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 7961–7980 of 32695 papers
Jo- Chen Lin M.
This paper examines the development of fuel cell technology and the green hydrogen economy in Taiwan. It outlines the role of hydrogen in Taiwan's energy transition policy and discusses its potential contribution to decarbonization. Specifi…
Suryantini N.P.S.
This paper employs bibliometric methods to analyze the existing literature on the relationship between green finance and sustainability, mapping research trends, key themes, and future directions. It offers a comprehensive overview of the g…
Kosi U.
This paper investigates the readiness of firms for the EU's Corporate Sustainability Reporting Directive (CSRD). It analyzes the complexity of disclosure requirements and data collection challenges, assessing the degree of corporate prepare…
Mutmainna Rachman, Ismail Rasulong, Muhammad Yusuf
This systematic literature review (PRISMA 2020) synthesizes 32 studies on green management and corporate sustainability outcomes. It identifies four themes: governance, disclosure credibility, operational integration, and outcome trade-offs…
Ching Li, Ting-Yen (Tim) Huang, Jia-Rui Zheng
This study analyzes maladaptation risks in Japan's ski industry, where adaptation measures can create new vulnerabilities. Using an elevation-based Snow Reliability Line (SRL) screening framework with JMA climate data and resort documents, …
Yating Zhang, Dustin T. Cook, S. Sattar +3
This paper proposes a hybrid method combining unit process analysis and economic input-output analysis to quantify embodied carbon emissions from post-earthquake building repair and functional loss. It accounts for repair materials, transpo…
Thu Hang Ha, Lan Hoang Nguyen, Q. H. Nguyen +3
This paper presents SmartGHG, an Excel-VBA tool for automating Scope 1 and 2 GHG emission calculations at Vietnamese thermal power plants, aligned with Circular 38/2023/TT-BCT and Decision 2626/QĐ-BTNMT. It integrates national emission fact…
Tianzheng Luo, Zhipeng Cui, Zixin Tian
This study uses a difference-in-differences approach on 105 Chinese listed construction firms (2010-2020) to show that the Green Finance Reform and Innovation Pilot Zone (GFRIPZ) policy significantly boosts green innovation, with improved f…
Sohidul Islam, Reday Chandra Bhowmik, H. G. Sulimany +3
Using quantile-on-quantile regression on G7 data (1995-2023), this study finds green finance consistently reduces ecological footprint, while green innovation and recycling show positive effects in most quantiles, and energy transition has …
Xufei Li, Junfa Fu, Qi Ding +2
This review summarizes recent advances in hydrogen-bonded organic frameworks (HOFs) for C2 gas separation, including C2H2/CO2, C2H2/C2H4, and C2H6/C2H4. HOFs offer low-energy adsorptive separation alternatives to traditional distillation, p…
Akshay Mehta, K. Sonawane, P. Saini +3
This paper presents a digital CCUS subsurface monitoring framework integrating sparse seismic, 3D/4D seismic, and VSP data. It leverages AI/ML for plume tracking, leakage risk assessment, and uncertainty management. The modular, cloud-enabl…
Akshay Mehta, K. Sonawane, P. Saini +3
This paper proposes a KPI-driven digital platform for CCUS operations, integrating IoT, cloud, and predictive analytics to unify data from capture, transport, and storage. It enables real-time monitoring, anomaly detection, and automated ca…
Annisa Fithria, R. Ainy, Andreas Vernando +2
Using panel data of 576 banks across 62 countries from 2009-2023, this study finds that IFRS adoption is positively associated with ESG disclosure, especially for environmental and social components. Major events like the Paris Agreement an…
Chethan K Murthy, Prateek Verma, Subhash Mondal
This paper introduces an agentic AI ESG consultant using a privacy-preserving, localized RAG system to automate ESG compliance gap analysis for regulations like CSRD and BRSR. It bridges corporate disclosures and legal statutes via iterativ…
Aliyah Ardiwati Puspita, I. Imronudin
This study examines the impact of eco-efficiency and ESG disclosure on the financial performance of LQ45 companies listed on the Indonesia Stock Exchange from 2021 to 2024. Using 84 firm-year observations, the analysis reveals that variatio…
Tong Ni, Wanlong Huang, Yifei Tang +2
This paper addresses low liquidity and fiscal policy mismatches in Green Electricity Certificate (GEC) markets by developing a supply-demand model integrating tax credits and tiered carbon taxes. Using an ε-constraint multi-objective optimi…
Nhung Nguyen-Hong, Anh Vu-Tuan, Tung Vu-Quang
This paper proposes an optimization framework for a Virtual Power Plant (VPP) integrating CCS and P2G technologies, participating in both day-ahead electricity and carbon trading markets. Using mixed-integer linear programming, it maximizes…
Teru Ogawa, Junji Otani, Mika Goto
This study examines the impact of participation in environmental initiatives (RE100, SBTi) on productivity for 642 Japanese manufacturing firms. Using propensity score matching and a Malmquist index from DEA with panel models, it finds that…
Yutong Shen, Wang Yang, Yue Shen
CogDeBias is a multilingual framework integrating LLMs and ML to automatically detect and mitigate six cognitive biases (e.g., confirmation bias, sunk cost fallacy) in corporate annual reports. A bilingual corpus of 1,200 reports (600 Engli…
Yihan Qiao
This paper empirically analyzes the impact of carbon emission intensity on firm value using panel data of Chinese A-share listed companies from 2003 to 2021. The results show that carbon emission intensity has a significant negative effect …
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