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The Transition Towards the Electrification of Construction Sites—A Systematic Review of Drivers, Barriers and the Way Forward

建設現場の電化への移行—ドライバー、障壁、そして今後の方向性に関する系統的レビュー (AI 翻訳)

Shabnam Homaei, Aileen Yang, Selamawit Mamo Fufa, Marianne Kjendseth Wiik

Buildingsジャーナル2026-06-26#エネルギー転換Origin: EU経営インパクト: コスト削減対象セクター: construction
DOI: 10.3390/buildings16132534
原典: https://doi.org/10.3390/buildings16132534

🤖 gxceed AI 要約

日本語

本論文は建設現場の電化に関する55件の文献を系統的にレビューし、8つの主要テーマ(要件、技術・市場、経済、プロセス・運営、インフラ、知識・経験、環境、態度)を抽出した。ドライバーと障壁の強い相互連関を示し、明確な政策枠組み、戦略的公共調達、知識共有イニシアチブ、堅牢なデータシステムが排出ゼロ建設現場の拡大に不可欠な促進要因であると結論づけた。知見は主にノルウェーの経験に基づくが、他地域にも適用可能である。

English

This systematic review of 55 publications on electrification of construction sites identifies eight key themes: requirements, technology & market, economics, process & operations, infrastructure, knowledge & experience, environment, and attitude. It finds strong interconnections between barriers and drivers, and concludes that clear policy frameworks, strategic public procurement, knowledge sharing initiatives, and robust data systems are critical enablers for scaling emission-free construction sites. Lessons drawn from Norwegian experiences are transferable to other regions.

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

日本でも建設現場の脱炭素化が進む中、本レビューの知見は公共調達やデータ整備の政策設計に示唆を与える。SSBJ開示基準において、建設機械の電化はスコープ1排出削減に直結するため、実務者・規制当局の双方に参考となる。

In the global GX context

This review provides a structured framework for understanding the transition to electric construction sites, which is relevant to global disclosure frameworks such as ISSB and TCFD as companies report scope 1 emissions from mobile machinery. The identified enablers—clear policy, public procurement, and data systems—offer actionable insights for policymakers and practitioners worldwide.

👥 読者別の含意

🔬研究者:A systematic mapping of drivers and barriers, revealing interconnections and research gaps in construction site electrification.

🏢実務担当者:Identifies critical enablers such as strategic procurement and data systems for implementing emission-free construction sites.

🏛政策担当者:Highlights the necessity of clear policy frameworks and public procurement strategies to accelerate electrification, with transferable lessons from Norway.

📄 Abstract(原文)

The construction industry is a major contributor to global greenhouse gas (GHG) emissions. Different strategies have been implemented to reduce the environmental impact of construction sites and create better city environments for construction workers and citizens. Electrification of construction machinery is one such measure and is rapidly evolving. However, existing literature has largely concentrated on either electrification of road vehicles or emission reduction via the electrification of a building’s operational energy use. This paper presents a systematic literature review on available publications focusing on the electrification of construction sites, identifying and analyzing the key drivers and barriers influencing this. In addition, it provides recommendations for better and effective electrification of construction sites. A total of 55 publications were analyzed to extract insights and organize findings into eight key themes: requirements, technology and market, economic, process and operations, infrastructure, knowledge and experience, environmental, and attitude. The findings indicate strong interconnections between the barriers and drivers to electrification of construction sites. Clear policy frameworks, strategic public procurement, knowledge sharing initiatives, and robust data systems emerged as critical enablers for scaling emission-free construction sites. The lessons learnt are largely drawn from Norwegian experiences but are highly transferable to other cities and regions and offer practical insights into policy design, procurement strategies, and collaborative models for actors interested in reducing GHG emissions and transition into electrification of construction sites.

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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。