ESG rating disagreement as a greenwashing signal: asymmetric effects of digital transformation through disclosure and performance channels

Abstract

This study examines whether ESG rating disagreement is a leading indicator of corporate greenwashing and how digital transformation (DTI) moderates this relationship through disclosure and performance channels. Using 8111 firm-year observations from Chinese A-share companies (2012-2022), we employ two-way fixed-effects panel regression complemented by Bayesian-optimised machine learning models interpreted through SHAP. Aggregate rating disagreement is a strong and robust predictor of greenwashing. Channel decomposition reveals asymmetric DTI moderation: the disclosure channel amplifies greenwashing risk as digitally advanced firms expand reporting capacity to widen the gap between disclosed and actual ESG performance (bloom_DTI: beta = +0.2471, p < 0.01), while the performance channel attenuates greenwashing risk as digital operational monitoring translates substantive performance into a measurable reduction (hua_DTI: beta = -0.2804, p < 0.01). This pattern is robust across ownership structure, pollution intensity, and region. Machine learning analysis confirms the econometric findings and reveals nonlinear threshold effects invisible to panel regression. This asymmetric channel mechanism contributes to the ESG rating divergence literature and has implications for disclosure regulation and ESG-based investment screening.