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.
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http://dx.doi.org/10.1016/j.jenvman.2025.124850 | DOI Listing |
J Environ Manage
March 2025
University of Belgrade, Faculty of Transport and Traffic Engineering, Vojvode Stepe 305, Belgrade, 11010, Serbia; Department of Industrial Engineering and Management, College of Engineering, Yuan Ze University, Taoyuan City, 320315, Taiwan. Electronic address:
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.
View Article and Find Full Text PDFPLoS One
March 2025
Graduate School, Lyceum of the Philippines University-Batangas, Batangas, Philippines.
The accurate prediction and interpretation of corporate Environmental, Social, and Governance (ESG) greenwashing behavior is crucial for enhancing information transparency and improving regulatory effectiveness. This paper addresses the limitations in hyperparameter optimization and interpretability of existing prediction models by introducing an optimized machine learning framework. The framework integrates an Improved Hunter-Prey Optimization (IHPO) algorithm, an eXtreme Gradient Boosting (XGBoost) model, and SHapley Additive exPlanations (SHAP) theory to predict and interpret corporate ESG greenwashing behavior.
View Article and Find Full Text PDFJ Environ Manage
March 2025
CMCC Foundation - Euro-Mediterranean Center on Climate Change, Via Della Libertà 12, 30175, Venice, VE, Italy.
This study examines the relationship between political contributions and Environmental, Social, and Governance (ESG) measures in US firms. Using data from LSEG Workspace (2010-2023), we implement GMM-SYS estimation to analyze the impact of corporate political donations on ESG metrics. Our results show that political contributions increase the ESG Score (through the E and G pillars) but also cause more ESG controversies for the firm.
View Article and Find Full Text PDFJ Environ Manage
January 2025
Center for Chinese Urbanization Studies, Collaborative Innovation Center for New Urbanization and Social Governance, Soochow University, 199 Renai Road, Suzhou, 215006, PR China. Electronic address:
In this study, we investigate the impacts of three institutional pressures on corporate greenwashing strategies, with a special focus on the regulative, normative, and cognitive pressures stemming respectively from governmental supervision, media coverage, and ESG rating divergence. We further examine the moderating effects that campaign-style environmental enforcement has on these impacts - specifically, the effects of the top-down intervention facilitated by the central environmental protection inspection mechanism. Our empirical analyses provide robust evidence to substantiate the constraining effects of various institutional pressures on greenwashing.
View Article and Find Full Text PDFJ Environ Manage
January 2025
School of Banking and Finance, National Economics University, Hanoi, Viet Nam.
This study examines the impact of the mandatory greenhouse gas emissions reporting program (GHGRP) on corporate greenwashing behaviour. Utilising the GHGRP in the United States as a quasi-natural experiment, we perform a difference-in-difference analysis to a panel dataset of 2731 publicly listed US firms from 2007 to 2022. The data consist of annual observations of firm-level variables, including ESG performance and disclosure metrics, financial characteristics, and environmental innovation indicators.
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