GX Research Hub · English

GX & Decarbonization Research

This page provides an English interface to the gxceed GX paper corpus. The corpus aggregates papers from 13 open 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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Topic: #AI × ESG (clear)

Showing 201–220 of 991 papers

Peer-reviewedCNJournalScience and Technology for Energy Transition2024#AI × ESGDOI

The energy effect of blockchain technology innovation in the Industry 5.0 Era: From the perspective of carbon emissions

Yunjing Wang, Jinfang Tian, Siyang Sun +2

Using LLM and text analysis of Chinese listed firms' blockchain patents (2010–2022), this study shows that blockchain innovation reduces fossil energy intensity. Mechanisms include lower internal control costs, stronger external oversight, …

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Peer-reviewed🇪🇺 EuropeJournalZeitschrift für wirtschaftlichen Fabrikbetrieb2025#AI × ESGDOI

Sustainable Product Development and Production with AI and Knowledge Graphs

Svenja Hauck, Lucas Greif

This article reviews the role of knowledge graphs and AI in sustainability assessment, enabling comparison of environmental impacts during product development. A case study demonstrates carbon footprint analysis using these technologies, hi…

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🇯🇵→🌍 Japan-to-Global🇯🇵 JapanReport神戸大学経営学研究科 ディスカッション・ペーパー2026#AI × ESG

Survey findings on the use of AI support tools in responding to ESG/sustainability questionnaires

ESG/サステナビリティ質問票対応におけるAI支援ツール活用に関する調査結果

中尾 悠利子 中園 宏幸 石野 亜耶

This survey explores how companies utilize AI support tools when responding to ESG/sustainability questionnaires (e.g., CDP, EcoVadis), clarifying current practices and challenges. It also examines the benefits of AI adoption and future pro…

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Preprint🇨🇳 China2024#AI × ESG

Policy & Management Research

Wei Yigang, Shi Jiawei, Xu Guannan

This study analyzes 1,743 low-carbon policies issued in China from 2000 to 2021 using text mining and policy econometrics within a framework of 'policy objectives—policy themes—policy fluctuations.' It systematically reviews the development…

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Peer-reviewedJournalSustainability2026#AI × ESGDOI

Decoupling Economic Growth from CO2 Emissions in Honduras: A Longitudinal Machine-Learning and Econometric Assessment of Low-Carbon Development, 1990–2023

Dely Ramírez, Jonathan Muñoz Tabora, Ozy D. Melgar‐Dominguez

This study assesses GDP-CO2 decoupling in Honduras (1990-2023) using k-means, PELT, Tapio index, EKC modeling, Granger causality, and Random Forest. An inverted-U EKC is supported, but renewable share has negligible predictive power, sugges…

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Peer-reviewedConferenceEmnlp 2024 2024 Conference on Empirical Methods in Natural Language Processing Proceedings of the Conference2024#AI × ESGDOI

ClimRetrieve: A Benchmarking Dataset for Information Retrieval from Corporate Climate Disclosures

Schimanski T.

ClimRetrieve is a benchmarking dataset for evaluating information retrieval systems on corporate climate disclosures. It enables assessment of retrieval and question-answering performance on TCFD/ISSB-aligned reports, supporting the develop…

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Peer-reviewedJournalKaraelmas Science and Engineering Journal2026#AI × ESGDOI

Assessment of Regional Green Hydrogen Production Potential Using Multilayer Sensor and SHAP Analysis for Smart City Applications

Abdulsamed Güneş, Orhan Yaman, Elif Feyza Sari +1

This study develops an MLP model to predict green hydrogen production potential for 2,535 cities using renewable energy and hydrogen capacity data, with SHAP interpretability and Folium mapping. It accurately identifies high- and low-potent…

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