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Trade-offs and synergy between educational equity and low-carbon urban mobility

教育公平性と低炭素都市モビリティの間のトレードオフと相乗効果 (AI 翻訳)

Jiahong Qi, Biying Yu, ZM Xu, Shuo Xu, Y H, Sujuan Song, Wangni Gao, Xinyue Lv, Jia-Ning Kang, zhang Chengyao, Xiao-Chen Yuan, Yufang Zhou, Lan-Cui Liu, Felix Creutzig, Andrea Pellegrini, John M. Rose, David A. Hensher, Y Wei

Zenodo (CERN European Organization for Nuclear Research)データセット2026-06-16#AI×ESGOrigin: Global対象セクター: transport
DOI: 10.5281/zenodo.20720121
原典: https://doi.org/10.5281/zenodo.20720121

🤖 gxceed AI 要約

日本語

本論文は、学校登録政策下での教育公平性と低炭素交通のトレードオフと相乗効果を調査する。XGBoostモデルで通学手段選択の決定要因を特定し、Nested Logitモデルで各交通手段選択確率への影響を定量化する。非線形関係も考慮した分析結果から、政策介入の示唆を得る。

English

This paper investigates trade-offs and synergies between educational equity and low-carbon transportation under school enrollment policies. It uses an XGBoost model to identify key determinants of school travel mode choice and a Nested Logit model to quantify their effects on mode probabilities, revealing nonlinear relationships. The findings offer policy insights for balancing equity and decarbonization.

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

日本でもコンパクトシティ政策やスクールバスの電化が進む中、教育機会の平等と低炭素モビリティの両立は重要課題。本論文の手法は、地域の通学実態に応じた政策設計に応用可能。

In the global GX context

As cities globally pursue low-carbon mobility, this paper addresses the often-overlooked intersection with educational equity. Its modeling framework can inform integrated transport and education policies, contributing to sustainable urban development discussions under frameworks like the UN SDGs.

👥 読者別の含意

🔬研究者:Provides a two-stage ML-econometric method to analyze trade-offs between equity and carbon goals, applicable to other policy domains.

🏢実務担当者:Urban planners and education authorities can use findings to design school enrollment policies that support both equity and low-carbon transport.

🏛政策担当者:Highlights potential conflicts between equity and decarbonization, urging integrated cross-sectoral policy design.

📄 Abstract（原文）

This is a two-stage modeling framework for the article, 'Trade-offs and synergy between educational equity and low-carbon urban mobility', which investigates the trade-offs and synergies between educational equity and low-carbon transportation under various school enrollment policies. It includes a XGBoost Model and a Nested Logit Model. The XGBoost model is used to identify the key determinants of school travel mode choice and to reveal both linear and nonlinear relationships between explanatory variables and travel behavior. The significant factors and their functional forms identified by the XGBoost model are incorporated into a Nested Logit model to quantify their effects on the probabilities of choosing different travel modes.

🔗 Provenance — このレコードを発見したソース

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