GX & Decarbonization Research

Hina Ahmad, Kinza Kamran, Fizzah Muhammad

This study analyzes the 'AI-climate nexus' reshaping international relations. Through document analysis of 127 sources and four case studies, it finds AI enhances emissions verification and grid optimization but introduces vulnerabilities l…

Xinxiu Liu

ESG ratings are crucial in capital markets, but the surge in disclosed data leads to transparency data bias, potentially compromising rating accountability. This interview-based study reveals awareness of this bias, its causes (data quality…

Farinu Uthman, Philip Edward, Adekola Priscilla

This study develops a hybrid AI model integrating random forest, LSTM, and gradient boosting to forecast carbon sequestration and financial returns of afforestation projects. Using satellite, soil, carbon price, climate, and cost data, it g…

Saeed Askary, Davood Askarany, Hassan Yazdifar +3

This study examines the interplay between AI-related environmental perceptions, ESG reporting timing, and CDP disclosure quality across 18 European countries. Mandatory reporting modestly improves disclosure quality, but effects on carbon i…

Arpit Darbari

Proposes a Unified Digital ESG Framework (UDEF) for manufacturing that integrates CSRD/ESRS compliance, GHG Protocol-based accounting, and SDG alignment. Leverages smart metering, IIoT, cloud EMS, and AI-assisted decision support for contin…

Nihad Isgandarov

This paper theorizes and measures systemic economic fragility arising from the simultaneous acceleration of AI adoption and decarbonization. It proposes the Isgandarov Adaptive Transition Theory (IATT) and develops the Isgandarov Transition…

Makhrus Ali, Amin Zaki, Zain Nizam

This paper examines green fintech at the intersection of financial technology and sustainability, analyzing applications such as digital payments, sustainable investment platforms, and climate-risk analytics. It shows that big data, AI, and…

(著者不明)

This paper addresses AI-based ESG evaluation and risk analysis. Although details are unavailable, it focuses on the intersection of AI and ESG, applicable to corporate sustainability assessment and climate risk quantification.

Hermanus, Davy Ronald

This study proposes an AI-driven situational awareness architecture for citywide energy governance, integrating digital twins and multi-drone verification. Simulations show reduced false anomaly confirmations from 16% to 6%, improved Situat…

Wang J.

This paper proposes a hybrid CEEMDAN-LSTM model to predict green bond index movements. By applying AI to ESG financial instruments, it offers insights for investment decisions and risk management in the green bond market.

He Jiang, Rongyu Cao

This paper proposes an explainable time-varying feature selection method for predicting EU ETS carbon prices. It uses AI/ML to dynamically identify key drivers, balancing predictive accuracy with interpretability. Empirical analysis on EU E…

Chao He, Yunjie Su, Sirui Zhang +2

This review systematically examines the use of large language models (LLMs) in low-carbon smart energy systems, focusing on cloud-edge power IoT. It analyzes five technical themes: task offloading, dynamic edge resource allocation, low-late…

Archie Nathanael Mulyawan, Nataniella Eva Kezia, Verena Jesslyn Utama +1

This qualitative study examines how accountants, as ESG analysts and strategic leaders, enhance sustainability report transparency using the Susteineri system integrating IoT and AI. Real-time data collection enables monitoring of carbon em…

Jason Chen

This study proposes an optimization framework to reduce greenhouse gas emissions in Hong Kong's logistics and transport network. It models 18 administrative districts as a dynamic topological graph and integrates real-time traffic, terrain,…

Pothin F

Using staggered difference-in-differences on SBTi and CDP data (2015-2023), this study finds that pledging firms expand their measurement boundary: within four years they report 2.5 more Scope 3 categories, lifting reported Scope 3 emission…

CINAR U

Proposes a false-alarm-controlled protocol to fairly compare gas indices and deep learning for early detection of coal spontaneous combustion. In simulation and field data from three mines, Graham's index fails to detect fires at false-alar…

J. Taborda, Cesar Enrique Polo Castro, Alexander Armando Bustamante +1

This paper proposes a cybernetic governance framework integrating blockchain, IoT, and LCA for trustworthy monitoring of renewable energy impacts. Implemented in Colombia's wind and solar projects, it achieved high performance and participa…

Fausania Hibatullah, Rico Dwi Firmansyah, D. Kusrini

This study proposes a portfolio optimization framework integrating FinBERT-based sentiment analysis and DBSCAN clustering for IDX ESG Leaders stocks. Empirical results show that sentiment-informed clustering improves risk-adjusted performan…

I. Ferdiyansyah, R. Masman

This study analyzes the relationship between Digital ESG Leadership (DEL) and ESG disclosure quality, strategic integration, and performance in eight Indonesian technology companies (39 firm-years, 2019-2024). Using dictionary-based scoring…

Fnu Aishwariya Kannan R. Uma, Nandini Jagannarayan

This review examines the latest literature on Green FinTech from an economic perspective. It discusses how digital technologies such as AI, blockchain, and big data contribute to environmental risk assessment, carbon market transparency, an…