This page provides an English interface to the gxceed GX paper corpus. The corpus aggregates papers from 14 contributing scholarly metadata sources and uses AI-assisted classification to identify signals related to measurement, policy narratives, outcomes, implementation, industrial adoption, and verification.
The goal is not only to discover papers, but to observe how GX research is distributed across research substance, implementation narratives, external expectations, implementation substance, and judgment formation.
Summaries are AI-assisted. Always refer to the original paper for authoritative conclusions.
Showing 401–403 of 403 papers
Dr.Rachana Saxena, Hashim Khan, Dr.Mohsina Hayat
This paper critically examines how AI is reshaping corporate sustainability reporting and green accounting. It analyzes AI applications such as automated carbon accounting, environmental footprint analysis, real-time monitoring, and AI-assi…
Tianyi Ren
This paper examines how AI-powered carbon footprint tracking can reshape green investment decision-making by delivering near-real-time, high-resolution estimates of Scope 1-3 emissions, especially Scope 3. It synthesizes methods combining N…
Nadia Mansour
This systematic review of 42 studies (2018–2025) examines AI, IoT, and blockchain in sustainable finance. It identifies three application areas: enhanced MRV of environmental impacts, improved physical and transition risk control via predic…
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