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<p>Mining policies significantly influence the mining industry’s adoption of technical innovation and pollution control. This study employs evolutionary game theory to investigate how Chinese 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.</p>

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

  • 期刊论文

  • 发表日期：

    2026年5月21日

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  • Yang Li,
  • Guoyan Zhao,
  • Zhengxin Zhang,
  • Lluis Sanmiquel,
  • Pan Wu

摘要

Mining policies significantly influence the mining industry’s adoption of technical innovation and pollution control. This study employs evolutionary game theory to investigate how Chinese 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.