Improving the efficiency of industrial water resource is one way to alleviate the contradiction between water supply and demand and it is also an important guarantee for ecological protection and high-quality development in the Yellow River Basin. Based on the super-efficiency EBM model, ML index and Tobit model of undesired output, this study analyzes the temporal and spatial differentiation and influencing factors of industrial water resource efficiency in the nine provinces (autonomous regions) of the Yellow River Basin from 2010 to 2019. The results indicate that the overall average value of industrial water resource efficiency in the nine provinces is 0.77, lower than the effective level, but shows a fluctuating upward trend. There are obvious differences among these provinces, with Shandong having the highest efficiency and Ningxia the lowest. The main driving force for the improvement of ML index comes from technological progress, and the scale efficiency of some provinces hinders the positive adjustment of ML index by technical efficiency. The technological level and degree of industrialization have a promoting effect on the increase of industrial water resource efficiency; the inhibitory effects of water resource endowment, industrial water use intensity and government regulation intensity are significant. Finally, the article puts forward some corresponding suggestions.
MIAO Junyu
,
ZHANG Chunying
. Temporal and spatial differentiation and influencing factors of industrial water resources efficiency in nine provinces (regions) of the Yellow River Basin[J]. Science & Technology Review, 2022
, 40(19)
: 71
-80
.
DOI: 10.3981/j.issn.1000-7857.2022.19.008
[1] 魏楚, 沈满洪. 水资源效率的测度及影响因素: 基于文献的述评[J]. 长江流域资源与环境, 2014, 23(2): 197- 204.
[2] 杨高升, 谢秋皓. 长江经济带绿色水资源效率时空分异研究——基于SE-SBM与ML指数法[J]. 长江流域资源与环境, 2019, 28(2): 349-358.
[3] 许晶荣, 黄德春, 方隽敏. 中国区域全要素水资源利用效率及其影响[J]. 河海大学学报(哲学社会科学版), 2021, 23(6): 77-84.
[4] 胡林凯. 基于WCA-MEPP模型的云南省水资源利用效率动态评价[J]. 水资源与水工程学报, 2017, 28(4): 75- 81.
[5] Azad M A S, Ancev T, Hernández-Sancho F. Efficient water use for sustainable irrigation industry[J]. Water Resources Management, 2015, 29(5): 1683-1696.
[6] 焦士兴, 王安周, 张崇崇, 等. 河南省水资源效率综合测度及时空分异[J]. 水资源保护, 2022, 38(2): 48-55.
[7] 钟丽雯, 张建兵, 蔡芸霜, 等. 广西水资源利用效率及其时空格局[J]. 经济地理, 2020, 40(6): 193-202.
[8] 钱文婧, 贺灿飞. 中国水资源利用效率区域差异及影响因素研究[J]. 中国人口·资源与环境, 2011, 21(2): 54-60.
[9] 张兆方, 沈菊琴, 何伟军, 等.“一带一路” 中国区域水资源利用效率评价——基于超效率DEA-Malmquist-Tobit方法[J]. 河海大学学报(哲学社会科学版), 2018, 20(4): 60-66.
[10] 李健, 谢衡. 京津冀绿色水资源利用效率及其时空差异与驱动因素分析[J]. 水资源与水工程学报, 2021, 32(6): 10-18.
[11] 苏喜军, 纪德红, 何慧爽. 黄淮海平原农业水资源绿色效率时空差异与影响因素研究[J]. 生态经济, 2021, 37(3): 106-111
[12] 沈晓梅, 谢雨涵. 农业绿色水资源利用效率及其影响因素研究[J]. 中国农村水利水电, 2022(3): 13-18.
[13] 买亚宗, 孙福丽, 石磊, 等. 基于DEA的中国工业水资源利用效率评价研究[J]. 干旱区资源与环境, 2014, 28(11): 42-47.
[14] 胡彪, 侯绍波. 京津冀地区城市工业用水效率的时空差异性研究[J]. 干旱区资源与环境, 2016, 30(7): 1-7.
[15] 谭粤元. 中国工业用水效率研究[D]. 北京: 中国地质大学(北京), 2018.
[16] 郑乐, 杨法暄, 钱会, 等. 基于超效率DEA模型的宁夏工业水资源利用效率研究[J]. 水资源与水工程学报, 2020, 31(2): 81-86.
[17] 李明璗. 基于DEA方法的中国农业水资源利用效率研究[J]. 中国农业资源与区划, 2017, 38(9): 106-114.
[18] Tone K, Tsutsui M. An epsilon-based measure of efficiency in DEA: A third pole of technical efficiency[J]. European Journal of Operational Research, 2010, 207(3): 1554-1563.
[19] 韩洁平, 程序, 闫晶, 等. 基于网络超效率EBM模型的城市工业生态绿色发展测度研究——以三区十群47个重点城市为例[J]. 科技管理研究, 2019, 39(5): 228- 236.
[20] 谢秋皓, 杨高升.新型城镇化背景下中国区域绿色发展效率测算[J]. 统计与决策, 2019, 35(24): 132-136.
[21] 高赢, 冯宗宪.“一带一路” 沿线国家低碳发展效率测评及影响因素探究[J]. 科技进步与对策, 2018, 35(21): 39-47.
[22] 赵明亮, 刘芳毅, 王欢, 等. FDI、 环境规制与黄河流域城市绿色全要素生产率[J]. 经济地理, 2020, 40(4): 38- 47.
[23] 吴凤平, 邱泽硕, 邵志颖, 等. 中国水权交易政策对提高水资源利用效率的地区差异性评估[J]. 经济与管理评论, 2022, 38(1): 23-32.
