Implementation of green mining strategy under responsibility division: An evolutionary game research from the perspective of mining policy

Implementation of green mining strategy under responsibility division: An evolutionary game research from the perspective of mining policy | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Implementation of green mining strategy under responsibility division: An evolutionary game research from the perspective of mining policy YANG LI, Guoyan Zhao, Zhengxin Zhang, Lluis Sanmiquel, Pan Wu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6937241/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Mining policies significantly influence the mining industry's adoption of technical innovation and pollution control. This study employs evolutionary game theory to investigate how policy factors shape the strategies of local governments (LGs), metal mines (MMs), and regulatory agencies (RAs) in promoting green mining (GM). Firstly, a tripartite evolutionary game model was developed to analyze the challenges of GM in MMs and the impact of policy efficiency; Secondly, replicator dynamics and equilibrium points were examined to identify optimal strategies and stability conditions. At last, numerical simulations informed by field investigations and expert consultations, validated the model and delineated three GM stages with distinct evolutionary patterns. Results show that LGs predominantly drive GM activities, with MMs exhibiting limited autonomy and delayed responses to policy changes, directly influenced by mining policies. To achieve GM goals, we recommend consolidating small MMs to standardize management and foster innovation, and leveraging technological advancements in tailing disposal to reduce costs and enhance benefits. For long-term planning, LGs should implement reasonable accountability penalties to boost RA efficiency and optimize incentive-penalty structures, as MMs are highly sensitive to pollution penalties. GM in MMs requires a phased, context-specific approach, necessitating dynamic policy adjustments. These findings elucidate the role of mining policies in facilitating GM, supporting the green transformation of MMs and enhancing the efficiency of LGs' policy implementation. Green mining Evolutionary game Policy adjustments Numerical simulation Policy recommendations Full Text Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6937241","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":477051042,"identity":"8706ba8a-5459-49b6-9e00-ed8d3e997ca0","order_by":0,"name":"YANG LI","email":"","orcid":"","institution":"Central South University","correspondingAuthor":false,"prefix":"","firstName":"YANG","middleName":"","lastName":"LI","suffix":""},{"id":477051044,"identity":"da17f641-407d-4fb8-9956-657b366cb58d","order_by":1,"name":"Guoyan Zhao","email":"","orcid":"","institution":"Central South University","correspondingAuthor":false,"prefix":"","firstName":"Guoyan","middleName":"","lastName":"Zhao","suffix":""},{"id":477051047,"identity":"950b721a-2e23-4b5a-9239-bbc8957269fb","order_by":2,"name":"Zhengxin Zhang","email":"","orcid":"","institution":"Shandong Gold Group","correspondingAuthor":false,"prefix":"","firstName":"Zhengxin","middleName":"","lastName":"Zhang","suffix":""},{"id":477051048,"identity":"1e2d19c3-9cac-4aef-91f8-615eef534f4e","order_by":3,"name":"Lluis Sanmiquel","email":"","orcid":"","institution":"Polytechnic University of Catalonia","correspondingAuthor":false,"prefix":"","firstName":"Lluis","middleName":"","lastName":"Sanmiquel","suffix":""},{"id":477051049,"identity":"7e6f1a95-5e6c-4a2b-9faa-4a8654a8e8ce","order_by":4,"name":"Pan Wu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA5klEQVRIiWNgGAWjYBACPghlIQMkGB8ACR4+QlrYIJQEDwMDM7MBSAsbKVrYJJBE8Ghhbz724EeFBA+/dP+xyq85djJsDMwPH93Ap4XnWLphzxkJHsk5h9luy25LBjqMzdg4B58WiRwzacY2CR6DG8lstyW3MQO18LBJ49Ui/wao5Z8Ejz1QS7HktnoitEjwALU0AG2RSGZj/LjtMBFaeNLSJHuOSfBI3Eg2lmbcdpyHjZmAX/jZDx+T+FFjI8c/I/Hhx5/bqu352ZsfPsanBQUw84BJYpWDAOMPUlSPglEwCkbBiAEAGoo3Y8789+QAAAAASUVORK5CYII=","orcid":"","institution":"Central South University","correspondingAuthor":true,"prefix":"","firstName":"Pan","middleName":"","lastName":"Wu","suffix":""}],"badges":[],"createdAt":"2025-06-20 09:08:08","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6937241/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6937241/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":85721000,"identity":"f10f7684-1cff-47a2-95c8-fc0be524ba40","added_by":"auto","created_at":"2025-07-01 05:36:31","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":7493793,"visible":true,"origin":"","legend":"","description":"","filename":"AnonymisedManuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6937241/v1_covered_d8586ae4-d7cd-4255-9fd8-237d365d0fb1.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Implementation of green mining strategy under\n\tresponsibility division: An evolutionary game research from\n\tthe perspective of mining policy","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Green mining, Evolutionary game, Policy adjustments, Numerical simulation, Policy recommendations","lastPublishedDoi":"10.21203/rs.3.rs-6937241/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6937241/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Mining policies significantly influence the mining industry's adoption of technical innovation and pollution control. This study employs evolutionary game theory to investigate how policy factors shape the strategies of local governments (LGs), metal mines (MMs), and regulatory agencies (RAs) in promoting green mining (GM). Firstly, a tripartite evolutionary game model was developed to analyze the challenges of GM in MMs and the impact of policy efficiency; Secondly, replicator dynamics and equilibrium points were examined to identify optimal strategies and stability conditions. At last, numerical simulations informed by field investigations and expert consultations, validated the model and delineated three GM stages with distinct evolutionary patterns. Results show that LGs predominantly drive GM activities, with MMs exhibiting limited autonomy and delayed responses to policy changes, directly influenced by mining policies. To achieve GM goals, we recommend consolidating small MMs to standardize management and foster innovation, and leveraging technological advancements in tailing disposal to reduce costs and enhance benefits. For long-term planning, LGs should implement reasonable accountability penalties to boost RA efficiency and optimize incentive-penalty structures, as MMs are highly sensitive to pollution penalties. GM in MMs requires a phased, context-specific approach, necessitating dynamic policy adjustments. 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