GX & Decarbonization Research

Małgorzata Radomska

This chapter analyzes the relationship between sustainability reporting and AI from a regulatory perspective. ESG disclosure and AI regulation have developed separately, leading to fragmentation and practical challenges. It maps key legisla…

Jacopo Ghirri, Carlos Rodriguez-Pardo, Lara Aleluia Reis +1

Using deep learning on high-resolution socioeconomic and sectoral data, this study projects EU27 CO2 trajectories to 2030 under current trends. It finds emissions will exceed the 2030 target by 35% (620 Mt shortfall), with only a minority o…

Yihsu Chen, Abel Souza, Fargol Nematkhah +1

This paper models power markets where hyperscalers shift LLM inference workloads to modular datacenters co-located with renewables. It reveals that contract reshuffling can undermine emission reductions from cleaner procurement, and that fo…

J. Z. Lin

This study constructs a financial health rating system using Deep Belief Networks (DBN) to classify enterprises into seven tiers. Using 2,486 firm-year observations from 247 textile, apparel, and leather companies listed on Shanghai-Shenzhe…

Alessandra Allini, Alessandro Corrado, Luca Ferri +1

This study examines how abnormal tone in ESG reporting (discretionary narrative unexplained by fundamentals) affects firm value and the value relevance of accounting information, using a sample of 2,002 European listed firms (2017-2024). Us…

Qing Wang

This review systematically explains the concept of circular logistics, integrating circular economy principles into logistics engineering to minimize waste and carbon footprint. It clarifies differences from traditional logistics and presen…

Yuanyang Guo, Liqi Xu, Miaoxi Gu

Using panel data from Chinese cities (2008-2023), this study empirically examines how AI entrepreneurship affects carbon emission intensity. It finds an inverted U-shaped relationship: early expansion increases emissions, but after a thresh…

Jolly Masih, Dinesh Yadav, Sanskriti Singh +3

This study examines whether carbon credits are credible climate solutions or greenwashing, focusing on the gap between institutional narratives and public discourse. Using mixed methods including VADER sentiment analysis, Google Trends, Tal…

Xiaoyuan Feng

This paper empirically examines how corporate digital capabilities affect ESG performance, focusing on the mediating role of low-carbon innovation. Results show digital capabilities significantly boost ESG performance, with low-carbon innov…

Sanjana Santra, Kishore Kumar, Ankita Sharma

This paper proposes a roadmap for AI-powered circular value chains to achieve carbon neutrality and corporate sustainability in emerging economies. It integrates AI technologies with circular economy principles to enhance resource efficienc…

Arnima Pathak, Monika Sharma, Devendra Kumar

This paper proposes a hybrid process and machine learning framework to predict and classify nitrous oxide emissions in legume-based cropping systems. Using 22 years of field data, the ensemble model achieved high predictive accuracy (R²=0.9…

Michael Bane

This study shows that for computational matrix operations, shifting computation in time and space based on carbon intensity yields far greater carbon savings (up to 354x) than energy reductions from code-level optimizations (up to 51x). A r…

Desmond Bayong, Dejun Zhou, Andrews Osei Agyemang

This study examines the impact of AI adoption on ESG disclosure quality among manufacturing firms in G7 economies using panel data from 2017-2024 (5,600 firm-year observations). Quantile regression reveals a consistently positive relationsh…

L. Lin, X. Yao, J. L. Liang

This paper proposes a method using an integrated Knowledge Graph (KG) and NLP to quantify green finance policy impacts by integrating policy, market, ESG, and carbon data. Validation with DID on China's green finance pilot zones (2016-2023)…

X. L. Wang, X. Xue, Y. Lin +1

Proposes a Graphormer-TCN fusion model to assess market operation of new energy settlement mechanisms in industrial parks. Models transmission topology as a weighted graph, integrating spatial and temporal features to score market operation…

Nugroho Nugroho, Rahmatul Husni

This longitudinal critical discourse analysis compares how National Oil Companies (NOCs) and International Oil Companies (IOCs) responded to evolving climate disclosure regulations from the Paris Agreement to EU Omnibus I (2016-2026). Analy…

Yifei Lu, Jia Lu, L. Jin +2

This paper proposes a dual-channel deep learning framework using mixed-frequency data to forecast region-specific daily industrial carbon emissions with high accuracy. It applies AI to carbon emission monitoring, aiding climate action and e…

Mahmoud Elmarzouky, Sabrina Khemiri, Doaa Shohaieb

This study examines how board gender diversity affects the quality of climate impact disclosure in UK nonfinancial firms. Using a novel text-analysis-based index, it finds that boards with at least four female directors significantly enhanc…

Haibo Du, Youping Zhao

This paper presents a multi-agent simulation framework to explain ESG rating divergence among agencies. Using CSI 300 firms, it shows weight differences alone cause significant divergence (4.19 points), low disclosure quality amplifies it b…

Courtney Bower, Farzin Lotfi-Jam, Jennifer S. Minner +2

This study uses agent-based modeling (ABM) to simulate how building reuse and deconstruction choices affect city-wide embodied carbon emissions in Ithaca, NY. Comparing four scenarios, it finds that maximizing preservation achieves the lowe…