关键词: ESG Evaluation index system Machine learning Solid waste disposal companies (SWDCs) Type identification

Mesh : China Machine Learning Refuse Disposal Solid Waste Waste Management / methods

来  源:   DOI:10.1016/j.jenvman.2024.121235

Abstract:
In the context of China\'s efforts to combat climate change and promote sustainable development, the solid waste treatment industry\'s environmental, social, and corporate governance (ESG) performance is receiving significant attention. To comprehensively assess the ESG performance of the solid waste treatment industry and identify company types, this study constructs a targeted ESG evaluation index system based on existing literature, SASB industry standards, and company reports and utilizes a random forest approach combined with K-means clustering to determine indicator weights. Based on this index system, the paper evaluates the ESG performance of 71 solid waste disposal companies (SWDCs) from 2013 to 2021 and identifies their ESG types from static and dynamic perspectives. In the static view, company types are determined based on annual ESG performance, while the dynamic view considers time-series changes to observe the evolution of company ESG types. The results show that the overall ESG performance of SWDCs falls within the 2-8-point range, indicating a noticeable high-low imbalance. Key initiatives to improve ESG performance in this industry include enhancing waste management measures, developing emergency plans, and reinforcing ESG disclosure. From a static perspective, this paper can identify companies into three categories: delayed development, single-wheel-driven, and coordinated development. Finally, from a dynamic perspective considering the time factor, companies are further subdivided into five types: continual leading, growth catch-up, slow progress, fluctuating change, and retrogressive inertia. This study not only provides targeted recommendations for different types of ESG companies but also helps various sectors of society better understand the ESG conditions of this high environmental risk industry, thereby enhancing the regulation and support for its sustainable development.
摘要:
在中国努力应对气候变化和促进可持续发展的背景下,固体废物处理行业的环境,社会,公司治理(ESG)绩效受到了极大的关注。全面评估固废处理行业的ESG表现,确定公司类型,本研究在已有文献的基础上,构建了有针对性的ESG评价指标体系,SASB行业标准,和公司报告,并利用随机森林方法结合K均值聚类来确定指标权重。基于这个指标体系,本文评估了2013年至2021年71家固体废物处理公司(SWDC)的ESG绩效,并从静态和动态角度确定了它们的ESG类型。在静态视图中,公司类型是根据年度ESG业绩确定的,而动态视图考虑了时间序列的变化,以观察公司ESG类型的演变。结果表明,SWDC的整体ESG性能落在2-8点范围内,表明明显的高低不平衡。改善该行业ESG绩效的关键举措包括加强废物管理措施,制定应急计划,并加强ESG披露。从静态的角度来看,本文可以将公司分为三类:延迟开发,单轮驱动,协调发展。最后,从动态角度考虑时间因素,公司进一步细分为五种类型:持续领先,增长追赶,进展缓慢,波动变化,和倒退的惯性。这项研究不仅为不同类型的ESG公司提供了有针对性的建议,而且有助于社会各界更好地了解这个高环境风险行业的ESG状况,从而加强对其可持续发展的监管和支持。
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