China's ESG scorecard: A predictive machine learning model

Lemuel Kenneth David, Jianling Wang, Vanessa Angel and Meiling Luo

Corporate Social Responsibility and Environmental Management, 2024, vol. 31, issue 4, 3468-3486

Abstract: In today's globalized business environment, the intersection of Environmental, Social, and Governance (ESG) factors has come to the forefront, shaping the paradigms of Corporate Social Responsibility (CSR) and environmental stewardship. As China, with its economic prowess and distinct socio‐cultural milieu, takes center stage, deciphering its ESG dynamics becomes imperative for both local and global stakeholders. This groundbreaking research unveils a pioneering multidimensional ESG scoring system tailored for the Chinese corporate landscape. Drawing on an extensive dataset from Bloomberg, spanning an 11‐year period and encompassing 1496 companies, this study stands as a seminal contribution to the ESG literature. By harnessing advanced mathematical explorations coupled with state‐of‐the‐art machine learning techniques, the model's predictive prowess is heightened, ensuring its adaptability and robustness. Venturing beyond mere metrics, this research accentuates the practical implications of ESG in shaping sustainable and responsible business practices in China, thereby catalyzing a more ethically aligned corporate trajectory in the region.

Date: 2024
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https://doi.org/10.1002/csr.2746

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Persistent link: https://EconPapers.repec.org/RePEc:wly:corsem:v:31:y:2024:i:4:p:3468-3486

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