GX & Decarbonization Research

K. Umer, Sajjad Ahmad, I. Raisani +5

This study examines the impact of transparency on the relationship between AI-driven finance and sustainable performance. Using a survey of 252 respondents from financial institutions and corporations, the findings indicate that transparenc…

Wenze Wu, Mei Sun, Mark Goh

This study constructs firm-level indices of supply chain digitalization (SCD) and corporate green transition (CGT) via textual analysis of Chinese A-share manufacturing firms' annual reports. It finds that SCD significantly promotes CGT, me…

Marina Nazir, Marina Nazir, Minhas Akbar +2

This paper explores how artificial intelligence and environmental digitalization contribute to mitigating climate risks and promoting sustainable development amid geopolitical uncertainty. It examines the potential of AI-driven climate risk…

Shukai Zhang, Chengzhi Yu, Shuang Liang

This study reframes street-level urban renewal as a coordination problem between vitality and low-carbon performance. Using multisource data and interpretable machine learning, it diagnoses vitality-carbon mismatches in Chengdu, China, find…

Abdul Rehman, Suyang Zhou, Sheeraz Iqbal +3

This paper proposes an Adaptive Quantum-DRL Multi-Objective Optimization (AQ-DRLMO) framework for low-carbon CCHP systems. It integrates quantum-inspired evolutionary algorithms with deep reinforcement learning, achieving 40.08% emission re…

Rency Dayne Duque, John Rein Vinuya, Kristenz Mingoy +2

This study presents Cravely, an AI-integrated digital platform for food waste reduction in the Philippines. It enables surplus food redistribution at discounted prices and uses an AI module to estimate avoided methane emissions. Evaluation …

Human Sciences Research Council

This chapter proposes a dynamic policy formulation system inspired by natural systems, using AI and big data to monitor climate indicators and automatically update policies via rapid feedback loops, avoiding delays of traditional policy pro…

NOUNANGNONHOU CT, DIDAVI KBA, AZA-GNANDJI MR

This paper proposes a hybrid deep learning model (B6) combining CEEMDAN-VMD dual decomposition with a GRU-attention backbone for wind power forecasting. Evaluated on seven wind farms, it reduces MAE and RMSE by 25-35% over baselines for 1h,…

Maataoui, Wijdane El, Abounada, Abdelouahed

This paper proposes replacing the classical virtual synchronous generator (VSG) control with a deep neural network (DNN) for wind power systems. The DNN is trained end-to-end using supervised learning to generate inverter control signals fr…

Somasundaram, Deepa, Krishnamoorthy, N., Anand, J. Vijay +3

This paper proposes an AI-driven framework for EV charging station placement integrating LSTM-based spatiotemporal demand forecasting, GA-PSO multi-objective optimization, and deep reinforcement learning for adaptive resilience. Evaluation …

Yantong Li, Taoyu Chen, Yajie Guo +3

This study uses NLP and XGBoost-SHAP on Sina Weibo data to analyze urban travel behavior changes under extreme heat and oil price shocks. Key findings: heat leads to trip reduction (52.4%) and motorized travel (24.6%), with a transition int…

Siyi Wang

This paper proposes a low-carbon intelligent path planning method using genetic algorithms for machining carbon fiber reinforced polymer aerospace components. Experimental results show a reduction in path length, machining time, energy cons…

Yaping Luo, Jianxian Wu

This paper explores the potential of AI technologies to reduce carbon emissions in the transport sector, focusing on optimization, automation, and data-driven decision-making. It likely examines case studies or models where AI steers transp…

Amal Alharthi, Ahmad Alomari, Fawwaz Alrwabdah +3

This paper examines how green digital technologies (ERP, cloud, IoT, AI, big data analytics) improve ESG disclosure quality for industrial firms listed on the Amman Stock Exchange. Using panel data from 30 firms (2020-2024) and institutiona…

Mohsin Khan, Wendy Ashurst

This paper examines the role of AI in enhancing ESG reporting quality, proposing a sector-specific hybrid governance framework. It finds environmental metrics are more amenable to AI verification, while social and governance disclosures req…

Qiao Wang, Bin Li, Shaojie Kong +1

This study uses double machine learning on panel data from 266 Chinese cities to investigate how digital governance policy upgrades (from IBP to IGS) dynamically propel cities toward carbon neutrality. Findings show that the policy upgrade …

Hieu Thanh Nguyen, Hoa Minh Pham, Anh Thao Nguyen +3

This study examines the impact of ESG disclosure on tax avoidance of 118 Vietnamese non-financial listed firms (2020-2024). Using random effects models, it finds that ESG performance (individual E, S, G pillars and a composite index) is neg…

Galina Lisa

This paper examines innovative approaches to sustainability reporting by integrating ESG principles, digital technologies, and transparency mechanisms. Using comparative analysis of GRI, SASB, CSRD/ESRS and case studies from EU and emerging…

Francisco Javier Rodríguez-Ruiz, Ana María García-Berbaneu, Alexsander Luiz Telpisow-Scheid

This study proposes an automated methodology using NLP to extract, classify, and assess ESG content from corporate sustainability reports. It uses a taxonomy aligned with European reporting standards for listed SMEs, enabling scalable and r…

Amir Amel-Zadeh, Tami Dinh, Andreas Seebeck +1

This paper uses deep learning to analyze visuals and text in 3,923 European sustainability reports (2013-2021), documenting a functional separation between graphics and photographs. Firms with stronger ESG performance use more graphics but …