Abstract
PURPOSE: This paper reviews the existing literature on Environmental, Social, and Governance (ESG) ratings divergence and aggregation methods. It highlights the challenges posed by inconsistent ESG ratings and their implications for investment decisions. DESIGN/METHODOLOGY/APPROACH: The study conducts a comprehensive review of prior research focusing on ESG ratings, examining their correlation levels and the methodologies employed to assess corporate sustainability. It also investigates traditional aggregation techniques and modern machine learning approaches used to address these inconsistencies. FINDINGS: The review reveals that ESG ratings exhibit a low level of correlation across different providers, raising concerns about their reliability as investment indicators. Although some studies propose advanced aggregation methods to enhance accuracy, significant gaps remain in understanding how to effectively consolidate ESG information to create a dependable sustainability indicator. ORIGINALITY: This paper provides a critical analysis of the current state of ESG rating methodologies, emphasizing the need for improved aggregation strategies. It underscores the importance of future research in leveraging ESG data to develop more consistent and reliable measures of corporate sustainability.