GX & Decarbonization Research

J. Chinna

This study analyzes the impact of AI on ESG reporting from 2019 to 2025, showing adoption surged from 15% to 63%. AI evolved from basic data collection to machine learning, NLP, and generative AI, improving transparency, accuracy, and timel…

Maria Aluchna, Leszek Bohdanowicz, Bogumił Kamiński

This study examines how female board representation affects the scope of climate-related disclosure (energy use and GHG emissions) after mandatory NFRD reporting. Using a difference-in-differences design on 72 Warsaw Stock Exchange firms, i…

Xiaoyu Guo, Weisen Wang, Zhanghua Xu +6

This study develops a UAV-LiDAR and machine learning framework for organ-level aboveground carbon (AGC) estimation in bamboo forests. XGBoost and Random Forest achieved highest accuracy (stem R2=0.82, leaf R2=0.73), offering a cost-effectiv…

Bochen Zhang, H. Huang, Zhili Han +1

This paper empirically analyzes the impact of digital-real integration (DRI) on green total factor productivity (GTFP) using panel data from Chinese industrial enterprises. Fixed-effects and mediation analyses show that DRI significantly im…

Yuxuan Guo, Linxin Yin, Ruihan Xiong +2

This study addresses the severe risk of capital chain rupture in China's construction industry, focusing on vulnerable subcontractors. It proposes an AI-assisted risk control platform and innovative insurance products, using gradient boosti…

Zahra Yaghoubi, Mahyar Mansouri, Hosein Alimardani +2

This study applies explainable machine learning to optimize methane tri-reforming (TRM) for low-emission hydrogen production and CO2 utilization. Using 46,464 equilibrium data points, a neural network achieved the best predictive performanc…

Jiyoung Ko, Yong-Woon Kim, Y. Byun

This study proposes a deep learning framework for accurate greenhouse detection and segmentation from high-resolution aerial images. By integrating class-weighted loss and class-aware sampling into YOLOv8, it achieved [email protected]:0.95 of 0.566.…

Laura Elena Jiménez-Casillas, Román Rodríguez-Aguilar, Marisol Velázquez-Salazar +1

This study measures the individual impact of CSR and sustainable operations on financial performance for Mexican listed firms using Random Forest and explainable ML (ICE, PDP, SHAP). Environmental scores show the most consistent contributio…

Sajjad Ahmed

This systematic review analyzes how digitalizing integrated management systems (IMS) impacts operational efficiency, sustainability, and strategic value, drawing on 69 studies and corporate reports. AI, IoT, and cloud technologies enable re…

Yubao Wang, Zhenzhong Liu

This study proposes a four-dimensional evaluation system with 22 indicators and a Fuzzy DEMATEL-MultiMOORA-Borda model to assess synergy between digitalization and decarbonization in coal power. Evaluating seven transition scenarios, it fin…

Adedokun A. Adebowale

This study evaluates Nigeria's digital procurement reforms and proposes a Policy-Driven Digital Governance Framework (PDGF) integrating AI anomaly detection, OCDS, and gender-responsive green procurement. Simulation suggests potential savin…

Xing Bao, Xu Zhang

This paper constructs a climate risk perception index from Chinese A-share firms' annual reports (2003-2023) and examines its impact on corporate green innovation. Stronger climate risk perception significantly promotes both quality and qua…

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…