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Article type: Research Article
Authors: Yin, Songyia | Wang, Yua; b; * | Fu, Yelinc
Affiliations: School of Management, Jinan University, Guangzhou, China | International Business School, Jinan University, Zhuhai, China | College of Economics, Shenzhen University, Shenzhen, China
Correspondence: [*] Corresponding author. Yu Wang, School of Management, Jinan University, Guangzhou, 510632, China. E-mail: [email protected].
Abstract: The environmental, social, and governance (ESG) rating method is a powerful tool that can help investors to judge the investment value of companies based on the information disclosure. However, mainstream ESG rating methods ignore the distinction between companies with incomplete information disclosure and companies without information disclosure, which decreases the initiative and enthusiasm of companies to disclose information. In this study, a self-disclosure ESG (SDESG) rating method is proposed to evaluate companies’ ESG performance capabilities. First, based on the fuzzy set, fuzzy data is defined and applied to the SDESG rating method. Second, analogous to the academic reward system of a university, a reward mechanism of disclosure is used in the SDESG rating method. Finally, the effectiveness and reliability of the SDESG rating method are demonstrated through Refinitiv’s case. The results show that the SDESG rating method can distinguish companies with incomplete information disclosure from companies without information disclosure and allow companies that proactively disclose information to obtain better ESG scores under each industry. The implications of the study would increase companies’ enthusiasm to disclose information and maintain transparency within a company.
Keywords: ESG rating method, information disclosure, fuzzy set, reward mechanism
DOI: 10.3233/JIFS-230777
Journal: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-13, 2024
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