In recent years, companies have increasingly adopted visual tools to communicate their sustainability practices, responding to growing stakeholder demand for more transparent and accessible non-financial information. Within this context, the use of visual content in environmental, social, and governance (ESG) disclosure has also gained prominence in academic literature. Under the lens of signaling theory, the purpose of this study is to investigate the relationship between visual ESG disclosure and the cost of debt.
This study adopts a machine-supported approach, relying on Google’s Vision API to assess the extent to which a sample of 279 listed firms included in the MSCI Europe Index incorporate photographs and images related to ESG issues in their non-financial reports for the 2023 financial year. A regression model was used to assess the relationship between the level of visual ESG disclosure, proxied by the natural logarithm of the number of ESG photographs and images retrieved from sampled non-financial reports, and the cost of debt.
The results of this study reveal that the majority of ESG photographs and images in corporate non-financial reports are linked to environmental themes, followed by social topics and, to a much lesser extent, governance content. In addition, the findings of this study indicate that a greater use of visual ESG disclosure is associated with a reduction in the cost of debt.
This study enriches the ESG disclosure literature by shifting attention from the content to the form of disclosure, emphasizing the strategic role of visual elements in non-financial reporting and their influence on the cost of debt. To the best of the authors’ knowledge, this is the first study to offer empirical insight into the impact of using photographs and images for ESG disclosure on borrowing costs. This study also advances the application of signaling theory by demonstrating how visual communication can serve as a credible signal of corporate transparency in capital markets.
