Domestic Applicability of SASB ESG Issues Using Generative AI-based Embedding: Healthcare News Analysis

SASB provides industry-specific guidelines on material ESG issues and is rapidly becoming a global standard for ESG disclosure, with its importance further highlighted by the recent official adoption of SASB guidelines by the International Sustainability Standards Board (ISSB). However, empirical examinations on whether SASB’s industry-specific issues adequately reflect the structure and characteristics of domestic industries have been limited. Prior studies have predominantly focused on theoretical assessments or limited discussions on specific industries, lacking systematic empirical analyses. This study selects the healthcare industry as a representative case and employs generative AI-based sentence embedding techniques to quantitatively classify corporate news data, identify recurrent issues within sub-industries, and analyze the actual significance of ESG issues. The findings reveal statistically significant relationships between news-based ESG issue prominence and SASB guidelines (p < 0.05), while other issues were separately highlighted in domestic news, indicating industry-specific and regional peculiarities. These results suggest that, instead of uniformly applying SASB guidelines, domestic firms should reconstruct the importance of ESG issues based on empirical industry data and adjust their disclosure strategies and response priorities by incorporating specific industrial and regional characteristics.