How Useful are Greenwashing Metrics for Investors from Developing Countries: A Thematic Analysis

The global rise of ESG (environmental, social, and governance) investing poses unique challenges for investors in emerging markets, who must navigate the pervasive risk of greenwashing without access to the sophisticated data, robust regulation, and institutional oversight available in developed countries. This study conducts a thematic analysis to critically assess the practical utility of existing greenwashing measurement methodologies in these limited contexts. The study fills a critical gap by focusing on environments where core analytical tools (e.g., Bloomberg, MSCI, Sustainalytics) are often unavailable, mandatory non-financial disclosures are lacking, and the ecosystem of NGOs and active regulators is underdeveloped. Based on a systematic review of academic literature following PRISMA guidelines, this article identifies and categorizes common greenwashing detection metrics into five thematic categories: data-driven methods, regulation-based models, and proactive analytical methods. The analysis introduces "usefulness" as a multi-dimensional analytical construct defined by data accessibility, regulatory independence, verification cost, and contextual robustness. The findings suggest that while data-driven methods dominate the literature, they possess limited direct utility for investors in emerging markets due to their reliance on inaccessible data and formal regulatory structures. Consequently, proactive analytical methods utilizing publicly available textual data offer greater practical viability.