| 摘要: |
| 随着“ 双碳”目标推进，海洋经济作为国民经济发展的重要支柱， 亟须探索低碳转型与协同降碳路径。文章基于包含非期望产出的超效率 SBM-GML 模型测度碳排放约束下的海洋经济效率，引入修正引力模型和社会网络分析法（SNA），解析碳排放约束下的海洋经济效率的空间关联网络结构特征，并运用二次指派程序（QAP）实证分析网络形成的驱动因素。研究发现：
（1）海洋经济效率整体呈现“波动上升—调整—稳定”的波动趋势，区域分化显著，江苏和浙江等省份效率持续领先，河北和广西等地区陷入“低效率锁定”；（2）空间关联网络密度从 0.209上升至 0.291， 等级度下降 67.3％， 网络结构从“ 核心— 边缘”向“ 多中心网状” 转型， 江苏和浙江等核心节点在空间关联网络中占据主导地位，辽宁和山东等北方省份逐步向次级枢纽跃升；
（3）板块功能分化显著，长三角地区为“净受益板块”，环渤海地区为“双向溢出板块”，各板块内部关联紧密，跨板块协同较弱；（4）空间关联网络的形成主要受地理邻近性、环境规制差异和科研实力差异影响。研究为优化海洋经济低碳协同发展路径提供了依据，对实现区域均衡发展与 “双碳”目标深度融合具有政策启示作用。 |
| 关键词: 海洋经济 海洋低碳 空间关联 社会网络分析 |
| DOI：10.20016/j.cnki.hykfygl.2025.12.004 |
| 投稿时间：2025-09-02修订日期：2025-12-23 |
| 基金项目: |
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| Research on the Spatial Correlation Network and Influencing Factors of Marine Economic Efficiency Under Carbon Emission Constraints |
| REN Xianling,WANG Yiqian |
| School of Economics，Ocean University of China |
| Abstract: |
| With the advancement of the“dual carbon”goals，the marine economy，as a vital pillar of national economic development，urgently requires exploration of low-carbon transition and collaborative carbon reduction pathways．This study employs a super-efficiency SBM-GML model incorporating undesirable outputs to measure marine economic efficiency under carbon emission constraints．It introduces a modified gravity model and social network analysis（SNA）to analyze the structural characteristics of the spatial correlation network of marine economic efficiency under these constraints．Additionally，quadratic assignment procedure（QAP）is used to empirically examine the driving factors of the network．The findings reveal that：（1）Marine economic efficiency overall exhibits a fluctuating trend of“rising fluctuation–adjustment– stabilization，”with significant regional divergence．Provinces like Jiangsu and Zhejiang maintain leading efficiency，while regions such as Hebei and Guangxi are trapped in a “low-efficiency lock-in.”（2）The density of the spatial correlation network increased from 0.209 to 0.291，while the network hierarchy decreased by 67.3％．The network structure transitioned from a“core-periphery”pattern to a “multi-center mesh” pattern．Core nodes like Jiangsu and Zhejiang dominate the network，while northern provinces such as Liaoning and Shandong gradually ascended to secondary hubs．（3）Functional differentiation among blocks is significant：the Yangtze River Delta region acts as a“net beneficiary block，”and the Bohai Rim region serves as a“bidirectional spillover block.”Internal connections within blocks are strong，but cross-block synergy remains weak．
（4）The formation of the spatial correlation network is primarily influenced by geographical proximity， differences in environmental regulation intensity，and disparities in scientific research capability．This research provides a basis for optimizing low-carbon collaborative development pathways for the marine economy and offers
policy insights for achieving balanced regional development and deep integration with the“dual carbon”goals． |
| Key words: Marine economy,Marine low-carbon,Spatial correlation,Social network analysis |
