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 21–40 of 1487 papers
(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 …
D'Adamo I.
Proposes a hybrid method combining neural networks with multicriteria decision analysis to assess emission trading systems and carbon leakage. It links carbon pricing policy to industrial competitiveness and emission shifting, blending ML p…
Hong Viet Le
Using a five-year panel of 500 S&P 500 firms and Sustainalytics ESG Risk Ratings, this study applies Light GBM to test whether ESG risk maps linearly to equity returns. It finds a U-shaped pattern: high-risk firms deliver the strongest retu…
Rabia Akram, Hafiz Muhammad Naveed, Muhammad Usman Anwer +4
Using quarterly-decomposed data (ICEEMDAN) for 15 RCEP economies (2000–2024), the study benchmarks 15 neural/deep-learning models to predict CO2 emissions; an RBF network performed best (MAE 0.028, RMSE 0.040). SHAP analysis shows patents a…
Andreas Errikos Delegkos, Evangelia Arsenou, Dionisis Cavouras +2
Using Ohlson's framework, this study combines panel econometrics with Random Forest to assess value relevance of ESG and innovation disclosures in European non-financial firms. Social-governance and environmental innovation show no linear l…
Hamdi Khalfaoui, Ameni Trabelsi
A qualitative case study of a Tunisian energy-intensive tobacco plant examines how green finance and AI can jointly enable the industrial energy transition. Based on 30 interviews and triangulated institutional data, it reveals a significan…
Alessio Faccia
Using 1,450 Form 10-K firm-years from 250 CIKs (FY2014–2024), this study examines whether the US Inline XBRL phase-in is associated with disclosed AI orientation. After Holm adjustment, none of four reporting indicators support the hypothes…
Angga Eka Wahyu Ramadan, W. Widodo, Erick Abriandi +1
Pertamina's Bandung fuel terminal evaluated a 2-hectare biodiversity and reforestation program in West Java. Using the AI-driven ARUNA Carbon Intelligence platform with QR coding and geotagging, the study measured tree, sapling, understory,…
Jiyizhe Zhang, P. Yaseneva, Alexei A. Lapkin
This Account reviews how AI and digitalization can accelerate chemistry's transition to net-zero. It covers data-mining of value chains for net-zero feedstocks, AI-driven discovery of catalysts, solvents, and reaction conditions, and AI age…
Agus Munandar
A bibliometric mapping of 277 Scopus-indexed articles (2000-2026) using Bibliometrix and VOSviewer traces how AI entered accounting research. Publication surged after 2021 around auditing, generative AI/LLMs, blockchain, and machine learnin…
Mansi Sudhir Kadam
This paper examines how AI can strengthen the link between ESG and financial reporting through data processing, anomaly detection, disclosure preparation, forecasting and digital reporting. Drawing on IFRS S1/S2, the IFRS Sustainability Dis…
John Amoah-Nuamah, Emmanuel Yeboah Okyere, Osman Adams +1
A PRISMA-S review of ~95 studies (2010–2026) synthesizes how AI, machine learning, and deep learning are applied to forest-carbon assessment and climate mitigation. AI expands capacity for biomass estimation, carbon-stock mapping, flux mode…
Xavier Martínez-Barbero, Ana Pastor-Merino, Josep Domènech
This paper proposes a scalable method to measure firm-level energy transition engagement using corporate website disclosures and LLMs. A restrictive, policy-aligned rubric codes energy efficiency, decarbonization strategies, and renewable e…
Bondinuba, Francis Kwesi
Generative AI is used to design lower-carbon buildings, yet standards like EN 15978 and RICS whole-life carbon exclude the energy used to train and run AI models. This concept note proposes Computational Carbon Accounting (CCA), which measu…
José Alejandro Fernández Fernández, Renata Kubus, Inés Martín de Santos
Using 2,612 US firm-year observations (Refinitiv, 2019–2022) across five sectors, this study applies explainable ML (random forests, SHAP, partial dependence) to link financial health and ESG scores. Firm size is the most consistent predict…
Andy Dwiki Iranda, M. Mujiya Ulkhaq
This study analyzes 62 sustainability reports from Indonesian listed companies (fiscal 2023) using word frequency analysis via Orange Data Mining. Terms were categorized into four CSR dimensions: environmental (54.6%), social-labor (28.7%),…
Masradin Masradin, Syamsuddin Syamsuddin, Neks Triani +2
This systematic literature review (PRISMA 2020) examines Big Data and AI in capital-market-based accounting, synthesizing 29 studies into four aspects: data infrastructure, analytics, disclosure/reporting, and governance/assurance, integrat…
Rinaldi Sinaga, Enny Susilowati Mardjono, Nila Tristiarini
Using NLP on 198 palm oil plantation firms across eight producing countries, this study builds a Greenwashing Severity Index (GSI) measuring divergence between corporate ESG self-disclosure and external media/NGO narratives. It integrates E…
Dong-Xue Qiao
As EV competition shifts to data-driven agility, traditional rear-view marketing causes forecast distortion, inventory imbalance, and higher lifecycle emissions. Based on BYD, Tesla, and Geely, this paper builds a sustainable marketing fram…
J. de Lara, Esther Guerra, Jacinto Corral +1
This paper proposes an intelligent, model-based approach to automating sustainability reporting. It appears to use model-driven methods to structure disclosure items and streamline the reporting process. Though no abstract is available, it …
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