GX & Decarbonization Research

Filiz Mızrak, Umut Elbir

This study develops a reliability-aware Bayesian framework to assess readiness for digital-twin-enabled smart-energy systems across 20 major international airports. Using 15 capability indicators in four domains plus an auxiliary transparen…

Baptiste Rigaux, Mark Vergouwen

DETeCT proposes a data-efficient method for classifying low-carbon technologies into multiple categories. It achieves high classification performance with limited data, aiming to automate technology classification. This can support corporat…

Daichen Guo, Sanglin Zhao

This study empirically examines the impact of corporate digital transformation (DX) on carbon emissions and the mediating role of ESG performance, using Chinese A-share listed companies from 2010 to 2023. DX reduces carbon emissions by impr…

Yuanyuan Ma, Siyu Peng, Yun Yu

This study develops a hybrid forecasting framework integrating CEEMDAN, sample entropy reconstruction, and coefficient of variation ensemble to capture multi-scale nonlinear carbon price dynamics. SHAP and TVP-SV-VAR reveal scale-specific a…

Sohail M.

This paper empirically examines how AI adoption affects ESG performance in the German banking sector, focusing on the mediating role of green finance. It suggests that AI can enhance banks' ESG assessments and promote green lending.

Xuelong Zhang, Xiaoling He, Mei Li +3

Using panel data of Chinese listed energy firms (2010-2023), this study shows AI adoption significantly reduces carbon emission intensity. Executive digital background strengthens the effect, and low-carbon city pilots provide complementary…

Saad Khan, Ahmed A. Aboushady, Firdous Nazir +1

This study proposes a privacy-preserving framework to detect, classify, and localize unregistered behind-the-meter low-carbon technologies (PV, EVs, heat pumps) in low-voltage networks. Using GDPR-compliant measurements, it combines LSTM au…

Aurélien Saussay, Misato Sato, Francesco Vona

Using U.S. online job vacancy data, this paper develops a skill-based NLP method to identify low-carbon jobs within occupations. Low-carbon job creation is prevalent in low-skilled occupations but requires more complex skills, yielding a mo…

Issam Benhayoun

This study analyzes factors determining ISSB adoption intention among 335 Moroccan accounting professionals. It demonstrates that institutional pressures influence adoption intention only through perceived usefulness and ease of use. Using …

Kishore Kumar, Susela Devi Suppiah, Preeti Bhaskar +1

This paper examines policy architectures for governing AI to facilitate circular economy transitions, focusing on challenges and opportunities in emerging economies. It discusses how AI technologies can support circular economy principles a…

João Oliveira, Tiago Santos, Fernanda Brito Correia +3

This study proposes a Digital Twin-inspired simulation framework to support renewable energy community (REC) planning. It integrates high-resolution smart-meter data, demographic filtering, and an AI-based N-HiTS forecasting model, applied …

Shangjie Liu, Agyemang Kwasi Sampene, Hazrat Hassan

This study analyzes nonlinear effects of digital technologies, clean energy transition, and industrial upgrading on climate change in five major robot-adopting economies (China, Japan, Germany, US, South Korea) using a multilayer neural net…

Radosveta Krasteva-Hristova

This study analyzes how the UK Big Four audit firms disclose safeguards for human oversight and accountability in AI-assisted work within their 2024 transparency reports. Developing an AI-Judgment Governance Disclosure Index (AI-JGDI) acros…

Summaiya Unnisa Begum, Mohammed Nadeem Ullah, Mohammed Abdul Ghani Khan

Carbon price forecasting is hard; existing work clusters on EU/China, compresses policy text into sentiment, and lacks calibration or explanation stability. This paper distills ten gaps into an impact-feasibility matrix and proposes EPA-Car…

Huanbei Zhao, Changhong Yu, Guobin Fu +3

This paper proposes a multi-stage low-carbon planning method for data center clusters that coordinates construction sequencing and load growth to avoid redundant early investment while ensuring supply reliability. It integrates a tiered car…

Abdulrahman H. Ba-Alawi, Abdo Abdullah Ahmed Gassar

This review examines AI's role in enabling net-zero buildings (NZBs) through HVAC efficiency, renewable integration, and intelligent control. AI techniques, especially reinforcement learning and digital twins, improve energy forecasting (R2…

Mingyang You, Xiaohui He, Xinyu Pu +2

Using panel data from 286 Chinese cities (2011-2021), this study examines the spatial spillover effects of AI technology innovation (AITI) on carbon inequality. Findings show AITI significantly reduces carbon inequality and has spatial spil…

Dandan Song, Q. Truong, Ha-Oanh Vu +2

Using U.S. firm data from 2002-2023, this paper examines the causal impact of climate risk on corporate financial constraints, combining text-based climate risk measures with carbon intensity. Transition risks significantly tighten financin…

Radosveta Krasteva-Hristova, Vanya Georgieva

This conceptual paper systematically examines AI's role in sustainability assurance, identifying five value-adding domains: evidence extraction, criteria mapping, anomaly/greenwashing screening, external-data triangulation, and documentatio…

ANJALI CHAUDHARY, Hebah Shalhoob, Kholoud Y. Bajunaied +5

This study provides a comprehensive analysis integrating AI optimization for biofuel production on degraded lands with climate mitigation and green finance mobilization. Based on 152 studies and international datasets, it shows AI technique…