Article(id=1322164702587768917, tenantId=1146029695717560320, journalId=1225396423026438145, issueId=1322164546295410919, 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=1732636800000, receivedDateStr=2024-11-27, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1793158229728, onlineDateStr=2026-10-28, pubDate=1764000000000, pubDateStr=2025-11-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1793158229728, onlineIssueDateStr=2026-10-28, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1793158229728, creator=13701087609, updateTime=1793158229728, updator=13701087609, issue=Issue{id=1322164546295410919, tenantId=1146029695717560320, journalId=1225396423026438145, year='2025', volume='45', issue='11', pageStart='1', pageEnd='284', issueExtLink='null', onlineDate='null', pubDate='1764000000000', pubDateStr='2025-11-25', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1793158192465, creator='13701087609', updateTime=1793158905697, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1322167537857573862, tenantId=1146029695717560320, journalId=1225396423026438145, issueId=1322164546295410919, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1322167537861768167, tenantId=1146029695717560320, journalId=1225396423026438145, issueId=1322164546295410919, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=198, endPage=208, ext={EN=ArticleExt(id=1322164702831038550, articleId=1322164702587768917, tenantId=1146029695717560320, journalId=1225396423026438145, language=EN, title=Model of Mine Environmental Treatment Based on Evolutionary Game Theory, columnId=null, journalTitle=Mining Research and Development, columnName=null, runingTitle=null, highlight=null, articleAbstract=

The project of mine environmental treatment is an important link to promote green development, and it is very important to study how to game and coordinate the relevant stakeholders to promote the green development of mines. First of all, based on the perspective of stakeholders of mine environmental treatment, with the help of evolutionary game tools of limited rationality, a tripartite evolutionary game model of mine environmental treatment was constructed among local governments, mining enterprises and local residents. Secondly, the actual operation data of a mine company in Xiangxi, Hunan Province were introduced, and the long-term dynamic game process of stakeholders was modeled and analyzed in combination with system dynamics, so as to study the influencing factors of the behavior strategy of the main body of mining environmental treatment. The research results show that the five influencing factors of the intensity of government subsidies to enterprises, the intensity of government punishment on enterprises, enterprise public relations costs, additional cost-benefit differences for enterprises, and residents' supervision will all have an impact on the strategic choices of stakeholders. From the perspective of stakeholders, targeted measures and suggestions for mine environmental treatment are formulated according to five influencing factors, in order to provide reference for decision makers' mine environmental treatment strategies. According to the research results, it is expected to put forward the optimal operation mode and sustainable development path of mine environmental treatment, and promote the sustainable development of mine in economy, society and environment.

, authors=Hongbing LI1, Xiaoxiao LIU2, authorsList=Hongbing LI, Xiaoxiao LIU, authorCompany=null, correspAuthors=Xiaoxiao LIU, 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=1322164708350742665, articleId=1322164702587768917, tenantId=1146029695717560320, journalId=1225396423026438145, language=CN, title=基于演化博弈的矿山恢复治理模式研究, columnId=1226462295417598973, journalTitle=矿业研究与开发, columnName=矿山安全与环保, runingTitle=null, highlight=null, articleAbstract=

矿山的恢复治理工程是推动绿色发展的重要环节,研究相关利益者如何博弈和协调以推进矿山绿色发展十分重要。首先,从矿山恢复治理利益相关者视角,借助有限理性的演化博弈工具,构建矿山恢复治理地方政府、矿山企业、当地居民三方演化博弈模型。其次,引入湖南湘西某矿山公司实际运营数据,结合系统动力学对利益相关者长期动态博弈过程进行建模和分析,研究矿山恢复治理主体行为策略的影响因素。研究表明,政府对企业的补贴力度、政府对企业的惩罚力度、企业公关费、企业额外成本收益差和居民监督力度这5个影响因素均会对利益相关者的策略选择产生影响。从利益相关者的角度分别根据5个影响因素制定了矿山恢复治理的定向措施建议,以期为各决策者的矿山恢复治理策略提供参考。根据研究结果,有望提出矿山恢复治理最优的运行模式和可持续发展路径,促进矿山在经济、社会、环境上的可持续发展。

, authors=李红兵1, 刘晓晓2, authorsList=李红兵, 刘晓晓, authorCompany=null, correspAuthors=刘晓晓, authorNote=

李红兵(1970—),男,江苏新沂人,博士,副教授,主要从事项目管理、建设项目投融资、绿色建造与管理等方面的研究工作。E-mail:

, correspAuthorsNote=
刘晓晓(2000—),女,湖南长沙人,博士研究生,主要从事绿色建造与管理等方面的研究工作。E-mail:
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李红兵(1970—),男,江苏新沂人,博士,副教授,主要从事项目管理、建设项目投融资、绿色建造与管理等方面的研究工作。E-mail:

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李红兵(1970—),男,江苏新沂人,博士,副教授,主要从事项目管理、建设项目投融资、绿色建造与管理等方面的研究工作。E-mail:

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Beijing: University of Science and Technology Beijing, 2020., articleTitle=Research on game and strategy of environmental remediation evolution in Ion-Type rare earth mines, refAbstract=null)], funds=[Fund(id=1322164712696041658, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322164702587768917, awardId=SKJC-2022-PTDX-021, language=CN, fundingSource=三亚崖州湾科技城配套资助定向组织项目(SKJC-2022-PTDX-021), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1322164708585623690, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322164702587768917, xref=1., ext=[AuthorCompanyExt(id=1322164708598206603, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322164702587768917, companyId=1322164708585623690, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1.School of Civil Engineering and Architecture, Wuhan University of Technology, Wuhan, Hubei 430070, China), 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figureFileSmall=0l320lAmPqcdmyqqZUXmVg==, figureFileBig=Pv07R+APoZhi6a//GQJ07g==, tableContent=null), ArticleFig(id=1322164711500665006, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322164702587768917, language=EN, label=Fig.7, caption=The impact of the enterprises' additional cost-benefit difference on the choices of tripartite strategic entities, figureFileSmall=9ZqAJiKs8fgmzfjGGRWVhw==, figureFileBig=9J+zzyLVbBZgY8hqTw3cBw==, tableContent=null), ArticleFig(id=1322164711622299823, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322164702587768917, language=CN, label=图7, caption=企业额外成本收益差对三方策略主体选择的影响, figureFileSmall=9ZqAJiKs8fgmzfjGGRWVhw==, figureFileBig=9J+zzyLVbBZgY8hqTw3cBw==, tableContent=null), ArticleFig(id=1322164711706185904, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322164702587768917, language=EN, label=Fig.8, caption=The impact of the intensity of residents' supervision on the choices of tripartite strategic entities, figureFileSmall=NA5PEUmCTQNGXyhAwhrJcQ==, figureFileBig=F+BVJ2GSfbpU8R7+iC155w==, tableContent=null), ArticleFig(id=1322164711785877681, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322164702587768917, language=CN, label=图8, caption=居民监督力度对三方策略主体选择的影响, figureFileSmall=NA5PEUmCTQNGXyhAwhrJcQ==, figureFileBig=F+BVJ2GSfbpU8R7+iC155w==, tableContent=null), ArticleFig(id=1322164711869763762, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322164702587768917, language=EN, label=Table 1, caption=

Parameter settings for the tripartite evolutionary game

, figureFileSmall=null, figureFileBig=null, tableContent=
博弈方需要的参数数据变量名称含义
地方政府C1政府监管成本地方政府高强度监管时需要承担的监管成本。
L1政府收益矿山企业积极参与时政府获得的综合效益。
S1政府公信力损失值地方政府低强度监管,矿山企业消极治理引发一系列环境问题,对地方政府造成公信力的损失。
λ监管下降程度政府低强度监管时,政府监管下降程度。
矿山企业L2企业基本收益矿山企业每年的开采、销售收益。
L3企业附加收益矿山企业积极治理所获得的未来收益。
C2企业消极治理成本矿山企业进行消极治理时所需成本。
C3企业积极治理成本矿山企业进行积极治理开发时所需额外成本。
S2企业公关费用矿山企业消极治理时,企业为消除负面影响所付出的公关费用。
aM1政府给予企业的补贴矿山企业得到的积极治理补贴,a为政府对企业的补贴力度。
M2企业对居民的补偿当地居民发现矿山企业消极行为并举报,地方政府强制要求矿山企业对当地居民进行补偿。
ck政府对企业的惩罚矿山企业消极治理的罚款,c为惩罚力度。
当地居民C4居民监督成本当地居民参与监督需要消耗的监督成本。
P居民监督力度矿山企业消极行为被当地居民发现的概率。
bM3政府给予居民的奖励当地居民得到的监督奖励,b为政府对居民的奖励力度。
S3居民发展机会损失矿山企业消极治理时,当地居民发展机会的损失。
L4居民收益矿山企业积极治理所带来的区域效益的提升。
), ArticleFig(id=1322164711987204275, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322164702587768917, language=CN, label=表1, caption=

三方演化博弈参数设置

, figureFileSmall=null, figureFileBig=null, tableContent=
博弈方需要的参数数据变量名称含义
地方政府C1政府监管成本地方政府高强度监管时需要承担的监管成本。
L1政府收益矿山企业积极参与时政府获得的综合效益。
S1政府公信力损失值地方政府低强度监管,矿山企业消极治理引发一系列环境问题,对地方政府造成公信力的损失。
λ监管下降程度政府低强度监管时,政府监管下降程度。
矿山企业L2企业基本收益矿山企业每年的开采、销售收益。
L3企业附加收益矿山企业积极治理所获得的未来收益。
C2企业消极治理成本矿山企业进行消极治理时所需成本。
C3企业积极治理成本矿山企业进行积极治理开发时所需额外成本。
S2企业公关费用矿山企业消极治理时,企业为消除负面影响所付出的公关费用。
aM1政府给予企业的补贴矿山企业得到的积极治理补贴,a为政府对企业的补贴力度。
M2企业对居民的补偿当地居民发现矿山企业消极行为并举报,地方政府强制要求矿山企业对当地居民进行补偿。
ck政府对企业的惩罚矿山企业消极治理的罚款,c为惩罚力度。
当地居民C4居民监督成本当地居民参与监督需要消耗的监督成本。
P居民监督力度矿山企业消极行为被当地居民发现的概率。
bM3政府给予居民的奖励当地居民得到的监督奖励,b为政府对居民的奖励力度。
S3居民发展机会损失矿山企业消极治理时,当地居民发展机会的损失。
L4居民收益矿山企业积极治理所带来的区域效益的提升。
), ArticleFig(id=1322164712058507444, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322164702587768917, language=EN, label=Table 2, caption=

Income matrix of local governments, mining enterprises and local residents

, figureFileSmall=null, figureFileBig=null, tableContent=
当地政府矿山企业当地居民
参与监督z不参与监督1-z
L1-C1-aM1-bM3L1-C1-aM1
积极治理yL2+L3-C2-C3+aM1L2+L3-C2-C3+aM1
高强度监管xL4+bM3-C4L4
-C1-bM3+ck-C1+ck
消极治理1-yL2-C2-ck-S2-PM2L2-C2-ck-S2
bM3-C4-S3+PM2-S3
L1-λC1-λaM1-λbM3L1-λC1-λaM1
积极治理yL2+L3-C2-C3+λaM1L2+L3-C2-C3+λaM1
低强度监管1-xλbM3-C4+L4L4
-λC1+λck-λbM3-S1-λC1+λck-S1
消极治理1-yL2-C2-S2-PM2-λckL2-C2-λck-S2
λbM3-C4-S3+PM2-S3
), ArticleFig(id=1322164712209502389, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322164702587768917, language=CN, label=表2, caption=

地方政府、矿山企业、当地居民收益矩阵

, figureFileSmall=null, figureFileBig=null, tableContent=
当地政府矿山企业当地居民
参与监督z不参与监督1-z
L1-C1-aM1-bM3L1-C1-aM1
积极治理yL2+L3-C2-C3+aM1L2+L3-C2-C3+aM1
高强度监管xL4+bM3-C4L4
-C1-bM3+ck-C1+ck
消极治理1-yL2-C2-ck-S2-PM2L2-C2-ck-S2
bM3-C4-S3+PM2-S3
L1-λC1-λaM1-λbM3L1-λC1-λaM1
积极治理yL2+L3-C2-C3+λaM1L2+L3-C2-C3+λaM1
低强度监管1-xλbM3-C4+L4L4
-λC1+λck-λbM3-S1-λC1+λck-S1
消极治理1-yL2-C2-S2-PM2-λckL2-C2-λck-S2
λbM3-C4-S3+PM2-S3
), ArticleFig(id=1322164712301777078, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322164702587768917, language=EN, label=Table 3, caption=

Determination of stability of equilibrium points

, figureFileSmall=null, figureFileBig=null, tableContent=
均衡点特征值及符号状态
λ1=(ck-C1)(1-λ)(±)
A1(0,0,0)λ2=L3-C3+λaM1+λck+S2(±)未知
λ3=λbM3+PM2-C4(±)
λ1=(ck-C1-bM3)(1-λ)+S1(±)
A2(0,0,1)λ2=L3-C3+λaM1+λck+S2+PM2(±)未知
λ3=-λbM3+C4-PM2(±)
λ1=(λ-1)(aM1+C1)(-)
A3(0,1,0)λ2=C3-L3-λaM1-λck-S2(±)鞍点/稳定点
λ3=λbM3-C4(±)
λ1=(λ-1)(ck-C1)-S1(±)
A4(1,0,0)λ2=aM1+L3-C3+ck+S2(±)未知
λ3=bM3-C4+PM2(±)
λ1=(λ-1)(ck-C1-bM3)-S1(±)
A5(1,0,1)λ2=aM1+L3-C3+ck+S2+PM2(±)未知
λ3=-bM3+C4-PM2(±)
λ1=(λ-1)(aM1+bM3+C1)(-)
A6(0,1,1)λ2=-L3+C3-λaM1-λck-S2-PM2(±)鞍点/稳定点
λ3=C4-λbM3(±)
λ1=(1-λ)(aM1+C1)(+)
A7(1,1,0)λ2=-aM1-L3+C3-ck-S2(±)鞍点/不稳定点
λ3=bM3-C4(±)
λ1=(1-λ)(aM1+bM3+C1)(+)
A8(1,1,1)λ2=-aM1-L3+C3-ck-S2-PM2(±)鞍点/不稳定点
λ3=C4-bM3(±)
), ArticleFig(id=1322164712381468855, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322164702587768917, language=CN, label=表3, caption=

均衡点稳定性判定

, figureFileSmall=null, figureFileBig=null, tableContent=
均衡点特征值及符号状态
λ1=(ck-C1)(1-λ)(±)
A1(0,0,0)λ2=L3-C3+λaM1+λck+S2(±)未知
λ3=λbM3+PM2-C4(±)
λ1=(ck-C1-bM3)(1-λ)+S1(±)
A2(0,0,1)λ2=L3-C3+λaM1+λck+S2+PM2(±)未知
λ3=-λbM3+C4-PM2(±)
λ1=(λ-1)(aM1+C1)(-)
A3(0,1,0)λ2=C3-L3-λaM1-λck-S2(±)鞍点/稳定点
λ3=λbM3-C4(±)
λ1=(λ-1)(ck-C1)-S1(±)
A4(1,0,0)λ2=aM1+L3-C3+ck+S2(±)未知
λ3=bM3-C4+PM2(±)
λ1=(λ-1)(ck-C1-bM3)-S1(±)
A5(1,0,1)λ2=aM1+L3-C3+ck+S2+PM2(±)未知
λ3=-bM3+C4-PM2(±)
λ1=(λ-1)(aM1+bM3+C1)(-)
A6(0,1,1)λ2=-L3+C3-λaM1-λck-S2-PM2(±)鞍点/稳定点
λ3=C4-λbM3(±)
λ1=(1-λ)(aM1+C1)(+)
A7(1,1,0)λ2=-aM1-L3+C3-ck-S2(±)鞍点/不稳定点
λ3=bM3-C4(±)
λ1=(1-λ)(aM1+bM3+C1)(+)
A8(1,1,1)λ2=-aM1-L3+C3-ck-S2-PM2(±)鞍点/不稳定点
λ3=C4-bM3(±)
), ArticleFig(id=1322164712490520760, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322164702587768917, language=EN, label=Table 4, caption=

Value assignment of game parameters for subjects in mine environmental treatment

, figureFileSmall=null, figureFileBig=null, tableContent=
参数名称数值参数名称数值
C1政府监管成本65万元M2企业对居民的补偿80万元
L1政府收益460万元k政府对企业的惩罚140万元
S1政府公信力损失值30万元c政府对企业的惩罚力度0.5
L2企业基本收益1 990万元C4居民监督成本25万元
L3企业附加收益320万元P居民监督力度0.5
C2矿山消极治理成本1 320万元M3政府给予居民的奖励100万元
C3企业积极治理成本460万元b政府对居民的奖励力度0.5
S2企业公关费用55万元S3居民发展机会损失200万元
M1政府给予企业的补贴120万元L4居民收益135万元
a政府对企业的补贴力度0.5λ政府监管下降程度0.3
x地方政府行为策略概率0.5y矿山企业行为策略概率0.4
z当地居民行为策略概率0.4
), ArticleFig(id=1322164712566018233, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322164702587768917, language=CN, label=表4, caption=

矿山恢复治理主体博弈参数赋值

, figureFileSmall=null, figureFileBig=null, tableContent=
参数名称数值参数名称数值
C1政府监管成本65万元M2企业对居民的补偿80万元
L1政府收益460万元k政府对企业的惩罚140万元
S1政府公信力损失值30万元c政府对企业的惩罚力度0.5
L2企业基本收益1 990万元C4居民监督成本25万元
L3企业附加收益320万元P居民监督力度0.5
C2矿山消极治理成本1 320万元M3政府给予居民的奖励100万元
C3企业积极治理成本460万元b政府对居民的奖励力度0.5
S2企业公关费用55万元S3居民发展机会损失200万元
M1政府给予企业的补贴120万元L4居民收益135万元
a政府对企业的补贴力度0.5λ政府监管下降程度0.3
x地方政府行为策略概率0.5y矿山企业行为策略概率0.4
z当地居民行为策略概率0.4
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基于演化博弈的矿山恢复治理模式研究
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李红兵 1 , 刘晓晓 2
矿业研究与开发 | 矿山安全与环保 2025,45(11): 198-208
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矿业研究与开发 |矿山安全与环保 2025 , 45 (11) : 198 -208
基于演化博弈的矿山恢复治理模式研究
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李红兵(1970—),男,江苏新沂人,博士,副教授,主要从事项目管理、建设项目投融资、绿色建造与管理等方面的研究工作。E-mail:

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李红兵(1970—),男,江苏新沂人,博士,副教授,主要从事项目管理、建设项目投融资、绿色建造与管理等方面的研究工作。E-mail:

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李红兵1 , 刘晓晓2
作者信息
  • 1.武汉理工大学 土木工程与建筑学院,湖北 武汉 430070
  • 2.中南大学 土木工程学院,湖南 长沙 410083
通讯作者:
刘晓晓(2000—),女,湖南长沙人,博士研究生,主要从事绿色建造与管理等方面的研究工作。E-mail:
作者简介:

李红兵(1970—),男,江苏新沂人,博士,副教授,主要从事项目管理、建设项目投融资、绿色建造与管理等方面的研究工作。E-mail:

Model of Mine Environmental Treatment Based on Evolutionary Game Theory
Hongbing LI1 , Xiaoxiao LIU2
Affiliations
  • 1.School of Civil Engineering and Architecture, Wuhan University of Technology, Wuhan, Hubei 430070, China
  • 2.School of Civil Engineering, Central South University, Changsha, Hunan 410083, China
出版时间: 2025-11-25
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矿山的恢复治理工程是推动绿色发展的重要环节,研究相关利益者如何博弈和协调以推进矿山绿色发展十分重要。首先,从矿山恢复治理利益相关者视角,借助有限理性的演化博弈工具,构建矿山恢复治理地方政府、矿山企业、当地居民三方演化博弈模型。其次,引入湖南湘西某矿山公司实际运营数据,结合系统动力学对利益相关者长期动态博弈过程进行建模和分析,研究矿山恢复治理主体行为策略的影响因素。研究表明,政府对企业的补贴力度、政府对企业的惩罚力度、企业公关费、企业额外成本收益差和居民监督力度这5个影响因素均会对利益相关者的策略选择产生影响。从利益相关者的角度分别根据5个影响因素制定了矿山恢复治理的定向措施建议,以期为各决策者的矿山恢复治理策略提供参考。根据研究结果,有望提出矿山恢复治理最优的运行模式和可持续发展路径,促进矿山在经济、社会、环境上的可持续发展。

矿山恢复治理  /  利益相关者  /  演化博弈  /  系统动力学

The project of mine environmental treatment is an important link to promote green development, and it is very important to study how to game and coordinate the relevant stakeholders to promote the green development of mines. First of all, based on the perspective of stakeholders of mine environmental treatment, with the help of evolutionary game tools of limited rationality, a tripartite evolutionary game model of mine environmental treatment was constructed among local governments, mining enterprises and local residents. Secondly, the actual operation data of a mine company in Xiangxi, Hunan Province were introduced, and the long-term dynamic game process of stakeholders was modeled and analyzed in combination with system dynamics, so as to study the influencing factors of the behavior strategy of the main body of mining environmental treatment. The research results show that the five influencing factors of the intensity of government subsidies to enterprises, the intensity of government punishment on enterprises, enterprise public relations costs, additional cost-benefit differences for enterprises, and residents' supervision will all have an impact on the strategic choices of stakeholders. From the perspective of stakeholders, targeted measures and suggestions for mine environmental treatment are formulated according to five influencing factors, in order to provide reference for decision makers' mine environmental treatment strategies. According to the research results, it is expected to put forward the optimal operation mode and sustainable development path of mine environmental treatment, and promote the sustainable development of mine in economy, society and environment.

Mine environmental treatment  /  Stakeholder  /  Evolutionary game theory  /  System dynamics
李红兵, 刘晓晓. 基于演化博弈的矿山恢复治理模式研究. 矿业研究与开发, 2025 , 45 (11) : 198 -208 .
Hongbing LI, Xiaoxiao LIU. Model of Mine Environmental Treatment Based on Evolutionary Game Theory[J]. Mining Research and Development, 2025 , 45 (11) : 198 -208 .
党的二十大报告中提出,推动绿色发展,促进人与自然和谐共生。这要求我国必须牢固树立并践行绿水青山就是金山银山的“两山”理论,结合不同产业的资源禀赋与自然环境条件,走一条绿色生态环保的文明建设之路[1]。绿色发展理念秉持着绿色、低碳、循环的原则,是当前我国打破资源环境瓶颈、实现可持续发展的关键环节[2-3]。矿业作为我国经济发展的支柱产业,在促进区域经济协调发展的同时,也增强了国家的经济实力。但是,矿产资源的大规模开采对生态环境造成了严重破坏,因此对矿山的恢复治理成为我国生态文明建设的重要环节。我国矿山恢复治理存在压力大、资金不足、缺乏系统性和稳定性以及利益相关者难以协调一致等问题,且面临“旧账”未还、又欠“新账”的困境[4]。在国家政策的指引和矿山可持续发展呼声的驱动下,我国亟需找出一条最优的矿山恢复治理路径。
目前关于矿山恢复的研究文献主要集中在恢复战略制定,恢复效益评估,恢复模式探讨以及影响因素分析等方面[5-8]。通过对文献的梳理发现,当前矿山恢复治理的研究侧重于对矿山恢复后的评价和衡量,缺乏对矿山恢复治理前的科学论证,对矿山恢复治理过程也尚未形成完整的恢复治理路径。矿山恢复治理是一项复杂的系统工程,治理过程需要耗费大量的资金且涉及多方利益主体,同时由于一些历史遗留的治理问题,使得矿山恢复的形势更为严峻。为推动矿山绿色发展,一些学者从利益相关者角度对绿色矿山进行了研究。刘亦晴等[9]为探索矿业生态文明建设各利益协调机制,构建了地方政府、矿山企业及矿区公众三方博弈模型。赖小君等[10]鉴于当前存在的煤矿区土地复垦工作执行力差、部门监管力度不足等问题,从演化博弈的视角构建了以地方政府、煤炭企业以及矿区居民为相关利益主体的煤矿区土地复垦三方博弈模型。史玉芳等[11]为研究矿山地质环境治理PPP项目运营过程中各主体利益冲突的形成机理,构建了地方政府、企业、公众三方的演化博弈模型。Mahdevari S等[12]提出了进化博弈论(GT)模型,研究在河道砂石矿实施绿色采矿原则时,矿山管理层与政府之间的动态关系。关钊[13]构建了公众参与情形下政府与矿山企业废弃地生态修复行为博弈模型,讨论公众参与对地方政府和矿山企业的决策态度。
综上所述,利益主体之间的博弈关系逐渐成为矿山绿色发展研究的重点。运用演化博弈理论模型,可以对各个参与主体进行长期的博弈行为分析,但该理论方法不能直观反映出其动态的演变进程。鉴于此,引入系统动力学方法,将演化博弈和系统动力学结合起来,不仅可以对博弈主体的博弈重点进行更为全面的分析,还能对其动态演化轨迹进行更深入的剖析,从而找出相关参与主体策略决策的决定性因素。本文通过矿山恢复治理利益相关者视角,借助有限理性的演化博弈工具,构建矿山恢复治理地方政府、矿山企业、当地居民三方演化博弈模型,并结合系统动力学对利益相关者长期动态博弈过程进行建模和分析,针对分析结果提出矿山恢复治理最优的运行模式和可持续发展路径,为各决策者的矿山恢复治理策略提供参考。
地方政府、矿山企业和当地居民三方博弈存在信息不对称,因此采取的行动以及行动导致的结果存在差异,三方关系如图1所示。
假设1:选择当地政府、矿山企业和当地居民三方为博弈主体。三方均是有限理性的参与主体,博弈过程中各博弈对象的博弈行为随时间的推移逐步趋于最优策略。
假设2:当地政府的策略选择为“高强度监管”和“低强度监管”,当地居民的策略选择为“参与监督”和“不参与监督”,矿山企业的策略选择为“积极治理”和“消极治理”。积极治理指矿山企业根据矿山实际情况制定治理规划方案,并按照方案在期限内高质量完成矿山恢复治理项目。消极治理指矿山企业未按照批准的矿山地质环境保护与土地复垦方案治理,或者在矿山被批准关闭、闭坑前未完成治理恢复工程。
假设3:在矿山恢复治理工程中,地方政府高强度监管时的监管成本为C1,地方政府低强度监管时,政府监管的下降程度为λ。矿山企业积极参与矿山恢复治理项目时,政府所获得的综合环境、经济和社会效益为L1。当政府低强度监管、矿山企业消极治理引发不好的影响时,地方政府造成公信力的损失值为S1。
假设4:在矿山恢复治理项目中,矿山企业在经营中所获得的基本收益为L2,矿山企业积极治理所获得的额外收益为L3。矿山企业消极治理时所需成本为C2,积极治理时所需成本为C3。矿山企业消极治理时,企业为消除负面影响所付出的公关费用为S2;政府对企业的罚款为ck,其中c为政府对企业的惩罚力度;当地居民发现企业消极行为时举报,政府强制要求企业对当地居民进行的补偿为M2。矿山企业积极治理时,政府给予企业的补贴为aM1,其中a为政府对企业的补贴力度。
假设5:在矿山恢复治理过程中,当地居民参与监督需要消耗的监督成本为C4,矿山企业消极行为被当地居民发现的概率为P(0≤P≤1),当地居民得到的政府的监督奖励为bM3,其中b为政府对居民的奖励力度。矿山企业消极治理时,当地居民就业等发展机会的损失值为S3,矿山企业积极治理所带来的区域效益的提升值为L4。
假设6:在演化博弈过程中,政府部门高强度监管的概率为x(0≤x≤1),则低强度监管的概率为1-x;矿山企业积极治理的概率为y(0≤y≤1),则消极治理的概率为1-y;当地居民参与监督的概率为z(0≤z≤1),则不参与监督的概率为1-z。
基于以上假设和博弈三方的行为关系,设定相关参数及其含义,具体见表1。
由以上假设和参数依次得到地方政府、矿山企业及当地居民的收益矩阵,见表2。
根据表2可求出政府高强度监管的期望收益Ux1、低强度监管的期望收益Ux2和平均收益分别为:
地方政府的复制动态方程为:
当时,∀x∈[0,1]使F(x)=0恒成立,即所有的x为稳定状态,地方政府可以选择高强度监管或低强度监管,演化策略都不会随时间变化。
当时,F′(0)>0,F′(1)<0,x=1为稳定点。
当时,F′(0)<0,F′(1)>0,x=0为稳定点。
同理,矿山企业复制动态方程为:
当时,∀y∈[0,1]使F(y)=0恒成立,即所有的y为稳定状态,矿山企业可以选择积极治理或消极治理,其演化策略的选择比例都不会随时间变化。
当时,F′(0)<0,F′(1)>0,y=0为稳定点。
当时,F′(0)>0,F′(1)<0,y=1为稳定点。
当地居民复制动态方程为:
当时,∀z ∈[0,1]使F(z)=0恒成立,即所有的z为稳定状态,当地居民可以选择参与监督或不参与监督,其演化策略的选择比例都不会随时间变化。
当时,F′(0)< 0,F′(1)>0,z=0为稳定点。
当时,F′(0)> 0,F′(1)<0,z=1为稳定点。
令F(x)=0,F(y)=0,F(z)=0,可得到9个博弈三方达到稳定状态的均衡点:A1(0,0,0)、A2(0,0,1)、A3(0,1,0)、A4(1,0,0)、A5(1,0,1)、A6(0,1,1)、A7(1,1,0)、A8(1,1,1)、A9(x∗,y∗,z∗)。根据Ritzberger关于复制动态方程的均衡点是否为演化稳定策略的结论,只有当均衡点同时满足严格纳什均衡和纯策略纳什均衡时,才能达到渐近稳定状态。但均衡点A9为混合策略,不可能达到演化稳定状态,因此本文只需要对8个纯策略均衡点进行稳定性分析,演化系统均衡点的稳定性可由雅克比矩阵的局部稳定性分析中得到[14],对于复制动态方程求其雅克比矩阵J,可表示为:
根据李雅普诺夫间接法[15],雅可比矩阵的特征值可作为判断演化稳定性的依据。在某点处,若J的特征值均小于0,则该均衡点有渐进稳定性,是演化稳定策略;若J的特征值有1个或2个大于0,则该均衡点为鞍点;若J的特征值均大于0,则是不稳定点[16]。均衡点稳定性判断如表3所示。由表3可知,A1、A2、A3、A4、A5、A6为潜在演化稳定策略。
在以上矿山恢复治理主体三方的演化博弈模型基础上,为使治理主体行为策略的演化过程更加直观和可视化,采用Venish PLE软件建立面向矿山恢复治理主体的演化博弈系统动力学模型,如图2所示。
依据《关于进一步加强新建和生产矿山生态保护修复工作的通知》《湖南省国土空间生态保护修复项目预算编制指导意见(暂行)》《湖南省地质环境保护条例》等相关文件,以湖南湘西某矿山公司的矿山生态修复项目为例,利用收集到的矿山实际运营数据,结合经验值确定仿真数据,各参数赋值见表4。
基于演化博弈系统动力学仿真模型,依据赋值数据绘制地方政府、矿山企业、当地居民行为策略演化路径图,如图3所示。
从图3可以看出,当前状态下,地方政府相信矿山企业能够按照方案在期限内完成矿山恢复治理项目而选择低强度监管,而矿山企业作为逐利的理性主体,在积极治理所要承担的高成本压力下,有逐渐放弃积极治理策略的趋势,直至选择消极治理。此时,当地居民由于矿山企业的消极治理而使他们所处的环境受到了损害,为了维护他们自身的利益,会主动参与监督向地方政府举报矿山企业的违规行为。这种平衡状态不利于当地经济和环境的可持续发展,同时也不利于地方政府公信力的提高和当地居民生活环境的改善。
通过改变政府对企业的补贴力度,可得到其对三方策略主体选择的影响,如图4所示。从图4可以看出,地方政府和当地居民对补贴力度因素的敏感度较低。在5种不同程度的补贴力度下,地方政府都更偏向于低强度监管。虽然在补贴力度为0.9时,当地居民的策略选择有小幅度浮动,但总体都更偏向于参与监督。矿山企业对补贴力度因素的敏感度较高,随着补贴力度的增加,矿山企业也越来越偏向于积极治理。当政府对企业的补贴力度低于0.7时,矿山企业会选择消极治理。随着补贴力度的提高,矿山企业会更偏向于积极治理。当补贴力度达到0.9时,矿山企业积极治理概率快速上升,最终偏向于积极治理策略。
分析表明,地方政府对企业的补贴力度,能够弥补矿山企业积极治理过程中的额外成本,但如果地方政府一味增加补贴的力度,可能会使当地居民逐渐放弃对矿山企业的监督,从而让矿山企业有了松懈的机会。因此,地方政府想要促进矿山企业选择积极治理的行为策略,可以采取适当的经济奖励手段来促进矿山企业的积极性。
政府对企业的惩罚力度对三方策略主体选择的影响如图5所示。通过图5可知,在政府对企业的5种惩罚力度情形下,当地居民的策略选择都更偏向于参与监督。矿山企业对惩罚力度因素敏感度较高,随着惩罚力度的增加,矿山企业的策略选择会更偏向于积极治理,而惩罚力度的改变并未对地方政府的策略选择产生较大的影响。当政府的惩罚力度在0.7及以下时,提高惩罚力度会对矿山企业的策略选择产生明显的影响,矿山企业会逐渐偏向于积极治理策略。但随着惩罚力度的增加,政府对企业的惩罚数额过大会使矿山企业的压力较大,从而产生不满消极的情绪。矿山企业的积极性降低的同时,随着政府的惩罚力度的增加,当地居民的监督力度也更加宽松,从而导致矿山企业对积极治理策略选择的偏向会降低,达到积极治理稳定状态的时间会变长。
分析表明,地方政府对企业增加的惩罚力度,逐渐成为矿山企业治理过程中重要的支出,当消极治理的收益不足以弥补惩罚的数额时,矿山企业会权衡利弊而更偏向于选择积极治理的策略。但当政府的惩罚力度过大时,会减弱矿山企业恢复治理的积极性,产生负面的效果。因此政府可以采取适当的惩罚手段来促使矿山企业选择积极治理的策略。
通过图6可知,地方政府对企业公关费因素的敏感度较低,在企业公关费5种程度变化下,地方政府都偏向于低强度监管策略。而矿山企业和当地居民对企业公关费的敏感度都较高,随着企业公关费用的增加,矿山企业更偏向积极治理,当地居民更偏向不参与监督。当企业公关费小于等于55万元时,矿山企业会选择消极治理策略,随着公关费用的增加,矿山企业会逐渐偏向积极治理。尤其当公关费用达到105万元时,矿山企业会在10个月内达到积极治理策略的稳定状态。当企业公关费小于等于55万元时,当地居民会选择参与监督策略,随着公关费用的增加,当地居民会逐渐偏向不参与监督,当公关费用达到105万元时,当地居民会在第45个月达到不参与监督策略的稳定状态。
分析表明,企业公关费用的增加,会使企业因支出变多而产生经济压力,同时矿山企业的声誉也会受到负面影响。矿山企业在自身经济效益和发展潜力可能双重受损的压力下,会迅速改变自身策略而偏向于积极治理。此时,当地居民在监督过程中没有发现企业消极治理的行为,逐渐对企业产生信任和肯定,从而渐渐偏向于不参与监督。因此,各大媒体组织和社会群众要多多关注矿山企业的恢复治理工程,从而加大企业消极治理时企业为消除负面影响所付出的公关费用,对企业选择积极治理策略有很好的推动作用。
企业额外成本收益差指矿山企业积极治理时产生的额外成本与所获得的未来收益的差值。通过图7可知,地方政府对企业额外成本收益差因素的敏感度较低,在企业额外成本收益差5种程度变化下,地方政府都偏向于低强度监管策略。矿山企业和当地居民对该因素的敏感度均较高,随着企业额外成本收益差的增加,矿山企业的策略选择从积极治理逐渐向消极治理偏移,当地居民的策略选择从不参与监督向参与监督转变。当企业额外成本收益差小于等于100万元时,矿山企业的策略选择偏向于积极治理;当企业额外成本收益差大于100万元时,矿山企业选择消极治理策略。对于当地居民而言,当企业额外成本收益差小于等于100万元时,当地居民的策略选择偏向于不参与监督;当企业额外成本收益差大于100万元时,当地居民选择参与监督策略。
分析表明,企业作为追逐利益的经济人,更加关注自身的经济效益,矿山企业积极治理的成本收益差越小,越能激发矿山企业积极治理的积极性。因此,矿山企业可以多引进矿山治理新技术,降低修复成本。同时,地方政府需要引导矿山企业正确处理获取经济利益和妥善治理环境之间的关系,可以采取税收优惠等政策来减小矿山企业的成本,从而缩小矿山企业积极治理的成本收益差。
通过图8可知,地方政府和当地居民对居民监督力度因素的敏感度相比于矿山企业较低。在5种居民监督力度情形下,地方政府的策略选择都更偏向于低强度监管,当地居民的策略选择都更偏向于参与监督;矿山企业的策略选择则随着居民监督力度的增大,从消极治理策略逐渐转变为积极治理策略。当P=0.1时,地方政府的策略选择产生了较小的波动性变化,这是由于居民的监督力度过小无法对矿山企业的策略选择产生实质性影响,地方政府需要加强监管来督促矿山企业的积极治理行为。随着居民监督力度的增加,地方政府逐渐稳定在低强度监管的策略。对于矿山企业而言,当居民监督力度小于等于0.5时,矿山企业的策略选择会稳定在消极治理,当居民监督力度大于0.5时,矿山企业的策略会倾向于积极治理。当P=0.9时,在居民高强度监督力度下,矿山企业积极治理概率在前期会迅速上升,并在第35个月达到峰值。当地居民监督力度过大耗费了居民大量的时间和精力,且并未发现矿山企业消极治理的行为,使得参与监督的居民逐渐减少,因此在第55个月前,当地居民的策略选择更偏向于不参与监督。由于当地居民监督人数的减少,矿山企业为了更高的经济利益,使得策略选择产生了小范围波动,积极治理概率下降。但随着当地居民发现矿山企业消极治理的行为而加强监督后,矿山企业积极治理概率在第65个月再次上升,逐渐偏向于积极治理策略的稳定状态。
分析表明,当地居民的监督力度会影响矿山企业的策略选择,随着居民监督力度的增大,矿山企业会更偏向于积极治理。但当居民监督力度过大,居民消耗大量的时间和精力去监督,得到的成果却甚微时,当地居民参与监督的人数会逐渐减少,从而对矿山企业的策略选择产生一定的影响。因此,政府可以通过加大对当地居民的奖励力度,完善居民参与监督机制以及增加居民举报渠道,来提高当地居民监督的积极性,从而间接加大居民的监督力度,以推动矿山企业选择积极治理策略。
本文通过矿山恢复治理利益相关者视角,借助有限理性的演化博弈工具,构建矿山恢复治理地方政府、矿山企业、当地居民三方演化博弈模型,并结合系统动力学对利益相关者长期动态博弈过程进行了建模和分析。根据分析结果,结合矿山恢复治理可持续发展原则,针对地方政府、矿山企业和当地居民三方利益主体提出以下对策建议。
(1)对地方政府的建议。
对于地方政府来说,加大对矿山企业的激励和惩罚力度是规范企业待遇行为的重要措施。通过加大惩罚力度,地方政府可以增加矿山企业的消极治理成本,此时矿山企业会权衡利益而选择积极治理。惩罚措施可以较好地规制企业环境违法行为,但惩罚力度不宜过大,否则会导致企业积极性减弱而产生负面效果。在奖励措施上,对积极履行矿山恢复治理的企业,地方政府应给予适当的补偿,加大相关税收的减免力度。此外,地方政府可以通过媒体公开表彰来提升企业在社会上的声誉,以增强企业自身的自豪感和责任感。
对于矿山企业,地方政府也可以开发市场激励型的环境规制,借助市场的手段来影响企业的决策,例如碳税、生态补偿等[17],并通过市场的指导来激励企业自发进行恢复治理技术的创新。对于当地居民,地方政府可以开发自愿性环境规制,通过完善居民参与监督的机制,方便当地居民自愿对矿山企业进行监督举报,以对企业的消极行为进行约束;同时,也可以开发非正式的环境规制,鼓励社会团体、新闻媒体等对矿山企业的恢复治理项目进行关注与监督,增加矿山企业产生负面影响时的公关费用,从而达到规范矿山企业环境治理行为的效果。
(2)对矿山企业的建议。
对于矿山企业来说,可以通过促进技术升级来降低企业治理成本。矿山企业积极治理的成本收益差是限制矿山恢复治理积极性的一个重要因素,差值越小,矿山企业进行恢复治理工作的动力就越大,而降低成本可以有效减小差值。降低矿山恢复治理成本可以引进绿色修复技术,推动企业恢复治理技术的升级。这些绿色修复技术的应用,能在修复过程中对资源进行再利用、再制造和再循环,提高环境恢复治理效益,促进矿山环境的可持续发展。
矿山企业可以培养专业的管理团队,提高环境治理效益。提升环境修复效益也是促进矿山企业积极开展恢复治理工作的一条重要途径。矿山企业应加大对矿山恢复治理的资源投入和人员投入,注重矿山修复技术人才培养,培训更多的专业治理团队,形成成熟的矿山恢复治理体系;矿山企业可以建立矿山治理评价体系,实时监控项目进展,尽可能让恢复治理工作的社会经济环境效益达到最大化。
(3)对当地居民的建议。
当地居民应提高矿山环境治理意识,强化环境保护责任。当地居民常年居住在矿区,直接受到矿区环境的影响,他们可以立即感知到企业的负面行为。提高当地居民的矿山治理意识,强化环境保护责任具有重要意义。因此,媒体应积极宣传矿山环境治理项目,增强当地居民的环保意识。居民委员会等组织要表彰积极监督和举报企业不良行为的居民,以身作则激发居民监督积极性,引导居民树立环保责任感。同时,对积极监督或举报矿山企业环境违法行为的居民,可以给予相应的物质奖励,以提高当地居民的监督积极性。
通过拓宽居民参与渠道,可以加强居民监督,从而有效促进矿山企业积极开展矿山环境治理。首先,可以充分利用微博和官方账号等新媒体网络平台分享矿山环境治理信息,使当地居民能够及时获取相关信息。其次,可以在矿区设置举报邮箱,粘贴相关举报部门的电话和电子邮件等信息,方便居民随时监督和举报。再次,建立健全社会听证制度。对于矿山环境治理过程中的纠纷,应邀请矿山企业人员、矿山专家、环保组织和当地居民共同参与,确保矿山环境治理工作的民主和科学。通过这些方法,将加强居民监督,鼓励矿山企业积极开展矿山环境治理工作。
  • 三亚崖州湾科技城配套资助定向组织项目(SKJC-2022-PTDX-021)
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2025年第45卷第11期
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  • 接收时间:2024-11-27
  • 首发时间:2026-10-28
  • 出版时间:2025-11-25
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  • 收稿日期:2024-11-27
基金
三亚崖州湾科技城配套资助定向组织项目(SKJC-2022-PTDX-021)
作者信息
    1.武汉理工大学 土木工程与建筑学院,湖北 武汉 430070
    2.中南大学 土木工程学院,湖南 长沙 410083

通讯作者:

刘晓晓(2000—),女,湖南长沙人,博士研究生,主要从事绿色建造与管理等方面的研究工作。E-mail:
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2种不同金属材料的力学参数
科
Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
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属
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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