A Text-Mining Approach to the Evaluation of Sustainability Reporting Practices: Evidence from a Cross-Country Study

Abstract

This study examines the sustainability reports (SRs)of 200 firms in both developed and emerging economies in order to identify the words most frequently used in disclosing sustainability practices within the Triple Bottom Line (TBL) approach to reporting (which emphasizes economic, environmental, and social dimensions). Its aim is to evaluate these sustainability reports under the umbrella of the GRI framework. It adopts a semi-automated Text-Mining (TM) technique to evaluate the corporate SRs of select firms from the top ten economies by GDP at current prices. Based on the GRI Standards guidelines, a total of 208 keywords were identified for analysis. The disclosures were then awarded points based on the appearance of these keywords so that the appearance of one resulted in the awarding of a score of one; if a keyword did not appear then the report was scored a zero for that word. Furthermore, a wordcloud was also generated in order to better understand the inclination of reporting language towards various TBL reporting categories. This analysis of the SRs of 200 firms from the top ten economies of the world sheds light on the differences in reporting practices and priorities as they relate to various aspects of the GRI Standards guidelines. The results indicate that SR practices have grown rapidly in the last half decade of the period selected for study (2013-2017) as compared to the first half (2008-2012). Canada ranked highest for its disclosure practices in this analysis followed by the UK, Germany, US, Japan, France, Italy, Brazil, India, and China. This study found that all included countries improved their sustainability performance over the period 2008-2017.