GX & Decarbonization Research

H. T. Dinh, Hà Thị Thu Bùi, H. Nguyen +3

Using survey data from 853 hotel employees in Vietnam, this study employs PLS-SEM to examine how AI and CSR influence employee green behavior (EGB), green finance (GF), and green performance (GP). Findings show AI positively impacts GF and …

Mohamed Vajeebu Mohamed Hussain Pareeth

This review proposes an AI-driven optimization framework for green hydrogen production networks in Saudi industrial cities (NEOM, Yanbu, Jubail, etc.). It integrates machine learning, digital twins, stochastic optimization, and explainable …

Sanjana Kewalramani, Sharvari Nimje, Tanishq Rajpuria +2

This review systematically organizes research applying AI/ML to Kubernetes scheduling for improving energy efficiency and reducing carbon emissions. It shows that ML-based workload placement optimization can effectively reduce data center e…

T. Sindhu, Dr. K. Sivakumar, Dr. D. Jayanthi +2

This review examines geospatial technologies (GIS, remote sensing, UAV, LiDAR) combined with machine learning for carbon stock estimation in mango orchards. Integration of satellite imagery and ML models (Random Forest, SVM, ANN) improves p…

Winda Wulandari, Sri Widyastuti, Harnovinsah Harnovinsah +1

This systematic literature review reconceptualizes financial reporting integrity as a socio-technical governance phenomenon shaped by governance accountability, sustainability legitimacy, and technological transparency. Analyzing 28 Scopus …

Yaacob Ibrahim, Khaled Hussainey, Taghred Mokhtar Sayed Moawad

This study examines whether carbon exposure affects corporate borrowing costs in the MENA region using a panel of 771 firm-year observations from 2016 to 2023. Combining fixed effects, IV, GMM, quantile regression, and machine learning, it …

Ke W

This paper frames environmental monitoring as collaborative governance infrastructure under ESG and net-zero policies, and explores how 'Quantum Intelligence (QI)'—combining quantum optimization and quantum machine learning—can reshape the …

(著者不明)

This paper demonstrates that integrating IoT and BI platforms improves Scope 3 emissions reporting accuracy by 40% in logistics. It emphasizes data unification from a governance perspective, offering new possibilities for carbon tracking an…

Seyed Ali Hosseini, Francesco Grimaccia, A. Niccolai

This paper introduces fuzzy logic into reward design for deep reinforcement learning agents in carbon emission trading (ETS), aiming to optimize trading strategies. Fuzzy rewards improve decision-making under uncertainty, balancing emission…

Md Qamruzzaman

Using panel regressions and a deep learning (MLP) model on 62 listed Bangladeshi financial institutions (2005-2023, 1,178 firm-years), this study finds that intellectual, human, and natural capital disclosures each positively and significan…

Sina Rostami, Muhammad Bilal, Mehrdad Taghipour

This scoping review systematically maps technologies and strategies to reduce energy use and carbon footprints in operating rooms, evaluating methods from HVAC optimization to AI-driven management. It identifies a gap in kinetic energy harv…

Venkata Krishna Reddy, Aadam Quraishi, G. C. Prashant +1

This paper proposes a deep learning-based decision support system (DSS) for renewable energy (RE) investment and deployment. It uses CNNs to extract features from weather, energy, and economic data, RNNs to forecast energy demand and supply…

Lila Simon, Abino Simon, Aalbin Simon

This chapter explores the integration of AI and renewable energy for a sustainable energy ecosystem. It reviews the renewable landscape in India and globally, detailing AI applications in solar, wind, hydro, biomass, and geothermal, includi…

Michelangelo Misuraca, Luca D’Aniello, Maria Spano

This study analyzes renewable energy social representations in Reddit climate discourse (2018-2026, 91,817 comments) using a computational adaptation of the Hierarchical Evocation Method. Combining theory-informed lexical anchoring with dat…

Bingler J.A.

This paper uses ClimateBert, a specialized language model, to analyze corporate climate risk disclosures, focusing on 'cheap talk' (substantively empty claims) and 'cherry-picking' (selective disclosure of favorable information). It offers …

Xiao Qin, Quan Fang, Yuan Virtanen

This study empirically examines the impact of climate policy uncertainty on corporate sustainability (ESG scores) using Chinese A-share listed firms from 2016 to 2025. Employing a two-way fixed-effects model, it finds that climate policy un…

Mengqi Yuan, Wenfei Zang, Guangchong Chen

Using provincial data from China (2012-2022), this study analyzes the coupling coordination between AI and high-quality energy development (AHCC). Both advanced, but AI lagged and regional disparities persisted, with intensifying spatial au…

Mehrdad Taghipour, Sina Rostami, Muhammad Bilal

This scoping review systematically maps technologies and strategies to reduce energy use and carbon footprints in operating rooms, including HVAC optimization and AI-driven management. It identifies a methodological gap in kinetic energy ha…

Rufaizal Che Mamat, Azuin Ramli, M. N. A. Ghani +3

This study compares fine tree regression and ANFIS for predicting carbon footprints across four stages of residential construction. Using 2000 observations, ANFIS outperformed Rtree in all stages, achieving lower RMSE values, especially in …

Adrian Friday, Abdessalam Elhabbash, Ignatius Ezeani +3

This volume contains the proceedings of the 2nd International Workshop on Low Carbon Computing (LOCO 2026), held at Lancaster University, UK. It covers topics such as carbon measurement and reporting, sustainable software engineering, energ…