The economic and social development has been facing with serious challenge brought by global climate change due to carbon emissions. As a responsible developing country, China pledged to reduce its carbon emission intensity by 40%-45% below 2005 levels by 2020. The realization of this target depends on not only the substantive transition of society, economy and industrial structure in national scale, but also the specific action and share of energy saving and emissions reduction in provincial scale. Based on the method provided by the IPCC, this paper examines the spatio-temporal dynamic patterns and domain factors of China's carbon emission intensity from energy consumption in 1997-2010 using spatial autocorrelation analysis and spatial panel econometric model. The aim is to provide scientific basis for making different policies on energy conservation and carbon emission reduction in China. The results are shown as follows. Firstly, China's carbon emissions increased from 4.16 Gt to 11.29 Gt in 1997-2010, with an annual rate of 7.15%, which was much slower than that of annual growth rate of GDP (11.72%); therefore, China's carbon emission intensity tended to decline. Secondly, the changing curve of Moran's I indicated that China's carbon emission intensity from energy consumption has a continued strengthening tendency of spatial agglomeration at provincial scale. The provinces with higher and lower values appeared to be path-dependent or space-locked to some extent. Third, according to the analysis of spatial panel econometric model, it can be found that energy intensity, energy structure, industrial structure and urbanization rate were the domain factors that have impact on the spatio-temporal patterns of China's carbon emission intensity from energy consumption. Therefore, in order to realize the targets of energy conservation and emission reduction, we should improve the utilizing efficiency of energy, and optimize energy and industrial structure, and choose the low-carbon urbanization way and implement regional cooperation strategy of energy conservation and emissions reduction.

碳排放所引起的全球气候变化对人类经济社会发展带来了严峻的挑战。中国政府承诺到2020 年GDP碳排放强度较2005 年降低40%~45%,这一目标的实现有赖于全国层面社会经济和产业结构的实质性转型,更有赖于省区层面节能减排的具体行动。基于联合国政府间气候变化专门委员会(IPCC) 提供的方法,本文估算了全国30 个省区1997-2010 年碳排放强度,采用空间自相关分析方法和空间面板计量模型,探讨了中国省级尺度碳排放强度的时空格局特征及其主要影响因素,旨在为政府制定差异化节能减排的政策和发展低碳经济提供科学依据。研究结果表明:① 1997-2010 年,中国能能源消费CO₂排放总量从4.16 Gt 增加到11.29Gt,年均增长率为7.15%,而同期GDP年均增长率达11.72%,碳排放强度总体上呈逐年下降的态势;② 1997-2010 年,碳排放强度的Moran's I 指数呈波动型增长,说明中国能源消费碳排放强度在省区尺度上具有明显的空间集聚特征,且集聚程度有不断增强的态势,同时,碳排放强度高值集聚区和低值集聚区表现出一定程度的路径依赖或空间锁定;③ 空间面板计量模型分析结果表明,能源强度、能源结构、产业结构和城市化率对中国能源消费碳排放强度时空格局演变具有重要影响;④ 提高能源利用效率,优化能源结构和产业结构,走低碳城市化道路,以及实行节能减排省区联动策略是推动中国实现节能减排目标的重要途径。

In recent years, network behaviour has been analysed extensively as the emerging model for economic growth. By network behaviour, a metaphor for co-operative behaviour among individuals, corporate or territorial partners is intended. This is increasingly becoming the reference paradigm in an era of continuing innovation and fast technological change, in the presence of 'market failure' where dynamic and innovative behaviours are concerned and of the high costs of a growth strategy based solely on internal know-how. The theory of the city network paradigm claims that, through participation in the network, cities exploit scale economies in complementary relationships and synergies in co-operative activities. In this sense, network advantage is a real club good, achieved only by those economic actors who are partners in the economic and spatial network, and is distributed among partners despite the private marginal costs each partner bears to participate in the network. In this sense, the private marginal costs of network participation differ from private marginal benefits, and network advantages turn out to be network externalities. The aim of the present paper is to measure the impacts that city network behaviour has on city performance-i.e. to provide a quantitative measurement of network externalities stemming from network behaviour in territorial systems.

In recent years, increased attention has been given to the role of city networks in promoting economic performance. Nevertheless, the empirical evidence concerning urban network externalities and its transmission mechanisms is at best patchy. This study sets out to gain a better understanding of network externalities through the lens of corporate networks in China. Information on the headquarter and branch locations of China's top 500 public companies in 2017 are subjected to ownership linkage model to construct the urban network, resulting in a panel data with 265 cities in 2006 and 2016. Then the impacts of network linking strength and economic performance of partners on urban economic growth are quantitatively measured, and the dynamic mechanisms of network links that affect urban economic growth under the production fragmentation environment are discussed. Two conclusions are drawn. First, the transmission mechanisms of network embeddedness influencing urban economic growth in China have different effects. The analysis results of all samples show that the strength of network links has a profound impact on the quality of urban economic growth, but the impact of economic performance of partners is not obvious. This means that, in general, the transmission mechanisms of network embeddedness are to highlight the comparative advantages and economies of scale of cities, rather than to promote knowledge spillovers and technical progress. Second, the impact of network embeddedness on urban economic growth is heterogeneous in many dimensions. Cities in the eastern region, core position or with a large population size benefit more from the network competitive advantage and the knowledge flow system of "local buzz and global pipelines", while cities in the central and western regions, peripheral position or with a small population, bounded by lack of network competitiveness and "knowledge gatekeeper", increase the risks of low-end lock of industrial economy. In the future, the policy and governance of urbanization in China need to be adjusted accordingly. The Chinese government should promote network cooperation among cities on a larger spatial scale, and attach great importance to the multi-dimensional development gap between cities under the network environment.

近些年来城市网络的快速发展深刻改变了中国城市经济的发展环境,城市网络外部性及其传导机制的研究已经成为新时期城市地理学的重要课题,也将为中国城镇化政策的优化调整提供直接参考。本文以产品价值链生产分割为主线,利用2017年中国上市公司500强企业和隶属联系模型建立城市网络,定量测度了网络链接强度和合作伙伴经济绩效对城市经济增长的影响,揭示了生产分割环境下网络外部性的多样性和异质性特征。研究发现：① 网络嵌入影响中国城市经济增长的传导机制具有不同的作用效果,总体来看网络链接强度对城市经济增长具有显著促进作用,但是合作伙伴经济绩效的影响不明显,表明网络嵌入主要是通过凸显比较优势和规模经济而不是知识外溢来提高城市经济绩效。② 网络嵌入对中国城市经济增长的影响具有异质性特征,东部地区、核心地位、较大规模城市从网络中获得的利益分别明显高于中西部地区、外围地位和较小规模城市,表明网络外部性的经济效果受到城市网络竞争力和知识利用能力的强烈约束。未来中国城镇化政策体系和治理模式需要做出相应调整,中国政府需要在更大空间尺度上推动城市之间的网络合作,同时高度重视网络环境下城市间多维度的发展差距问题。

On the basis of patent transaction data in 2015, spatial pattern of interurban technology transfer network in China was portrayed by integrating big data mining, social network, and GIS, from the perspectives of nodal strength and centrality, linkage intensity, and modular divisions. Then, its key influencing factors were identified as well using the Negative Binominal Regression Analysis. Some findings were ontained as follows. First of all, the intensity of interurban technology transfers in China is not well distributed with obvious polarization. Those cities with higher-level technology transfers are concentrated in the three urban clusters, namely, the Yangtze River Delta, the Pearl River Delta and Beijing-Tianjin-Hebei urban agglomeration. Secondly, a typical core-periphery structure with hub-and-spoke organization is evidently observed, which consists of several hubs and the majority of cities with far lower technology transfers. Beijing, Shenzhen, Shanghai and Guangzhou are acting as the pivot of the technology transfer network and playing a critical role in aggregating and dispersing technology flows. Thirdly, technology linkage intensities of urban pairs appear to be significantly uneven with hierarchies, centralizing in the three edges from Beijing to Shanghai, from Shanghai to Guangzhou and Shenzhen, and from Beijing to Guangzhou and Shenzhen, which shapes a triangle pattern. Fourthly, the technology transfer network is divided into four communities or plates, with prominent reflexivity and spillover effects, which is resulted from geographical proximity and technological complementary. Last but not least, spatial flows of technology are co-organized by a variety of spatial diffusion modes such as hierarchical diffusion, contact diffusion and leapfrog diffusion, owing to economic and administrative powers. They are greatly influenced by urban economic scale, foreign linkage, policy making, as well as multiple proximity factors related to geographical, technological, social and industrial proximities.

基于2015年专利交易数据,融合数据挖掘、社会网络、空间分析等方法,从节点、关联、模块及影响因素4个方面揭示中国城际技术转移的空间格局及其影响因素：① 技术转移整体强度偏低,空间极化严重,长三角、珠三角、京津冀城市群成为技术转移的活跃地带。② 北京、深圳、上海、广州是全国技术转移网络的“集线器”,发挥城际技术流的集散枢纽和中转桥梁作用,中西部大部分城市处于网络边缘,整个网络发育典型的核心—边缘式和枢纽—网络式结构。③ 技术关联的空间层级和马太效应凸显,形成以北京、上海、广深为顶点的“三角形”技术关联骨架结构,技术流集聚在东部地带经济发达的城市之间和具有高技术能级的城市之间,中西部技术结网不足,呈现碎片化。④ 技术转移网络形成明显的四类板块（子群）,具明显自反性和溢出效应,其空间聚类既有“近水楼台先得月”式块状集聚,也有“舍近求远”式点状“飞地”镶嵌。⑤ 城际技术流呈现等级扩散、接触扩散、跳跃扩散等多种空间扩散模式,其流向表现出经济指向性和行政等级指向性特征。⑥ 城市经济发展水平、对外开放程度、政策支持等主体属性和地理、技术、社会、产业邻近性的城市主体关系均会影响其技术转移强度。

Since the Paris Climate Change Conference in 2015, reducing carbon emission and lowering carbon intensity has become a global consensus to deal with climate change. Due to different economic development stages, carbon intensity is regarded as a better index to measure regional energy-related carbon emissions. Although previous scholars have made great efforts to explore the spatiotemporal patterns and key driving factors of carbon intensity in China, the results lack the perspective from city level because of limited availability of statistical data of city-level carbon emission. In this study, based on carbon intensity of 283 cities in China from 1992-2013, we used the kernel density estimation, spatial autocorrelation, spatial Markov-chain and quantile regression panel model to empirically reveal its spatial spillover effects and explore the critical impact factors of carbon intensity at the city level. Our result indicates that although the total carbon emission increased during the study period, carbon intensity saw a gradual decline and regional differences were shrinking. Secondly, the city-level carbon intensity presented a strong spatial spillover effect and diverse regional backgrounds exerted heterogeneous effects on regions. Thirdly, quantile panel data analysis result showed that for low-intensity cities, on the one hand, FDI and transport sector were main contributing factors, and economic growth, technical progress and high population density negatively affected carbon intensity. On the other hand, industrial activity, extensive growth of investment and urban sprawl were key promoting factors for high-intensity cities, and population density was beneficial to emission reduction task. Furthermore, technological advance has not exerted negative influence on carbon intensity in high-intensity cities. At last, we suggested that Chinese government should take different carbon intensity levels into full consideration before policy making.

采用核密度估计、空间自相关、空间马尔科夫链和面板分位数回归等方法对1992-2013年全国283个城市碳排放强度的空间溢出效应和驱动因素进行了分析。① 核密度估计结果表明,中国城市碳排放强度总体均值下降,差异在逐步缩小。② 空间自相关Moran's I指数表明城市碳排放强度存在显著的空间集聚性且空间集聚性在逐渐增强,但空间集聚水平的变化逐年缩小。③ 空间马尔科夫链分析结果表明：第一,中国城市碳排放强度存在马太效应,低强度与高强度的城市在相邻年份转移过程中呈现维持初始状态的特征。第二,城市碳排放“空间溢出”效应明显,且不同区域背景下溢出效应存在异质性,即若与碳排放强度低的城市为邻,该城市的碳强度能够增加向上转移的概率,反之亦然。④ 面板分位数结果显示：在碳排放强度低的城市,经济增长、技术进步、适当的人口密度起到减排作用;外商投资强度与交通排放是使碳强度增大的主要因素。在碳排放强度高的城市,人口密度是重要的减排因素,技术进步暂时没起减排作用;工业排放、粗放式的资本投资以及城市土地蔓延则是碳强度上升的主要因素。

China puts forward the strategic goal of achieving carbon peaks by 2030 and carbon neutrality by 2060. Improving carbon emission efficiency and promoting green and low-carbon development are important ways to achieve the "dual carbon" goal. The study uses the Super-SBM model that includes undesired output to measure the carbon emission efficiency of 68 low carbon cities in China from 2003 to 2018 and analyzes their spatio-temporal evolution characteristics. The panel regression model is used to analyze the influencing factors of urban carbon emission efficiency. The following conclusions are drawn: (1) The carbon emission efficiency of low carbon city has shown an overall upward trend over time, from 0.169 to 0.423, with an average annual growth rate of 6.31%, and there is still room for improvement. (2) Regional differences in the carbon emission efficiency of low carbon cities show a trend of shrinking first and then gradually expanding, and a declining distribution pattern of "from eastern to central and western region" in space; the carbon emission efficiency of pilot city at various levels is characterized as "megacity > supercity > large city > medium-sized city > small city". (3) Economic development level, industrial structure, urbanization level, green technology innovation and carbon emission efficiency of a pilot city are significantly positively correlated, and the intensity of foreign investment has restrictions on urban carbon emission efficiency. There are some differences in the degree of influence of each factor on the three regions and cities of different sizes. The paper puts forward countermeasures and suggestions from the aspects of innovation input, industrial structure and regional differentiation, which has certain reference significance for promoting urban green and low-carbon development and the construction of ecological civilization.

中国提出2030年前实现碳达峰、2060年前实现碳中和的战略目标,提高碳排放效率,推动绿色低碳发展是实现“双碳”目标的重要途径。运用包含非期望产出的Super-SBM模型,测度了2003—2018年中国68个低碳试点城市的碳排放效率并分析其时空演变特征,运用面板回归模型分析城市碳排放效率的影响因素,得出以下结论：（1）低碳试点城市碳排放效率在时间上整体呈上升趋势,效率值从0.169上升至0.423,年均增长率为6.31%,仍有一定的提升空间。（2）低碳试点城市碳排放效率的区域差异呈先缩小后逐渐扩大趋势,空间上呈现“东中西”递减分布格局;从城市等级规模来看呈现“超大城市>特大城市>大城市>中等城市>小城市”特征。（3）经济发展水平、产业结构、城镇化水平、绿色技术创新与试点城市碳排放效率呈显著正相关,外资强度与碳排放效率呈显著负相关,各影响因素对三大地区和不同规模城市的作用程度存在一定的差异性。从创新投入、产业结构和区域差异化等方面提出对策建议,对促进城市绿色低碳发展和生态文明建设具有一定的借鉴意义。

Global warming is a great challenge faced by all mankind. The continued increase in greenhouse gas emissions will have a negative impact on agricultural production, socio-economic activities and human life, and ultimately hinder the process of achieving global sustainable development. This study attempts to introduce the variable of digital economy development into the research framework of carbon emission impact factor theory to systematically examine the effect of digital economy development on urban carbon emissions. This study was conducted to investigate the spatial effects of the digital economy on urban carbon emissions. Based on the panel data of 286 cities from 2011 to 2017, this study analyzes the impact of digital economy development on urban carbon emissions using the spatial Durbin model and the spatial DID model. The main conclusions are as follows:(1) There is spatial heterogeneity in the development pattern of digital economy, and the development pattern changes from "multi-point" sporadic distribution to "cluster" agglomeration, but the gap between the development levels of cities has not been narrowed, and the Yangtze River Delta becomes an important digital economy agglomeration area. (2) The digital economy has a significant negative effect on urban carbon emissions, and the findings are robust to the introduction of the exogenous policy shock of "smart cities". Moreover, there is spatial heterogeneity in this effect, with the negative effect of digital economy on carbon emissions being stronger in the eastern region, and the influence of digital economy is stronger in regions located within urban agglomerations. (3) In order to investigate the spatial decay characteristics of the spillover effect of the digital economy on urban carbon emissions, the spillover effect analysis of the multi-distance economic circle is carried out, and it is found that the spillover effect of the digital economy on carbon emissions peaks at 1100 km. (4) The coverage of digital infrastructure does not have a significant negative effect on carbon emissions in the region, while digital industry development, digital innovation capacity and digital inclusive finance all have a significant negative effect on carbon emissions in the region and neighboring areas. This study adds to the lack of research on the digital economy and carbon emissions, and provides some theoretical reference for the study of the environmental improvement effects of the digital economy.

为探讨数字经济对城市碳排放影响的空间效应,基于2011—2017年286个城市面板数据综合测度数字经济发展水平,运用空间杜宾模型及空间DID模型分析数字经济发展对城市碳排放的影响。主要得到以下结论：① 数字经济发展存在明显的空间异质性,发展格局从“多点式”零星分布向“组团式”聚集形态转变,但各城市发展层级差距仍未改善,长三角成为重要的数字经济高水平集聚区。② 数字经济发展显著改善了城市碳排放,通过引入“智慧城市”这一外生政策冲击进行检验,发现结论具有稳健性,而且这种效应存在明显的空间异质性,东部地区数字经济发展对碳排放的负向影响作用较强,位于城市群内部的区域受数字经济的影响更大。③ 数字经济发展对碳排放的作用在不同经济圈层内有所差异,空间外溢具有边界效应,在1100km处外溢达到峰值。④ 数字产业发展、数字创新能力以及数字普惠金融是数字经济影响城市碳排放效应发挥的重要因素。

The Yangtze River Delta is a demonstration area for China's high-quality integrated development and an important area for China to achieve its peak dioxide emissions by 2030 and carbon neutrality targets by 2060. In the context of the transformation of China's administrative region economy to an integrated economy, the regional integration of the Yangtze River Delta has reduced administrative barriers and optimized the allocation of factors. At the same time, what impact does it have on urban carbon emissions? Based on the panel data of prefecture level and above cities in China, this paper regards the issuance of The Regional Planning of Yangtze River Delta as a quasi-natural experiment, using the difference-in-difference (DID) method to estimate the effects of regional integration in the study area on urban carbon emissions. Furthermore, by using the mediation effect model, we identify the possible internal mechanism of regional integration on carbon emission effects. The results showed that regional integration policy of this delta in 2010 significantly reduced urban carbon emissions, and after a series of robustness tests such as the parallel trend test, PSM-DID and placebo test were still true. From the perspective of dynamic effects, the carbon emission reduction effect appeared in the third year after the issuance of regional integration policy. At the same time, compared with general hierarchy cities, regional integration had a greater effect on carbon emissions reduction of high hierarchy cities. Mechanism verification showed that regional integration policy aggravated urban carbon emissions through the strengthening of economic links between cities, and reduced urban carbon emissions by promoting the upgrading of the industrial structure and the improvement of urban technology. From the perspective of better achieving the goal of high-quality integration in the Yangtze River Delta, it is suggested that the delta should actively explore the cooperation mechanism of carbon emission reduction and green development between cities, and establish a green development evaluation index system that can be monitored and operated. Besides, we should focus on the green transformation of industries and increase investment in green technology research and development among cities in the Yangtze River Delta.

长三角地区是中国高质量一体化发展的示范区,也是实现“双碳”目标的重要区域。在中国行政区经济向一体化经济转变的背景下,长三角区域一体化政策在降低行政壁垒,优化要素配置的同时,产生了怎样的碳排放效应?本文基于中国地级及以上城市的面板数据,以2010年《长江三角洲地区区域规划》的颁布视作一项准自然实验,运用双重差分（DID）模型,研究长三角区域一体化对城市碳排放的影响。在此基础上,采用中介效应模型,识别区域一体化碳排放效应的内在机理。结果表明：2010 年实施的长三角一体化政策显著降低了城市碳排放,并经过共同趋势检验、PSM-DID、安慰剂检验等稳健性检验依然成立;从动态效应来看,区域一体化政策的碳减排效应出现在政策实施后的第三年;从城市等级来看,区域一体化政策对高等级城市碳排放减少的促进作用大于一般城市;从作用机理来看,区域一体化政策通过促进产业结构的升级和城市技术水平的提高,显著降低了城市碳排放,而通过城市间经济联系的增强,在一定程度上增加了城市碳排放。因此,建议建立长三角城市间碳减排与绿色发展的互动合作机制,构建可监测、可操作的绿色发展评价指标体系,加大长三角城市绿色科技联合攻关力度,推动产业低碳化发展。

Low-carbon pilot project is an important policy to realize the development of low-carbon economy in China. Objectively evaluating its implementation effect is not only conducive to better promoting low-carbon work in low-carbon pilot project areas, but also of great significance for the further promotion of low-carbon pilot policy. However, there is no consistent conclusion on whether the low-carbon pilot policy can enhance the performance of carbon emissions. Taking the second batch of low-carbon pilot projects as an example and using city panel data from 2012 to 2016, this study examined the impact of low-carbon pilot policy on the reduction of local carbon emission intensity by using the Propensity Score Matching-Difference in Difference (PSM-DID) method in order to effectively reduce the processing effect bias caused by the problem of sample selection and policy endogeneity. It was found that the low-carbon pilot policy had a significant and sustained effect on local carbon intensity reduction. Further mechanism identification results show that low-carbon pilot areas mainly achieve a decline in carbon intensity through the improvement of energy efficiency and upgrading of industrial structure, and the upgrading of industrial structure shows a trend of increase year by year. However, the goal of reducing carbon emissions by raising the level of carbon sink in urban green spaces has not yet been achieved. Based on this conclusion, we believe that China should further promote the low-carbon pilot policy and actively explore the development model of low-carbon cities, in particular by further establishing a livable and green urban environment.

低碳试点是实现中国低碳经济发展的一项重要政策,客观评价其实施效果,不仅有利于低碳试点地区更好地推进低碳工作,而且对于低碳试点政策的进一步推广具有重要意义,但低碳试点政策能否实现碳排放绩效的提升尚未得出一致的结论。本文以第二批低碳试点政策为例,基于2012—2016年的地级市面板数据,采用倾向得分匹配—双重差分（PSM-DID）方法研究低碳试点政策对降低城市碳排放强度的影响,以有效降低样本自选择及政策内生性等问题导致的处理效应偏差。研究发现：低碳试点政策对城市的碳排放强度下降具有显著且持续的推动作用;进一步的机制识别结果显示,低碳试点城市主要是通过能源效率的提高以及产业结构升级等方式实现碳强度的下降,且产业升级的效果有逐年增强的趋势,但通过城市绿地碳汇水平的提高而降低碳排放的目标尚未实现。基于此结论,本文认为中国应进一步推广低碳试点政策,积极探索低碳城市的发展模式,特别是提升宜居绿色的城市环境。

Fuelled by globalization, informatization and rapid urbanization, the Chinese urban system has witnessed dramatic changes in the past four decades, which shows a combined changing characteristic in both expanded geographical scope and intensified intercity connections. This paper investigates an integrated network-based approaches and spatial analysis to explore the spatial organization process and the basic regularity of Chinese intercity networks. More specifically, this study examines how 330 Chinese cities are connected through 108,570 ownership linkages of 307,915 local corporations for the year 2010. Major findings include: (1) the backbone of the Chinese intercity corporate network is diamond-shaped and anchored by four major metropolitan areas (Beijing in the North; Shanghai, East; Guangzhou-Shenzhen, South; Chengdu, West), intercity network strengths reveal a significant spatial heterogeneity; (2) urban network organization is a complicated process that involve both preferential attachment and geographic proximity interactions; (3) the overall structure of the intercity corporate networks undergo a transition process that from a simple random period to a complex but orderly one and also features small-world network properties; (4) city degree distribution of Chinese intercity networks is characterized by weak assortativity and rich-club effects; and (5) a combination interpretation of clustering coefficient and degree distribution identifies hierarchical and regional tendencies.

全球化、信息化与快速城市化深刻影响了中国的城市体系,多区位企业组织所形成的城市网络正处于日益复杂的空间嬗变过程。基于2010年企业名录的总部—分支机构型关联数据,研究构建了330×330的地级以上城市网络连接关系,并运用复杂网络分析工具来探索中国城市网络的空间组织特征。研究发现：① 中国的城市网络联系呈现以“北京—上海—广深—成都”为核心的菱形空间结构,不同等级的网络流强度具有显著的空间异质性,城市网络的空间组织是一个择优性和地理邻近性复杂作用的过程;② 中国城市网络正处于一个简单随机向复杂有序结构的转化期,整体大尺度的网络结构还有待形成;③ 中国城市网络整体表现出明显的小世界网络效应;④ 中国城市的二值点度网络为明显的异配性连接特征,而加权强度网络连接则一定程度上表现出“富人圈”的现象;⑤ 中国城市网络的层级性并不明显,城市网络的点度和强度的关系呈非线性增加特征。

Cohesive subgroup constitutes a bridge connecting individual cities and urban network. This paper aims to analyze the cohesive subgroups and their mechanisms in the urban network in China. First, data on headquarter and branch locations of China's top 500 public companies in 2016 are subjected to ownership linkage model to approximate the urban network, resulting in a 294×294 valued urban network. Second, four measures of cohesive subgroup analysis, i.e. cliques, k-cores, lambda sets and core-periphery techniques are employed to generalize about the link strengths between cities. Finally, the influencing factors of the cohesive subgroups in the urban network are examined by using quadratic assignment procedure, and the mechanisms are explored under a conceptual framework of urban network growth. Three main findings are concluded. First, the four measures of cliques, k-cores, lambda sets and core-periphery techniques all indicate the presence of cohesive subgroups, revealing the hierarchical structure of link strengths in the urban network in China. The cohesive subgroups are mainly composed of core cities of urban agglomerations, and the cities in the eastern and central regions have more active economic ties compared to the cities in the western region. Second, key resources possessed by cities, such as economic scale, political resources, and knowledge capital, are important factors underlying the formation of cohesive subgroups. Links are more likely to occur between cities with larger economies, richer political resources and more intensive knowledge capital. Temporal distance, geographical location and path dependence also have a profound influence on the spatial pattern of cohesive subgroups. Third, network homophily and path dependence are the dynamic mechanisms underlying the development of cohesive subgroups, and the key resources and location advantages of cities will be further translated into network competitiveness. In the network environment, China's urban governance system and urbanization policies need to be adjusted accordingly. The Chinese government needs to promote network cooperation between cities on a larger spatial scale, and actively respond to the widening economic gap between cities under the network environment.

凝聚子群特征及形成机理的研究是理解城市网络发育规律及其动力机制的重要切入点。利用2016年中国上市公司500强企业总部-分支机构数据,研究了中国城市网络凝聚子群的多维度特征,定量测度了城市间链接关系的影响因素,探索性的分析了凝聚子群的形成机理。结果发现：派系、k-核、lambda集合、核心-边缘方法都表明中国城市网络存在凝聚子群现象,揭示了城市网络链接强度的层级特征;经济规模、政治资源、知识资本是凝聚子群发育的重要影响因素,网络邻近性、地理区位和历史基础也深刻的影响着凝聚子群的空间格局;择优链接和路径依赖是凝聚子群发育的动力机制,城市关键资源和区位优势将进一步转化为城市网络竞争优势。在网络发展环境下,中国政府需要在更大空间尺度上推动城市间合作,并积极应对城市间发展差距趋于扩大的问题。

From the perspective of interlocking network, this paper compares two methods of defining urban hinterworld in the Yangtze River Delta, including the measurement of connectivity and relative connectivity. According to the theory of space of flows, relational data of enterprise branches is selected on the county-level space units in the 16 core cities. Three features have been identified. First, regional network structure could be revealed through the measurement of connectivity but the relative weak connections would be omitted. Second, administrative economy and cross-border connections could be examined deeply through the measurement of relative connectivity, especially to those space units with smaller aggregated connectivity. Third, combining these two methods together, a new way of defining urban hinterworld is proposed which could both reflect the connections between cities and also show the spaciality in the region. The findings of this paper are meaningful when the regional policies are formulated. The division of hinterworld is helpful for assessing the influences of cities and determining reasonable urban system. Empirical results enrich our understanding of the hinterworld in which both relatively strong and relatively weak connections exist at the same time. New perspectives and ways are provided to describe and analyze the relationship between center city and its hinterworld. In the new background and theoretical system, only through analysis of multi-angle observation and combination of a variety of methods we could have a deeper understanding of the regional city network, which is also an important area for future research concern.

从城市关联网络的视角,以企业分支数据为基础,以长三角地区16个核心城市的区市县单元为研究对象,将两种网络腹地的划分方法----网络关联度法和相对关联度法进行了实证分析和比较.结果发现,网络关联度法更能体现区域网络的主要格局,有利于把握区域内主要空间单元的网络联系,但是却会忽略绝对值较小,相对值较大的网络联系;而相对关联度法则可以更为深入的揭示行政区经济和跨行政区联系的特征,特别适用于分析总关联度较低单元(郊区,县,县级市)的网络腹地.在此基础上,本文尝试将两种方法结合起来,既能够体现流动空间中的跨区域网络联系,也能兼顾网络腹地的地域性.实证分析的结论丰富了对于网络腹地的认识,即存在绝对联系较强(弱),相对联系较弱(强)的网络格局,并提供了描述和分析"中心--腹地"关系的新视角和新途径.

The structural resilience of a city network is a rising concept in the field of regional resilience; it focuses on how structural properties affect a region responding to external shocks, as well as recovering, maintaining, or improving the characteristics and key functions of the original system, which is of great significance to the healthy development of regional space. With the help of the Gephi social network analysis tool, this article takes the urban agglomeration in the middle reaches of the Yangtze River as the example and constructs three kinds of networks of economy, information, and transportation, and attempts to measure the structural resilience of the network and spatial characteristics of urban agglomerations. The results show that the structure of the urban agglomeration in the middle reaches of the Yangtze River has a certain resilience. Specifically, the study includes four distinct dimensions: (1) Hierarchy. Economy and information networks have higher levels of hierarchy, and regional locking is more prominent. (2) Assortativity. The disassortativity of information and transportation networks is evident, and they have heterogeneous and diverse contact paths. The economy network has weak disassortativity, leading to an inhibited structural resilience. (3) Transmission. The average path length of the above three networks is generally long and the diffusion efficiency of the material flow is satisfactory. (4) Clustering. Although the spatial clustering of the three network types is different, the aggregation degree is high and the level is equivalent. In a word, the aggregation effect of the three networks is obvious. From the perspective of spatial structure, the structural resilience presents three characteristics. (1) Disparity of the overall morphological patterns. The economy network mainly presents the structural model of "broken core-heterogeneous nested triangle". The information network mainly presents the structural model of "core triangle-star radiation". The transportation network mainly presents the structural model of "core triangle + heterogeneous star radiation". (2) Dislocation of the classified central cities. Wuhan urban agglomeration shows a unique network structure characteristic, which will be summarized as "a single core + edge cities". The Changsha-Zhuzhou-Xiangtan city group exhibits a local network of the city's balanced trend, the performance of "core group + edge city". The comprehensive level of the Poyang Lake urban agglomeration is low, and is mainly based on the isolated structure model of the "single core" of Nanchang. (3) Diversification of the network connection characteristics. The measure of structural toughness is not dependent on the single index value—it should be combined with hierarchy, match, transmission, and clustering. Furthermore, some suggestions are put forward to optimize the spatial structure of urban agglomeration in the aspects of general structure, area structure, and element flow.

城市网络结构韧性是国际上区域韧性（regional resilience,也译作区域弹性）研究领域正在兴起的概念,着眼于城市网络结构对区域应对冲击并恢复、保持或改善原有系统特征和关键功能的影响力,对区域空间的健康发展意义重大。以长江中游城市群为研究对象,在构建经济、信息、交通三类联系网络的基础上,借助于Gephi社会网络分析工具,尝试评估城市群城市网络的结构韧性能力及其空间特征。结果表明：长江中游城市群网络具有一定韧性能力,结构韧性的层级性和匹配性差异较大,传输性和集聚性差距不明显;在空间上呈现出总体形态模式差异化、分区形态模式错位化、网络联系特征多样化的特征。进而,对城市群空间结构在总体结构、片区结构和要素流动等方面的优化提出建议。

In recent years, network analysis has been widely used to understand urban and regional organizational patterns and their spatial effects. A single city benefits from the scale economy of 'networking' in the inter-city synergy relationship. Some cities or regions also suffer from the loss of resources or elements due to more convenient connections to other cities. The traditional urban endogenous growth theory emphasizing agglomeration economy is no longer suitable to explain the urban and regional organization shaped by 'spaces of flow' alone. The externality of urban network has become another important factor affecting urban growth and regional integration. At present, the existing research (especially in China) is relatively scarce, and most of the studies focus on the spatial pattern and process of the network, and the effects (externalities) of network connections are relatively ignored, i.e., how the urban network externalities interact with the agglomeration economy, which types of cities will benefit or suffer from urban network externalities, and what are the conditions for generating urban network externalities. The above need to be discussed urgently. In order to call on academia to shift more attention on network research to the scientific exploration of 'what' and 'how' regarding the effects of urban and regional development and its optimization, this special issue has selected 15 related papers which carry out the systematic theoretical discussion and empirical research aiming at the 'urban network externalities'. They outline the research agenda on Chinese experience of urban network externalities, and use this as a starting point to promote the deepening of urban network research from pattern description to network performance.

近年来,网络分析被广泛应用至理解城市与区域组织模式及其空间效应中。单个城市在城际协同关系中借助“网络化”的规模经济而受益,一些城市或地区也因更便捷地连接其他城市从而导致资源或要素的流失。传统强调集聚经济的城市内生增长理论不再适宜用来单独解释“流动空间”塑造下的城市与区域组织,而城市网络的外部性成为影响城市增长、区域一体化的另一重要动因。目前,已有的研究（特别在国内）相对匮乏,多集中在网络的空间格局、过程等方面,针对网络联系的效应（外部性）较为忽视,比如城市网络外部性与集聚经济如何相互作用,哪些类型的城市将从城市网络外部性中获益或受损,城市网络外部性的产生条件如何等问题亟需探讨。为呼吁学术同行将更多对网络研究的关注移向探究城市网络对城市与区域发展有何作用、如何作用、怎样优化的科学探索,本专辑精心遴选了15篇相关论文,针对“城市网络外部性”开展系统的理论探讨与实证研究,勾勒城市网络外部性的研究议程与中国经验,并以此为起点推动城市网络研究从格局描述走向网络绩效的研究深化。

With the rise of the knowledge economy and network society, knowledge collaboration networks have become vital to understanding innovation processes. There are two types of collaboration patterns within interurban knowledge collaboration networks, namely "local buzz" and "global pipelines". This study discusses the characteristics of intraregional and interregional collaboration linkages and their impacts on the knowledge output based on the logic and hypotheses of the "buzz-and-pipelines" model. First, the study proposes novel measures of buzz and pipelines. Second, the study constructs knowledge collaboration networks among 215 cities at prefecture-level and above across 20 urban agglomerations in China based on the co-publication data drawn from the Web of Science. An investigation of the evolution paths and combination patterns of buzz and pipelines in the networks identifies different collaboration patterns among Chinese cities. Finally, the impacts of buzz and pipelines on cities' scientific output are examined. The results show that: (1) The evolution of buzz and pipelines in China's interurban collaboration networks presents cumulative and self-reinforced path dependences. (2) Chinese cities can be categorized into four types, namely "networked", "outward-oriented", "inward-oriented" and "isolated" cities. Different kinds of cities present distinct features in terms of collaboration trajectories and knowledge production. (3) There is an inverted U-shaped relation between intraregional linkages and the knowledge output performance of Chinese cities, whereas the relation between interregional linkages and knowledge output is significantly positive. The relationship between intraregional and interregional linkages is complementary in facilitating cities' knowledge production processes.

知识经济与网络社会时代,知识合作网络成为理解城市创新过程的重要视角。在知识合作网络中,存在两种不同类型的合作模式,即“本地蜂鸣”和“全球管道”。本文以“蜂鸣—管道”模型的逻辑思想和理论假设为基础,探讨区域内和跨区域两种不同城市知识合作模式的特征及其对城市知识产出的影响。首先提出了蜂鸣与管道的测度方法;然后以“Web of Science”数据库为基础构建了中国20个城市群的知识合作网络,考察了网络中蜂鸣和管道的演化路径和组合特征,归纳出城市知识合作模式的不同类型;最后,通过计量模型揭示了蜂鸣和管道对城市知识产出的影响。结果显示：① 中国城市知识合作网络中的蜂鸣与管道表现出渐进积累和自我强化的空间演化特征;② 根据蜂鸣和管道的组合特征,可将城市划分为“网络型”“外向型”“孤岛型”“内向型”4类,不同类型的城市在知识网络中的空间分布规律和发展演进路径存在差异;③ 根据负二项回归模型发现,蜂鸣与城市知识产出呈倒“U”型关系;管道与城市知识产出显著正相关;此外,两种合作模式在促进城市知识生产的过程中存在互补效应。

In the context of urban network externalities, the borrowed size can empower towns to break through the restrictions of geographical distance and size, but realize the joint economic growth of cities and towns through network connections. By virtue of the theoretical analysis, this research examines, in the framework of network externalities, the role of urban borrowed-size performance on urban economic growth from the perspective of the borrowed-size effect of urban networks. Based on the review of network externalities theories, this research has taken towns in the Guangzhou-Foshan urban area as the object and firstly, adopted the deviation from the mean standard deviation multiplier method to investigate the features of regional performance and agglomeration shadows. Secondly, it established a multiple regression model to test the mechanism of network externalities, by incorporating the coupling effects of town size, borrowed size, transportation network accessibility, and science and technology innovation spillover, etc., on the economic growth of towns. The research has found that (1) with the population size of 100,000 as the cut-off point of performance characteristics, the smaller the existing population size of the town, the lower the value of regional performance, whereas towns with a population size greater or less than 100,000 showcase borrowed-size performance and agglomeration shadow respectively. (2) Regional performance based on the number of newly registered enterprises and enterprise network point degree demonstrate more notable circled spatial characteristics, and the spatial divergence based on the enterprise network point degree test is more prominent; the performance of the suburban near the main urban area is quite notable, while the agglomeration shadow phenomenon of the distant suburbs near the main urban area is more significant. (3) The performance of the number of newly registered enterprises is most closely related to the established size of the town, and the elasticity coefficients of such explanatory variables as regional transportation hub, borrowed size, borrowed-size performance and cross-town cooperation patent decrease decrease in order; besides, the improvement of regional transportation networks and technical cooperation channels is conducive to promoting the agglomeration of urban factors and influencing the urbanization development of urban areas with network externalities effects.

在城市网络外部性的环境下,借用规模可以使城镇突破地理距离和规模等级限制,通过网络联系实现城镇经济的共同增长。基于理论辨析,以城市网络的借用规模效应为视角,检验网络外部性下城镇借用规模绩效对城镇经济增长的作用。在回顾网络外部性理论的基础上,以广佛都市圈城镇作为研究对象,首先利用偏离均值标准差倍数的方法解析区域绩效、集聚阴影等特征;其次,基于城镇规模、借用规模、交通网络通达性、科技创新外溢性对城镇经济增长的耦合作用,建立多元回归模型检验网络外部性的发生机制。研究发现：① 城镇既有人口规模越小,区域绩效值越低,10万人的人口规模是绩效特征的分界点,大于和小于10万人的城镇分别呈现出借用规模绩效和集聚阴影特征;② 基于新增注册企业数量和企业网络点度的区域绩效均呈现出较为明显的圈层式空间特征,且基于企业网络点度检验的空间分异特征更为突出;都市圈主城区近郊圈层城镇的绩效较明显,而主城区远郊圈层城镇的集聚阴影现象显著;③ 新增注册企业数的绩效与城镇既有规模关系最为紧密,与区域交通枢纽、借用规模、借用绩效、跨镇合作专利等解释变量的弹性系数依次降低;区域交通网络、技术合作网络的提升有利于促进城镇要素集聚,并通过网络外部性效应影响都市圈的城镇化发展。

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.

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边形成“集聚阴影”。本文希望能有助于完善城市网络外部性理论,为区域网络化发展提供理论支撑。

The paper is concerned with spatial clustering of economic activity and its relation to the spatiality of knowledge creation in interactive learning processes. It questions the view that tacit knowledge transfer is confined to local milieus whereas codified knowledge may roam the globe almost frictionlessly. The paper highlights the conditions under which both tacit and codified knowledge can be exchanged locally and globally. A distinction is made between, on the one hand, the learning processes taking place among actors embedded in a community by just being there dubbed buzz and, on the other, the knowledge attained by investing in building channels of communication called pipelines to selected providers located outside the local milieu. It is argued that the co-existence of high levels of buzz and many pipelines may provide firms located in outward-looking and lively clusters with a string of particular advantages not available to outsiders. Finally, some policy implications, stemming from this argument, are identified.

China has implemented the low-carbon city pilot (LCCP) policy in the hopes of efficiently limiting carbon emission intensity to combat global warming and promote green economic growth. Urban land utilization, the second-largest source of carbon emissions, is key to the LCCP policy being able to have the desired effect, which has attracted widespread attention. Based on the panel data from prefecture-level cities in China from 2006 to 2019, this study used the propensity score matching difference-in-differences method (PSM-DID) to examine the impacts of LCCP policy on green utilization efficiency of urban land (GUEUL). The results reveal that LCCP policy has a beneficial impact on GUEUL and can effectively boost the future possibilities of green and low-carbon city development. Due to variances in regional economic and resource endowment level, the impacts of LCCP are different. The pilot has pushed GUEUL in the eastern region, western region, and growing resource-based cities, but has failed to improve GUEUL in other regions. Policymakers should adhere to the long-term sustainability of the LCCP policy and adopt differentiated action strategies to promote GUEUL when implementing it in different regions.

Quantitative analysis of influencing factors of carbon emissions has an important guiding effect on reducing regional carbon emissions. This article, based on STIRPAT model, made an analysis of several factors influencing carbon emissions from energy consumption in Jiangsu province, respectively population, affluence (in form of per capita GDP), techonology (in form of energy intensity) and urbanization. The results of Ridge regression showed that for 1% change in population, per capita GDP, energy intensity and the level of urbanization, there was 3.467%, (0.242+0.024lnA)%, 0.313%, and 0.151% change in energy carbon emissions in Jiangsu, respectively. Based on this study, the paper set eight scenarios to furthur analyze and predict the future trend of carbon emission in Jiangsu. It is found that low growth rate of population, low growth rate of per capita GDP and high technology progress rate would help to control carbon emissions, and the carbon emissions in 2020 would be 202.81 MtC in that case. To control Jiangsu's future carbon emissions, it is essential to not only improve the technology progress rate and control the population quantity, but also to reduce the growth rate of per capita GDP, which indicates the government should slow down economic development and transform the economic growth mode to New Normal.

定量分析碳排放的影响因素,对降低区域碳排放具有重要的指导意义。利用STIRPAT模型,定量分析江苏省能源消费碳排放量与人口、富裕度（以人均GDP表示）、技术进步（以能源强度表示）和城镇化水平之间的关系,通过岭回归拟合后发现,人口数量、人均GDP、能源强度、城市化水平每变化1%,江苏省能源消费碳排放量将分别发生3.467%、(0.242+0.024 lnA)%、0.313%和0.151%的变化。在以上研究的基础上,设置8种不同的发展情景,分析了江苏省未来能源消费碳排放量的发展趋势。结果表明,当人口、经济保持低速增长,并保持高技术增长率时,有利于控制江苏省的能源消费碳排放量,2020年江苏省的能源消费碳排放量预测值为202.81 MtC。

In this article, we attempt to distinguish between the properties of moderator and mediator variables at a number of levels. First, we seek to make theorists and researchers aware of the importance of not using the terms moderator and mediator interchangeably by carefully elaborating, both conceptually and strategically, the many ways in which moderators and mediators differ. We then go beyond this largely pedagogical function and delineate the conceptual and strategic implications of making use of such distinctions with regard to a wide range of phenomena, including control and stress, attitudes, and personality traits. We also provide a specific compendium of analytic procedures appropriate for making the most effective use of the moderator and mediator distinction, both separately and in terms of a broader causal system that includes both moderators and mediators.