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 1–20 of 1055 papers
Arslan M.
This paper thematically analyzes blockchain and AI applications in sustainable finance, mapping research trends around green bonds, ESG assessment, and transparency. It offers a foundational overview of how these technologies shape sustaina…
Xingjun Ru, Yingying Lu, Shaofeng Chen +1
This study analyzes 3,460 Chinese central environmental policy documents (1978–2025) using an integrated computational framework combining LLM-based semantic enhancement, dynamic topic modeling, and multi-layer validation. It traces five cu…
M. A. F. Singh, Navjit Singh, Vikas Sharma +1
Using 625 Indian IPO prospectuses (2018-2024), this study examines construct alignment between LLM-generated and lexicon-based ESG scores. Methods converge for environmental disclosure (κ=0.56) but diverge for social and governance, with on…
Hemendra Kumar R R, Jayanthi P
This paper proposes an AI framework that estimates meal-level carbon footprints directly from food images. A YOLOv8m object detection model trained on 31 Indian food categories (7,438 images) achieved 90.4% mAP@50. Detected items are mapped…
Ioannis C. Ploumpis, Nikolaos Eriotis, A. Christopoulos +2
This study uses PLS-SEM on survey data from 150 ESG audit professionals to test how AI automation and AI decision making affect audit efficiency, accountability, and transparency. Both AI dimensions improve all three outcomes, with human ov…
Tamara Menichini, José María Fernández-Crehuet, Nicoletta Maria Strollo
This study develops the tech-quality reporting (TQR) framework, conceptualizing digital reporting as a dynamic capability that enhances sustainability reporting quality (SRQ). Through a systematic literature review, it shows how blockchain …
Pavan Manjunath, Thomas
CarbonCreditBuy is an open-source geospatial platform that estimates tree-based carbon removal on farmland using Earth-observation layers (ESA WorldCover, Sentinel-2 NDVI/NDMI) and configurable parameters, applying IPCC 2006 Tier 1 (Tier 2 …
Hoko Energy and Projects, Siyabulela Hoko, Asithandile Mgweba
EGSIS is a low-cost, solar-powered, AI-enabled irrigation and water management system for small-scale vegetable growers in South Africa. It replaces calendar-based watering with soil-moisture-responsive irrigation, runs on a LiFePO4 battery…
Essam AlArbed
Using a 2016–2025 panel of 100 U.S. firms, this study examines how AI adoption affects ESG assurance quality and whether CPA expertise moderates this link. AI adoption and CPA expertise each directly improve assurance quality, and their int…
Ahmad, Iftikhar
This study examines whether cognitive AI recommendations can drive carbon-neutral consumption, modeling links among AI recommendation quality, carbon literacy, green trust, and sustainable purchase intention. It posits that AI recommendatio…
Shi-Hong Wei, Kai-Ming Tan
This study builds a binary classifier predicting high-ESG Chinese A-share firms from financial and governance indicators (2014-2022). Random Forest outperformed Logistic Regression with accuracy 0.6734, F1 0.6186, and ROC-AUC 0.7824. It sho…
Juan-Juan Luo, Yu-Ru Zong, Di-Yu Ou Yang
This study develops an LLM-based (Claude 3.5 Sonnet) ESG analytics pipeline to automatically extract six indicators from 12 ESG reports (2021–2024) of three leading Chinese logistics firms: SF Express, Cainiao, and JD Logistics. Achieving 9…
Luis Martín-Domingo
A 6-minute podcast summarizing Martín-Domingo et al. (2025), which uses LLMs to extract airline emission KPIs from sustainability reports. Generated with NotebookLM and author-reviewed, it highlights how AI can automate extraction of emissi…
Isnaini Nuzula Agustin, Frendy Wijaya, Lusianus Heronimus Sinyo Kelen +1
Using Indonesian Stock Exchange non-financial firms (2016-2024), this study examines carbon risk's effect on stock performance and AI innovation's moderating role. Carbon risk marginally lowers returns and raises volatility, while AI innova…
Jianhua Ma, Yongzhang Zhou, Xian Liu +2
This paper proposes Mini-CarbonLLM, a resource-efficient knowledge-augmented LLM framework for environmental decision support in carbon neutrality engineering. By augmenting domain knowledge externally rather than scaling model size, it ena…
A. Masum, Md. Abul Kalam Azad, Najmus Saadat +5
A bibliometric review of 388 documents plus systematic analysis of 39 implementation studies on AI in sustainable finance. Tree-based ensembles dominate structured ESG assessment, while Transformers/LLMs extract narrative signals from text …
Atul S. Kurzekar, Khalid S. Ansari, Mukhtar Hamid Abed +5
This study assesses the performance and carbon footprint of marble-dust geopolymer concrete, integrating a CNN-based crack classification framework. It combines cement-substitution decarbonization with AI-driven quality inspection, illustra…
Congmin Zhu, Esperanza Deigo
AI climate solutions are often credited with gross avoided emissions without deducting AI's own life-cycle footprint. This study proposes a reproducible framework combining gross avoided emissions, operational emissions from training/infere…
Ziru Bao, Xiaowen Zhang, Chengcheng Lu +1
This study examines whether the topic complexity of ESG report text affects ESG scores. It links disclosure content characteristics to rating outcomes, likely using text-analytic methods to probe how rating agencies form scores. It offers i…
(著者不明)
Based on the title alone (no abstract available), this work appears to apply large language models to energy and carbon footprint assessment. It sits at the AI × ESG intersection gxceed prioritizes, with potential to automate carbon/energy …
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