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 141–160 of 1232 papers
Jiang Y.
This study builds and empirically tests a machine-learning-based risk assessment model for green finance. It offers a data-driven approach to quantifying risks in green lending and investment. Though the abstract is unavailable, the work si…
Yim T.Y.
This work proposes an AI-powered framework for analyzing TCFD climate disclosures. It aims to enhance transparency and trust, helping investors and regulators compare and verify disclosure quality. The approach advances automated, higher-qu…
Hairin Nisa Meor Nordin, Zamri Miskan, Anis Shafiqah Mohd Saidun +2
Using RBV and dynamic capabilities theory, this study tests how AI-driven operational integration affects environmental performance through case studies of Unilever, Amazon, and Tesla. It reports 64% logistics CO₂ cuts via predictive load p…
Aditya Ravindra Pawar, A. Zuting, Arjun Dhanjay Shedage +2
Proposes an ML framework to classify construction material combinations into carbon-impact categories, targeting embodied carbon in large residential projects. Using 520 scenarios built from ICE carbon-intensity data and Pune, India constru…
Mariem Mrad, M. Frikha
A systematic scoping review of 23 Scopus studies (2013–2024) on AI and robotics for low-carbon supply chains. AI-driven logistics optimization is the most reported transport-emission strategy, while robotic automation improves warehousing e…
Chang Shu, Xiao Kang
This repository provides Python code for constructing and validating an Employee Welfare Semantic Score (EWS) using transformer-based semantic embeddings, cosine similarity, and top-K aggregation. It also implements OLS regression, two-way …
Chanjuan Zhang, Yuee Guo
This work builds a neural-network-based risk assessment model for low-carbon project financing and discusses its application. It targets quantitative evaluation of credit and project risk in financing decarbonization projects. With no abstr…
Chua Shang Hu, Dr Chua Chong Keow
This paper proposes a Malaysia-specific framework linking AI-enabled ESG reporting to profitability, firm value, and cost of capital. It treats AI capability as a multidimensional reporting construct (automated capture, analytics, assurance…
Sandhya Rani, Rukmini Mythili
This study examines integrating AI into ESG reporting, focusing on India's BRSR framework. It argues traditional reporting is data-heavy, slow and error-prone, and that AI can mitigate these challenges across ESG frameworks. Using secondary…
A. Rahmath Nisha, V. S. Deepthi, M. Ashwin Kumar
This book chapter examines how AI can accelerate sustainability transitions and green innovation systems for climate action. It surveys AI applications across energy optimization, climate modelling, sustainable agriculture, circular economy…
Douthat, Thomas, Valladares-Castellanos, Mariam, Mukhopadhyay, Supratik
This dataset and supplementary code support a graph-based geospatial resource integrating multiple data sources for AI-driven CO₂ storage site selection. It organizes geological, environmental, infrastructural, and socio-economic data into …
Nainesh Patel
This paper examines how AI can strengthen transparency and accountability in CSR, addressing greenwashing, inconsistent metrics, and self-interested point-in-time assurance. Based on a structured review of 2011–2024 literature and instituti…
Naseema N.
An introductory piece framing the integration of sustainable finance and AI. It likely surveys how AI can support ESG data analysis and evaluation, though no abstract is available to confirm findings. Useful as a conceptual entry point to t…
Di Tollo G.D.
This study applies a neural network to predict ESG disclosure behavior among SMEs, a segment with sparse disclosure data. It demonstrates how machine learning can estimate disclosure likelihood where reporting is limited, with potential use…
Guan-Jie Li
Examines how AI is reshaping financial risk management as sustainable finance shifts from principles to hard limits. Reviews AI applications in ESG data integration, climate transition risk quantification, and carbon finance pricing, while …
Iryna Spilnyk, Pavlo Spilnyk
This conceptual study develops the 'From Data to Green Value' framework, positioning AI-enabled accounting as an information-transformation mechanism that converts data assets into reliable, connected financial and non-financial information…
Zhyhlei, Iryna
A dataset scoring 24 major Ukrainian firms across six sectors on 37 ESRS-aligned indicators for FY2024–2025 (48 company-years). It links 1,776 coding decisions to source documents, pages and excerpts, and releases Python scripts for text ex…
Mohammad Hatta Fahamsyah, Dian Sulistyorini Wulandari, Muhammad Najamuddin Dwi Miharja +3
Using 2020–2025 panel data from Indonesian Islamic commercial banks, this study tests whether AI readiness and digital infrastructure improve profitability (ROA) via sustainability performance. Disclosure-index measures show both capabiliti…
Swati Dronkar, Sapana Choudhari, Shruti Wankhede +3
CarbonWise is an AI-driven Green Software Engineering platform that analyzes GitHub repositories to estimate energy use and CO₂e emissions from CI runtime, storage, and network activity. It computes a composite sustainability score combinin…
Lujia Yang, Yiheng Lu, Zherui Wang +4
This paper introduces MineClaim, a benchmark for LLM-based verification of ESG claims and greenwashing detection in Australian mining reports. It systematizes the task of matching qualitative ESG claims against supporting evidence, enabling…
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