Unveiling Greenwashing: Analyzing the interaction of factors discouraging ESG Greenwashing through TISM and MICMAC

Abstract

Corporations, as major contributors to carbon emissions, face mounting pressure to adopt genuine sustainability practices. However, the rise of Environmental, Social, and Governance (ESG) disclosures has concurrently given rise to greenwashing—misleading claims that erode stakeholder trust and obstruct sustainability progress. Despite the widespread acknowledgment of greenwashing, there is a notable gap in research identifying the key factors that can mitigate it. This study addresses this gap by developing a comprehensive framework using Total Interpretive Structural Modeling (TISM) and Matriced' Impacts Croisés Multiplication Appliquée à un Classement (MICMAC) analysis. Drawing on an extensive literature review and expert opinions, the study identifies critical factors, including artificial intelligence, digital transformation, green finance, and robust monitoring mechanisms, as instrumental in combating ESG greenwashing, while environmental awareness is found to have minimal influence. TISM uncovers causal relationships among these factors, and MICMAC categorizes them based on their driving and dependence power. The findings provide actionable insights for policymakers, corporations, and investors, offering a structured pathway to enhance transparency, strengthen corporate accountability, and align business practices with global sustainability objectives.