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 481–500 of 986 papers
Constantinos Varsos, Adamantia Stamou, George Stamoulis +1
This presentation introduces an incentive-based framework for improving energy efficiency in ICT services, from the EXIGENCE project. It explores gamified incentives for sustainable video streaming, renewable-aware federated learning, and f…
Neetal Vyas, Manmohan Vyas, Komal Singh
This paper examines how fintech startups leverage blockchain, AI, and machine learning to drive sustainable finance, including ESG analysis, green payments, and carbon credits. They enhance transparency, reduce greenwashing, and fill gaps l…
Ameni Boumaiza
This paper proposes an AI-driven demand-side management approach for sustainable power systems in Qatar, integrating reliability and carbon pricing to achieve decarbonization and grid stability.
Ngone Mirimi, H. Manuere
AI-enabled climate decision-support systems are de facto governance infrastructures with political and accountability consequences, yet they are treated as neutral technical tools. The paper reframes transparency as an enforceable instituti…
Dr. Thanakit Ouanhlee
This study examines the relationship between AI integration in compensation systems and human capital accounting disclosure (HCAD) quality among manufacturing organizations in Thailand. It finds that while AI integration is moderate, disclo…
Hasan Talaş, E. Gök, Özen Akçakanat +4
This study uses tree-based machine learning on 428 Turkish non-financial firms to show that ESG and governance signals provide statistically significant additional information for predicting ROE beyond traditional financial ratios. Random F…
Chen Xu, Batkhuyag Ganbaatar
This study examines the impact of intelligent manufacturing on ESG performance for Chinese A-share listed companies (2015-2023) using two-way fixed-effects panel regression, PSM-DID, and System GMM. It finds that intelligent manufacturing s…
Jianfeng Zhang, Tiantian Qi
This study proposes an interpretable predictive model for ESG greenwashing in listed companies using XGBoost and SHAP, based on Chinese listed companies data from 2009-2022 with 16 input variables. The one-period-lagged model achieves 86.82…
Xiaoqian Liu, Gazi Md. Nurul Islam, Xuelian Bai
This paper develops a credit evaluation system for new energy enterprises integrating big data (807 wind/solar plants, over 84 million photovoltaic and 570 million wind power records) with AI time-series modeling, game-theoretic weighting, …
Javier Nieves Almanza, Roberto Yoan Castillo Dieguez
This study analyzes the relationship between CSR (measured by ESG scores) and financial performance of Mexican listed firms from 2014-2024 using ANCOVA, random forest, and probit models. Results show a positive association with ROA and ROE,…
M. Rao, Falguni Nayak
This study analyzes the short-term relationship between ESG performance and stock prices of 45 Indian BSE-listed companies across nine industries in the post-BRSR period (FY2023-24 and FY2024-25). Using descriptive statistics, ANOVA, regres…
Sasmita Mishra, Zefree Lazarus Mayaluri, C. Liew +2
Proposes a hybrid deep learning model combining ESG scores and news sentiment for asset return forecasting. Uses TFT, SVR residual correction, and gated fusion to quantify ESG-sentiment interactions, finding regime dependence. A latency-opt…
Zilong Yang
This paper examines how negative ESG news affect short-run trading in China's A-share market (2015-2023). Using a BERT classifier, it identifies 4,873 events and finds abnormal turnover +2.84pp (28.3% relative increase), volume +35%, and id…
Guangxing Hu, Bin Li
This study examines the impact of China's Intelligent Manufacturing Demonstration Projects (IMDPs, 2015-2018) on corporate ESG ratings using a quasi-experimental design with propensity score matching and difference-in-differences. IMDP part…
Soon-Ae Choi
This study employs a systematic review to analyze how AI/ML technologies can mitigate the structural dilemma of high initial investment costs and declining financial performance due to strengthened ESG regulations in the Korean cruise indus…
Kahyun Lee
This paper proposes a data-driven predictive framework that uses machine learning to map financial disclosures to ESG ratings, demonstrating practical applicability in linking disclosure content to scores.
Giuseppe Pernagallo, F. Quatraro, Eleonora Rubichi
This paper proposes a text-based circularity index using mandatory non-financial disclosures from large Italian companies. By computing cosine similarity between FTSE MIB sustainability reports (2017-2022) and a circular economy vocabulary …
Benjamin Josef Schüßler, Jakob Prange
This study extends a sentence-level dataset of German ESG reports with crowdsourced readability annotations and evaluates various readability scoring methods. It finds that while LLM prompting can distinguish clear from hard-to-read sentenc…
Tamás Zelles, Bernadett Domokos, Sándor Remsei
This paper examines how combining narrative techniques with machine learning can enhance decision-making, particularly in accounting and sustainability reporting. It finds that narrative-driven reporting with expert interpretation improves …
Huipeng Yang, Yihang Yu, Yuhan Wu +2
This study constructs a climate risk index from annual report text mining of Chinese A-share firms (2016-2024) and examines its impact on the cost of debt financing. Using regression and mediation analysis, it identifies two channels: reduc…
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