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Research on the rules of ESG performance and value creation based on rough sets

    Xue Hu Affiliation
    ; Weidong Zhu Affiliation
    ; Chao Zhang Affiliation
    ; Tianjiao Zhang Affiliation
    ; Chen Zhang Affiliation

Abstract

In the context of global sustainable development, the relationship between environmental, social responsibility, and governance (ESG) performance and multi-stakeholder value creation has been widely discussed. However, there is a complex causal relationship between ESG performance and value creation, many firm characteristics are involved, and there is no systematic study on them. In this study, we aim to explore the relationship between ESG performance and value creation, the joint role of firms’ internal and external characteristics in this relationship, and how the three components of ESG performance act on value creation through their various configurations. To identify complex causal relationships among variables, this study introduces rough sets method to describe these configuration relationships by generating rules. We use China’s 300 CSI-listed companies on the Shanghai and Shenzhen Stock Exchanges from 2015 to 2020 as research samples and find that firms with good ESG performance are more likely to have high-efficiency value creation; moreover, this relationship exists only among firms with specific characteristics. Additionally, different combinations of ESG components may have a differential impact on value creation, and we identify four configurations that generate high-efficiency value creation. This study contributes to guiding companies to strengthen their ESG practices and rationally allocate resources.


First published online 09 January 2024

Keyword : ESG performance, value creation, rough sets, rule mining, firm characteristics, stakeholder theory

How to Cite
Hu, X., Zhu, W., Zhang, C., Zhang, T., & Zhang, C. (2023). Research on the rules of ESG performance and value creation based on rough sets. Journal of Business Economics and Management, 24(6), 996–1018. https://doi.org/10.3846/jbem.2023.20631
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Dec 29, 2023
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This work is licensed under a Creative Commons Attribution 4.0 International License.

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