ESG Greenwashing and Applications of AI for Measurement

Dao, Daniel and Chu, Ngoc Anh and Bowden, James and Cummins, Mark (2024) ESG Greenwashing and Applications of AI for Measurement. University of Strathclyde, Glasgow.

Full text not available in this repository.Request a copy

Abstract

“ESG greenwashing” refers to the strategic communication tactics firms use to selectively disclose their ESG conduct to stakeholders. ESG greenwashing strategy, while it may attract and satisfy stakeholders at the beginning, may cause different issues for firms later, such as adverse publicity, lobbying, or boycott campaigns by consumer or pressure groups or divestment by socially responsible investors. The complex impacts of ESG greenwashing underscore the imperative of discerning and quantifying instances of such practices. We aim to consolidate recent literature reviews of ESG greenwashing, methodologies to measure ESG greenwashing and developing applications of AI, text analysis and machine learning models to advance such measurement. This white paper makes significant contributions to policy developments, such as the greenwashing regulations of the UK FCA and the European Parliament.

ORCID iDs

Dao, Daniel ORCID logoORCID: https://orcid.org/0000-0001-9449-8003, Chu, Ngoc Anh, Bowden, James ORCID logoORCID: https://orcid.org/0000-0002-0419-1882 and Cummins, Mark ORCID logoORCID: https://orcid.org/0000-0002-3539-8843;
CORE (COnnecting REpositories)