Purpose Business sustainability has become a cornerstone concept for business research because of the need for organisations to make a profit while meeting environmental and social responsibility. Although research in this field has grown continuously in the past two decades, there is still scope to identify a clear thematic classification that links diverse areas of business research. This study aims to identify nine potential research topics based on the topic modelling analysis. Design/methodology/approach The study applies latent Dirichlet allocation (LDA) for topic modelling on a data set of 775 journal research papers, published between 2000 and 2025, extracted from the Scopus database using the keyword “Business Sustainability”. Findings The results reveal that topic modelling methods such as LDA contribute to the analysis and identification of the evolving framing of “Business sustainability” in business research. Furthermore, this research revealed the prominent topics such as sustainability reporting and environmental disclosure, and green marketing and consumer behaviour in sustainable business; while relatively underexplored topics include circular economy and supply chain management, corporate social responsibility and green human resource management and innovation and technology in sustainable business. Originality/value This paper addresses this gap by identifying the potential areas for business sustainability research by using an unsupervised machine learning algorithm. It reveals the underlying thematic structure of the literature, quantifies topic prevalence and offers insights into emerging trends, underexplored areas and provides a robust framework for future studies.
Singh et al. (Mon,) studied this question.