GX Research Hub · English

GX & Decarbonization Research

This page provides an English interface to the gxceed GX paper corpus. The corpus aggregates papers from 13 open 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.

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Topic: #Climate Risk (clear)

Showing 121–140 of 239 papers

Peer-reviewed🌍 GlobalJournalSocial Science Research Network2026#Climate RiskDOI

Physical Climate Risks, Firm Defaults, and Supply Chain Network Propagation

Daniel Dao, A. Jindal, G. Shrimali

This paper develops a forward-looking framework to quantify expected systemic economic losses from physical climate risks and applies it to Indian firm-level data. It shows that physical climate risks increase firm default risk, which propa…

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Peer-reviewedJournalAccounting Horizons2026#Climate RiskDOI

Getting Physical: The Foundations of Climate Evidence in Accounting

Tanya Fiedler, A. Pitman, Sarah Perkins-Kirpatrick

This paper addresses the need for credible evidence on physical climate risk in accounting. It examines the use of global climate models (GCMs), their limitations, and proposes four principles for responsible use to produce decision-useful …

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Peer-reviewedJournalInternational Journal of Finance & Economics2026#Climate RiskDOI

Climate‐Related Extreme Events, Firm Value and Stock Price Crashes

Saeedeh Mehrabi, Mahmoud Lari Dashtbayaz, Taqi Abdul Redha Al Abdwani +1

This study examines the impact of climate-related extreme events (CREE) on firm value and stock price crash risk using 142 Iranian firms from 2012 to 2022. It finds that CREE significantly reduce firm value and increase crash risk in the fo…

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Peer-reviewedJournalOIDA International Journal of Sustainable Development2026#Climate RiskDOI

An Open-Source Geo-spatial Landslide High Risk Area Demarcation for Advancing Sustainable Development in Sri Lanka’s Rathnapura Divisional Secretariat Division

Kokawalage . I.T.H, Jayasinghe K.D.D.P.

This study presents an open-source geospatial methodology using freely available satellite data and QGIS to demarcate high-risk landslide zones in Sri Lanka's Rathnapura District. Weighted overlay analysis identified 70.37 km² as highly sus…

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