Impacts of network power and knowledge spillovers on China’s urban green economic efficiency
Impacts of network power and knowledge spillovers on China’s urban green economic efficiency
复制标题
网络力量和知识溢出对中国城市绿色经济效率的影响
DOI：
10.18402/resci.2021.08.01
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发表时间：
2021
期刊：
影响因子：
--
通讯作者：
Wei
中科院分区：
文献类型：
--
作者：
Kerong Sheng;Liping Wang;Wei
在过去的30年里，价值链的生产碎片化推动了中国城市网络的快速发展。中国的城市正日益从“场所空间”中的生产基地向“流动空间”中的网络节点转变。在网络模式下，城市的绿色经济效率将越来越多地受到网络效应的影响，尤其是城市利用重要网络资源的能力和网络伙伴的知识溢出。本研究以2019年中国500强上市公司总部和分支机构所在地数据为基础，采用所有权关联模型近似城市网络，基于数据包络分析（DEA）窗口模型测度城市的绿色要素总生产率，并利用网络力量和知识溢出对城市绿色经济效率的影响进行分析。面板Tobit模型和Hansen阈值模型。三个主要发现如下。首先，网络力量和管道知识溢出在城市经济可持续发展中发挥着重要作用。网络资源的支配度越高，伙伴经济的绩效越高，绿色效率就越高。第二，中国城市网络正处于收益递增阶段。网络力量和知识溢出对城市绿色经济效率既有门槛效应，又有递增的边际效应。第三，与边缘城市、中西部人口规模小的城市相比，网络力量和知识溢出对核心城市、东部人口规模大的城市具有显著的正向影响，表明中国城市之间的绿色效率差距在多个维度上呈扩大的趋势。分析结果具有明确的政策含义。未来，中国政府应促进资源和知识在城市网络内部的流动，以实现更高水平的绿色发展，并密切关注网络发展的异质性影响，积极应对城市绿色经济效率可能扩大的差距。
: Over the past 30 years, production fragmentation of value chains has promoted the rapid development of urban networks in China. Cities in China have increasingly been transformed from production bases in the “ space of places ” to network nodes in the “ space of flows ” . In the network paradigm, the green economic efficiency of cities would be increasingly more affected by network effects, especially their power to utilize vital network resources and knowledge spillovers from network partners. In this study, data on headquarter and branch locations of the largest 500 public companies in China in 2019 were subjected to the ownership linkage model to approximate the urban network, and the total green factor productivity of cities were measured based on the data envelopment analysis (DEA) windows model, then the impacts of network power and knowledge spillovers on urban green economic efficiency were examined by using two broad types of econometric models, i.e., the panel Tobit model and Hansen threshold model. The three main findings are as follows. First, network power and knowledge spillovers through pipeline have been playing an important role in the sustainable development of urban economy. Higher dominance of network resources and higher performance of partners ’ economy both induce higher green efficiency. Second, China ’ s urban network is in the stage of increasing returns. Network power and knowledge spillovers have both threshold effects and increasing marginal effects on urban green economic efficiency. Third, compared with cities in the periphery position, in the central and western regions and with small population size, network power and knowledge spillovers show significant positive impacts on cities in the core position, in the eastern regions and with large population size, indicating that the green efficiency gap between cities in China tends to be widened in multiple dimensions. The analysis results have clear policy implications. In the future, the Chinese government should promote the flow of resources and knowledge within urban networks to achieve higher levels of green development, and pay close attention to the heterogeneous impacts of network development and actively respond to the possibly increasing gaps in urban green economic efficiency.