GX Research Hub · English

GX & Decarbonization Research

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.

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Showing 5681–5700 of 27952 papers

Peer-reviewedJournalSustainability Switzerland2023#Energy TransitionDOI

Perspectives on Taiwan’s Pathway to Net-Zero Emissions

Chen P.H.

This paper provides perspectives on Taiwan's pathway to net-zero emissions, likely discussing renewable energy deployment and policy frameworks. Specific findings are unclear due to lack of abstract, but it focuses on policy and technologic…

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Peer-reviewedJournalAnnals of "Constantin Brâncuși" University of Târgu Jiu - Economy Series2026#Climate FinanceDOI

GREEN INVESTMENTS, ENERGY TRANSITION, AND FINANCIAL MARKETS: A BIBLIOMETRIC REVIEW OF THE 2021–2025 LITERATURE

DENISA-MARIA Marin, I. Croitoru, Andreea Barbu +4

This study provides a bibliometric review of literature on green investments, energy transition, and financial markets from 2021-2025. Analyzing 154 documents from Web of Science with VOSviewer, it identifies three thematic clusters: green …

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Conference2026 International Conference on Sustainable Engineering and Technology Innovations (ICSETI)2026#AI × ESGDOI

Green Finance Decision Support System: ML and XAI-based Loan Assessment for Renewable Energy and Smart Infrastructure

R.Kaladevi, V.Umarani, V. N +1

This study builds an ML and explainable AI system to assess green loan eligibility. Using synthetic data, multiple models were evaluated, with Gradient Boosting achieving high accuracy. SHAP analysis identified credit score and energy effic…

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Peer-reviewedCNJournalSustainability2026#AI × ESGDOI

Artificial Intelligence and Corporate Sustainability: Evidence from China’s National Artificial Intelligence Innovation and Development Pilot Zone Policy

Yukun Sang, Kannan Loganathan, Lu Lin

Using China's AI Pilot Zone policy as a quasi-natural experiment, this study employs a multi-period DID approach on listed firms (2014-2024) to show the policy significantly improves corporate sustainable development performance (SDP). Dyna…

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