Climate Washing Signals Behind the ESG Illusion Veil: Symbolic Spillovers, Market Response Channels, and AI-Driven Transitions

This thesis examines the darker side of Environmental, Social and Governance (ESG) practices using a global panel of 13,486 publicly listed firms across six continents between 2010-2023.

The first essay investigates the internal dynamics of the ESG washing cycle, examining the interdependence among governance, social and climate washing, and the role of human rights and legal enforcement mechanisms in disrupting the cycle. Drawing on legitimacy theory, institutional isomorphism, and the normalisation of deception, it shows that social washing precedes and significantly drives climate washing, with mediation analysis confirming that governance washing provides the legitimacy cover that enables this spillover. Contextual analysis reveal that the ESG washing cycle is most prevalent in North America and Asia, and in real estate, technology, and telecommunications sectors. At the firm level, it is strongest in firms with high ESG ratings, positive returns, larger operations, and operating efficiency (profitability). Moderation analysis reveal that internal human rights compliance and country level legal enforcement significantly moderate and weaken this cycle. This essay contributes a novel conceptualisation of the ESG washing cycle and its mitigating mechanisms.

The second essay investigates how financial markets price climate washing signals over short and long horizon windows, and the channels through which these signals affect firm valuation, specifically stock price crash risk, ESG rating downgrades, heightened agency costs and deteriorating profitability. Grounded in signalling and market efficiency theories, the findings show that investors initially misprice climate washing, rewarding firms with short term valuation gains. However, as misrepresentation becomes evident, markets impose sharp corrections, resulting in long term underperformance. Cross-sectional tests further validate the information-asymmetry mechanism. The boom-bust pattern is stronger in environments with lower transparency and weaker monitoring and attenuated where disclosure verification and institutional oversight are stronger. Mediation analysis reveal that stock price crash risk, ESG rating downgrades, agency costs, and reduced profitability mediate the negative effect of climate washing on long term. This essay contributes the first evidence of a systematic market-pricing cycle for climate washing and identifies the mechanisms through which misrepresentation erodes firm value.

The third essay evaluates whether artificial intelligence adoption (AIA) can mitigate climate washing, investigating then mediating channels, and the condition under which mitigation is possible. Drawing on institutional, dynamic capability, and ecological modernisation theories, the study shows that AIA significantly reduces the likelihood of climate washing and increases firms' probability of transitioning away from it. Mediation analysis demonstrates that AIA operates through improved emission performance, reduced information asymmetry, and strengthened climate governance. Moderation analysis reveals that the mitigating effect of AI only materialises when it is strategically aligned, whereas unaligned AI produces sophisticated forms of algorithmic climate washing. This essay contributes a new theoretical link between AI strategic alignment and credible sustainability practices, positioning AI as a dynamic capability that enhances climate accountability only when strategically aligned.

Collectively, this thesis advances theory by conceptualising the ESG washing cycle, uncovering the market-pricing mechanisms of climate misrepresentation, and identifying AI strategic alignment as a capability that fosters credible climate practices. It introduces the first comprehensive multidimensional ESG-washing metric and integrates mediation-moderation frameworks across institutional, financial, and technological domains. Empirically, it provides global, sectoral, and firm-level evidence on the drivers, consequences, and mitigation of ESG misrepresentation. The findings offer actionable insights for regulators, investors, and firms seeking to strengthen sustainability governance and restore trust in ESG disclosures.