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2026, 07, v.42 26-38
机器学习视角下不同类型企业碳减排策略选择研究
基金项目(Foundation): 国家自然科学基金面上项目“环境规制协同驱动跨区域产业链企业合作减排机制与效应研究”(72174080);国家自然科学基金项目“数字基础设施‘降碳—增效’协同效应与空间配置优化研究”(72563016); 国家社会科学基金项目“数据要素价值创造、贡献测度与收益分配研究”(23CJY006)
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发布时间: 2026-07-03
出版时间: 2026-07-03
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摘要:

企业是碳排放的主体,也是碳排放治理的主体。在降碳减排治理的不同阶段,企业如何选择碳减排策略对碳减排绩效至关重要。论文以2010—2022年A股上市企业的数据为研究样本,根据企业所在地区环境规制强度、行业碳排放强度以及企业高管绿色认知程度对企业进行K-Means聚类分析。聚类结果为四类,分别是地区环境规制严格型、行业排放严格型、行业排放宽松型、碳排放治理高管重视型。在此基础上,通过LightGBM机器学习方法,探究不同类型企业在碳治理不同阶段的最优策略选择。结果显示:在前端预防阶段,属于地区严格型、行业严格型、行业宽松型企业的最优策略为规模性减排,高管重视型企业更倾向于以技术性减排为牵引,协同运用规模性、市场化和结构性减排等多元化策略;在过程管控阶段,市场化减排是所有企业实现碳减排的最优策略;在末端治理阶段,各类企业更倾向于规模性减排、技术性减排、市场化减排和结构性减排等多种碳减排策略的综合运用,强调策略之间的协同效应。

Abstract:

Enterprises are the primary entities responsible for carbon emissions and also the principal actors in carbon emission governance.The selection of carbon emission reduction strategies by enterprises at different stages of governance is crucial to their carbon emission reduction performance.This paper takes data from A-share listed companies in China from 2010 to 2022 as the research sample and conducts a K-Means cluster analysis on enterprises based on the intensity of environmental regulations in their respective regions,the intensity of carbon emissions in their industries,and the degree of green awareness among their senior executives.The clustering results yield four categories:enterprises in regions with strict environmental regulations,enterprises in industries with strict emission regulations,enterprises in industries with lenient emission regulations,and enterprises whose senior executives prioritize carbon emission governance.On this basis,the LightGBM machine learning method is employed to explore the optimal strategy choices for different types of enterprises at various stages of carbon governance.The results show that:in the front-end prevention stage,the optimal strategy for enterprises belonging to the strict regional,strict industry,and loose industry categories is large-scale emission reduction.Executive-attentive enterprises are more inclined to use technological emission reduction as a driving force,synergistically applying diversified strategies such as large-scale,market-oriented,and structural emission reduction.In the process control stage,market-oriented emission reduction is the optimal strategy for all enterprises to achieve carbon emission reduction.In the end-of-pipe treatment stage,various enterprises prefer the comprehensive application of multiple carbon emission reduction strategies such as large-scale emission reduction,technological emission reduction,market-oriented emission reduction,and structural emission reduction,emphasizing the synergistic effect between strategies.

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基本信息:

中图分类号:F279.2;X322

引用信息:

[1]刘满凤,杨刚,王亮.机器学习视角下不同类型企业碳减排策略选择研究[J].生态经济,2026,42(07):26-38.

基金信息:

国家自然科学基金面上项目“环境规制协同驱动跨区域产业链企业合作减排机制与效应研究”(72174080);国家自然科学基金项目“数字基础设施‘降碳—增效’协同效应与空间配置优化研究”(72563016); 国家社会科学基金项目“数据要素价值创造、贡献测度与收益分配研究”(23CJY006)

发布时间:

2026-07-03

出版时间:

2026-07-03

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