Extraction dataset for: System boundary, not technology: a systematic review of Avoid–Shift–Improve strategies for passenger transport decarbonization
抽出データセット：システム境界、技術ではなく：旅客輸送脱炭素化のための回避・転換・改善戦略の系統的レビュー (AI 翻訳)
Gutiérrez Pascual, Joan Pau
🤖 gxceed AI 要約
日本語
本データセットは、旅客輸送脱炭素化におけるASI（回避・転換・改善）戦略の系統的レビューを支えるもので、46件の研究の抽出コーディングを含む。各研究について、地理的焦点、ASIピラー分類、分析方法、システム境界、排出削減推定値などを記録している。このデータセットは、レビュー論文の文献計量分析と証拠統合に使用された。
English
This dataset supports a systematic review of Avoid-Shift-Improve strategies for passenger transport decarbonization, containing structured extraction coding for 46 peer-reviewed studies. It captures variables such as geographic focus, ASI pillar classification, analytical method, system boundary, and reported emission reductions. The dataset underpins the bibliometric analysis and evidence synthesis in the associated review.
Unofficial AI-generated summary based on the public title and abstract. Not an official translation.
📝 gxceed 編集解説 — Why this matters
日本のGX文脈において
日本の運輸部門の脱炭素化政策（次世代自動車戦略、公共交通利用促進など）において、システム境界の重要性を示す本レビューは、政策評価や企業のScope 3算定の精緻化に示唆を与える。
In the global GX context
This systematic review highlights the critical role of system boundaries in assessing transport decarbonization strategies, offering a framework relevant to global policy evaluation and corporate Scope 3 accounting under ISSB and CSRD.
👥 読者別の含意
🔬研究者:Provides a structured dataset and framework for analyzing ASI strategies and system boundaries in transport decarbonization research.
🏢実務担当者:Offers insights into how system boundary choices affect reported emission reductions, useful for corporate transport-related Scope 3 reporting.
🏛政策担当者:Informs transport policy design by clarifying the impact of system boundaries on the effectiveness of Avoid-Shift-Improve measures.
📄 Abstract（原文）
This dataset supports the systematic review The dataset contains the structured extraction coding for all 46 peer-reviewed studies included in the final synthesis, identified through a Scopus database search (September 2025) and backward and forward citation tracking. Each record corresponds to one included study and captures the following variables: study reference and publication year; geographic focus and spatial scale; ASI pillar classification (Avoid, Shift, Improve, Shift/Improve, or Integrated ASI); sub-strategy; whether the study adopts a multi-pillar approach; analytical method (life-cycle assessment, scenario/integrated-assessment model, empirical analysis, policy assessment, or review); system boundary (tailpipe, operational/energy-system, partial well-to-wheel, full life cycle, or unspecified); reported emission-reduction estimate or key finding; baseline metric and temporal horizon; key limitation as reported by the original study; identification source (database search or snowball); and methodological quality rating (High, Medium, or Low) based on the appraisal criteria described in the Methods section of the associated review. The dataset was used to produce the bibliometric analysis, the ASI pillar and system-boundary distributions, the attention-effort mismatch figure, and the evidence synthesis reported in the paper.
🔗 Provenance — このレコードを発見したソース
- Zenodo https://zenodo.org/records/21892163first seen 2026-08-12 04:23:22 · last seen 2026-08-13 04:34:51
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gxceed は公開メタデータに基づく研究支援データセットです。要約・翻訳・解説は AI 支援で生成されています。 最終的な解釈・検証は利用者が原典資料に基づいて行うことを前提とします。