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<p>Coal serves as the cornerstone of energy security across multiple countries. Green and intelligent mining technology (GIMT) for coal resources is required to achieve sustainable development in the coal industry and ensure national energy security. To facilitate coal enterprises’ ability to develop and implement green and intelligent mining technologies, this work seeks to establish an evolutionary game model of green mining regulatory strategies between coal enterprises and the government. Under incentive mechanisms, a revenue matrix was constructed between regulatory authorities and coal mines. Through computational analysis and MATLAB simulations, the replication dynamics method was employed to simulate their strategic adjustments. Evolutionary game analysis reveals behavioral evolution paths and stable strategies for stakeholders in GIMT implementation. Based on the results of the dynamic game process and strategic adjustments between coal mines and regulatory units, strategies for optimizing relevant regulatory policies were proposed, providing a theoretical basis for government departments to formulate targeted regulatory policies. By dynamically evaluating three scenarios, recommendations were provided to address the potential risks in the adoption of GIMT. Key recommendations include reducing opportunistic gains, optimizing incentives, enhancing accountability, and promoting marketization. Future efforts should focus on technological innovation, collaborative governance, and dynamic policy adjustments.</p>

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Green and Intelligent Development Strategy and Evolutionary Game Model Under Government Incentive Mechanism

  • 期刊论文

  • 发表日期：

    2025年4月9日

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  • Bingqian Yan

摘要

Coal serves as the cornerstone of energy security across multiple countries. Green and intelligent mining technology (GIMT) for coal resources is required to achieve sustainable development in the coal industry and ensure national energy security. To facilitate coal enterprises’ ability to develop and implement green and intelligent mining technologies, this work seeks to establish an evolutionary game model of green mining regulatory strategies between coal enterprises and the government. Under incentive mechanisms, a revenue matrix was constructed between regulatory authorities and coal mines. Through computational analysis and MATLAB simulations, the replication dynamics method was employed to simulate their strategic adjustments. Evolutionary game analysis reveals behavioral evolution paths and stable strategies for stakeholders in GIMT implementation. Based on the results of the dynamic game process and strategic adjustments between coal mines and regulatory units, strategies for optimizing relevant regulatory policies were proposed, providing a theoretical basis for government departments to formulate targeted regulatory policies. By dynamically evaluating three scenarios, recommendations were provided to address the potential risks in the adoption of GIMT. Key recommendations include reducing opportunistic gains, optimizing incentives, enhancing accountability, and promoting marketization. Future efforts should focus on technological innovation, collaborative governance, and dynamic policy adjustments.