GX & Decarbonization Research

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…

Yunjing Wang, Jinfang Tian, Siyang Sun +2

Using LLM and text analysis of Chinese listed firms' blockchain patents (2010–2022), this study shows that blockchain innovation reduces fossil energy intensity. Mechanisms include lower internal control costs, stronger external oversight, …

Andreas Froemelt, Thomas Wiedmann

This study employs a two-stage clustering approach (Self-Organising Map and Ward clustering) to analyze household consumption patterns and lifestyle carbon footprints in Sydney and Melbourne. By combining expenditure data with socio-economi…

Svenja Hauck, Lucas Greif

This article reviews the role of knowledge graphs and AI in sustainability assessment, enabling comparison of environmental impacts during product development. A case study demonstrates carbon footprint analysis using these technologies, hi…

Azeez Lamidi Olamide, Omolola Badmus

This study proposes a comprehensive evaluation model to improve carbon accounting accuracy across Scope 1, 2, and 3. It integrates machine-learning anomaly detection, uncertainty quantification, and materiality assessment, aligning with GHG…

中尾 悠利子 中園 宏幸 石野 亜耶

This survey explores how companies utilize AI support tools when responding to ESG/sustainability questionnaires (e.g., CDP, EcoVadis), clarifying current practices and challenges. It also examines the benefits of AI adoption and future pro…

ZHANG Chunhui^1^  ZHANG Zhen^2^

This paper examines the power generation sector, the first to launch domestic carbon emissions trading. It presents management measures and implementation schemes for emissions trading, highlighting the role of smart meters in emissions acc…

Wei Yigang, Shi Jiawei, Xu Guannan

This study analyzes 1,743 low-carbon policies issued in China from 2000 to 2021 using text mining and policy econometrics within a framework of 'policy objectives—policy themes—policy fluctuations.' It systematically reviews the development…

Zihang Wang, Ling Zhang, Mengmeng Pu

This study develops a machine learning framework to predict project-level embodied carbon emissions in buildings across design stages, using data from 78 projects (426 buildings). The residual-corrected weighted ensemble model achieved the …