This page provides an English interface to the gxceed GX paper corpus. The corpus aggregates papers from 13 open 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 181–200 of 991 papers
Ekwuye, Ben Madu, Lawal I. Lamidi, Okoroiwu, Kemdi Lugard +1
This study examines the impact of blockchain, AI, big data, and XBRL on sustainable financial reporting in emerging markets like Nigeria. Based on stakeholder theory and TAM, it discusses automation of ESG data collection, predictive analyt…
Kunjie Zhu, Simin Yang, Mingkun Zhou +1
Using patent data from 4,728 Chinese listed firms, this study shows that China's National Big Data Comprehensive Pilot Zones policy boosts green innovation quantity by 4.5%, driven by improved financing, subsidies, and reduced information a…
Nabeela Ehsan
This study examines whether AI-driven ESG compliance monitoring reduces corporate sustainability risk using panel data from 320 listed firms (2016-2024). GLS regression shows AI monitoring significantly lowers risk (coefficient -6.84), and …
Jiehui Chen, Dexing Sun, Feiwei Li +4
This paper proposes a dynamic multi-objective optimization framework for industrial electricity consumption, integrating high-precision load forecasting and optimal scheduling. An improved LSTM model (DGO-TA-LSTM) is used for forecasting, a…
Santosh Kumar, Neha Gupta, Swarnima Gorani
This paper discusses the importance of policy frameworks and incentive design for applying AI in green finance. It argues that without proper governance, risks such as algorithmic discrimination and data bias could undermine social goals, a…
Yinhao Zhu, Sheng Li, Juan Yin +2
This paper integrates meta-analysis with machine learning to optimize biochar application for greenhouse gas mitigation and yield improvement. It aims to identify optimal application conditions, providing quantitative evidence for biochar a…
Monica Canepa
This paper proposes an explainable multi-criteria decision framework for maritime and port decarbonization, integrating AHP, TOPSIS, and SHAP. It incorporates cyber-physical security as a core criterion and is validated with real-world data…
Yunhua Zhang, Jia Wu
This paper examines the impact of China's green finance reform policy on corporate sustainable innovation, drawing on institutional and stakeholder theory. Using DID analysis on Chinese A-share listed firms from 2012-2022, it finds the poli…
Sendy Dwi Haryanto, Dian Agustia, Iman Harymawan
This study analyzes 205 European oil and gas firms (2018-2023) to show that risk management committees (RMCs) mitigate 37% of emissions-related value destruction, and GRI compliance mediates 12% of the emissions-value relationship, but only…
B. Gyamfi, Richard Arhinful, Leviticus Mensah +2
Using data from 143 UK non-financial firms (2008-2024), this study applies CS-ARDL, FGLS, and GMM to show that sustainable finance (environmental expenditures, emission reduction policies, green bond issuance) positively impacts product res…
Nanlan Du
This paper empirically analyzes the impact of green finance policies on corporate low-carbon transition in China using a multilayer perceptron (MLP) algorithm and difference-in-differences (DID) method. Using panel data from 30 provinces fr…
Aiying Zhao, Qian Chen, Yang Zhao +3
This paper proposes a hybrid Transformer-sLSTM model for carbon price forecasting, integrating VMD for multi-scale decomposition and WOA for parameter optimization. Achieving R2=0.9862 and MAPE=0.56% on real datasets, it enhances prediction…
Abdullah Kursat Merter, Beylem Çeli̇k, Gökhan Özer
This study examines the relationship between ESG content intensity and disclosure speed using a panel of BIST Sustainability Index firms (2014-2023). BERT-based text analysis measures ESG intensity, and fixed-effects regressions show that h…
S. Shin, Seon-Mi Kim, Seung-Weon Yoo
This study uses text mining to analyze sustainability reports of Korean listed firms, quantitatively assessing ESG disclosure similarity and completeness. Similarity declined over time but rose in 2023 due to postponed mandatory disclosure.…
Marek R. Helinski
This paper presents a generative-AI decision-support framework that optimizes sustainable logistics by integrating EU policy variables (CBAM, EU ETS for maritime, FuelEU, Digital Product Passport, CSRD) into planning equations. Using genera…
R. Purushothaman, R. Alamelu, Sathya Manickam +2
This chapter examines how AI and emerging technologies reshape sustainable supply chains amid ESG goals and tighter regulations. It covers AI-driven design and inventory optimization to cut waste and emissions, plus blockchain for transpare…
(著者不明)
This article presents Nutritics' AI-based technology that automatically matches food items to lifecycle inventory carbon and water data, enabling food service companies to measure and report Scope 3 emissions. It highlights the current lack…
Bamidele Samuel Adelusi, Abel Chukwuemeke Uzoka, Yewande Goodness Hassan +1
Scope 3 emissions are hardest to manage across Tier-2 supplier networks. This study combines LCA with multi-objective genetic algorithms to find Pareto-efficient strategies balancing carbon reduction, compliance cost, and operational contin…
Harish Narne
This paper proposes a cloud-based system that uses AI, IoT sensors, and big data analytics to monitor carbon footprints in real time and generate predictive reports. The scalable infrastructure enables continuous observation of inter-indust…
X.F. Wang
This paper examines how AI can empower sustainable supply chains, addressing efficiency-environmental protection-equity challenges. It identifies key AI capabilities such as demand forecasting, logistics optimization, risk management, suppl…
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