长三角城市网络外部性的空间异质性

城市网络中是否存在“低端锁定”现象，低等级城市能否从网络中获益，高等级城市是否发挥了辐射带动作用，这些问题关系城市群发展的战略导向，当前仍缺乏深入论证。城市网络外部性是指城市因联系而得到的效益，为回答上述问题提供了理论依据，已成为城市网络研究的新热点。但现有研究主要关注网络外部性的整体特征，忽视区域内城市间的网络外部性差异。本文使用地理加权回归模型将网络外部性测度精确到每个城市，揭示网络外部性的空间异质性特征。研究以长三角地区41个城市为研究对象，按城市汇总企业之间相互投资规模构建城市网络，分析网络联系对城市发展水平的影响，证实了长三角地区存在网络外部性。研究发现：(1)虽然网络外部性未成为主导，但嵌入城市网络已经对江浙沪城市发展起到了积极影响。(2)网络外部性的地域差异较大，江苏省城市的网络外部性普遍强于浙江省，安徽省的网络外部性不强，城市发展仍主要由人、土地和资本的本地集聚决定。(3)长三角地区的网络外部性主要是在上海的辐射带动作用下形成的，3个省会城市南京、合肥、杭州对周边城市的辐射带动作用有限。(4)低等级城市虽未从网络中获得明显的效益，但也未被“低端锁定”，高等级城市没有在周...

Spatial heterogeneity of urban network externalities in the Yangtze River Delta

Is there is a phenomenon of "low-end locking" in the urban network? Can low-grade cities benefit from the urban network? Have high-grade cities played a leading role in the urban network? These issues are related to the strategic orientation of the development of urban agglomeration, which is still lack of in-depth research. Urban network externalities refer to cities benefited by connecting with other cities, which provides a theory for answering the above questions and has become a new hotspot in urban network research. Existing studies focus on the overall characteristics of urban network externalities, but ignore the differences of urban network externalities between cities. In this paper geographical weighted regression model is used to accurately measure the urban network externalities to each city and reveal the spatial heterogeneity of urban network externalities. Taking 41 cities in the Yangtze River Delta region as case studies, we construct the urban network according to the scale of mutual investment of enterprises between cities. Then we analyze the influence of network connection on urban development, which proves that there exist urban network externalities in the study area. The results are as follows: (1) Although the urban network externalities are not dominant, joining urban networks has played a positive role in the urban development of Jiangsu, Zhejiang and Shanghai. (2) There are great regional differences in urban network externalities. The urban network externalities of cities in Jiangsu are generally stronger than those of Zhejiang, while those in Anhui are not strong. Urban development is still mainly determined by the local agglomeration of people, land and capital. (3) The urban network externalities in the Yangtze River Delta are formed mainly under the influence of Shanghai, but the influence of the three provincial capitals — Nanjing, Hefei and Hangzhou — is limited. (4) Although low-grade cities have not benefited from the network, they are not "low-end locking" either. High-grade cities do not form a "cluster shadow" around them. This paper hopes to improve the theory of urban network externalities and provide theoretical support for regional network development.