GX & Decarbonization Research

Zeyu Wang

This paper analyzes how Climatiq's AI carbon computing capabilities are translated into thyssenkrupp Rasselstein's transport and procurement processes via the Celonis platform, supporting Scope 3 emission reduction potential identification.…

Nitin Singh, Kee‐hung Lai, Zuopeng Zhang

This study examines how firms can use generative AI to create value in ESG reporting. It finds GenAI drives digital innovation via automated data extraction, accelerated analytics and dynamic reporting, enhances stakeholder engagement by in…

Pothin, Florian, Rondeau, Fabien, Razafindrabe, Tovonony +1

This replication package accompanies a study that corrects corporate Scope 3 disclosures category by category across the 15 GHG Protocol categories. Each firm report is classified as activity exclusion, boundary incompleteness, or sound dis…

Erofeev, Yury, Majer, Stefan, Thrän, Daniela

This deposit accompanies a paper validating a layered indicator specification for corporate aviation Scope 3 (Category 6) reporting. It contains anonymised data from a two-round modified Policy Delphi (N=211; N=172 matched), all analysis ou…

Atia Alam, Myra Nadeem

Using NLP and entropy methods on FTSE non-financial firms' disclosures (2020–2024), the study builds firm-level digital transformation (DT) and ESG measures. Fixed-effects regressions show both exploitative and explorative DT are positively…

Pei-Xuan Wu

This paper proposes a Multi-Party Computation (MPC) framework integrated with permissioned blockchain to enable cross-border ESG data sharing while preserving corporate confidentiality and national data sovereignty. Using China's PBOC green…

Alessio Faccia

Using 1,450 Form 10-K firm-years from 250 CIKs (FY2014–2024), this study examines whether the US Inline XBRL phase-in is associated with disclosed AI orientation. After Holm adjustment, none of four reporting indicators support the hypothes…

Maciej M. Sokołowski

This chapter examines AI's role in climate action and energy policy, focusing on energy transition, grid modernization, efficiency, renewables, and emissions reduction. It compares how the EU and Japan integrate AI into climate, energy, and…

S. Nawazish, Serish Umer, T. Jabeen

This review maps the intersection of AI, fintech, and climate-risk assessment across 2022–2026 literature, regulation, and practice. It builds a taxonomy of AI applications—physical and transition risk modelling, scenario analysis, greenwas…

Kingsuk Majumdar, Sohini Ghosh

This study applies Random Forest, XGBoost, and SVM to a 65-country, five-sector EU ETS trade panel (2000–2018) to predict carbon leakage. XGBoost achieves R²=0.965 for embodied CO2 regression and ROC-AUC=0.765 for leakage classification, su…

Murali Krishna Pasupuleti

This monograph proposes a research architecture linking financial statements, management commentary, sustainability metrics, climate-risk evidence and operational telemetry via multimodal AI. It frames reporting quality as a joint function …

Qiao-Rong Yang

A critical review of 15 studies at the intersection of AI, carbon accounting, and green accounting. It identifies three technical pathways: data-centric systems, ontology-driven hybrids for SMEs, and real-time tagging platforms. The paper h…

Anonymous

Replication deposit for a firm-level study of CSRD climate disclosure quality before and after the 2026 Omnibus scope reduction. Covers 188 EU firms and 376 reports coded on a ten-dimension instrument using a frozen LLM prompt. Includes the…

Adeboye Oyegunle, Olaf Weber

This study uses AI and NLP to examine how well 16 major global climate risk banking regulations align with 83 peer-reviewed articles (2017–2024). It finds only moderate alignment (74.2% cosine similarity), showing regulators partially incor…

(著者不明)

This study examines how CEO narcissism affects the quality of TCFD-aligned climate-related financial disclosure among S&P 1500 firms. Using generative NLP measures across the four TCFD pillars, it finds narcissistic CEOs produce weaker, les…

Naveen Virmani, Srikant Gupta, Koppiahraj Karuppiah +1

This paper examines federated learning as a means to enhance the scalability and credibility of ESG reporting, identifying and prioritizing adoption challenges. Through literature review and expert panels, 18 validated challenges were analy…

Xunzhang Pan, Tianming Shao, Jianxiao Wang +5

This paper uses LLM agents to generate and evaluate global mitigation pathways for the 1.5°C target, integrating Sustainable Development Goals (SDGs). It sits at the intersection of AI and climate policy, offering a novel approach that comb…

Marcus Becker, Timo Zimmermann, Judith Maria Beermann

This study applies a GRI-oriented RAG workflow to eight years of Borussia Dortmund's sustainability reports, finding moderate and fluctuating evidence quality rather than steady improvement. It demonstrates RAG's utility in structuring disc…

Jin Yan, Yang Zhao, Xue Gao +3

Combining machine learning with causal inference, this study detects low-carbon technology innovation take-offs across 18 countries (2001-2022) and evaluates over 1,600 policy interventions. It finds that market-based instruments (especiall…

Rui Lu

Proposes request-level carbon accounting for AI inference, considering service boundaries, routes, and electricity sources. Public-data implementation reduces median absolute percentage error by 56.3% vs EcoLogits.