A Review of Occupational Health and Safety Disclosures: Trends Identified through Structural Topic Modelling - Podayan, Arun; Balakrishnan, Charumathi (Information Research Communications, 2024)
This paper evaluates the evolution of Occupational Health and Safety Disclosure (OHSD) practices in corporate reporting by applying structural topic modeling to literature from the Scopus database. The study explores prominent research themes within OHSD by utilizing machine learning techniques. A comprehensive keyword search in Scopus identified 956 relevant articles published between 1974 and 2024, which were analyzed using STM and bibliometric analysis to highlight key research objectives, affiliations, focal areas and epistemological trends. The findings reveal that OHSD research has grown steadily over time, focusing on OHS auditing in construction supply chains, sustainable business practices, regulatory frameworks and global safety standards. Emerging areas of interest include OHSD in corporate reporting, employee well-being and workplace dynamics. These insights provide a deeper understanding of OHSD research priorities and trends, which can guide businesses in improving their OHSD practices and aligning them with sustainability initiatives. Furthermore, these findings offer valuable guidance to researchers, funders and policymakers in addressing contemporary OHSD issues. This study is unique in its use of STM to identify research themes and trends. It utilizes the find Thoughts function to explore relevant articles derived from the STM process, thereby offering a novel approach to understanding OHSD developments in corporate reporting.
Keywords: Machine learning; Occupational health and safety; Reporting disclosure; Structural topic modeling