This page provides an English interface to the gxceed GX paper corpus. The corpus aggregates papers from 14 contributing scholarly metadata sources and uses AI-assisted classification to identify signals related to measurement, policy narratives, outcomes, implementation, industrial adoption, and verification.
The goal is not only to discover papers, but to observe how GX research is distributed across research substance, implementation narratives, external expectations, implementation substance, and judgment formation.
Summaries are AI-assisted. Always refer to the original paper for authoritative conclusions.
Showing 4041–4060 of 4195 papers
Paweł Szalacha
This paper compares CSRD/ESRS E1 disclosure requirements with actual reporting practices of Polish companies in environmentally impactful sectors. Content analysis of 2024 reports shows progress in narrative descriptions of climate risks bu…
Le Luo, Xin Tan, Q. Zhou
This paper conducts a systematic review of economic consequences of ESG practices disaggregated by the ESRS framework. It reveals that climate change, consumers, and own workforce dominate the literature, while biodiversity and circular eco…
Mohammad Talha
This study examines the early effects of the EU's CSRD on firms' sustainability and financial performance using panel data from 2017-2023. Using a difference-in-differences approach, it finds that mandatory ESG disclosure leads to significa…
Gabriela Marques, A. Aguiar
This paper reviews the role of sustainability accounting in enhancing ESG transparency, stakeholder trust, and long-term value creation. It finds that stronger sustainability accounting capabilities lead to higher ESG scores, investor confi…
Zhaoyang Lu, Martijn Sander
Using firm-level panel data from eight G20 economies (2015-2023), this paper examines the impact of ESG disclosure and circular economy (CE) practices on firm performance, with regulatory strength as a moderator. Applying second-generation …
Jiacheng Liu, Ye Yuan, Zhelun Zhu
This paper synthesizes interdisciplinary insights from accounting, finance, and computational linguistics to review how AI (especially NLP and ML) enhances ESG disclosure quality across readability, comparability, informativeness, and credi…
Nazaf Quaser, Articl Info
This study qualitatively analyzes the role of ESG reporting in enhancing market transparency and investor confidence. Through a systematic review of international disclosure standards and regulatory frameworks, it demonstrates that high-qua…
Deepti Pathak, Monika Chopra
This study uses S&P 500 data (2012-2023) to examine how institutional ownership affects ESG disclosure scores. It finds significant influence in visible sectors like utilities, consumer staples, and industrials, with governance disclosure m…
C. Cepêda, A. Monteiro, Cristina Aibar‐Guzmán
This study examines factors influencing ESG decoupling (gap between disclosure and performance). Using panel data from 3,465 large firms (2009-2023), it finds that higher financial performance increases decoupling, while normative and coerc…
Corinna Irina Ketterling
This paper analyzes the shift from voluntary CSR reporting to legally binding ESG disclosure frameworks from a legal perspective. It examines the evolution of sustainability disclosure standards and their legal implications.
Muhammad Adnan Ali, Dr. Gohar Mahmood, Shahid Mahmood
This study uses a 30-country panel (2015-2024) to examine how national ESG disclosure quality, green bond issuance, and carbon reporting transparency affect sustainability performance. It finds that green investment flows fully mediate the …
Mardi ani
This paper analyzes the role of ESG disclosure in improving financial reporting quality under IFRS S1. Using a quantitative approach, it measures reporting quality via earnings quality, value relevance, and earnings management, and ESG disc…
Huan Wu
This study examines the dual carbon pressures from China's Emissions Trading System (ETS) and the EU's Carbon Border Adjustment Mechanism (CBAM) on the cement and aluminum sectors. It analyzes impacts on operating costs, competitiveness, an…
Junhao Ren, Honglin Gao, Lan Zhao +3
This study develops a multi-agent reinforcement learning framework for self-interested microgrids in P2P electricity trading, addressing renewable generation and demand uncertainties. Each microgrid independently bids price and quantity, op…
Z. Gao
This study proposes a hybrid deep learning model integrating LSTM, GCN, and multi-head attention for dynamic carbon pricing optimization in green transportation supply chains. It improves prediction accuracy by 23.7% and cost optimization b…
M. Luomi, Sarah Wahbah
This paper analyzes design choices in emissions trading schemes (ETS) using data from 38 operational systems worldwide. It covers key elements such as scope, cap setting, allocation, and price management, offering best-practice insights for…
Murat Yıldız, Abdurrahim Akgundogdu, Güldem Elmas
This study develops a distribution-free causal forecasting framework for voyage-level CO2 intensity, using 1440 real-world voyages on four Nigerian coastal routes. A physics-informed LightGBM model with leave-one-route-out protocol predicts…
O. Olawore, Y. Kuti, Kazeem O. Oyerinde +7
Through a systematic review of literature from 2007-2024, this paper analyzes the effects of carbon taxes and emissions trading systems on GHG reduction, technological innovation, and structural change. It examines challenges such as distri…
Mariusz Pyra
This paper analyzes the long-run co-evolution of carbon pricing mechanisms, emissions coverage, and revenues using annual global time-series data (1990-2024). It finds a robust positive correlation between the number of mechanisms and cover…
Rui Tang, Dingyao Yu, Yanping Li +5
This study conducts an ex-post analysis of carbon pricing's emission reduction effects and mechanisms using international data. Results show that carbon pricing significantly reduces emissions, with higher prices leading to greater reductio…
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