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 301–320 of 1055 papers
Gyamfi B.A.
This paper uses causal machine learning and Bayesian methods to analyze the impact of green financing on corporate leverage and dividend policy. It estimates the causal effects of green bonds and sustainability-linked loans on firm financia…
Van Tam N.
This paper maps the causal relationships of generative AI adoption for net-zero built environments using expert insights and paradox theory. It reveals complex interactions between opportunities and challenges, offering implications for pol…
Jing Song, Xiaoyu Xu, Qi Li +2
This study proposes an improved AHP-Ridge Regression hybrid model for evaluating consumer trust in cross-border B2C e-commerce, integrating expert knowledge with consumer data. Validated on 387 survey responses, it achieves better predictiv…
F. Kelechi, A. Aribisala
This paper proposes a blockchain-based (Hyperledger Fabric) automated system for tracking Scope 1 and 2 emissions in indigenous Nigerian oil and gas companies. It reduces manual reporting time by 75%, eliminates errors, and ensures IFRS S2-…
Sheikh Ali Tanzil, Kishor Chandra Meher
This qualitative study examines how Fijian listed companies navigate global ESG mandates and local institutional constraints, using managerial sensemaking. It reveals a 'digital decoupling' where firms use digital infrastructures as a symbo…
Thi Loan Bui, Oanh Thi Tran, Nguyen Thi Kim Oanh +2
This paper proposes an NLP-based method to automatically classify ESG-related information from Vietnamese corporate annual reports, aiming to streamline disclosure analysis and automate ESG assessment. It sits at the intersection of AI and …
Shaofei Wang, Ruyi Wei, Yuqi Li +4
This study proposes ReDP-VT, a novel deep learning model for forecasting greenhouse gas concentrations using TCCON observations. It leverages frequency-domain inter-gas dependencies to guide Transformer self-attention, capturing dynamic rel…
Michelle Doorasamy, O. Fapetu, Pelumi Abdulmalik Adewumi
Using panel data from Nigeria and South Africa (2010-2022), this study examines how climate finance (CF) and environmental risk accounting (ERA) affect firm value. Employing AI-powered textual analysis to measure climate financial exposure …
Shawn Wang
Using panel data from 266 Chinese cities (2011-2020), this study finds an inverted U-shaped relationship between AI development and urban carbon emission intensity (CEI): AI initially increases CEI but reduces it after a turning point. By 2…
Umesh Ganesh Iyer, Sukhpal Singh Gill
This paper explores how AI-driven cloud resource management can contribute to net-zero carbon emission goals. It proposes methods to optimize energy consumption and reduce carbon emissions through AI, enhancing sustainability of cloud data …
Sunday Idowu
An IoT platform using ESP32 and PZEM-004T sensors monitors household electricity usage and CO2 emissions in real time. Tested with 100W incandescent and LED bulbs, it achieved <3% error and <2s response time. CO2 is calculated using an emis…
I. P. Okwuosa, O. J. Odejobi
This study optimizes biogas steam reforming for low-carbon hydrogen production using ANN integrated with GA. The ANN was trained on Aspen HYSYS simulation data, and GA optimized operating conditions to achieve a hydrogen mole fraction of 0.…
E. P. Egbe, E. O. Diemuodeke, E. G. Udonkwo +1
This paper develops a data-driven GHG accounting software for Nigeria's oil and gas sector, automating Scope 1 and 2 emissions estimation based on the API Compendium. It addresses manual, fragmented practices by integrating operational and …
Kashaf
This review outlines smart plantation as a nature-based solution integrating strategic vegetation placement with digital technologies (AI, sensors, remote sensing) to reduce air pollutants, store carbon, and improve urban microclimates. It …
Natalia Fabra, Clément Leblanc, Mateus Souza
This study quantifies the distributional impacts of the Iberian solution, a wholesale electricity market intervention in Spain and Portugal during the 2021-2023 European energy crisis, using machine learning and market simulations. The cris…
Futi Liu, Zian Zhao
This paper addresses ESG-aware portfolio optimization under decision-dependent return uncertainty. It constructs a joint polyhedral uncertainty set and formulates a two-stage robust optimization with CVaR constraints, solved via column-and-…
Idham Idham, Chusnul Rofiah
This study examines how cyber-auditing and the conceptual foundation of digital assurance redefine auditors' roles in multinational firms. Using a systematic literature review, it finds that integrating AI and data analytics into audit prac…
Yingwen Guo, Miao He, Weiyin Zhang
This study examines the impact of geographic proximity to cancer villages on firm valuation using Chinese listed firms from 2004 to 2022. A one-standard-deviation increase in proximity reduces Tobin's Q by about 1.7%, driven by higher compl…
S. Amoo, Ali Attajer, Ismahen Zaid +1
This study develops an optimization framework for sustainable AAC production using discrete-event simulation and machine-learning surrogates. It generates 116,640 production scenarios and trains ML models to predict CO2e emissions, cost, an…
K. Sonawane, P. Saini, U. Biradar +3
This paper proposes an AI-driven integrated digital framework for CCUS to enhance containment assurance and carbon credit credibility. It integrates multi-modal data (DAS/DTS, microseismic, satellite) and uses anomaly detection, Bayesian in…
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