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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., authors=MIAO Junyu, ZHANG Chunying, authorsList=MIAO Junyu, ZHANG Chunying, authorCompany=Center for Industrial and Business Organization, Dongbei University of Finance and Economics, Dalian 116025, China, correspAuthors=null, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=TKWDVoEipyeNvRzkV7W/Yw==, pdfFileSize=652722, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1242140092588958507, articleId=1242140091418747684, tenantId=1146029695717560320, journalId=1146031591421210625, language=CN, title=黄河流域九省(区)工业水资源效率时空分异及影响因素, columnId=1242140086171673364, journalTitle=科技导报, columnName=专题:推动绿色发展 建设美丽中国, runingTitle=null, highlight=null, articleAbstract=基于非期望产出的超效率EBM模型、ML指数和Tobit模型分析了黄河流域九省(区)2010—2019年工业水资源效率时空分异及影响因素。结果表明:黄河流域九省(区)工业水资源效率整体均值为0.77,未达到有效水平,但呈现出波动上升态势,各省(区)间差异明显,山东效率最高,宁夏最低。ML指数提高的主驱动力源自技术进步,部分省(区)的规模效率阻碍了技术效率对ML指数的正向调节。技术水平和工业化程度对工业水资源效率攀升有促进作用;水资源禀赋、工业用水强度和政府管制强度的负面效应显著。, authors=苗峻瑜, 张春英, authorsList=苗峻瑜, 张春英, authorCompany=东北财经大学产业组织与企业组织研究中心, 大连 116025, correspAuthors=null, authorNote=苗峻瑜,博士研究生,研究方向为环境经济与产业发展,电子信箱:miaojunyu-0909@163.com, correspAuthorsNote=张春英(通信作者),教授,研究方向为产业经济学,电子信箱:399152429@qq.com, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=X8gl+1QiqwGtMjc1nMJBPw==, pdfFileSize=652722, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null)}, authors=null, keywords=[Keyword(id=1242140092190499622, 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黄河流域九省(区)工业水资源效率时空分异及影响因素
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科技导报 | 专题:推动绿色发展 建设美丽中国 2022,40(19): 71-80
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科技导报 | 专题:推动绿色发展 建设美丽中国 2022, 40(19): 71-80
黄河流域九省(区)工业水资源效率时空分异及影响因素
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苗峻瑜, 张春英
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    东北财经大学产业组织与企业组织研究中心, 大连 116025

通讯作者:

张春英(通信作者),教授,研究方向为产业经济学,电子信箱:399152429@qq.com
Temporal and spatial differentiation and influencing factors of industrial water resources efficiency in nine provinces (regions) of the Yellow River Basin
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出版时间: 2022-10-13 doi: 10.3981/j.issn.1000-7857.2022.19.008
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基于非期望产出的超效率EBM模型、ML指数和Tobit模型分析了黄河流域九省(区)2010—2019年工业水资源效率时空分异及影响因素。结果表明:黄河流域九省(区)工业水资源效率整体均值为0.77,未达到有效水平,但呈现出波动上升态势,各省(区)间差异明显,山东效率最高,宁夏最低。ML指数提高的主驱动力源自技术进步,部分省(区)的规模效率阻碍了技术效率对ML指数的正向调节。技术水平和工业化程度对工业水资源效率攀升有促进作用;水资源禀赋、工业用水强度和政府管制强度的负面效应显著。
工业水资源  /  用水效率  /  时空分异  /  黄河流域
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.
industrial water resources  /  water use efficiency  /  spatiotemporal differentiation  /  Yellow River Basin
苗峻瑜, 张春英. 黄河流域九省(区)工业水资源效率时空分异及影响因素. 科技导报, 2022 , 40 (19) : 71 -80 . DOI: 10.3981/j.issn.1000-7857.2022.19.008
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
2022年第40卷第19期
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doi: 10.3981/j.issn.1000-7857.2022.19.008
  • 接收时间:2022-04-12
  • 首发时间:2022-11-04
  • 出版时间:2022-10-13
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  • 收稿日期:2022-04-12
  • 修回日期:2022-08-30
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张春英(通信作者),教授,研究方向为产业经济学,电子信箱:399152429@qq.com
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2种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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