannot actively be studied, this will impact the development of all parties—especially the study of the water resources’ governance mode, which is needed to help society adapt to the sustainable development governance paradigm [4]. In the rapidly developing information age, shared governance and smart governance are inevitable trends of the development of water resource management [5]. Claudia (2019) pointed out that a synergistic hybrid governance could greatly promote the solution to complex water resource management

Results

Discussion

Conclusion