| 中国绿色发展空间关联网络特征及动态演化 |
| 摘要点击 538 全文点击 12 投稿时间：2025-05-06 修订日期：2025-09-17 |
| 查看HTML全文
查看全文 查看/发表评论 下载PDF阅读器 |
| 中文关键词 绿色发展 空间关联网络 社会网络分析 模体结构 动态指数随机图模型 |
| 英文关键词 green development spatial association networks social network analysis motif structure temporal exponential random graph model |
| DOI 10.13227/j.hjkx.202505025 |
|
| 中文摘要 |
| 绿色发展是实现高质量发展的核心关键环节与鲜明特色标识，精准厘清其发展状况，对于推动中国经济社会实现全面绿色转型极为重要. 选择2012~2023年中国31省域（中国台湾、香港和澳门资料暂缺）为研究对象，综合运用非期望Super-SBM模型和修正型引力模型架构绿色发展空间关联网络，解析绿色发展空间关联网络宏观特征和微观结构，构建动态指数随机图模型（TERGM）探究网络的动态演化机制. 结果表明：①中国绿色发展水平呈现波动中增长的趋势，区域差异缩小. ②绿色发展的空间关联呈现了“东密西疏”特征，京津冀和江浙沪地区始终处于网络中心，上海、北京和江苏等少数关键省域始终占据网络主导地位. ③“双向溢出”和“净溢出”板块主要分布在中西部省域，“净收益”和“经纪人”则以东部沿海省域为主，研究期内各板块均发生了不同程度的重组；研究期网络模体主要呈现为链式结构，但在2023年网络和均值网络中，全通道式模体结构已呈现出最重要地位. ④地理空间邻接、网络内生结构、经济规模、对外开放、产业结构和金融发展等关系变量均对绿色发展空间关联网络的形成和演化产生了重要影响，且影响依照时间间隔呈现了明显的异质性特征. |
| 英文摘要 |
| Green development is a core and key link as well as a distinct characteristic identifier for achieving high-quality development. Accurately clarifying its development status is of great significance for promoting the comprehensive green transformation of China's economy and society. Taking 31 provinces in China from 2012 to 2023 as the research objects （excluding data from Hong Kong， Macao， and Taiwan）， this study comprehensively employs the non-desired Super-SBM model and the modified gravity model to construct the spatial correlation network of green development. From both macro and micro perspectives， the social network and motif analysis models are utilized to analyze the characteristics and structure of the spatial correlation network of green development， and the dynamic exponential random graph model （TERGM） is constructed to explore the dynamic evolution mechanism of the network. The research shows that： ① The spatial correlation of green development among various provinces in China was increasingly close， but the total amount of network relations had not yet reached its maximum potential. It also showed a feature of "dense in the east and sparse in the west" in spatial distribution. The Beijing-Tianjin-Hebei region and the Jiangsu-Zhejiang-Shanghai region were always at the center of the green development network. ② A few key provinces such as Shanghai， Beijing， and Jiangsu consistently held a dominant position in the spatial correlation network， showing a clear “club convergence” feature. Currently， the eastern region has formed an internal cohesive sub-group， while the central and western regions have established more inter-regional correlation relations with the eastern region. ③ The “bidirectional spillover” and “net spillover” sectors were mainly distributed in the central and western provinces， while the “net benefit” and “broker” sectors were mainly in the eastern coastal provinces. During the research period， all sectors had undergone varying degrees of reorganization. The network motifs in the research period mainly presented a chain structure， but in the 2023 network and the mean network， the full-channel motif structure had taken on the most important position. ④ Geographical spatial adjacency， endogenous network structure， economic scale， openness to the outside world， industrial structure， and financial development， among other relationship variables， all exerted significant influences on the formation and evolution of the spatial correlation network of green development， and these influences have shown obvious heterogeneity characteristics over time intervals. |
