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 121–140 of 1232 papers
Bhagyashri K Kulkarni, Shashank Urs H P, Vinod V +2
Evaluates CarbonTrack, a completed AI logistics carbon-footprint platform, against its own code, models, and tests. Re-running the pipeline reproduced 87.5% predictive-maintenance and 91.0% route-recommendation accuracy with regression MAEs…
Liyuan Chen, Jiaying Pan
This study couples machine learning with process-level carbon accounting to quantify the net carbon benefit of CO₂ curing of cement. By integrating CO₂ uptake and emissions, it clarifies when curing technology delivers genuine climate benef…
Neema Mwita Kinyasi, Amina Juma Msuya, Baraka Mwinyi Hamisi
This paper derives identification conditions under which conventional permanence deductions in mangrove-restoration carbon credits become biased under staggered enrollment and unobserved baseline loss. Combining a potential-outcomes model w…
Shirin Saiyed, Made Ratih Nurmalasari
This integrative review examines how data-driven decision-making (DDDM) can strengthen corporate environmental performance during carbon-neutrality transitions. It identifies five value-creating mechanisms—impact visibility, analytical diag…
Marcin Trybulec, Barbara Konat, Anna Sędłak +2
A pilot, human-annotated dataset of rhetorical features in ESG reports, coded via an Aristotelian ethos/pathos/logos scheme. It serves as reference data to develop and calibrate LLM prompts for scalable rhetorical analysis across 100 ESG re…
Culasso F.
Applies topic modeling to integrated reports, mapping cross-industry disclosure themes and global patterns. It shows how AI text analysis can reveal the thematic structure of corporate integrated reporting. Useful evidence for disclosure-in…
Lehenchuk, Serhii, Zhyhlei, Iryna
Cross-sectional dataset of 101 European listed consumer goods (n=56) and food & beverage (n=45) firms for FY2024. It provides five readability indices of sustainability reports plus page length and a composite PC1 measure, LSEG ESG ratings …
Ngoc-Son Truong, T. Nguyen, T. Nguyen +2
This study integrates 6D BIM, Autodesk Insight simulation, and machine learning to analyze and predict total embodied plus operational carbon for a bank building in Da Nang, Vietnam. Multi-scenario envelope simulations generate data used to…
Inez Permatasari, Noer Sasongko
Using 138 firm-year observations from 46 Indonesian energy firms listed on IDX (2022–2024), this study tests how AI and big data analytics (BDA) affect sustainability reporting audit quality (SRAQ), moderated by ESG disclosure and operation…
Tizian Latzka
Up to 80% of a product's lifecycle impacts are locked in early design, yet traditional LCA demands full BOMs and expert knowledge—the 'Ecodesign Paradox.' Using an AI-assisted PRISMA review and empirical testing of eight tool archetypes on …
Rajesh Kumar, L. Malusare, Farhan Alam +2
This conceptual paper reviews how AI is transforming financial reporting and auditing—from automated bookkeeping and fraud detection to continuous auditing, blockchain assurance, and AI-based sustainability reporting. It catalogues challeng…
Yi-Kang Ji, Tian-Zhen Li, Meng-Di Liu
This paper proposes and validates AutoCarbonVAR, an LLM-driven framework that automates carbon price factor decomposition via plain-language queries, combining LLM reasoning with VAR estimation, impulse response, and variance decomposition.…
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The paper introduces CMP-DSTCL, a deep-learning model that forecasts corporate green innovation (green patents) by fusing ESG disclosure text with mechanism-typed signed interfirm graphs. It adds a greenwashing contrast loss, an edge-mechan…
Mutmainah _, Melinda Wijaya
Panel fixed-effects study of Indonesian and Malaysian Islamic commercial banks (2021–2025) testing whether disclosed AI capability improves ESG disclosure quality, reduces greenwashing, and lifts sustainability performance. AI is positively…
Hugo Prasetyo Winotoatmojo, Meiryani Meiryani, Bambang Leo Handoko +1
Using a balanced panel of 1,230 bank-year observations across 205 banks in 10 Southeast Asian countries (2020–2025), this study examines links between AI disclosure, ESG performance, and Tobin's Q. AI disclosure is positively associated wit…
Thing-Yuan Chang, Chien-Chih Chen, Chin-Hsien Hsu +2
A GMM-based framework routes reference foods to outcome-specialized regressors (KNN, random forest, XGBoost) using predictor-space neighbors, trained on ~472k observations linking multilingual LEAF names to AGRIBALYSE 3.1.1 climate values a…
Tin-Yu Wu, Chu‐Fu Wang, Wei-Che Chien +2
Proposes a Deep Q-network reinforcement learning mechanism that dynamically adjusts routing to reduce carbon footprint. The AI optimizes emission-aware route selection, targeting logistics decarbonization. Detailed results are unavailable a…
Yi Yang
This paper proposes a framework combining multimodal remote sensing, LiDAR point clouds, and domain large language models to integrate 3D urban green-space assessment with full-life-cycle carbon accounting for landscape engineering. It desi…
Funmilayo C. Jayeola, Masengo Ilunga
This PRISMA-based systematic and bibliometric review of Scopus literature (2015–2026) maps how AI and explainable AI (XAI) are used to assess embodied carbon (EC) and decarbonize building materials. Research surged after 2023, with ML metho…
Zhu J.
An empirical study forecasting Chinese corporate green bond issuance using ESG scores and tree-based machine learning models. It tests whether ESG ratings serve as a predictive factor for green bond issuance, highlighting the value of ESG d…
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