Environmental, Social, and Governance (ESG) Fraud: A Systematic Literature Review - Sisdianto, Ersi (JABI (Jurnal Akuntansi Berkelanjutan Indonesia), 2025)
Purpose this study systematically examines the phenomenon of Environmental, Social, and Governance (ESG) fraud, analyzing its evolving trends, sector-specific manifestations, and underlying theoretical frameworks. The research investigates how governance gaps, regulatory arbitrage, and market pressures drive fraudulent ESG practices across industries. Methodology employing a systematic literature review (SLR) following PRISMA 2020 guidelines, this study analyzes 66 peer-reviewed articles from Scopus and Web of Science (2014–2023). Bibliometric tools (VOSviewer) and content analysis are used to map research trends, fraud schemes, and theoretical perspectives. Findings three key insights emerge: (1) ESG fraud is enabled by weak internal governance (e.g., unqualified board oversight, misaligned executive incentives) and regulatory inconsistencies; (2) firms prioritize fraud over genuine sustainability due to cost-benefit calculus and institutional isomorphism; (3) fraud patterns diverge across ESG pillars environmental fraud dominates high-impact sectors (energy, mining), social fraud thrives in supply chain-dependent industries (apparel, tech), while governance fraud permeates financial services. Agency theory, institutional theory, and stakeholder theory collectively explain these dynamics. Limitations/Implications the study’s focus on 66 articles may limit generalizability, while the dominance of quantitative methods (95% of sample) could marginalize qualitative insights. Findings underscore the need for standardized ESG metrics, cross-border enforcement, and sector-specific anti-fraud frameworks. Originality this research offers a novel integration of bibliometric analysis and multi-theoretical framing to decode ESG fraud. It provides practitioners with actionable insights for fraud detection and policymakers with evidence to strengthen ESG accountability mechanisms. The study identifies underexplored research avenues, including the role of AI in fraud detection and cultural influences on ESG disclosure integrity.