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 261–280 of 1055 papers
Sejan, Sajid Hassan, Apu, Arman Hossain
This dataset provides monthly embodied GHG emissions for 616 NAICS-6 commodities from US federal procurement (FY2015-FY2024), covering $2.77 trillion and 486.9 MtCO2e. It exactly joins contract obligations with EPA emission factors, validat…
Pengyu Zhang
This study empirically examines how ESG rating fluctuations affect investor psychology (anxiety, stress) and subsequent market reactions, using panel data from 1,236 Chinese A-share firms (2018-2023) and machine learning/big data analysis. …
K. Logožar
This paper proposes the VAF framework, arguing that smart ports can serve as governance infrastructures that make maritime flows visible and accountable. It integrates digital technologies like AI, digital twins, and blockchain with governa…
V. Vignesh, G. V. Narendran, R. Senthil Kumar +1
A hybrid framework integrating Fuzzy C-Means clustering with temporal deep learning (NARX, RNN, LSTM, GRU) is proposed for multi-parameter forecasting in blast furnaces. Evaluated on 43,396 industrial DCS samples, FCM-GRU achieved the best …
Kejun Xie
This study examines the relationship between board environmental expertise and carbon disclosure quality (CDQ) using 28 ASX-listed firms. Analyzing 140 firm-year observations from 2019-2023 with Tobit regression, it finds a significant posi…
Patrycja Hąbek, Kjartan Sigurðsson, Małgorzata Radomska
This paper examines the impact of AI on sustainability reporting. It discusses how AI can automate ESG data collection, analysis, and disclosure, enhancing efficiency and accuracy. It also addresses challenges and regulatory implications of…
Dajiang Liu, Tao Yu, Huiying Xu
This paper proposes a GAT-LSTM hybrid model for dynamic carbon footprint accounting in prefabricated steel structure buildings, integrating spatio-temporal data to estimate emissions across the construction process. It overcomes limitations…
Tarak Barhoumi, Najoua Mezghani
This paper proposes CarbontoScope IA–SFAX, an augmented intelligence system to visualize urban carbon footprints, applied to Sfax, Tunisia. It identifies hidden emission sources, providing data for urban planning and policy. Integrating AI …
P. Vibin Sri Balaji, Srinivasan R
This study proposes an AI-based framework integrating satellite data and machine learning to identify optimal solar plant sites and forecast 10-year energy output. Using NASA POWER data and Random Forest regression, it achieves high predict…
P. Vibin Sri Balaji, Srinivasan R
This study integrates satellite data and machine learning to identify optimal solar installation sites and forecast 10-year energy output. Using NASA POWER data and physical PV modeling, Random Forest achieves high predictive accuracy (R²≈0…
Kaithari D.K.
This review surveys AI systems for real-time monitoring and optimization of ocean-based carbon capture, utilization, and storage (CCUS) networks. It synthesizes how AI enhances efficiency and risk management in carbon capture and storage, a…
Pranav Nerurkar
This paper empirically examines the 'green halo effect,' revealing real-world inconsistencies between ESG scores and retail investor sentiment. It analyzes how ESG ratings influence investor perception and behavior, questioning the reliabil…
B.K. Tripathy, Riya, Hemant Kumar Saini
This chapter explores energy-saving solutions to reduce the carbon footprint of UAVs across their life cycle. It covers AI-based optimization (ML for energy-aware routing, RL for navigation, GANs for flight energy prediction), blockchain fo…
(著者不明)
This paper explores AI-driven circular economy strategies to achieve carbon neutrality in emerging economies. It discusses how AI optimizes resource efficiency and waste reduction, contributing to emission cuts, with implications for policy…
Isaiah Oluwasegun Owolabi
This paper introduces ESG-as-Code, a deterministic rule-based framework that converts ESG regulatory obligations (CSRD, SFDR, SDR, SEC rules) into machine-executable rule logic. It separates probabilistic interpretation from deterministic c…
Yang S.
This paper proposes a hybrid BiLSTM-XGBR model to predict corrosion depth and compressive strength of cement stone in CCUS wells. It applies AI to assess well integrity, contributing to safe and durable CO2 storage.
K. Strang, N. Vajjhala
This single-case study analyzes ESG compliance measurement in financial software engineering projects as a socio-technical system. Applying an open-source ML workflow to 207 archival records, it finds near-unity correlations between social/…
Xinyi Wang
This conceptual paper critically examines generative AI in ESG reporting. It argues that while generative AI enhances efficiency by reducing cost and time in processing text-intensive data and drafting disclosures, it introduces challenges …
Erica Mascarenhas, Oluseyi A Fayanju, Anna Arroyo +1
The US healthcare sector leads globally in per capita GHG emissions, and federal deregulation heightens the need for voluntary action. Decarbonization across infrastructure, supply chains, and operations is feasible via renewable energy, wa…
W. Wardhiah, Maimoona Majid, Said Musnadi +1
Using panel data from 30 Indonesian firms (2020-2025) linked to the LQ45 Low Carbon Leaders Index, this study examines whether digital transformation (DX) helps convert energy-transition strategies into financial value. A 30-item DX index a…
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