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.
Showing 21–30 of 30 papers
有価証券報告書からのリスク文抽出の試み
(著者不明)
This study reports an attempt to extract risk-related sentences from Japanese securities reports. Using natural language processing (NLP), it examines methods to automatically identify ESG-related disclosures, particularly climate risks. Th…
LLMを用いた情報系企業のESG評価についての一考察
(著者不明)
This study explores the use of LLMs for ESG evaluation of information companies, focusing on extracting and analyzing ESG-related information through natural language processing. It develops evaluation indicators tailored to the characteris…
企業における環境活動の改善案の自動生成
(著者不明)
This paper proposes a method for automatically generating improvement proposals for environmental activities in companies. By leveraging AI technology, it aims to derive efficient and effective environmental improvement measures, expecting …
BERTを用いた有価証券報告書からのESG関連文抽出
(著者不明)
This paper proposes a method using BERT to extract ESG-related sentences from Japanese securities reports, enabling automated ESG disclosure analysis.
テキストマイニングを用いた統合報告書の分析による企業戦略の特徴に関する研究‐大手不動産デベロッパーを対象として‐
(著者不明)
This paper applies text mining to integrated reports of major real estate developers to extract and analyze characteristics of corporate strategy. It quantitatively captures ESG-related trends in the reports and highlights differences withi…
Kokubu, Hiroyuki
This paper proposes a disclosure-based method for measuring non-financial evidence infrastructure maturity in corporate sustainability disclosures. It introduces N4 and N5 scoring axes, ΔN (year-on-year change), four regression-type classif…
Hiroyuki Kokubu
This paper empirically examines the value of reasoning-heavy LLMs for automated ESG narrative scoring, using data from ten Japanese listed firms. Using a four-model consensus design, it finds that the mean score deviation between the reason…
Hiroyuki Kokubu
This paper examines structured GHG disclosure accessibility for 89 major Japanese listed firms using EDINET statutory filings and LLM-assisted extraction from voluntary reports. Only 23 firms had current-year structured GHG tags in EDINET; …
UFO: 有価証券報告書の表を対象とした情報抽出タスクの提案
(著者不明)
This paper proposes a new task called UFO (Unstructured Financial Object) for extracting structured information from tables in Japanese securities reports. The authors develop a method combining layout recognition and semantic understanding…
使用済み家電の回収のマルチエージェントシミュレーション
(著者不明)
This paper analyzes the efficient collection of used home appliances using multi-agent simulation. It explores optimal collection routes and schedules under cooperative and competitive agent scenarios, demonstrating the feasibility of reduc…
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