Article(id=1321866349245218853, tenantId=1146029695717560320, journalId=1225396423026438145, issueId=1321866297609146910, articleNumber=null, orderNo=null, doi=null, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1748793600000, receivedDateStr=2025-06-02, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1793087096749, onlineDateStr=2026-10-27, pubDate=1779638400000, pubDateStr=2026-05-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1793087096749, onlineIssueDateStr=2026-10-27, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1793087096749, creator=13701087609, updateTime=1793087096749, updator=13701087609, issue=Issue{id=1321866297609146910, tenantId=1146029695717560320, journalId=1225396423026438145, year='2026', volume='46', issue='5', pageStart='1', pageEnd='312', issueExtLink='null', onlineDate='null', pubDate='1779638400000', pubDateStr='2026-05-25', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1793087084438, creator='13701087609', updateTime=1793094562481, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1321897662853533805, tenantId=1146029695717560320, journalId=1225396423026438145, issueId=1321866297609146910, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1321897662853533806, tenantId=1146029695717560320, journalId=1225396423026438145, issueId=1321866297609146910, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=295, endPage=304, ext={EN=ArticleExt(id=1321866349446545446, articleId=1321866349245218853, tenantId=1146029695717560320, journalId=1225396423026438145, language=EN, title=The Construction of Green Mining Cluster in Ecologically Fragile Areas Based on the Ecological-Technical-Economic Synergy Path, columnId=null, journalTitle=Mining Research and Development, columnName=null, runingTitle=null, highlight=null, articleAbstract=

Based on the ecological-technical-economic synergy path, the super-efficiency SBM model combined with the GML index method was used to accurately measure the green total factor productivity in Xinjiang, and systematically evaluate the green development level of Xinjiang mining industry cluster. The results show that the green total factor productivity of mining industry in Xinjiang is lower than the national average, and the lack of technological innovation ability is an important factor restricting the development of mining industry in the region. Through the method of location entropy, the degree of industrial agglomeration of mineral resources in Xinjiang is quantitatively analyzed, and finds that it presents the characteristics of "high agglomeration, low green and weak chain", and there is a phenomenon of "virtual fat" in the cluster. With the help of vector autoregressive model, the dynamic relationship between industrial agglomeration degree, green development level and regional economic growth is empirically analyzed. Among them, the green development level has a significant impact on the agglomeration degree of mining clusters. The synergy effect of green development level and industrial agglomeration degree is the core driving force of sustainable economic development, forming a positive feedback mechanism of "green technology-industrial agglomeration-economic efficiency". Based on this, it is proposed to build a "four-in-one" green development system with "ecological value-added, technological empowerment, network synergy and structural optimization" as the core, so as to provide practical countermeasures for the green and high-quality development of mining clusters in ecologically fragile areas.

, authors=Yuan Zhong1, Zhigang Gao2, Fengyun Gong1, Wulan Tuoya3, authorsList=Yuan Zhong, Zhigang Gao, Fengyun Gong, Wulan Tuoya, authorCompany=null, correspAuthors=null, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, 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=1321866349777895464, articleId=1321866349245218853, tenantId=1146029695717560320, journalId=1225396423026438145, language=CN, title=基于生态技术经济协同路径的生态脆弱地区绿色矿业集群建设, columnId=1321866349543014439, journalTitle=矿业研究与开发, columnName=矿业前沿交叉与综合, runingTitle=null, highlight=null, articleAbstract=

基于生态-技术-经济协同路径,运用超效率SBM模型结合GML指数方法,对新疆矿业绿色全要素生产率进行精准测算,系统评估新疆矿业产业集群的绿色发展水平。结果表明:新疆矿业绿色全要素生产率低于全国平均水平,技术创新能力不足是制约该地区矿业发展的重要因素;通过区位熵方法量化分析了新疆矿产资源产业集聚程度,发现其呈现“高集聚、低绿色、弱链条”特征,存在集群“虚胖”现象;借助向量自回归模型实证分析了产业集聚程度、绿色发展水平与区域经济增长之间的动态关系,其中绿色发展水平对矿业集群聚集程度影响显著,绿色发展水平与产业集聚程度的协同效应是经济可持续发展的核心动力,形成了“绿色技术-产业集聚-经济增效”的正反馈机制。基于此,提出需构建以“生态增值、技术赋能、网络协同、结构优化”为核心的“四位一体”绿色发展体系,为生态脆弱地区矿业集群绿色高质量发展提供切实可行的对策措施。

, authors=钟媛1, 高志刚2, 龚风云1, 乌兰托娅3, authorsList=钟媛, 高志刚, 龚风云, 乌兰托娅, authorCompany=null, correspAuthors=null, authorNote=

钟媛(1988—),女,四川内江人,硕士,讲师,主要从事资源环境审计及能源矿产业集群绿色发展研究。E-mail:

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钟媛(1988—),女,四川内江人,硕士,讲师,主要从事资源环境审计及能源矿产业集群绿色发展研究。E-mail:

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钟媛(1988—),女,四川内江人,硕士,讲师,主要从事资源环境审计及能源矿产业集群绿色发展研究。E-mail:

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基于生态技术经济协同路径的生态脆弱地区绿色矿业集群建设
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钟媛 1 , 高志刚 2 , 龚风云 1 , 乌兰托娅 3
矿业研究与开发 | 矿业前沿交叉与综合 2026,46(5): 295-304
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矿业研究与开发 |矿业前沿交叉与综合 2026 , 46 (5) : 295 -304
基于生态技术经济协同路径的生态脆弱地区绿色矿业集群建设
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钟媛(1988—),女,四川内江人,硕士,讲师,主要从事资源环境审计及能源矿产业集群绿色发展研究。E-mail:

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钟媛(1988—),女,四川内江人,硕士,讲师,主要从事资源环境审计及能源矿产业集群绿色发展研究。E-mail:

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钟媛1 , 高志刚2, 龚风云1, 乌兰托娅3
作者信息
  • 1.新疆科技学院 会计学院,新疆 库尔勒市 841000
  • 2.新疆科技学院 经济学院,新疆 库尔勒市 841000
  • 3.巴音郭楞蒙古自治州工业和信息化局产业科,新疆 库尔勒市 841000
作者简介:

钟媛(1988—),女,四川内江人,硕士,讲师,主要从事资源环境审计及能源矿产业集群绿色发展研究。E-mail:

The Construction of Green Mining Cluster in Ecologically Fragile Areas Based on the Ecological-Technical-Economic Synergy Path
Yuan Zhong1 , Zhigang Gao2, Fengyun Gong1, Wulan Tuoya3
Affiliations
  • 1.School of Accounting, Xinjiang College of Science & Technology, Korla, Xinjiang 841000, China
  • 2.School of Economics, Xinjiang College of Science & Technology, Korla, Xinjiang 841000, China
  • 3.Industrial Division, Bureau of Industry and Information Technology, Bayingolin Mongol Autonomous Prefecture, Korla, Xinjiang 841000, China
出版时间: 2026-05-25
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基于生态-技术-经济协同路径,运用超效率SBM模型结合GML指数方法,对新疆矿业绿色全要素生产率进行精准测算,系统评估新疆矿业产业集群的绿色发展水平。结果表明:新疆矿业绿色全要素生产率低于全国平均水平,技术创新能力不足是制约该地区矿业发展的重要因素;通过区位熵方法量化分析了新疆矿产资源产业集聚程度,发现其呈现“高集聚、低绿色、弱链条”特征,存在集群“虚胖”现象;借助向量自回归模型实证分析了产业集聚程度、绿色发展水平与区域经济增长之间的动态关系,其中绿色发展水平对矿业集群聚集程度影响显著,绿色发展水平与产业集聚程度的协同效应是经济可持续发展的核心动力,形成了“绿色技术-产业集聚-经济增效”的正反馈机制。基于此,提出需构建以“生态增值、技术赋能、网络协同、结构优化”为核心的“四位一体”绿色发展体系,为生态脆弱地区矿业集群绿色高质量发展提供切实可行的对策措施。

绿色矿业  /  产业集群  /  绿色全要素生产率  /  区位熵集聚度  /  向量自回归模型

Based on the ecological-technical-economic synergy path, the super-efficiency SBM model combined with the GML index method was used to accurately measure the green total factor productivity in Xinjiang, and systematically evaluate the green development level of Xinjiang mining industry cluster. The results show that the green total factor productivity of mining industry in Xinjiang is lower than the national average, and the lack of technological innovation ability is an important factor restricting the development of mining industry in the region. Through the method of location entropy, the degree of industrial agglomeration of mineral resources in Xinjiang is quantitatively analyzed, and finds that it presents the characteristics of "high agglomeration, low green and weak chain", and there is a phenomenon of "virtual fat" in the cluster. With the help of vector autoregressive model, the dynamic relationship between industrial agglomeration degree, green development level and regional economic growth is empirically analyzed. Among them, the green development level has a significant impact on the agglomeration degree of mining clusters. The synergy effect of green development level and industrial agglomeration degree is the core driving force of sustainable economic development, forming a positive feedback mechanism of "green technology-industrial agglomeration-economic efficiency". Based on this, it is proposed to build a "four-in-one" green development system with "ecological value-added, technological empowerment, network synergy and structural optimization" as the core, so as to provide practical countermeasures for the green and high-quality development of mining clusters in ecologically fragile areas.

Green mining  /  Industrial cluster  /  Green total factor productivity  /  Location entropy agglomeration degree  /  Vector autoregression model
钟媛, 高志刚, 龚风云, 乌兰托娅. 基于生态技术经济协同路径的生态脆弱地区绿色矿业集群建设. 矿业研究与开发, 2026 , 46 (5) : 295 -304 .
Yuan Zhong, Zhigang Gao, Fengyun Gong, Wulan Tuoya. The Construction of Green Mining Cluster in Ecologically Fragile Areas Based on the Ecological-Technical-Economic Synergy Path[J]. Mining Research and Development, 2026 , 46 (5) : 295 -304 .
  • 国家自然科学基金项目(72064035)
  • 新疆维吾尔自治区高校基本科研业务费科研项目(XJEDU2026P138)
  • 产教融合与新商科发展研究中心年度招标课题(2025-KYJD02)
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2026年第46卷第5期
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  • 接收时间:2025-06-02
  • 首发时间:2026-10-27
  • 出版时间:2026-05-25
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  • 收稿日期:2025-06-02
基金
国家自然科学基金项目(72064035)
新疆维吾尔自治区高校基本科研业务费科研项目(XJEDU2026P138)
产教融合与新商科发展研究中心年度招标课题(2025-KYJD02)
作者信息
    1.新疆科技学院 会计学院,新疆 库尔勒市 841000
    2.新疆科技学院 经济学院,新疆 库尔勒市 841000
    3.巴音郭楞蒙古自治州工业和信息化局产业科,新疆 库尔勒市 841000
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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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