Abstract
Environmental, social, and corporate governance (ESG) refers to the three important contributors to the sustainable growth of firms. Firms publish corporate social responsibility (CSR) reports that include quantitative and qualitative information concerning ESG activities. Although these reports are easily accessed, their qualitative information is hard to apply because manual analyses are difficult. We develop a text mining model that visualizes ESG activities from the structure of ESG-related words in CSR reports. This model quickly, effectively, and objectively facilitates processing CSR reports and comparing them with reports from peer firms. We analyze Japanese CSR reports and present an example. Further, we propose scores to evaluate the quantity and specificity of ESG activities. From the result, we obtain the following findings. First, large quantity and high specificity of ESG activities indicate a higher current ESG quantitative performance. Second, the high specificity of E-related and the large quantity of S and G-related activities portend subsequent improvement of ESG quantitative performance.
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Notes
As a similar study, Azhar et al. (2019) developed a text mining model for news articles to extract ESG-related information.
For example, there are studies that investigate the effects of ESG disclosure on firm performance (Sampong et al. 2018; Wang et al. 2017), of ESG quantitative performance on firm performance (Friede et al. 2015; Velte 2017; Busch and Friede 2018), and of a combination of ESG disclosure and quantitative performance on firm performance (Gutsche et al. 2017; Xie et al. 2018; Fatemi et al. 2018).
Please refer to Thomson Reuters (2011) for detailed information on the score.
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We thank the asset management department of Mitsubishi UFJ Trust and Banking Corporation for advice and cooperation. The authors are responsible for any remaining errors.
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Kiriu, T., Nozaki, M. A Text Mining Model to Evaluate Firms’ ESG Activities: An Application for Japanese Firms. Asia-Pac Financ Markets 27, 621–632 (2020). https://doi.org/10.1007/s10690-020-09309-1
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DOI: https://doi.org/10.1007/s10690-020-09309-1