Green operational performance comparison of container trailers between traditional container terminals based on carbon footprint analysis
カーボンフットプリント分析に基づくコンテナターミナル間のコンテナトレーラーのグリーン運営性能比較 (AI 翻訳)
Yi-Chih Yang
🤖 gxceed AI 要約
日本語
コンテナトレーラーの運転モードがCO2排出に与える影響をカーボンフットプリント分析とグレイリレーショナル分析を用いて評価。2つのターミナル運営モードを比較し、運転時間、エネルギーコスト、排出量の観点からグリーン性能を検証。ERPやAI技術の活用が効率向上と排出削減に寄与する可能性を示唆。
English
This study evaluates CO2 emissions from container trailer operations using carbon footprint and gray relational analysis. It compares two terminal operation modes and finds that factors like distance, speed limits, and loading affect efficiency. The paper suggests that ERP, big data, 5G, and AI can improve energy savings and carbon reduction.
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
日本のコンテナターミナルでもトレーラーのCO2排出削減は重要。本分析手法は日本の港湾の運用改善にも応用可能。
In the global GX context
This paper contributes to the growing body of research on carbon footprint in logistics, particularly port operations. It provides a method for comparing operational modes that can be applied to other container terminals globally, supporting energy efficiency and carbon reduction targets.
👥 読者別の含意
🔬研究者:Provides a methodology combining carbon footprint and gray relational analysis for green logistics performance comparison.
🏢実務担当者:Offers insights on how to evaluate and improve container trailer operations for energy cost and carbon emission reductions, with potential use of ERP and AI.
🏛政策担当者:Could inform port regulations and incentives for adopting more efficient container handling modes.
📄 Abstract（原文）
Purpose The purpose of this study is to explore the impact of CO2 emissions produced by container trailer operations on the climate-warming environment and to calculate the different operating modes of cross-port trailers at container terminals. Design/methodology/approach This article employs integrated methodologies, including the carbon footprint (CF) calculation method and gray relational analysis. The “CF calculation method” primarily utilizes an export container operating trailer to transport containers from the container terminal based on an activity-based approach. “Gray relational analysis” mainly compares two traditional container terminal modes based on the operational efficiency assessment criteria. Findings The improvement of container trailer operational efficiency is related to factors such as transportation distance, speed limit, road conditions, loading conditions and operating efficiency and other factors. Research limitations/implications We analyzed the overall performance of the two container yard operation modes through a gray relational analysis of three key factors: operation time, energy cost and carbon emissions. The gray correlation ranking order is TT> RT. Practical implications From the perspective of CF, we can understand which operating modes can better meet the requirements of green port operations and provide improvement suggestions for achieving energy conservation and carbon-reduction targets. Social implications The empirical examination revealed that using enterprise ERP, big data, 5G and artificial intelligence algorithms can enhance the operating efficiency of container trailers and improve energy-saving and carbon-reduction outcomes. Originality/value The empirical findings provide energy-saving and carbon-reducing green transportation logistics operation alternatives and countermeasures for areas or operating models with higher carbon emissions, which can serve as a reference for future container terminals, trailer companies and government authorities.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.1108/mabr-11-2025-0123first seen 2026-07-18 05:55:55
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