Article(id=1263557422405305176, tenantId=1146029695717560320, journalId=1240618002186551303, issueId=1263557421033767765, articleNumber=null, orderNo=null, doi=10.3969/j.issn.1000-4653.2026.01.010, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1736956800000, receivedDateStr=2025-01-16, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1779185165262, onlineDateStr=2026-05-19, pubDate=1771948800000, pubDateStr=2026-02-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1779185165262, onlineIssueDateStr=2026-05-19, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1779185165262, creator=13701087609, updateTime=1779185165262, updator=13701087609, issue=Issue{id=1263557421033767765, tenantId=1146029695717560320, journalId=1240618002186551303, year='2026', volume='49', issue='1', pageStart='1', pageEnd='197', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1779185164936, creator=13701087609, updateTime=1779185226134, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1263557677813252309, tenantId=1146029695717560320, journalId=1240618002186551303, issueId=1263557421033767765, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1263557677813252310, tenantId=1146029695717560320, journalId=1240618002186551303, issueId=1263557421033767765, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=96, endPage=104, ext={EN=ArticleExt(id=1263557423223194460, articleId=1263557422405305176, tenantId=1146029695717560320, journalId=1240618002186551303, language=EN, title=Measurement of carbon emission efficiency and influencing factors of port clusters in the Bohai Rim region, columnId=1240655021705065434, journalTitle=Navigation of China, columnName=Port and Waterway Engineering, runingTitle=null, highlight=null, articleAbstract=

With the implementation of the "2024-2025 Energy Conservation and Carbon Reduction Action Plan", the port industry, as a core component of the transportation system, faces urgent tasks in energy conservation and emission reduction. To enhance the carbon emission efficiency and competitiveness of regional port clusters, and to promote more sustainable development of port clusters in the Bohai Rim region, this study measures the carbon emission efficiency and dynamic efficiency of 14 major ports in the Bohai Rim from 2007 to 2022 using the unexpected output super-efficiency SBM-Malmquist model. A Tobit regression model is further constructed to analyze the influencing factors of port carbon emission efficiency. The results reveal an overall upward trend in carbon emission efficiency among Bohai Rim ports. The regional ranking of carbon emission efficiency has shifted from Shandong > Liaodong > Jingjinji to Jingjinji > Shandong >Liaodong, with the efficiency gap between Jingjinji and the Shandong and Liaodong Peninsula ports widening. Scientific innovation and ecological compensation are identified as primary drivers of port carbon emission efficiency improvement, while the level of openness, transport capacity, and industrial structure exert negative effects. Based on these findings, this paper proposes pathways for improving carbon emission efficiency and optimizing management in Bohai Rim port clusters.

, correspAuthors=Shaoqiang YU, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, authorCompany=null, fund=null, authors=null, authorsList=Shaoqiang YU, Jinghan WU, Xue LI, Kang CHEN), CN=ArticleExt(id=1263557426196956021, articleId=1263557422405305176, tenantId=1146029695717560320, journalId=1240618002186551303, language=CN, title=环渤海区域内港口群碳排放效率测度及影响因素研究, columnId=1240655021902197734, journalTitle=中国航海, columnName=水运工程, runingTitle=null, highlight=null, articleAbstract=

随着《2024—2025年节能降碳行动方案》的推出，港口行业作为交通运输系统的核心组成部分，面临着节能减排的紧迫任务。为提升区域港口群碳排放效率、增强港口群的竞争力、推动环渤海区域内港口群实现更加可持续的发展目标，文章基于非期望产出的超效率SBM-Malmquist模型，测算2007年~2022年环渤海14个主要港口的碳排放效率及动态效率，并构建Tobit回归模型对港口碳排放效率的影响因素进行研究。环渤海区域内港口群碳排放效率由山东地区>辽宁地区>京津冀地区转变为京津冀地区>山东地区>辽宁地区，并且京津冀及山东港口碳排放效率与辽宁港口的差距在不断加大。科技创新、生态补偿是港口碳排放效率提升的主要因素，而对外开放水平、交通运输能力、产业结构对港口碳排放效率产生负向影响。基于此，论文提出了环渤海区域内港口群碳排放效率提升及管理优化的途径。

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于少强（1969—），男，教授，研究方向为战略与决策管理。

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于少强（1969—），男，教授，研究方向为战略与决策管理。

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