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ESG performance and the green finance ecosystem

Sep 2026 · Journal on Innovation and Sustainability RISUS · 0 citations · 11 references

Abstract

Green credit has become a central financial instrument for channeling capital toward environmentally responsible economic activity, and corporate ESG performance is increasingly used by financial institutions to assess counterparty risk. Yet whether these two constructs form a genuinely reciprocal relationship, and how this relationship is embedded within the broader green finance ecosystem, remains inconsistently understood. This study conducts a PRISMA 2020-guided systematic review of the Scopus database, screening 802 records against pre-registered eligibility criteria to identify 383 eligible studies published between 2017 and 2026. Bibliometric analysis reveals a rapidly expanding literature, with 68.1% of the corpus published in the two most recent years, alongside pronounced geographic concentration: 72.3% of studies originate from Chinese institutions, and difference-in-differences designs anchored to China's 2012 Green Credit Guidelines dominate the methodology. A three-topic model identifies distinct thematic clusters spanning ESG disclosure and greenwashing, green finance policy and digital transformation, and banking governance. Manual reading-based coding of all included studies further reveals that only 66 studies (17.2%) directly test a green credit–ESG relationship, while the remaining majority examine ESG performance in relation to adjacent ecosystem constructs, including green innovation, governance, and digital transformation. These findings substantiate a directionality imbalance: reverse-pathway evidence, in which ESG performance shapes financing outcomes, is considerably thinner and less green-credit-specific than forward-pathway evidence. The review provides a systematic mapping of this literature's structure, geographic concentration, and methodological orientation, establishing a foundation for a forthcoming thematic synthesis addressing the field's core directionality and generalizability gaps.

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