A Text Mining Model to Evaluate Firms’ ESG Activities: An Application for Japanese Firms

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.