技术转移是区域经济发展的主要方式。城市作为多种要素流动的中心,彼此间的相互作用和联系状况,是城市地理研究的重要内容。因此,在知识经济时代,对技术转移的机理进行探讨尤为重要。在此背景下,论文基于国家知识产权局2000—2015年的专利转移数据,借助Gephi、ArcGIS和Stata等工具,对中国技术转移网络的主体结构、分部类模式及其空间特征进行了探究。结果表明：① 就技术转移网络的主体而言,虽然民营企业和高校的地位不断攀升,但多数联系建立在高校、科研院所与其衍生企业之间,说明网络整体连通性较低,溢出效应微弱;② 从分部类专利转移数据来看,对创新能力要求较高的知识往往在相对较少的地方产生,且其转移的空间尺度主要集中于城市内,说明中国城市间技术转移存在一定的地域阻隔;③ 对多维邻近性及其影响的回归分析表明,多数城市在建立创新联系时,更倾向与同一行政区内或地理、技术规模邻近的城市进行专利转移,即地理邻近、技术邻近、社会邻近对中国产学研合作网络的构架具有正向的促进作用。

Technology transfer is the main route of regional economic development. Cities are the center of the flow of various elements, and interactions and relationships between them is an important content of urban geography research. Therefore, in the era of knowledge economy, the mechanism of technology transfer is particularly important. Consequently, in the perspective of technology transfer and network capital and based on the patent transfer data from the State Intellectual Property Office for 2000-2015, this study explored the main structure, the sub-category model, and the spatial characteristics of the technology transfer network using Gephi, ArcGIS and Stata. The results show that: 1) Although private enterprises and universities are playing an increasingly important role in the technology transfer network in China, most of the connections are established between universities, research institutions, and their derivative enterprises, indicating that the overall connectivity is low and the network spillover effect is weak. 2) According to the patent transfer data of sub-categories, the knowledge required for innovation ability is often generated in relatively few places, and its transfer is mainly concentrated in cities, suggesting that there are some regional barriers to technology transfer between cities in China. 3) In addition, the vast majority of cities are more likely to carry out patent transfer in the same administrative area or between cities with geographical proximity or similar knowledge scale when establishing innovative ties—geographical proximity, technological proximity, and social proximity play a positive role in promoting the development of China's technology transfer network that comprises of enterprises, universities, and research institutions.

产业分工联系是区域一体化的基础,但已有产业技术关联的文献主要关注区域内部,缺乏对跨区域产业技术关联的探究。由于中国省际产业联系数据难以获取,论文运用引力模型和交叉熵法,基于2002、2007、2012年30省的投入产出表拟合出省际产业贸易流量矩阵,并进一步计算跨区域产业技术关联指数。跨区域产业技术关联呈现不断加强的趋势,尤其是城市群内部各地区产业之间的联系。基于2002、2007、2012年中国30个省16个制造业部门的面板数据,使用固定效应模型进一步考察了跨区域产业技术关联对产业创新的影响。结果发现,跨区域产业技术关联有利于区域产业创新,但在本地产业技术联系较强的地区,跨区域产业技术关联对产业创新的正效应会被削弱,本地产业技术关联和省际产业技术关联之间存在“替代效应”,知识产权的地方保护主义是导致这一结果的可能原因。因此,政策上应倡导扫清制度障碍、完善知识产权保护制度,促进跨区域产业对本地的技术溢出,进一步推动区域产业创新。

Geographic proximity arising from industrial agglomeration can promote firm innovation and thereby industrial development. Scholars of evolutionary economic geography further propose that technology proximity is more important than geographic proximity, which provides essential theoretical support for explaining the role of interregional industrial linkages in local industrial development. However, the existing literature mainly focuses on the technological relatedness within regions but lacks research for interregional relatedness, especially the effects of interregional technology relatedness on regional innovation. Based on the input-output panel data of 2002, 2007, and 2012 from 30 provinces of the mainland of China, this study used the gravity model and cross-entropy method to fit the interprovincial trade flow matrix of the industries and further computed the index of intraregional and interregional technological relatedness. This study then used a two-way fixed effect model to examine the effects of intraregional and interregional technological relatedness on industrial innovation based on the data of 16 manufacturing sectors in 30 provinces in 2002, 2007, and 2012. First, the results show that the degree of interregional technological relatedness of industries has been strengthened, especially the linkages within city agglomerations. Second, interregional technological relatedness of industries has a positive effect on industrial innovation, but local technological relatedness of industries would weaken this positive effect. Therefore, the government should remove institutional barriers and encourage the inter- or intraregional industrial linkages that promote regional industrial innovation.

以浙江省为例,基于区位熵方法借助从业人员数据刻画文化创意产业空间格局,并运用主成分分析法与OLS模型,甄别驱动因素佐证文化创意产业区位模型。结果表明：① 市域尺度浙江文化创意产业区位规律不仅具有“资本空间”（杭州）集聚性,还具有“地方空间”（舟山、金华和台州）分异性;② 经济科教、政府支持、市场需求、环境、交通和地方性是重要区位因素,且不同重点行业、不同地理层级所受区位因素不尽相同;③ 浙江文化创意产业全行业区位特征主要是基础设施和管治双要素驱动型,8重点行业区位特征主要是“软因子”驱动型;④ 研究有助于提升城市文化创意产业政策着力点与规划调控协同性。

<p>Industrial location has been a heated debate in the field of economic geography and urban geography. The selection of industrial location theory includes classical location theory, behavior location theory, strategic location theory, organizational structure location theory and new economic geography location theory. The location theory of cultural & creative industry is one of the crucial topics in the field of new industries, representing a new branch of the location study in terms of the new economic geography. Existing research has been lacking of the classic empirical materials to analyse the spatial pattern and driving factors of cultural & creative industry. This paper chooses Zhejiang as a case study to demonstrate location factors of cultural & creative industry and its impact on cities. Firstly, based on the perspective of enterprises, this paper attempts to build cultural & creative industry location model including infrastructure, governance, market, and soft factor. Secondly, this paper uses the employment data of each city / district to describe the spatial pattern of cultural creative industries at city level from the perspective of whole industries and the key industries dimension by means of location entropy. Then, principal component analysis and OLS model were used to identify the contribution of driving factors to industrial location. The results can be concluded as follows:(1) From the perspective of spatial selection of cultural & creative industry, cultural & creative industry tends to choose primate city in Zhejiang, and some of the key industries choose their locations in big cities such as Hangzhou, as well as in some historical small and medium-sized cities such as Zhoushan, Jinhua and Taizhou. So, the spatial pattern of cultural & creative industry in Zhejiang has presented a pattern of "capital space" agglomeration and differentiation of "local space". (2) Economic, science and technology, government support, market demand, environment, transportation and local characteristics are important location factors of cultural & creative industry in this province. Different key industries and their geospatial scales show their impact on geographical location factors, which colloborates the rationality of the location model of creative industry. That is to say, the cultural & creative industry location model has heterogeneity. (3) The spatial location of the whole industries in Zhejiang is mainly driven by factors of infrastructure provision and government policy. The spatial location of the key industries is mainly driven by the "soft factor", such as social tolerance. Jinhua became the "highland" in the field of art creation and trade and media publishing industry, and the industrial pattern of cultural & creative industry in Zhoushan and Taizhou, can respectively be characterized by the tourism and leisure industry and art creation and trading industry. (4) This research aims to construct the theoretical framework of integrating economic geography and cultural geography from the perspective of the theory of new industry location. In addition, the cultural & creative industry is actively rooted in local city, and leading industries of eleven cities in Zhejiang are not the same, so the location model can provide policy implication for the government in terms of cultural & creative industries policy, and targeted policies support with consideration of features of the city and industry.</p>

城市老工业区创意集群成长机理是产业集群研究新近热点领域。以宁波市为例,基于扎根理论和结构方程模型,借助问卷调查和半结构式访谈数据,构建并验证城市老工业区创意空间孕育机制理论模型。研究发现：①宁波老工业区创意空间孕育机制包括地方空间、资本空间和关系空间3个主维度,以及经济区位、制度因素、社会关系网络、文化氛围和办公环境5个内核,最终形成“地方空间的感性认可→资本空间和关系空间的理性约束→地方空间、资本空间和关系空间协同→关系空间的反馈”闭合空间生产链;②研究所开发的城市老工业区创意空间孕育机制量表包含5个维度13个问项,结构良好,且具有很好稳定性和鉴别度,并利用结构方程模型和地方性量化指标在宁波3个案例中检验了理论模型的准确性;③国有资本控制的老厂房改造式创意园(创意1956产业园)和国有资本控制的高端写字楼群主导的创意园(和丰创意广场)的创意空间均发育良好,而纯民营资本控制的老厂房改造式创意园(启运86微电影产业园)的创意空间发育较差,有关差异的影响因素及其作用被模型甄别。

Based on the experiences across the world, industrial clusters are generally divided into two categories—successful industrial clusters that play an important role in the economic growth in North America and Western Europe, known as the high-road and innovation-based clusters; and the low-road and low-cost based-clusters. As a kind of innovative low-tech cluster, cultural creative cluster in the old urban industrial districts can be categorized as the first type and has an important role to play in urban spatial reconstruction and industrial upgrading. The growth mechanism of cultural creative clusters in old urban industrial areas is a newly heated research topic in the field of industrial cluster research. This research chose Ningbo as the case study city and examine and validate the cultivation mechanism of creative spaces in its old industrial districts based on the grounded theory and SEM (structural equation modeling), as well as questionnaire and semi-structured interview data. The results demonstrate that: (1) The cultivation mechanism of creative spaces in the old industrial districts of Ningbo is comprised of three main dimensions—local, capital, and relational spaces; and five cores factors—locational, institutional, social relation network, cultural milieu, and office milieu factors, and ultimately forming a cycle of "recognition of local space→rational constraints of capital space and relational space→local space, capital space, and relational spatial coordination→relational space feedback." (2) A questionnaire was designed and applied to explore the cultivation mechanism of creative spaces in the old industrial districts, and the scale consists of 13 items, which belong to five dimensions, and is well-formed with good reliability and validity. (3) The LOFT-style creative park owned and managed by state-owned capital (1956 Creative Industrial Park) and the office building groups-led creative park owned and managed by state-owned capital (Hefeng Creative Plaza) are all well developed. However, the LOFT-style creative park owned and managed by pure private capital (Qiyun86 Microfilm Industrial Park) is poorly developed. The disparity in the cultivation of creative spaces is inevitable, which can be attributed to the capital attributes of the creative fix of old industrial districts. In addition, office milieu and location have become the key factors in the cultivation of creative space, particularly in the Hefeng Creative Plaza, and the theoretical model is proved as applicable by SEM and the local quantitative index. The renovation and regeneration of the old industrial districts through creative fix is confronted with a divergent path of upgrading, recession, and disappearance. The strength and persistence of the interactive relationship between local space, capital space, and relationship space have become the decisive factors in the direction of its evolution.

知识在产业集聚、区域创新中的地位越来越突出,城市知识储量及其在区域知识网络中的地位对城市的综合竞争力有重要影响。学术论文合作与专利合作是知识溢出的体现形式,是科学和技术发展的重要成果,也是度量区域创新能力的主要指标。以2000-2009年中国生物技术领域合著论文和共同申请专利的信息为原始数据,分别构建中国城市间科学知识网络(scientific knowledge network,SKN)与技术知识网络(technological knowledge network,TKN)。运用复杂网络与地学空间分析方法,从整体网络结构特征、择优链接性、中心城市及其自我网络的空间特征等方面进行分析,探究知识溢出的时空复杂性。研究表明：①SKN和TKN具有无标度网络特征;SKN节点度数的异质性高于TKN。②两种网络均呈异配性,即城市选择合作对象存在明显择优链接性,知识溢出具有粘着性和空间依赖性。③SKN中心城市具有明显的等级结构,空间分布总体呈&#x0201c;大分散小集聚&#x0201d;特点;TKN中心城市层级结构不明显,尚未形成明显极化中心。④SKN中心城市自我网络的合作空间,由最初的沿海省会城市间的合作转向长三角、珠三角、京津冀等区域间和沿海城市与内陆城市间的合作,区域间知识溢出明显;TKN中心城市自我网络仍多分布于沿海城市和少数中西部省会城市,区域间知识溢出不明显。⑤SKN中心城市及其自我网络的时空演变存在等级扩散和传染扩散的现象,符合时空梯度推移规律,且空间等级梯度逐渐向扁平化转变;TKN中心城市及其自我网络的时空演变以等级扩散为主,时空梯度推移现象不明显。研究结论为量化知识溢出及知识溢出网络结构的时空演化过程提供新的研究视角,对城市创新政策的制定有一定借鉴意义。

With the rise of the knowledge-based economy in the 1980s, knowledge (including code and tacit knowledge) as the backbone of innovation has become a key factor affecting production process. Cities have gathered not only a large number of professionals, universities and research institutions, but also a great many producers and consumers, which provides the premise for the innovation actions. City's knowledge storage and its position in the regional knowledge network play an important role in comprehensive competitiveness. Published papers and patents are main outcomes of innovation, which are used to evaluate the urban innovation capability. Moreover, co-publications and co-patents are not only the form of knowledge spillover, but also the key indicators to measure regional innovation. Taking the co-publication and co-patent in the field of biotechnology in China during 2000-2009 as the original data, we built scientific knowledge network (SKN) and technological knowledge network (TKN) between cities. From the perspective of complex networks and geospatial analysis, we explored the temporal and spatial complexity of knowledge spillovers combining the indicators of whole network structure, ego network, power-law, hubs and so on. The results show that: firstly, the nodes degree distribution of SKN and TKN is consistent with the power-law distribution, which means that the both networks not only have a scale-free network structure, but also present a preferential attachment rule when the cities choose the cooperation partner. Secondly, central cities have an obvious hierarchical structure, and are featured by a "big scattered and small gathering" spatial pattern in SKN, while the TKN is not showing this feature. From the view of central city ego network, the cooperation develops between the coastal capital cities at first, and then turns to inter-regional cooperation, such as Yangtze River Delta, Pearl River Delta, and inter-regional knowledge spillovers is obvious in SKN. The central cities and its partners are still in the coastal city instead of western provincial capitals, and inter-regional knowledge spillovers are not significant in TKN. Thirdly, the temporal evolution of central cities and its ego-network presents hierarchical diffusion and contagious diffusion, and conforms to law of grades process in SKN. The TKN is dominated by hierarchical diffusion. Finally, this study draws conclusions on the temporal and spatial complexity of innovation network, which has a positive impact on quantifying spatial knowledge spillovers and measuring its space-time evolution. Besides, the results clarify the status of each city in innovation networks, which provides a new perspective for the cities to formulate innovative policies.

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。

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.

以国家知识产权局专利检索及分析平台中历年专利转让记录为数据源，采用大数据挖掘技术、地理信息编码技术、空间自相关模型和多元线性回归模型，并从集聚和扩散两个方面构建城市创新技术转移能力评价指标体系及评估模型，对2001-2015年中国城市技术转移的时空格局、集聚模式及影响因素进行了研究。结果发现：① 2001-2015年，随着城市创新技术转移能力的不断上升，且在参与创新技术转移的城市数量不断增加情境下，中国城市创新技术转移能力的两极分化及强集聚特征持续发育;② 中国城市创新技术转移格局经历着空间不断极化的历程，由京津冀、长三角和珠三角主导的三极格局逐渐凸显;③ 中国城市创新技术集散体系不断完善，从全球至地方的中国创新技术集散体系已初步形成;④ 中国城市创新技术转移呈现出显著的空间关联与集聚效应，4种类型基本呈“抱团”分布，城市创新技术转移的地理邻近性显著;⑤ 多元线性回归模型发现，城市创新技术的需求能力和供给能力决定其转移能力，第三产业产值规模和专利申请量对城市创新技术转移能力影响较大。另外，研发人员数量也是影响城市技术转移能力的重要因素，但是相关性较低，而城市第一产值规模对城市创新技术转移能力具有显著的阻抗作用。（注：①考虑到专利技术从申请至授权以及转移的期限较长，因此本文城市吸收、转出的专利速度主要基于1年转移量、2年转移量和5年转移量来综合评定。）

<p>Based on the records of patent transfer from the patent retrieval and analysis platform in the State Intellectual Property Office of China, this research built an assessment index and model for technology transfer in China's city system in terms of agglomeration and dispersion, using big data mining technology, geo-coding technology, spatial autocorrelation model and multiple linear regression model. Then we studied the spatial-temporal pattern, agglomeration model and influencing factors of technology transfer in China's city system from 2001 to 2015, and obtained the following results. Firstly, with the increasing capability of city's technology transfer and the growing number of cities involved in transferring technology, the polarization and strong agglomeration of technology transfer in China's city system have been intensified. Secondly, technology transfer in China's city system has experienced a process of constant spatial polarization, the three-pole pattern led by the Beijing-Tianjin-Hebei region, the Yangtze River Delta region and the Pearl River Delta region has been gradually prominent. Thirdly, technology transfer system from global to local scale in China's city system has initially taken shape. Beijing, Shanghai and Shenzhen have become the three global centers of China in technology transfer. Fourthly, technology transfer in China's city system has produced an obvious spatial correlation and agglomeration effect. The four types are mainly in the cluster, and the geographical proximity of technology transfer in China's city system is significant. Last but not least, the influencing factors of technology transfer in China's city system were also verified by multiple linear regression model. We found that the demand and supply capacity respectively represented by the scale of tertiary industry and the number of patent applications has a great influence on the growth of technology transfer capability. In addition, the number of R & D employees is an important factor, but its correlation is low. The findings further confirm that the scale of primary industry has a significant impedance effect on city's technology transfer capability.</p>

知识经济时代城市间的创新关系是新时代城市间相互作用关系的新内涵,研究者尝试采用各种方法探索城市间创新关系及其网络特征。然而,如何从理论上建构知识流动空间的城市间创新关系?如何设计更加合理的城市间创新网络模拟方法?这些问题却少有专门探讨。基于相关研究,本文提出了城市间创新关系构建的理论框架,认为城市间创新网络本质上是区别于“硬网络”的“软网络”,是一种主观的关系建构过程,需要经过异城创新主体间的点—点关系向城—城之间关系的尺度转换,这一转换过程容易发生夸大或偏离城市间客观存在的创新关系,对结果的精确度产生很大影响,应对关系建构给予充分理论论证;本文论述了4种城市间创新关系建构和网络模拟方法,包括科技成果异城合作的城市间无向网络构建方法、科技成果转让转移的城市间有向网络构建方法、高端人才跨城移动的城市间创新网络建构方法和创新企业机构多城分布的城市间创新网络建构方法,并运用相关数据进行了模拟试验与结果展示,来反映城市间创新关系的不同方面。本研究有助于推动从城市地理学视角和城市关系的维度探讨全球/区域的创新空间格局,为城市间创新网络研究提供理论和方法支撑。

The interactive relationships between cities in the knowledge economy era have attracted much attention. Researchers have applied a range of methods to explore intercity innovative relationships and associated network characteristics. It nevertheless remains unclear just how intercity innovative relationships can be theoretically constructed based on knowledge flow space and how further scientific simulation methods can be designed. Research questions in this area have rarely been explored in detail, an issue which has inevitably placed obstacles on further exploration. A framework for the theoretical construction of intercity innovative relationships is presented in this study; the basis for this research is that an intercity innovation network is essentially a 'soft network', distinct from a 'hard network'. These interconnections are founded on a subjective relationship construction process and therefore necessitate scale transformation from 'point-point' connections between innovative subjects in different cities with respect to 'city-city' interactions. At the same time, this transformation process is prone to exaggerations and deviations from objective intercity innovative relationships and therefore exerts considerable influence on the accuracy of results such that constructions must be entirely theoretical. Four construction methods for intercity innovative relationships and network simulation are summarized in this study, including an intercity undirected network based on cross-city co-operations between scientific and technological achievements, an intercity directed network based on the cross-city transfer of scientific and technological achievements, an intercity innovation network based on the cross-city flow of high-end talents, and an intercity innovation network based on the multi-city distribution of innovative enterprises and institutions. Simulation tests were then undertaken using relevant data to reflect aspects of these relationships. The results of this analysis are conducive to further exploration of global and regional innovative spatial patterns from the perspective of urban geography and intercity relationships and provide a theoretical and methodological foundation for further research on intercity innovation networks.

进口能为区域带来新知识,而这些知识在本地的溢出具有多尺度的特征。论文认为,进口知识首先能够在企业内部溢出,继而跨越企业边界在区域内部溢出。企业通过在企业内部和区域内部对进口知识进行搜寻,能够促进自身的出口产品演化。基于此,论文建立知识溢出的多尺度研究框架,并利用2002—2016年中国海关进出口贸易库数据,证实了上述现象的存在。同时,研究发现,一方面,对于出口产品演化来说,企业内部和区域内部知识溢出的效用是相互替代的;另一方面,知识溢出效应呈现距离衰减的特征。分样本回归结果表明,在市场化水平较高的地区,区域内部的知识溢出对促进企业出口产品演化更有效,企业为实现产品出口更倾向于“求人”;而在市场化水平较低的地区,企业出口产品演化则更依赖于企业内部的知识溢出,倾向于“求己”。论文一定程度上丰富了学界关于不同地理尺度下的知识溢出及其相互关系的讨论,同时完善了学界对于企业出口产品演化机制的认识,具有一定的理论和实际意义。

Imports can bring new knowledge to a region, and the spillovers of this kind of knowledge show multi-scalar characteristics. This article held the view that imported knowledge can first show a spillover effect within the firms, and then cross firms' borders to have a spillover effect within the regions through inter-firm linkages. Firms can achieve the evolution of export products by searching for imported knowledge within firms as well as within the regions. Based on this theory, this article established a multi-scalar research framework of knowledge spillovers, and used the data of China Customs Trade Statistics from 2002 to 2016 to confirm the existence of the above phenomenon. The results show that on the one hand, for the evolution of export products, the effects of intra-firm and intra-region spillovers are mutually substituted. On the other hand, the knowledge spillovers show the characteristics of distance attenuation. The results of sub-sample regression show that in regions with higher marketization levels, intra-region knowledge spillovers are more effective for the evolution of firms' export products, and firms prefer to "learning from others" in order to achieve the goal of exporting more products, while in regions with lower marketization levels, firms rely more on intra-firm spillovers, which can be called "learning from yourself". To some extent, this article enriches the discussion of knowledge spillovers at different scales and their interrelationships, and improves the cognition of the mechanisms of firms' export products evolution, which is of certain academic and practical contributions.

创新地理学是研究人类创新活动与地理环境关系的地域系统,是一门独立的人文地理分支学科,具有交叉学科的性质。其研究的“人类创新活动”是人类活动的最为重要的方面,对智慧的人地关系系统建设具有重要的意义。创新地理学与其他人文地理学的分支学科具有密切的联系,也与政治学、管理学、经济学、政策学、城市规划等学科有关,创新地理学面临的主要任务是：① 创新地理学基本理论的研究;② 创新要素（人才、资本、技术等）在空间的地域分布与组合规律的研究;③ 创新环境、创新生态及评价研究;④ 创新地理测度、创新空间格局与效应的研究;⑤ 创新联系、创新网络及创新集群的研究;⑥ 多尺度的创新体系的研究;⑦ 创新、城市发展与规划的研究。

In the 1920s, Schumpeter proposed the theory of Innovation, but this theory did not arouse the attention by mainstream economists until 1950s-1960s. Though the space research of innovation had also aroused the concern of the geographers during that period, it failed to be the main areas of geography study. Since the 1980s, with "spatial turn" of human geography and emerging of knowledge economy, innovation geography has emerged as an important research area of geography, however, the research on the basic theory of innovation geography is still very limited, and that whether innovation geography as an independent subject is still under debating, therefore, those important issues concerned the discipline of innovation geography, such as the research object, discipline nature and tasks need to be examined further. This article argues that: Innovation Geography is an independent subject studying relationship between human’s innovation activities and geographical environment. The innovation activities of human beings as the most important aspect of human activities have great significances to establishing the intelligent human-earth relationship system. As a branch subject of human geography, innovation geography has cross-discipline nature, because it has close relationship with the branch subject of human geography and other subjects such as political science, management science, economics, policy science, urban planning and so on. We conclude the main tasks of innovation geography as follows: 1) The basic theory of innovation geography; 2) the regional distribution and combination of innovation elements such as talents, capital, technology, etc.; 3) the examination and evaluation of Innovation Milieu and innovation ecology and evaluation; 4) the survey of innovation geography and the study of the space pattern and regional effect of innovation; 5) the study of innovation links, innovation networks and innovation cluster; 6) the study of multi-scale innovation system; 7) the relationship of innovation, urban development and planning.

Trust is a key mechanism for explaining the ease and frequency of knowledge spillovers within regions. While the importance of trust is virtually uncontested, there have been few attempts to rigorously disentangle the way in which trust formation is related to space and proximity. The aim of this paper is to advance the understanding of trust formation in terms of its main antecedents within the context of regional studies. This is done by reviewing the rich literature on trust formation from psychology, sociology, and organization studies and connecting it conceptually to different types of proximity. In doing so, the paper maps out a number of avenues for future research on trust and geography.

本文以中国31个区域为样本，基于区域间合作申请发明专利数据，以核心政策节点分三个时段考察了1985-2015年中国跨区域研发合作模式的演变，研究发现中国跨区域研发合作模式演变具有明显的阶段性特征，并与中国科技体制改革的演进息息相关。本文进一步从邻近性视角分时段考察了影响中国跨区域研发合作模式的主要因素，结果表明：地理邻近的作用效果存在模式差异与阶段差异，且整体作用效果在减弱；技术邻近的作用效果具有阶段差异，其中跨区域企业与学研合作的最优技术邻近水平最高；基于既有合作关系紧密度表征的关系邻近作用效果均正向显著，其对跨区域企业与学研合作影响程度最高，而基于之前曾有过合作表征的关系邻近作用效果存在模式差异与阶段差异；制度邻近的作用效果均正向显著，且对跨区域企业间合作影响程度最高。

经济地理学者对于新兴产业的产生区位长期存在争论,在中美贸易战背景下,探究其区位规律既是重要的学科问题,又对国家培育新兴产业具有重要指导意义。通过梳理“区域产业分叉”和“区位机会窗口”的观点,辨析出知识流动是影响新兴产业区位的关键点;以燃料电池产业为例,结合“相关多样化”假说的观点,采用面板空间自回归模型对知识基础的具体影响进行测度,结论如下：① 北京、上海、大连是燃料电池技术创新的三大知识流动中心,各地区“增长极”城市间的强联系是当前知识流动的空间格局的基础,而地理邻近的作用并不显著;② 相关技术知识基础对知识吸收能力具有稳定且显著的积极作用,且除用工成本外的多数控制变量显著为正;而非相关技术知识基础在早期呈现显著负相关。正是由于早期不同知识基础与控制变量的不同作用,导致了既集中于发达城市、又具有一定自由度的空间格局。研究结果表明知识经济时代下,知识基础对创新的锚定效应明显,区域产业分叉出现的概率加大,区位机会窗口较难打开。③ 非相关多样化的作用会随着新兴产业技术的持续发展而产生变化,由早期的消极影响逐渐转变为积极影响,应从演化视角重新审视非相关多样化的作用。

Economic geographers have long argued about the location of emerging industry. Under the background of Sino-US trade war, exploring the location laws of emerging industries is not only a critical theoretical issue, but also has an important guiding significance for the country to cultivate emerging industry. Starting from the debate between "Regional Branching" and "Windows of Locational Opportunity", this paper identifies that knowledge flow is the key to affecting the location of emerging industry. According to the discussion of the relationship between variety and technological innovation in the related variety hypothesis, we use patent citation data to define related and unrelated variety. Then we use panel spatial autoregressive model to measure the specific impact of each factor in this paper. Finally, we can draw the following conclusions: (1) Beijing, Shanghai and Dalian are the three major knowledge flow centers of China's fuel cell industry. The strong connection between these "growth pole" cities is the basis of the current spatial pattern of knowledge flow, while the role of geographical proximity is not significant. (2) The related technology knowledge base has a stable and significant positive effect on knowledge absorption capacity, and most of the control variables are significantly positive except labor cost. The unrelated technology knowledge base has a significant negative impact in the early stage (the regression coefficient in the first stage was -0.038). Because of the different roles of different knowledge bases and control variables in the early stage (more positive effects and less negative effects), the overall spatial pattern is not only concentrated in the developed cities, but also has some freedom. The research results show that the anchoring effect of knowledge base on innovation is obvious, so "Regional Branching" is more likely to appear in the era of knowledge economy. (3) The impact of unrelated variety has gradually changed from negative in the early stage (-0.038) to positive in the final stage (0.079), which shows that the role of unrelated variety may change with the technological development of emerging industry. We should re-examine the role of unrelated variety from an evolutionary perspective.

产业地理学研究产业空间分布及其动态演化规律。基于地理邻近性的集聚理论揭示了产业地理不平衡分布的内在机制。演化经济地理学借鉴演化经济学的历史视角,从历史角度考察经济活动空间分布的渐进演化机制,认为地理邻近性不是产业地理格局演化的充分必要条件,以认知邻近性为核心的多维邻近性能够提供更好的解释。本文从认知邻近视角系统地分析了中国区域产业发展与布局动态演化规律,总结出中国产业发展与布局的“关联法则”,即一个企业或区域进入（或退出）某项经济活动的概率是该企业或地区拥有的基于相关知识基础的经济活动的函数。本文全面地回顾了关联法则涉及的关键概念,梳理企业和区域尺度的实证研究成果,讨论关联法则在中国的适用性及其补充和拓展。本文指出：① 在认知邻近视角下,基于资源转换和组织学习等理论基础,关联法则研究了企业或区域发展新产业与现有产业之间的关系。② 关联法则不仅适用于中国企业和区域尺度,还会影响区域经济发展、创新和韧性等。③ 外部联系、冲击以及内部制度环境等可能会降低区域产业动态对本地产业基础的依赖性。关联法则指出中国区域需培育内生发展模式,围绕现有区域能力、技术和知识积累发展区域产业和实现区际产业优化布局与分工,逐步建立相关多样化的产业体系,增强区域韧性,支撑国内经济循环。

Geographical distribution and agglomeration of industries have been a long lasting concern of economic geographers. Some studies have stressed geographical proximity and industrial agglomeration as the key driving force of uneven distribution of industries. Recently, evolutionary economic geography, based on evolutionary economics, has adopted a dynamic and historic perspective to study the evolution of regional industrial dynamics. It argues that geographical proximity is neither sufficient nor necessary for efficient knowledge spillovers; instead, it calls for more attention to the idea of cognitive proximity as well as its importance in regional industrial dynamics. The idea is that for knowledge spillovers to take place effectively, some kind of cognitive proximity in terms of shared competencies must be in place. Inspired by this, we examine China's regional industrial development through the lens of cognitive proximity, and propose the "principle of relatedness", that is, the probability of a region to enter/exit one specific economic activity is heavily dependent on regional pre-existing economic profile and local knowledge base. This paper first introduces some key, relevant concepts, and then reviews empirical studies that are underpinned by the "principle of relatedness". Furthermore, it discusses the applicability of "principle of relatedness" in the Chinese context. Our main findings are as follows: (1) theories on resource base view and knowledge spillovers both support the existence of the "principle of relatedness"; (2) the "principle of relatedness" enables us to better understand China's regional economic development, innovation and resilience; however, (3) the effectiveness of the "principle of relatedness" may be compromised by external shocks and internal institutions. One policy implication from the "principle of relatedness" as well as our empirical research is that Chinese regions should seek to diversify related industries and enhance related variety of their regional profiles. In doing so, they are able to become more economically resilient and achieve more sustainable economic development.

The role of exogenous sources of new path development has been underplayed in the literature on regional industrial change so far. The aim of this article is to explore in a conceptual way under which conditions and in what ways non-local knowledge can lead to new path development in different regional innovation systems (RISs). We distinguish between organizationally thick and diversified RISs, thick and specialized RISs and thin RISs and argue that these types vary substantially in their needs for exogenous sources as well as in their capacities to attract and absorb knowledge generated elsewhere.

In the era of the knowledge economy with the superfluidity of information, labor, and goods, the ability to establish external knowledge linkages has become an indispensable asset for the development of regional industries. Based on the assumption that knowledge spillovers decay with distance, several existing studies have explored the role of neighboring regions in local industrial upgrading. Meanwhile, a small but growing literature has explored the evolution of regional comparative advantage from the perspective of multi-location territorial knowledge dynamics (TKDs), exploring multi-locational knowledge interactions (including proximity interactions and distance interactions) and their regional economic effects in the process of knowledge flows. Inspired by the literature on multi-location TKDs, this paper examines two hypotheses: (1) In addition to local capabilities, external knowledge linkages also have a positive effect on local industrial upgrading; (2) the stronger the knowledge linkages, the more similar the regional comparative advantage. Through an analysis of data on authorized patent citation and the two-digit manufacturing industry from Chinese cities in 2011 and 2016, we find that the knowledge flow networks among Chinese cities are characterized by strong external knowledge linkages to both adjacent and distant regions. Further analysis reveals that a particular Chinese city has a higher probability of developing comparative advantages if it maintains strong knowledge linkages with a city specialized in the same industry. In addition, the comparative advantages of regions with strong knowledge linkages are more similar than regions with weak knowledge linkages.

城市网络研究已成为国际上城市研究的前沿学术领域并渐成热点,外部性作为城市网络的本质属性,对城市网络的演化及城市与区域的发展均具有重要意义。论文从集聚外部性与网络外部性比较的视角切入,重点对城市网络外部性形成机理、效用和测度方法等方面的研究进展进行梳理和评述。其中,协同效应、整合效应和规模借用被认为是城市网络外部性形成的重要原因。而城市网络外部性的效用研究较多集中在2个方面：一是关注要素流动对知识扩散和创新的促进作用,二是关注城市网络对竞争力提升和经济增长的影响。从已有文献来看,城市网络外部性测度研究主要涉及识别和估算2种类型,包括3种常用方法：关联分析、回归分析和空间计量分析。未来需要进一步关注的问题包括城市网络的外部性理论认识、外部性量度方法以及经验研究问题。

Urban network research has become the frontier academic field of international urban research and has gradually become a hot spot. At present, the related literature on "urban network" mostly focuses on conceptual discussion, dimension analysis, and network structure analysis. Research on the influence of network on regional economic development is relatively weak. Externality, as an essential attribute of urban network, is of great significance to the evolution of urban network and the development of cities and regions. This article starts from a comparison of agglomeration externalities with urban network externalities, focusing on the review and evaluation of the formation mechanism, utility, and measurement methods of urban network externalities. The synergy effect, integration effect, and borrowing size are considered important reasons for the formation of urban network externalities. The research on the effectiveness of urban network externalities focuses on two aspects. The first is the role of factor flow in promoting knowledge diffusion and innovation, and the second is the impact of urban network on competitiveness and economic growth. Based on the existing literature, the research on the measurement of urban network externalities mainly involves identification and estimation, including three common methods: correlation analysis, regression analysis, and spatial econometric analysis. The existing empirical research on externalities is still mostly based on static analysis and lacks dynamic consideration. To a large extent, the existing research has insufficient theoretical framing and insufficient explanatory power, often resulting in the discovery of conditional associations, but not causal relationships. The Western research on urban network externalities is relatively early and mainly focuses on the global and regional dimensions, while Chinese scholars focus on the national and regional dimensions. In terms of empirical methods and objects, Chinese scholars have also made some innovations based on the study of world city network. The issues that need further attention in the future include theoretical understanding of urban network externalities, externality measurement methods, and empirical research.

‘Borrowed size’ is an emerging policy concept in several European countries, presenting theoretical potential to explain contemporary urban dynamics unaddressed through conventional urban growth theories that emphasise the role of agglomeration economies. In its original conceptualisation by Alonso, the concept describes and explains the situation that especially smaller cities that are located in a larger ‘megapolitan complex’ do perform better because they have access to agglomeration benefits of larger neighbouring cities. This paper scrutinises the concept of borrowed size, thereby focusing on its conceptualisation and reviewing its empirical justification thus far. Our empirical analyses show that the concept must be stretched in terms of scale and scope to enhance its policy value. Borrowed size occurs when a city possesses urban functions and/or performance levels normally associated with larger cities. This is enabled through interactions in networks of cities across multiple spatial scales. These networks serve as a substitute for the benefits of agglomeration. Theoretically, the borrowed size concept demands a recasting of the geographical foundations of agglomeration theory.