Topic Trends in Sustainability Disclosure of German DAX 40 Companies—A Text Mining-Based Analysis

Given the increasing importance of sustainability in the business world, there has been growing interest in using topic modeling approaches to identify reported topics in corporate sustainability reports (CSR). Due to the inconsistent legal foundation and different sustainability standards, the content of individual reports can vary greatly. In this paper, the corporate social responsibility reports of DAX 40 companies from 2017 to 2021 are therefore analyzed using Latent Dirichlet Allocation (LDA). In particular, we attempt to identify topics that are suggested by the Global Reporting Initiative (GRI) Sustainability Standard for large public companies. In addition, a comparison is made throughout the years. The study shows that specific guidelines of the GRI can only be identified to a certain degree using LDA. Although some topics that partly reflect the content of the GRI can be found by the model, the overall structure of the GRI can’t be replicated. Overall, this study shows that an evaluation of the content of sustainability reports can be successful in terms of the relevance of the reported topics, although the results depend heavily on the respective pre-processing steps.