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地理学报, 2022, 77(2): 331-352 doi: 10.11821/dlxb202202005

百年变局与世界地理

中国跨国城际技术通道的空间演化及其影响因素

刘承良,1,2,3, 闫姗姗3

1.华东师范大学全球创新与发展研究院,上海 200062

2.华东师范大学世界地理与地缘战略研究中心,上海 200062

3.华东师范大学城市与区域科学学院,上海 200241

Spatial evolution and determinants of transnational technology transfer network in China

LIU Chengliang,1,2,3, YAN Shanshan3

1. Institute for Global Innovation and Development, East China Normal University, Shanghai 200062, China

2. Center for World Geography and Geostrategic Studies, East China Normal University, Shanghai 200062, China

3. School of Urban and Regional Science, East China Normal University, Shanghai 200241, China

收稿日期: 2020-07-21   修回日期: 2021-05-5  

基金资助: 国家社会科学基金重大项目(21ZDA011)

Received: 2020-07-21   Revised: 2021-05-5  

Fund supported: Major Program of National Social Science Foundation of China(21ZDA011)

作者简介 About authors

刘承良(1979-), 男, 湖北人, 教授, 博导, 研究方向主要为科技地理与区域创新。E-mail: clliu@re.ecnu.edu.cn

摘要

专利转移是国家和地区获取外部技术的重要通道,也是刻画技术流供求关系最直接的方式。基于全球—地方视角,本文建构了技术转移的跨国—国内城际双通道理论框架,融合社会网络、GIS空间分析和空间计量模型,尝试刻画中国城市跨国城际技术通道的空间演化规律及其影响因素。研究发现：① 中国跨国城际技术通道网络的空间异质性显著但随时间逐渐减弱。② 跨国城际技术通道加速东移,从北美和西欧（以美国纽约湾区和硅谷地区技术创新中心、加勒比海离岸金融中心、伦敦全球金融中心等为核心）快速向东亚（以日本东京、韩国首尔科技创新中心为核心）和东南亚（以新加坡科技创新中心为核心）扩展,中国对美国和西欧的专利技术依赖性明显减弱。③ 以北京、上海、深圳—中国香港、台北—新竹为核心的京津冀、长三角、粤港澳大湾区和中国台湾北部四大创新集群成为中国跨国城际技术流的集散地和全球性技术创新枢纽。中国香港凭借跨国公司及分支机构云集及离岸金融低税收优势,技术中介作用不断增强并成为技术转移的首位城市,而中国台湾的核心作用不断减弱。④ 国内通道的规模、强度以及城际紧密度有利于跨国城际技术引进通道的扩展;此外,地方经济实力对跨国联系通道具有正向促进作用,其技术实力和对外经济联系程度则具有多方面的影响。

关键词： 专利权交易; 技术转移双通道; 城际技术通道网络; 空间演化; 影响因素; 中国

Abstract

Patent transfer is an important channel for countries and regions to obtain technology from abroad, and it is also the most direct way to portray the relationship between supply and demand of technology flow. Based on the glocalisation perspective, this paper constructs a framework of technology transfer characterized by the transnational-domestic dual-channel theory. Combining social networks, GIS spatial analysis and spatial measurement models, it attempts to describe the spatial evolution and determining factors of transnational technological channels in Chinese cities. The research found that: (1) The spatial heterogeneity of China's transnational technology channel network is significant but gradually has weakened over time. (2) The transnational technology channel accelerates eastward movement, expanding from the technologically developed regions of North America and Western Europe (the New York Bay Area and Silicon Valley, the Caribbean offshore financial center, the London offshore financial center, etc.) to East Asia and Southeast Asia (Japan, South Korea and Singapore), China's technological dependence on the United States and Western Europe has been greatly reduced. (3) The Beijing-Tianjin-Hebei urban agglomeration, the Yangtze River Delta urban agglomeration, the Guangdong-Hong Kong-Macao Greater Bay Area and the northern Taiwan urban agglomeration with Beijing, Shanghai, Shenzhen-Guangzhou, Taipei-Hsinchu as the cores have become global technological innovation centres and hubs for transnational technology transfer flows. With the help of connections between headquarters and branch of multinational companies, offshore financial convenience and low tax advantages, Hong Kong mainly plays the role of technology intermediary and has become the city with the most technology transfer, while the core role of Taiwan Province is declining. (4) Intercity technology pipelines have a positive effect on transnational technology transfer pipelines. Enlarging the scale and flow of technology pipelines between cities and the distance between cities is conducive to expanding transnational technology introduction pipelines, while the intermediary of cities has no significant impact. In addition, the economic strength of a city has a positive influence on the promotion of transnational technology transfer pipelines, while technological strength and foreign economic relations have multiple effects.

Keywords： patent rights transaction; technology transfer dual pipelines; technology channel network; spatial evolution; determinant factor; China

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本文引用格式

刘承良, 闫姗姗. 中国跨国城际技术通道的空间演化及其影响因素. 地理学报, 2022, 77(2): 331-352 doi:10.11821/dlxb202202005

LIU Chengliang, YAN Shanshan. Spatial evolution and determinants of transnational technology transfer network in China. Acta Geographica Sinica, 2022, 77(2): 331-352 doi:10.11821/dlxb202202005

1 引言

科学和技术是经济增长的源头[1,2],是一个国家、地区或企业应对外部制约并实现长期发展的基础[3,4]。当前,经济全球化和新一轮科技革命加速推进产业与技术深度融合,知识全球化和技术跨国转移不断发展,交织形成错综复杂的全球创新网络。

全球创新网络是一种跨组织边界、跨区域边界对研发活动、产品开发、工程应用进行整合与分散的网络形态[5],是地方获取外部知识和技术的重要通道[6],已成为经济地理学研究的焦点和前沿,呈现研究内容从跨国公司的全球研发网络、特定产业的全球技术创新网络到以知识合作为媒介的全球知识创新网络[7,8],研究视域从全球化到地方化再到全球—地方化的发展脉络[5, 9-10]。其中,技术转移成为国家或区域之间实现技术追赶和技术控制的关键手段[11],是透视全球创新网络复杂性的重要指标,引起广泛关注。研究内容主要论及技术转移的主体及相互关系[12,13,14,15]、策略和渠道[16,17]、效率和溢出效应[18,19]、空间演化和影响因素[20,21]等方面。研究尺度以国家[22,23]、城市群[24]、城市[25,26]等单一尺度为主,存在较大的片面性[10],忽视了全球—地方不同尺度创新网络间的相互作用机制[27]。

为此,全球—地方视角的研究渐渐引起重视[6]。从20世纪90年代,地理学者就开始从全球—地方视角探讨资本要素的联系[27]。Bathelt等提出了全球通道—本地蜂鸣理论,为解释知识和技术要素的全球—地方互动过程提供了一个经典框架[28],进而衍生出全球—地方创新网络的理论构想[27]。大量研究表明,通过全球—地方创新网络,跨国公司不仅可以协调、整合内部的技术知识,在本地网络中受益;还可以通过不同尺度的非本地通道汲取外部环境的信息和技术,从而实现全球—地方跨区域的知识技术互动[10, 30-31]。中国2001年加入世界贸易组织（World Trade Organization, WTO）以来,受益于这种全球—地方跨区域的技术联系,不断融入全球创新网络,与美国等发达科技创新中心的差距不断缩小,部分指标出现反超[32],已经发展成为全球重要的创新经济体和科技创新中心。遗憾的是,现有全球—地方视角的研究在尺度上相对固定[30,31],不免遗漏其所包含的国际、国内、区域、地方之间的复杂技术联系[33,34],不同尺度全球通道之间以及全球通道和地方根植性之间的作用机制仍然是一个“灰箱”,以中国为视角的全球技术通道网络演化研究仍显薄弱,亟待深入研究。

鉴于此,本文构建全球—地方视角下的技术转移双通道理论框架,运用复杂网络方法,力图刻画中国跨国城际技术通道网络的空间演化规律,揭示城际技术通道对跨国技术通道的影响机制,以丰富和完善全球地方创新网络理论体系,为中国主动融入全球创新网络、建设世界创新高地提供决策支撑。

2 理论框架、研究假设与研究方法

2.1 技术转移双通道理论框架

当前科技全球化空前活跃,局域内部缄默知识与外部新异知识获取是促进区域技术流动和经济协调发展的重要途径。只有从全球—地方的多尺度与不同尺度之间相互联结和作用的视角,刻画本地行动者与非本地行动者交互、本地要素与非本地要素的重组作用,才能正确认识区域技术转移和知识创新的空间路径。全球—地方理论的“全球”和“地方”并不代表固定的尺度,而是一连串复杂相互作用的两个终端[35],是全局与局部之间的关系总和[36,37]。全球—地方通过相互联系实现垂直尺度扁平化（或立体网络化）[38],重点关注经济活动多尺度、跨尺度下的综合作用。

全球—地方视角下,城市作为技术转移集结点在全球创新网络的重要性日益凸显。依托跨国公司及中介机构主导的技术研发和市场开拓,大学和科研机构主导的知识生产,以及政府主导的地方创新系统,具有不同创新要素禀赋的城市不断嵌入全球创新网络,成为全球技术流枢纽的关键空间载体。

全球—地方视角下,技术通道被普遍理解为：技术由国际技术协会和地方技术联盟主导,在国家、地区、公司、个体内部或之间,借助市场交易、外商直接投资、“新阿尔戈英雄（New Argonaut）”等正式和非正式合作网络联系,所形成的显性知识（产品、设备、专利、技术标准、技术许可等）、缄默知识（市场信息、创新能力等）的转让、移植、吸收、交流的稳定渠道[29, 39]。技术通道具有多尺度耦合效应[37],从城市尺度可以解析为跨国城际技术通道和国内城际技术通道。其中,跨国城际技术通道是指技术来源地与技术转移目的地在不同国家或地区城市之间,国内城际技术通道则指技术来源地与技术转移目的地在国家或地区内部城市之间。跨国与国内城际技术通道存在双向互动效应[39,40],在技术通道强度、通道规模、通道距离及控制能力等方面形成了竞争—互补的复杂机制。

全球—地方视角下,影响地方技术创新能力的多种社会经济环境（包括地方经济水平、地方技术实力和地方对外联系强度[41,42,43,44]等）,通过要素结构和网络关系嵌入到跨国—国内双技术通道网络中,对二者产生多重影响。一方面,地方通过先前存在的知识和思想的积累和重组[45],依托本地集群内部的交流和联系促进技术创新的产生,提升本地的技术创新能力和技术集散能力,进而促进跨国和国内技术转移通道的发育。另一方面,地方知识或技术的结合和重组也会导致知识的价值不断降低从而出现“锁定效应”[46],有待于集群外部技术联系实现“路径突破”[28, 47],链接技术通道业已成为地方技术创新路径创造与演化的重要动力[48]。

总之,地方技术创新环境通过地方根植性不断嵌入和影响对外技术通道网络,而跨国和国内城际技术通道则通过技术传导效应提升地方技术创新能力,三者之间呈现共生竞合、动态演化的开放、复杂、多重交互机制（图1）。① 地方经济发展水平提高,推动产业结构向知识、技术和人力资本型转变,激发新兴产业部门对外部技术的需求和加速传统产业技术向边缘地区输出[49];② 由大学、科研机构、企业、政府等创新主体构筑的地方技术实力增强,促进了技术转移通道中知识、信息、资源等的流动和传递[50];③ 国内城际技术通道增强,城市对外社会经济联系紧密,有利于不同城市多样化知识和技术的学习和整合,从而提升地方城市对国外先进技术的理解、学习和改进的技术实力,进而促进跨国城际技术交流合作[51]。

图1

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图1   全球—地方视角下的技术转移双通道理论框架

Fig. 1   The dual-pipeline theoretical framework of technology transfer from the glocalisation perspective


2.2 研究假设

大量研究表明,通道的规模（城市节点的度中心性）、通道强度（加权度中心性）、通道距离（接近度中心性）和控制能力（中介度中心性）对城市的创新绩效具有正向促进作用[52,53],占据网络中心位置的城市,越有能力对创新资源要素进行调度和支配,从而增强其技术创新能力,并进一步对跨国技术转移通道产生影响。同时,城市经济发展水平、技术创新实力和对外社会经济联系强度等地方技术创新环境也会对其技术转移产生影响[54]。因此,本文提出以下假设：

H1：国内城际技术通道的规模对跨国城际技术转移通道具有正向影响。

H2：国内城际技术通道的强度对跨国城际技术转移通道具有正向影响。

H3：国内城际技术通道的距离对跨国城际技术转移通道具有正向影响。

H4：国内城际技术通道的控制能力对跨国城际技术转移通道具有正向影响。

H5：国内城市的技术创新环境对其跨国城际技术转移通道具有正向影响。

2.3 研究方法与数据

2.3.1 数据来源及处理 专利交易是衡量技术转移的重要指标,可以直观地反映技术市场的供求关系[55,56]。本文采取专利权交易数据表征技术转移,以测度区域获取外部技术的主要通道和流向。从全球和地方视角,通过构建分布式爬虫程序提取获得2004—2018年间中国（包括港澳台地区）对外及国内各城市间（暂未包括港澳台地区）的专利权交易数据,包括专利申请号、专利分类号、专利转让人和地址、专利受让人和地址、专利转让时间、专利申请时间和专利授予时间等信息。数据来源于国家知识产权局（http://www.cnipa.com/）“专利信息服务平台”,网站由国家法定专利文献出版单位建立,每周无滞后更新中国专利数据,包含了中国国内和中国对外的所有可公开的专利转移记录,数据的完整性较高。

以城市作为基本空间单元,清洗统计每条专利的所属国家和所属城市,城市的坐标信息通过Google Map API获得。首先,以地级市为单位（包括天门市、仙桃市、潜江市和各自治州）,中国香港和中国澳门作为城市单元考量,中国台湾划分成台北、高雄等6个市和11个县级市（县域内的专利信息全部统计到县级市）。其次,其他国家和地区则根据专利的转移前后地址分配到所在城市,再进行Python编程机器清洗和人工筛选。标准为：① 次国家单元政府（如美国的州政府）所在地或者人口规模前5的城市;② 拥有知名大学或者研发中心的创新型城市;③ 人口超过20万的城市;④ 不符合上述标准的小城市,通过谷歌地图查询地面交通45 min以内可达的大城市进行合并[57,58];⑤ 对于不满足上述4项条件的,则保留专利转移量多于5条的、或是某些国家唯一与中国有专利转移的城市。接着,将数据进行筛选,只保留不同城市之间的专利权转让数据,建立跨国和国内城际专利权转移时空数据库。最后,鉴于2004年后大量跨国公司进入中国[59],跨国专利权交易量不断增加,因此将2004年作为研究的初始年份,为避免专利权交易数据的年际突变性,将数据划分为2004—2008年、2009—2013年、2014—2018年3个时间段分别进行累计分析。

2.3.2 网络构建及建模 城市之间的专利权交易具有流量和流向,因此借鉴图论的思想建立一个有向加权网络G(v, e),参与专利权交易的城市作为网络节点v,城市间专利转移的数量关系作为网络的边e,构建全球（国际）和地方（国内）两个尺度的加权非对称矩阵M：

M=0M12⋯M1(n-1)M1nM210⋯M2(n-1)M2n⋯⋯0⋯⋯M(n-1)1M(n-1)2⋯0M(n-1)nMn1Mn2⋯Mn(n-1)0

引入复杂网络分析的多中心性评价模型：

（1）度中心性（Degree Centrality, CD）指与某城市直接相连的其他城市的数目,表征城市的重要性程度。由于专利转移网络是一个有向的网络,因此节点度分为入度和出度。节点入度表示向该城市转移专利权的城市数量,节点出度表示从该城市对外转移专利权的城市数量,以表示各城市跨国技术转移的通道规模：

CD(i)=∑j=1Naij

式中：aij表示城市专利转移邻接矩阵,有专利输出（引进）则赋值为1,无输出（引进）则赋值为0。

（2）加权度（Weighted Degree, CWD）指城市购买和卖出的专利权数量之和,分为加权入度和加权出度,加权入度表示向该城市转移的专利总量,加权出度表示从该城市转移的专利总量：

CWD(i)=∑j=1Nxij

式中：xij表示城市i向（从）城市j输出（引进）的实际专利数量,即专利转移的强度。

（3）接近度中心性（Closeness Centrality, CC）表示其他城市个数与该城市到其他所有城市最短路径之和的比值,表示该城市与其他城市之间的专利转移的欧式距离。它可以衡量技术通道网络中相关城市的紧密程度：

Cc(i)=N-1∑j=1;j≠iNdij

式中：dij表示城市i和城市j之间的最短路径个数;N表示城市节点的个数。

（4）介数中心性（Betweenness Centrality, CB）是指一个城市出现在技术通道网络中其他城市之间的最短路径上的频率,代表技术通道网络中城市的中转能力或“网关”功能。城市的介数值越大,表明该城市对技术通道网络的控制能力越大。

CB(i)=∑j=1;k=1;j≠k≠iNNjk(i)Njk

式中：Njk表示城市j和城市k之间的最短路径条数;Njk(i)表示城市j和城市k之间的最短路径经过城市i的条数。

2.3.3 回归模型 在回归分析中,网络的链接结构和节点的属性属于不同的概念,因此需要将这些变量分开处理[60]。首先,接近度中心性和介数中心性属于网络的链接结构,不具有任何的方向性。其次,节点的度值存在方向性和权重,由于方向性涉及输出或引进,因此需要根据方向和是否加权分开处理。另外,为了保证分析的准确性,设置了各节点城市的经济社会指标作为控制变量。

由于城市之间的专利转移量为非负整数,且专利输出量和专利引进量的方差均明显大于期望,认为存在“过度分散”。因此,引入面板负二项式回归方法探究中国跨国技术通道规模的影响因素：

Ti=α+β1indegree+β2outdegree+β3windegree+β4woutdegree+β5close+β6between+β7pergdp+β8exp+β9imp+β10tech+β11fdi+β12compony+β13innovation+β14college+ε

式中：α为常数项;ε为随机误差项;Ti为城市i向（从）国际输出（引进）的专利权总量;indegree为城市i在国内城际技术通道网络中的入度;outdegree为城市i在国内城际技术通道网络中的出度;windegree和woutdegree分别为城市i在国内技术通道网络中的加权入度和加权出度;close和between分别为城市i在国内技术通道网络中的接近度中心性值和介数中心性值;pergdp、exp、imp、tech、fdi、compony、innovation、college分别代表城市i的人均GDP、货物出口总额、货物进口总额、科技从业人员数、实际使用外资金额、上市公司数量、国家级企业技术中心数、大学数量。

3 中国跨国城际技术通道的空间演化

3.1 中国跨国城际技术通道规模的空间演化

2004—2018年间与中国进行技术转移的国外城市数量持续增长,密集分布于北美、西欧、东亚—东南亚三大板块（图2）。中国参与跨国技术转移的城市数量不断增多,专利权转移强度也持续增强,相对集聚形成中国台湾北部城市群、粤港澳大湾区、长三角城市群、京津冀城市群四大全球性技术创新高地（图3）。

图2

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图2   2004—2018年中国和海外城市专利转移强度的空间演化

注：基于自然资源部标准地图服务网站GS(2016)1666号标准地图绘制,底图边界无修改。

Fig. 2   Spatial evolution of patent transfer intensity in China and overseas cities in 2014-2008


图3

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图3   2004—2018年中国跨国城际技术转移强度的空间演化

注：基于自然资源部标准地图服务网站GS(2016)1569号标准地图绘制,底边界无修改。

Fig. 3   Spatial evolution of the intensity of transnational patent transfer in Chinese cities in 2004-2018


（1）2004—2008年间,中国主要依托中国香港和中国台湾与国外进行技术转移,与美国硅谷地区的圣何塞、纽约湾区的纽约和威尔明顿、西欧地区的艾恩德霍芬和巴黎、加勒比海离岸金融中心等全球创新型城市技术转移活跃。其中,北美和加勒比海地区的城市以专利引进为主,西欧地区的城市以专利输出为主。国内城市的专利转移强度偏弱,以专利权引进为主。专利权输出上,中国台湾的台北、台南、新竹、桃园以及中国香港位列前5位,中国台湾与中国香港以其低税率或零税率、宽松的监管制度、自由外汇结算等特殊区位因子,成为中国主要的技术辐散中心,其技术输入地集中于美国东北海岸（如威尔明顿）和中国东部沿海技术中心（如北京、上海）。上海、深圳、惠州、北京对外技术输出强度相对突出,但与中国香港和中国台湾主要城市差距显著。专利权引进上,粤港澳大湾区凭借外向开放程度大、创新型企业集聚度高、中国香港低税率管辖区等优势,成为中国主要技术输入高地,形成中国香港和深圳两大技术辐合中心。

（2）2009—2013年间,北美的创新型城市（纽约、波士顿、威尔明顿、圣何塞）及加勒比海地区离岸金融中心（乔治敦、罗德城）的枢纽地位不断凸显,东亚和东南亚的技术转移中心（新加坡、大阪府、东京）不断浮现。粤港澳大湾区、长三角城市群及京津冀城市群等城市群核心城市技术转移强度增长迅猛,成为中国主要的技术辐合中心和创新增长极。一方面,圣何塞、纽约、大阪府、东京等城市对中国的技术输出不断增加,威尔明顿、罗德城、新加坡、乔治敦则成为中国台湾、中国香港和东南沿海主要的技术汇聚地。另一方面,中国台湾的台北、新竹、台中和中国香港仍然是中国跨国技术输出的主要核心,上海和深圳分别凭借跨国公司研发机构和本土创新型引擎企业,对外专利权输出强度则位居其后。东部沿海的粤港澳大湾区（深圳、中国香港、东莞）、长三角城市群（上海、苏州）及京津冀城市群（如北京）创新型经济发展迅猛,对外专利引进强度不断上升,涌现成为全球性的技术辐合中心。期间,中国城市对外技术需求持续增长,专利权引进强度不断增加,同时部分科技创新中心技术生产能力明显增强,对外专利输出强度快速增长,与专利引进强度差距不断缩小。

（3）2014—2018年间,东亚和东南亚经济发达城市成为中国最主要的技术交互地,中国参与跨国技术转移的城市不断由东南部沿海向中西部地区扩散,但专利权转移量高度集中于中国台湾北部城市群、粤港澳大湾区城市群、长三角城市群、京津冀城市群四大技术创新城市群。期间,东亚的东京和首尔、东南亚的新加坡取代美国和西欧创新型城市,分别成为中国首位跨国技术输出中心和技术引进中心。中国台湾北部城市群以台北、新竹、台中等城市为技术增长中心,其专利权转移量维持稳定,技术生产能力强,成为全球性的技术辐散中心和生产中心。粤港澳大湾区城市群专利权转移量增长势头迅猛,相对集中于中国香港、深圳、东莞和广州4市。其中,中国香港因其国际自由贸易港地位,在专利权获取、持有和转让环节中税收低廉、监管宽松,成为中国高科技企业引进欧美和东亚专利技术的主要中转地;深圳凭借良好创新环境、持续研发投入、创新人才和科技基础设施集聚、高新技术产业发达等优势,技术生产能力显著提高,成为中国第一大国际性技术生产中心。长三角城市群整体技术发达,与粤港澳大湾区城市群不同,技术输出强度大于技术引进,相对集中于上海、杭州、苏州和常州。而京津冀城市群技术转移强度分布更加不均衡,高度集聚于北京,以技术引进为主,对外技术输出规模较小。

总的来看,中国跨国技术转移的境外枢纽城市从美国纽约湾区（纽约、波士顿、威尔明顿）和旧金山湾区（圣何塞、旧金山）、加勒比海离岸金融中心（罗德城、乔治敦）向东亚、东南亚（东京、首尔、新加坡等）转移。参与跨国技术转移的国内枢纽城市由中国香港、台北、新竹向国内沿海科技创新中心（北京、上海、深圳）转移,城市功能则相应由技术辐散型（中国台湾主要城市）向技术辐合型（北京等城市）、技术集散型（长三角城市群）和技术中转型（中国香港）分化（图3）。

3.2 中国跨国城际技术通道网络的空间演化

2004—2018年间,中国跨国城际专利转移通道在全球范围内存在明显的空间异质性,主要指向欧美和东亚等技术发达国家或地区。城际技术通道从美国、西欧向东亚和东南亚转移,技术转移枢纽从中国台湾和中国香港向国内东南沿海转移,高度集聚于京津冀、长三角、粤港澳大湾区三大创新型城市群,中国香港、北京、上海、深圳等成为中国对外技术通道网络的全球性核心枢纽。

（1）2004—2008年间,中国的跨国技术输出与引进通道存在明显的空间异配性。技术输出流高度流向美国纽约湾区及加勒比海离岸金融中心,而技术引进流则相对集中于西欧和东亚;对外技术流的枢纽性城市高度集中于中国台北、新竹、北京、上海等国际科技创新中心及中国香港等技术中转中心（图4a~4b、图5a~5b和表1）。

图4

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图4   2004—2018年中国跨国城际技术输出和引进通道的空间演化

注：基于自然资源部标准地图服务网站GS(2016)1666号标准地图绘制,底图边界无修改。

Fig. 4   Spatial evolution of China's transnational patent export and import channels in 2014-2008


图5

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图5   2004—2018年中国跨国技术输出和引进量前50名的城市对

Fig. 5   Top 50 cities in terms of China's transnational patent expert and import volume in 2004-2018


表1   2004—2018年中国跨国城际技术转移出度和入度排名前10的城市

Tab. 1  Top 10 Chinese cities in terms of out-degree and in-degree in 2004-2018

时段中国城市国外城市
出度值入度值出度值入度值
2004—2008年台北25中国香港26圣何塞12罗德城14
中国香港19台北20罗德城8圣何塞7
台中10北京17东京5东京6
新竹10上海15利物浦5乔治敦6
上海9新竹10纽约5威尔明顿6
北京8深圳7洛杉矶4阿皮亚5
台南7无锡6乔治敦4路易港5
桃园7天津5艾恩德霍芬3休斯顿5
杭州5大连4威尔明顿3芝加哥5
东莞4苏州4新加坡3洛杉矶4
深圳4首尔3新加坡4
2009—2013年中国香港38上海60罗德城20罗德城14
台北26中国香港50圣何塞13圣何塞7
北京24苏州47东京10东京6
上海23北京44威尔明顿10乔治敦6
新竹16深圳30乔治敦8威尔明顿6
台中11台北22新加坡7阿皮亚5
苏州10天津18洛杉矶6路易港5
深圳8杭州13芝加哥6休斯顿5
桃园8青岛13阿皮亚5芝加哥5
杭州7广州12墨尔本5洛杉矶4
无锡12首尔市5新加坡4
2014—2018年中国香港47中国香港65圣何塞41罗德城21
深圳38北京59首尔30圣何塞市20
上海36上海57新加坡24东京18
台北28深圳51东京23新加坡市14
北京21苏州46罗德城21乔治敦11
苏州20杭州28大阪18首尔9
厦门14广州26乔治敦18阿皮亚8
新竹14台北25多伦多16洛杉矶8
东莞12常州21京畿道16维多利亚7
台中11东莞19纽约14芝加哥7
新竹19旧金山14

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① 5年间中国对外技术转移流的节点高度集中于美国、西欧和东亚等少数科技创新型城市,这些占总数不到20%的技术创新中心承载了中国对外专利转移流总量的80%以上,而大多数城市间的专利转移通道只有1~2个。总的来看,中国跨国技术转移流量高度不均衡,专利转移高度集中于少数城市之间,呈现出典型的帕累托分布（“二八”原则）。

② 期间中国整体对外技术输出规模大于技术引进,台北成为中国对外技术流的辐散中心（图4a）。5年间中国专利的输出量（1290项）是其对外引进专利权量的2.1倍,且技术通道高度指向美国纽约湾区的威尔明顿和加勒比海地区维尔京群岛的罗德城和开曼群岛的乔治敦。其中,特拉华州由于税收和审批程序等方面的制度优势成为众多跨国公司在美注册的最偏好区位之一[61],享有“世界公司之都”之称。且威尔明顿被誉为“世界化工之都”,化学工业发达。凭借众多跨国公司总部—分支的联系,成为中国台湾研发分支机构（台北和新竹）技术的回流地。英属维尔京群岛的罗德城和开曼群岛的乔治敦则是全球著名的离岸金融中心,凭借税务优惠、保密权利、良好对外贸易关系[62],成为中国台湾和中国香港众多离岸创新型公司的注册地和全球技术生产的中转地。不难看出,中国台湾（台北、新竹、台南等）成为中国对外技术输出的高地和辐散中心（图5a）,台北则成为中国跨国技术通道网络的首位城市和全球性创新枢纽。中国台湾和中国香港的城市不仅具有相当大的对外专利转移深度,对外专利输出量占到总量的87%,而且也发育较大的对外专利转移广度,在整个对外技术转移通道网络中的出度值位居前10（表1）。

③ 2004—2008年间,中国对西欧（法国、荷兰、英国和芬兰等国）和美国的技术依赖程度较高,中国台湾和中国香港成为中国对外技术流的辐合中心（图5a）。期间,中国从荷兰艾恩德霍芬、法国巴黎、英国利物浦等西欧创新型城市专利引进规模达到194项,接近从美国引进的专利总量（204项）。中国香港、中国台湾的新竹、台北位列中国对外引进专利数量前3位城市,占据整个总量的63%,在整个跨国技术转移通道网络中的入度值均超过10（表1）。荷兰艾恩德霍芬和法国巴黎通过跨国公司总部—分支网络,成为中国香港的主要专利技术引进源,二者向中国香港输入的专利权量超过其总量的50%,位列中国对外技术引进通道前两位。而美国的纽约、波士顿、圣何塞（硅谷核心区域）及维尔京群岛的罗德城则成为中国台湾的主要技术供应地（图5d）。总的来看,全球技术生产中心和离岸公司中转中心成为中国技术引进的主要来源地,中国香港和中国台湾技术转移出现明显地域分工：中国香港对外技术引进高度指向西欧创新型城市,而中国台湾的专利技术则主要来源于美国的全球科技创新中心及加勒比海离岸金融中心。

（2）2009—2013年间,相较第一阶段,中国技术生产能力持续上升,跨国技术输出和引进规模相当,技术输出通道与引进通道的强度和广度日益增加,网络愈加稠密,空间异质性不断弱化但空间异配性持续增强。技术引进网络的重心开始东移,新加坡迅速涌现成继美国纽约湾区威尔明顿和英属维京群岛罗德城之后的第三大技术辐合中心。而技术引进流来源地则日益分散,由西欧向美国西海岸、日本、新加坡等地区转移;中国对外技术辐射中心高度锁定于中国台北和中国香港,而对外技术辐合中心则集中于东南沿海的上海、深圳、青岛和北京等经济发达城市（图4、图5b、5e和表1）。

① 中国对外技术输出通道呈现“路径锁定”与“路径突破”并存态势。一方面,与第一阶段一致,中国台湾（集中于台北和台中）和中国香港仍然是对外技术输出的辐散中心,在整个对外技术转移通道网络中的出度值始终位居前10（表1）,跨国公司总部—分支联系在其跨国技术转移中起主导作用,主要对外技术输出通道高度指向美国纽约湾区的威尔明顿及全球主要离岸金融中心（罗德城、乔治敦、阿皮亚）。另一方面,中国对外技术输出通道不断拓展,新的技术通道不断浮现,新加坡、东京、圣何塞等全球性创新中心或全球金融中心成为新的技术吸收中心,呈现由高度集中于西欧北美向分散于东南亚、东亚、美国的空间格局演化（图4c、图5b）;同时,中国的深圳、上海、北京等巨型城市科学技术实力不断增强,成为中国对外专利技术的主要供应地,以深圳、中国香港、上海、北京、台北为核心的粤港澳大湾区、长三角城市群、京津冀城市群、中国台湾北部城市群等四大创新集群正不断浮现,呈现出全球性技术创新集群的潜质。

② 中国对外技术引进通道空间变迁明显,也呈现出典型的路径创造性。一方面,中国对外技术输入通道指向由西欧加速向日本和美国转移,跨国技术引进来源地呈持续分散化和多元化趋势,但仍然高度依赖于日本和美国等少数技术发达国家（图4d、图5e）。期间,中国对外技术引进来源地相对散布于日本的大阪、东京、神奈川,美国的硅谷、圣保罗等科技创新中心,以及纽约、罗德城、乔治敦、新加坡等全球金融中心,但仍然相对集中于日本（东京和大阪输入314项专利）、美国（硅谷地区、纽约湾区总共向中国输出290项专利）和新加坡（输入86项专利）,三大技术生产国的专利权输出量占中国对外专利技术引进总量的55.1%。另一方面,中国对外技术辐合中心由中国台湾和中国香港迅速向国内沿海地区转移,高度集中于珠三角、长三角和京津冀三大城市群。一些技术辐合中心（青岛、苏州等）和技术集散中心（北京、深圳、上海等）迅速崛起,在整个跨国技术转移通道网络中的入度值大多超过20（表1）,开始挑战中国香港和中国台湾的绝对引领地位,成为了新的全球技术集聚中心和技术吸收地。

总的来看,全球技术生产中心和离岸公司中转中心依然是中国技术引进的主要来源地,中国对日本和美国的依赖度不断增大,对西欧的依赖度相对减小。

（3）2014—2018年间,中国跨国技术输出与引进通道的空间格局日趋均衡,参与技术转移核心城市不断增多,与东亚和东南亚地区技术转移日益紧密,呈现与全球经济中心系统性东移一致的技术流空间变迁趋势。技术输出流主要流向美国硅谷、新加坡、英国伦敦、日本东京等全球城市区域,而技术引进流则相对集中于东亚的东京、首尔、美国的硅谷等全球性科技创新中心和金融中心。深圳、上海、北京等沿海创新型城市不断崛起成为中国对外技术通道网络的核心枢纽,中国台湾的技术中转性作用明显下降（图4、图5c、5f和表1）。

一是中国对外技术输出的规模不断扩大,技术输出地由美国向西欧、东亚、东南亚转移,呈现由两核（美国的威尔明顿及加勒比海的罗德城）向多中心（美国硅谷、旧金山、新加坡、东京、伦敦等）演进,相对呈点状集聚于美国西海岸、西欧、东亚和东南亚等地区,高度集中于全球性金融中心和科技创新中心。凭借科技实力雄厚（如硅谷、东京、新加坡等）、跨国公司及分支机构云集（如东京、伦敦、硅谷等）、全球金融中心及低税管辖区（如新加坡、东京、伦敦等）等优势,这些城市成为中国巨型城市创新型公司的注册地,以及进行技术转移的集散地,相应形成技术中心型、总部集聚型和金融中心型3种类型技术转移高地（图5c）。

二是中国对外技术引进通道加速向亚太转移,对日本的技术依赖程度超过美国,沿海地区的中国香港、深圳、北京和上海4市成为中国对外技术流的辐合中心。主要表现在：① 中国从日本引进专利技术量明显超过美国,对美国的专利技术依赖度逐步下降（图5f）。期间,仅中国香港从日本东京引进专利的规模就达到1835项,超过从美国引进的专利总量（1197项）。② 中国对外技术引进通道形成明显的地域分工,全球主要技术生产中心成为来源地。日本东京凭借其在机械、工程、通信等领域发达的技术实力和跨国公司总部—分支网络组织,成为中国香港的主要专利技术来源地,而美国的纽约、圣何塞（硅谷核心区域）以及韩国的首尔则成为北京、上海等多个科技创新中心的主要技术供应地,美国的全球科技创新中心则成为中国台湾的主要专利技术源。③ 中国对外技术引进通道加速东移,日本的东京和大阪、韩国的首尔和京畿道以及新加坡成为中国跨国技术转移的枢纽。在整个技术引进通道网络中,其入度值均位列前10。跨国公司的总部—分支联系和技术联盟成为中国对外技术引进的主要组织形式,主要包括新加坡—常州（如瑞声科技总部→瑞声科技研发中心）、东京—中国香港（如日本电气有限公司→香港联想创新有限公司;日本精工爱普生公司→香港京东方科技有限公司;江森自控日立空调（东京）有限公司→江森自控日立空调技术（香港）有限公司）等技术引进通道。

总的来看,中国跨国技术转移总量逐年增长,技术通道的规模和强度不断提高,指向地从美国纽约湾区和硅谷地区、加勒比海离岸金融中心、伦敦全球金融中心向东亚、东南亚主要科技创新中心（东京、新加坡和首尔等）转移。中国的技术创新能力不断增强,深圳、北京、上海等全球科技创新中心不断浮现,逐渐形成以深圳、北京、上海为核心的粤港澳大湾区、京津冀、长三角三大沿海创新集群。中国香港的全球技术中介枢纽地位不断增强,而中国台湾等主要技术生产中心在中国对外技术转移网络中的枢纽地位持续下降。

4 中国跨国技术转移通道的影响因素

比较中国跨国城际技术通道和国内城际技术通道网络（图4、图6）发现,二者在全球——地方尺度上具有高度的空间同配现象,东南沿海崛起的科技创新中心及其创新集群不仅是中国对外技术转移的枢纽,也是国内技术转移的增长极和创新高地。

图6

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图6   2004—2018年中国城际技术转移通道的空间演化

注：基于自然资源部标准地图服务网站GS(2016)1569号标准地图绘制,底图边界无修改。

Fig. 6   Spatial evolution of intercity patent transfer network in China in 2004-2018


为进一步探究二者的内在作用机制,借鉴资本要素在全球—地方视角上的研究范式[63],通过豪斯曼检验,采用随机效应的面板负二项回归模型,以刻画国内城际技术转移通道结构及地方技术创新环境[64,65,66]对中国跨国城际技术通道的影响机制。由于专利权交易存在方向性,因此将两个被解释变量——专利权的引进和输出规模分别进行回归分析（表2、表3）。相应地,解释变量也分两个方向进行探究,其中模型1~5、9~13主要测度国内城际技术通道网络结构的影响,模型6~8、14~16则通过多维度城市社会经济指标揭示地方技术创新环境的影响。模型1、3、9、11用于解释H1假设,模型2、4、10、12用于解释H2假设,模型5、13用于解释H3、H4假设,模型6~8、14~16用于解释H5假设。

表2   面板负二项回归估计结果(专利引进)

Tab. 2  Results of panel negative binomial regression

解释变量跨国专利引入
模型1模型2模型3模型4模型5模型6模型7模型8
入度0.25**(2.08)
加权入度0.30***(3.64)
出度0.26**(2.45)
加权出度0.27***(4.45)
紧密度中心性3.34***(3.60)
中介中心性-0.00002
(-0.23)
人均GDP1.14***(6.43)0.69***(3.20)1.08***(5.68)0.75***(3.85)0.70***(3.00)1.46***(9.34)
货物出口总额0.34***(2.61)0.26**(2.30)0.34**(2.52)0.29**(2.45)0.31***(2.78)0.42***(2.66)0.32***(4.25)
货物进口总额-0.25***
(-2.98)		-0.16*
(-1.93)		-0.24**
(-2.59)		-0.18**
(-1.98)		-0.14
(-1.46)		-0.31***
(-3.26)		-0.11*
(-1.69)
技术人员数0.72***(5.72)0.67***(5.54)0.71***(5.16)0.69***(5.09)0.65***(4.99)0.74***(5.90)0.36**(2.53)
实际利用外商投资额0.12
(0.91)		0.13
(1.01)		0.13
(1.00)		0.13
(0.99)		0.10
(0.75)		0.09
(0.73)		0.22***
(2.84)
大学数量-0.46***
(-4.07)		-0.46***
(-4.45)		-0.46***
(-4.00)		-0.46***
(-4.43)		-0.39***
(-3.79)		-0.39***
(-3.79)		-0.42***
(-4.19)
上市公司数量-0.06
(-0.32)		-0.04
(-0.19)		-0.08
(-0.40)		-0.11
(-0.59)		-0.07
(-0.39)		-0.01
(-0.55)		0.19(1.61)
国家级企业
技术中心数量		-0.04
(-0.30)		-0.07
(-0.51)		-0.05
(-0.33)		-0.05
(-0.33)		-0.08
(-0.51)		-0.001
(-0.01)		0.39***(3.85)

注：*：p < 0.1,**：p < 0.05,***：p < 0.01。

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表3   面板负二项回归估计结果(专利输出)

Tab. 3  Results of panel negative binomial regression

解释变量跨国专利输出
模型9模型10模型11模型12模型13模型14模型15模型16
入度0.35**(2.09)
加权入度0.38***(4.35)
出度0.35**(1.99)
加权出度0.35***(4.20)
紧密度中心性5.44***(3.53)
中介中心性-0.00002
(-0.15)
人均GDP0.81*(1.66)0.40(1.09)0.73(1.40)0.36(0.90)0.13(0.45)1.17***(3.20)
货物出口总额0.10(0.88)0.10(0.99)0.12(1.11)0.11(1.17)0.15(1.33)0.19(1.52)0.35***(2.91)
货物进口总额0.04(0.30)0.08(0.74)0.07(0.54)0.09(0.86)0.14(1.43)-0.03(-0.25)-0.06(-0.54)
技术人员数0.21(1.04)0.18(0.96)0.17(0.83)0.18(0.95)0.19(0.91)0.22(1.05)0.06(0.29)
实际利用外商
投资额		-0.27
(-1.33)		-0.32*
(-1.71)		-0.29
(-1.38)		-0.27
(-1.35)		-0.29
(-1.42)		-0.32
(-1.54)		0.04(0.32)
大学数量0.003
(0.01)		-0.02
(-0.09)		0.02
(0.06)		-0.007
(-0.03)		-0.04
(-0.20)		0.04
(0.15)		-0.17
(-0.69)
上市公司数量-0.04
(-0.19)		-0.09
(-0.51)		-0.08
(-0.39)		-0.12
(-0.73)		-0.05
(-0.25)		-0.03
(-0.12)		0.23
(1.15)
国家级企业技术
中心数量		0.10
(0.54)		0.20
(1.08)		0.12
(0.60)		0.12
(0.65)		0.10
(0.59)		0.15
(0.72)		0.41***
(2.70)

注：*：p < 0.1,**：p < 0.05,***：p < 0.01。

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4.1 国内城际技术通道的影响效应

（1）地方创新网络拓展显著促进了创新型城市融入全球创新网络和引进吸收跨国技术。① 国内城际技术转移的广度对跨国城际技术的吸收具有显著正向促进效应。回归模型1和模型3结果表明,国内城际技术转移的入度值和出度值（反映了其技术联系的范围和广度）对跨国技术引进规模具有显著的正向促进作用。表明一个城市的城际技术转移通道越多则其跨国引进技术的扩散或吸收能力越强,进而有利于其跨国技术引入通道的发育。② 国内城际技术转移的强度则对跨国技术引入具有明显的正向效应,且这种效应强于国内城际技术转移广度的促进效应。综合回归模型2和模型4结果,中国城际技术转移的加权入度值和加权出度值（刻画其技术转移的强度）对跨国技术引进则具有正向促进作用。这充分表明,城际技术转移会提升城市的技术吸收和技术创新能力[28],有效增强对外部技术模仿和创新能力,进而扩展了跨国技术引入通道,验证了前人对区域技术转移驱动机制研究结论[67]。③ 国内城际技术转移的紧密度有利于跨国技术的引进。模型5回归结果表明,城市在城际技术转移网络中的接近度中心性与其跨国专利引入量呈正相关关系。即,城市在国内城际技术转移网络中的联系能力越强,对国内其他城市专利技术的获取或传播路径越短,不仅可以提升本地创新能力,还有利于学习和吸收跨国技术扩散,进一步证实了技术网络结构的创新绩效作用机制[68,69]。

（2）地方技术通道的广度、深度和紧密度有利于创新型城市专利技术的跨国输出和全球结网。① 国内城际技术通道的广度对地方专利技术的跨国输出具有显著正向促进效应。回归模型9和模型11结果表明,中国城际技术转移通道越广泛,城际技术引进和输出的开放程度越高,自身技术创新能力和参与国际技术竞争和合作能力则越强[69],从而促进其跨国技术输出通道的发展。② 国内城际技术通道的强度对地方嵌入全球创新网络同样具有明显的正向促进作用。综合回归模型10和模型12结果,城市的国内城际技术转移的强度与跨国技术输出呈现显著的正相关关系,说明城市的城际技术转移规模对提升创新绩效和优化创新网络作用显著[53]。③ 国内城际技术转移的紧密度也有利于地方对外技术输出。模型13回归结果显示,城市在国内城际技术通道网络中的紧密度中心性值对其技术的跨国输出强度存在显著的正相关作用。即城市之间技术转移联系紧密程度的提高,能够明显增强产业集群、多集群网络的交流和新技术的溢出[70]。

总之,地方在国内城际技术通道网络中的广度、强度和紧密度对其跨国技术引进和输出通道的发育和扩展均具有显著的正向促进效应,尤其是城际技术转移规模和强度的促进效应最为强烈,验证了本文的H1~H3假设。另外,国内城际技术转移网络中的节点中介性对其跨国技术转移并没有显著的影响,H4假设不成立。

4.2 地方技术创新环境的影响

（1）地方技术创新环境对其融入全球创新网络、促进跨国技术引入具有显著影响。① 地方经济水平显著影响跨国技术的吸收。回归模型1~6结果表明,城市经济发展水平（人均GDP）对跨国技术引进具有较高的解释水平。即城市的经济发展水平通过产业活力带来旺盛的技术需求[71],驱动城市对外部技术的引进和吸收。② 地方技术实力对跨国技术的引进具有多重影响。综合回归模型1~7的结果,城市的技术人员投入、国家级企业技术中心的建立可以有效提升对外技术引进强度,而城市的大学数量则会抑制其跨国技术的引进。因此,H5假设不成立。究其原因,跨国技术转移的主体是企业,企业技术人员或者国家级企业技术中心高度集聚的城市具有更强的技术储备和研发实力,可以更好地吸收国外的先进技术。而大学在跨国技术转移过程中参与度较低,对技术转移贡献有限,城市高等教育水平与其科技生产能力的耦合失调[72],往往阻碍企业的后续技术创新[73],因此大学的数量反而会抑制跨国技术引进通道的发展。③ 地方对外经济联系强度对跨国技术引进强度具有多重影响。模型1~6、8的结果表明,城市货物出口额能够促进跨国专利引入,货物进口额则呈负相关关系。货物出口是城市对外经济联系的重要渠道,促使城市获得更多的信息溢出和形成稳定的城际合作关系,从而促进跨国技术的引进和吸收。而货物进口不利于跨国技术引入,这与前人研究有所不同[74]。原因可能在于进口货物中消费品规模不断攀升,年增长率平均达到10%以上,对消费品进口的依赖会抑制本地的创新能力[75],从而难以实现技术的学习和吸收。另外,城市实际利用外商投资增加会促进国内城市与国外企业间的经济合作和技术交流,从而正向促进跨国技术引进通道的扩展,但其回归结果不够稳健。

（2）地方技术创新环境对技术跨国输出强度存在正向影响,但稳健性不佳。① 地方经济水平对跨国技术的输出规模具有正向促进作用。综合回归模型9~14结果表明,城市经济发展水平（人均GDP）越高,生产效率也越高,技术投入往往较大,研发能力较强,这必然带来更强的技术输出能力。② 地方技术实力和开放程度对其跨国技术输出强度存在一定影响,但稳健性较低。模型9~16的回归结果表明,当选取国家级企业技术中心数量和货物出口贸易额2个指标进行回归时,地方技术实力和开放程度对跨国技术输出强度存在显著积极影响,但纳入多个指标进行回归时,大多数指标不再显著。具体而言,城市的国家级企业技术中心数量越多,技术创新能力和国际竞争力则越强,则其跨国技术输出规模越大。城市的货物出口贸易额越大,跨国经济联系和技术交流紧密;此外,出口货物所参照的国际标准往往更为严格,要求相关企业掌握更为先进的技术,进而促进相关外贸企业的技术创新能力提升[76]。

总的来说,在跨国技术的引进和输出中,地方经济水平存在显著的正效应,而技术实力和对外经济联系则具有多重效应。其中地方货物出口、外商直接投资、技术人员数量、国家级企业技术中心数量有利于跨国技术的引进,而货物进口、大学数量起到抑制作用,货物出口、国家级企业技术中心则对其跨国技术输出通道发展具有较弱的促进作用。

5 结论与政策启示

5.1 结论和讨论

基于中国的跨国和国内城际专利转移数据,融合大数据挖掘技术、复杂网络分析、GIS空间分析和空间计量分析等方法,系统刻画了2004—2018年间中国跨国城际技术通道网络的空间演化规律,并基于全球—地方视角下的技术转移双通道理论框架解析了地方创新网络和地方技术创新环境对中国跨国技术通道演化的影响机制：

（1）跨国城际技术通道的形成和发育具有明显的空间异质性,但时序上不断弱化和均衡化。主要城际技术转移通道指向由两核（美国纽约湾区的威尔明顿和加勒比海的离岸金融中心）向多中心（美国硅谷地区、纽约湾区、日本东京、韩国首尔、新加坡等主要科技创新中心及离岸金融中心）演进,跨国城际技术通道加速系统性东移,中国对美国和西欧的专利技术依赖性明显减弱。

（2）跨国城际技术引进通道和输出通道存在一定的空间异配性。跨国城际技术引进以中国香港、深圳、北京和上海为枢纽,来源地相对集中于西欧和东亚,而技术输出流则以中国台湾为技术生产高地和中国香港为技术中转中心,主要流向美国的科技创新中心和加勒比海的离岸金融中心。

（3）跨国城际技术转移高度依赖于少数巨型城市区域,深圳、北京、上海等中国东南沿海全球性技术创新中心不断浮现,高度集聚形成以其为核心的粤港澳大湾区、京津冀城市群和长三角城市群三大技术创新集群。凭借邻近大陆市场、跨国公司总部—分支联系、离岸金融市场低税收优势,中国香港的技术中介作用（门户区位）不断增强,中国台湾的技术集散地位（枢纽区位）持续下降。

（4）跨国城际技术通道演化呈现明显的路径依赖和路径突破。一方面,中国对外城际技术转移通道高度指向日本、美国等少数发达国家,全球技术生产中心和离岸金融中心依然是中国技术引进的主要来源地,中国台湾和中国香港始终是其对外技术转移的核心枢纽。另一方面,中国对外城际技术转移加速向亚太地区转移,不断衍生出新的技术路径,对美国和西欧的技术依赖度持续减弱,深圳、北京、上海等东南沿海地区技术创新中心不断崛起,逐渐取代中国台湾成为新的技术转移枢纽。

（5）地方创新网络和技术创新环境对地方融入全球创新网络具有明显的促进作用。实证结果表明,地方技术通道网络、经济发展水平、技术实力和对外联系强度对其专利技术的跨国转移、跨国城际技术通道的发育和扩展具有显著的正向效应。地方技术通道的广度、强度和紧密度提升有利于地方与全球创新网络的嵌入和链接,对地方跨国技术引进和输出通道发育具有显著正向促进效应。而地方技术创新环境则对其跨国技术通道拓展具有复杂的多重效应：① 地方经济实力、货物出口规模、国家级企业技术中心数量有利于提升地方的技术生产能力和吸收转化能力,对地方跨国技术引进和输出具有正向促进效应;② 地方外商直接投资和技术人员数,对地方跨国技术引进具有显著正向影响,但其货物进口规模、大学数量则对其跨国专利引进具有抑制效应;③ 地方技术人员、外商直接投资、货物出口、大学规模则对地方跨国技术输出通道拓展缺乏明显作用。

（6）全球地方创新网络空间演化机理是科技创新地理与世界经济地理的交叉前沿命题。尽管论文试图解析地方创新环境及地方创新网络组织对中国对外创新网络空间演化的影响,但仍然存在明显不足,有待深化：因数据本身局限性,没有甄别专利技术交易双方与实际使用者之间关系,可能导致技术供需分析存在偏差;仅讨论了国内城际技术通道对跨国技术转移通道的影响,有待深入解析跨国技术通道与城际通道间的耦合机制;专利权交易虽是刻画技术市场供需的有效指标,但不够全面,有待从知识交流与合作、技术产品贸易、科研项目合作等方面进行综合分析;没有深入比较分析不同类型专利技术转移的时空异质性规律,尤其是“卡脖子”技术。

5.2 政策启示

（1）中国的跨国城际技术通道指向高度集中,对美国、日本等发达国家的技术依赖度居高不下,融入全球创新网络风险较大。一方面,有待持续扩展对外技术引进广度,促进与“一带一路”沿线国家间的专利技术交易,以增强跨国技术通道的多元性和均衡性。另一方面,坚持科技自立自强,强化国家战略科技力量,培育创新增长极,布局建设系列综合性国家科学中心和区域性创新高地。

（2）中国的跨国城际技术通道空间组织以跨国公司总部—分支联系为主,受制于国外主要跨国公司。为此,应持续加强中国企业“走出去”,建立研发中心和科技园区,主动布局和建设全球创新网络,集聚和利用全球创新要素;同时强化与国外跨国公司、一流大学和科研机构的技术贸易和技术研发合作,拓宽技术转移渠道,实现技术外溢。

（3）中国融入全球创新网络的枢纽城市高度集中于东南部沿海少数科技创新中心,辐射带动内陆地区的能力不足。一方面,充分发挥创新活动高度集聚的溢出效应,加快建设以北京、上海、深圳、中国香港等创新型城市为核心的京津冀、长三角、粤港澳大湾区创新高地,加强与中国台湾的技术市场联盟,构建海峡两岸创新共同体,建设健全统一的技术转移市场和高效的技术转移机制,促进创新集群内城际技术一体化发展。另一方面,增强创新集群之间的技术转移转化,促进创新集群与内陆城市间的技术联系和合作,布局和建设一批不同等级和功能梯次联动的创新型城市体系,吸引高科技人才、鼓励技术创新以及加强产学研合作等方式增强主要创新型城市的技术研发实力和转移转化能力,提高城际技术通道的密度和流量,从而提高跨国技术通道的强度,辐射带动全国,实现国家创新体系梯次联动发展。

（4）地方创新网络和技术创新环境建设对中国跨国技术通道拓展具有显著积极作用,但大学和企业技术中心对地方融入全球创新网络的支撑作用不突出。一方面,有待发挥一流大学和科研机构知识生产和人才培养的国家队作用,强化知识链、创新链和产业价值链的深度融合,深化产学研一体化体制机制创新,培育地方参与全球科技竞争和合作的新优势。另一方面,加快建设和完善国家技术转移体系,大力发展技术转移社会化中介机构,加强知识产权保护,拓宽企业、高校、科研机构间转移通道建设,加快国际技术转移中心建设,加速技术转移载体全球化布局。

致谢

感谢华东师范大学城市与区域科学学院毛炜圣博士对本文的修改与完善。

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Technology transfer is an important means to promote coordinated regional development and efficient allocation of innovative resources. Patent transfer is a major part of China's technology transfer trading market, but the mechanism behind it has not been fully explained. By using the existing genetic distance estimation method and the widely recognized Han population genetic data, this study explored the mechanism of cross-regional patent transfer from the perspective of genetic differences. By mining the patent transfer data of the Patent Search Platform of the State Intellectual Property Office and combining with other economic geographic data, we conducted a quantitative research on whether genetic distance has affected inter-provincial patent transfer. Considering the principle of "same-sex repelling and opposite-sex attracting," a model was constructed from the perspective of technical competition. Results of the regression analyses of the panel data show that the farther the genetic distance is, the more likely it is to have inter-regional patent transfers. In general, for one-standard-deviation rise of genetic differences between two provinces, the number of patent transfers between them increased by 9.8%. The results have undergone several robustness tests and the spatial differences also have been considered. This study highlights the importance of genetic diversity for human society, and suggests that policies should relax migration and settlement restrictions and encourage inter-regional exchanges and integration.

[ 钱超峰, 杜德斌, 胡璇, 等.

地区间基因差异会影响技术转移吗? 基于中国2001—2005年省际专利转让数据

地理科学进展, 2019, 38(5): 745-755.]

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Donges A, Selgert F.

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The Economic History Review, 2019, 72(1): 182-208.

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Wen Fangfang.

Research on the temporal and spatial distribution law of patent technology transfer in China

Information Studies: Theory & Application, 2014, 37(4): 32-36.

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[ 温芳芳.

我国专利技术转移的时间与空间分布规律研究: 基于SIPO专利许可信息的计量分析

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Liu C L, Niu C C, Han J.

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Sustainability, 2019, 11(6): 1647. DOI: 10.3390/su11061647.

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Duan Dezhong, Du Debin, Chen Ying, et al.

Spatial-temporal complexity and growth mechanism of City innovation network in China

Scientia Geographica Sinica, 2018, 38(11): 1759-1768.

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At present, China’s city innovation system is gradually taking shape. As the core component of innovation resources, innovative technology represented by patents has become the focus of competition among all cities. Its gathering and diffusion channels urgently need to build a compatible city technology transfer system. The construction of a national technology transfer system in line with the law of science and technology innovation, the law of technology transfer and the law of industrial development is an inevitable choice for serving the strategy of innovation development. Based on data mining from National Intellectual Property Office of China, the heterogeneities and its evolution characteristics of city innovation network depicted by patent transfer in topology and space from 2001 to 2015 were sketched using lots of visualizing tools such as Pajek, Gephi, VOSviewer, ArcGIS, and so on. Topologically, from 2001 to 2015, with the increasing number of cities involved in technology transfer, China city innovation network has emerged a significant small-world feature with the smaller average path length and the extremely large cluster coefficient compared to its counterpart. In addition, the entire network presents a core- periphery structure with hierarchies, which dominated by Beijing, Shanghai and Shenzhen. Spatially, the quadrilateral pattern of China city innovation network based on the triangular structure is gradually formed. Last but not least, the growth mechanism of city innovation network were also verified by correlational analysis, negative binomial regression approach and gravity model of STATA. The growth of city innovation network in China is significantly related to the technological innovation strength represented by the number of patent application. The findings further confirm that geographical distance has weakened cross-city patents transfer. Meanwhile, the similarity of economic development and industrial structure between cities are also important factors influencing the growth of city innovation network.

[ 段德忠, 杜德斌, 谌颖, 等.

中国城市创新网络的时空复杂性及生长机制研究

地理科学, 2018, 38(11): 1759-1768.]

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Zhang Yiou, Gu Renxu.

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[ 张翼鸥, 谷人旭.

中国城市知识复杂性的空间特征及影响研究

地理学报, 2018, 73(8): 1421-1432.]

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Chaminade C, Plechero M.

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Si Yuefang, Zeng Gang, Cao Xianzhong, et al.

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Progress in Geography, 2016, 35(5): 600-609.

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Against the background of economic globalization and technological development, innovation network has been a heated topic in the field of economic geography research. However, the scale of research of innovation network remains debatable. Among the global, nation, and local scales, which one is important? The concept of “glocalization” provides a new perspective to this research. Glocalization refers to the twin process whereby, firstly, institutional arrangements shift from the national scale both upwards to the global scale and downwards to local configurations and, secondly, economic activities and inter firm networks are becoming simultaneously more localized/ regionalized and transnational. Based on solid theoretical reviews, this article defines the concept of glocal innovation network and then discusses the main issues and research methods of glocal innovation networks. In this article, glocal innovation network is defined as the sum of knowledge network channels of various innovators, for example, firms, universities, and research institutes, which increasingly connect globally scattered innovation resources together. Local innovation networks, which are the sub-networks of global innovation networks, are connected by trans-local knowledge flows. Glocal innovation networks are organized by the negotiation among industrial associations and technology alliances and their members. Network knowledge measurement is the suitable method to analyze the structure, evolution, and mechanism of glocal innovation network. The concept of glocal innovation networks provides a new perspective to analyze the approaches of local/regional innovation capabilities promotion and economic development by utilizing global and local knowledge. We conclude that existing research remains at the stage of conceptual discussion and case studies. Therefore, the following issues should be further studied: (1) glocal innovation network evolution dynamics and its connection with economic development; (2) comparative study of glocal networks of different industries and technologies; (3) characteristics of Chinese glocal innovation networks, which can provide empirical evidence of latecomer regions in the catching-up process for further theoretical discussion.

[ 司月芳, 曾刚, 曹贤忠, 等.

基于全球—地方视角的创新网络研究进展

地理科学进展, 2016, 35(5): 600-609.]

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Xia Lili, Wang Runxiao, Liang Xinyi, et al.

Evolution of R&D behavior and influential factors of indigenous enterprises of host countries under the global-local background: A case study of manufacturing enterprises in Guangzhou from the perspective of technology spillover

Scientia Geographica Sinica, 2019, 39(2): 277-284.

DOI:10.13249/j.cnki.sgs.2019.02.012      [本文引用: 2]

<p>The global-local relationship generated in the process of innovation and transnational innovative mechanism has become a new topic of regional development. The research on the impact of globalizing forces on the innovation of host countries is mainly based on the perspective of technology spillover and the impact on the evolution of economic and innovation consequence of host countries has attracted great attention during the last two decades. Few literatures, however, have focused on the impact on the process of innovation,which is more significant for developing host countries to achieve technical transition and value upgrading in global production network. Based on a case study of Guangzhou, this article begs the question of what effect the technology spillover of transnational enterprises has on the process of innovation of China, especially on indigenous manufacturing firms, which play a key role in industrialization and face increasingly urgent environmental regulation and the demand of technical transition in China. Fieldwork is carried out to obtain R&D behavior’s characteristics of indigenous manufacturing firms using semi-structured questionnaire through face-to-face interviews with owners or responsible persons of the firms selected by convenient and snowball sampling. Location of the samples covers major manufacturing area in Guangzhou. The results show that since the 1990s, the indigenous firms have gradually increased R&D input, established independent R&D institutions as well as actively promoted R&D internationalization. Meanwhile, the R&D behavior of technology import and external cooperation are relatively weak. These changes indicate the indigenous manufacturing firms have experienced a R&D mode transition from highly dependent on introducing technology from developed Countries to the internalization and internationalization of R&D behavior dominated by self-dependent innovation. Promoting the motivation of self-dependent innovation of indigenous enterprises underlies the evolution of R&D behavior under the circumstance of integrating multinational innovation network. The study further investigates what impacts the technical spillover from foreign investments have on the evolution of R&D mode of indigenous manufacturing firms and its mechanism by building an ordinal polytomous logistic regression model. In the model, the effect of technical relation, productive cooperation and labor turnover between translational and indigenous manufacturing enterprises have been examined. The results show that technical spillover from foreign investments has a significant impact on the transition of R&D mode of local enterprises. Both of the decreased technical gaps and the free flow of labor force between international and local enterprises have significantly promoted the motivation of independent R&D behavior of local enterprises. More closely embedded in global production networks also has a positive effect. However, international technology procurement has a significant negative effect on self-dependent innovation of indigenous manufacturing firms. The results of this paper can help to enrich the understanding of the evolution of local innovation process and its mechanism under the background of globalization, and provide inspiration for the policy-making of regional innovation system integrated global forces.</p>

[ 夏丽丽, 王润晓, 梁新怡, 等.

全球—地方背景下东道国企业研发行为的演变及其影响因素研究: 基于技术溢出视角的广州市本土制造企业微观实证

地理科学, 2019, 39(2): 277-284.]

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Sun Peng, Cheng Danya.

Research on the innovation effect of Xi'an software industry cluster from global-local perspective

Human Geography, 2019, 34(5): 101-108.

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[ 孙鹏, 程丹亚.

全球—地方视角下西安市软件产业集群的创新效应研究

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Du Debin, Liu Chengliang, Duan Dezhong, et al. China-U.S. Science and Techonology Comptitiveness Assessment Report 2019. Shanghai: East China Normal University Press, 2019.

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Mackinnon D, Dawley S, Pike A, et al.

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Mao Xiyan, He Canfei.

Progress of environmental effects of international trade: A global-local perspective

Progress in Geography, 2016, 35(8): 1027-1038.

DOI:10.18306/dlkxjz.2016.08.012      [本文引用: 1]

Trade-environment relationship is one of the major manifestations of the coupled human-environment system, exhibiting significant complexity and uncertainty. Studies on the environmental effects of trade (EET) seek to explore the complementary or competing relationship between free trade and environment conservation, and give birth to a series of theories and hypotheses. Since globalization has witnessed increasing global-local interactions, this article outlines a framework of global connection, national power, and regional development to review existing studies on EET. It highlights how the process (flows) and the outcome (stocks) of trade work together to generate EET. Based on neo-classical international trade theory, this study identifies three types of stocks, namely location, growth, and regulation. In contrast, the integration of international trade and investment indicates the importance of intra-industry trade. This study shows that existing literature on EET is primarily based on the global and national scale, showing a "top-down" trend, where the role of environmental regulation stands at the center. However, these studies failed to incorporate the localized factors and neglected the interaction between trade policy and environmental regulation. They are also confined to the "north-south" trade and cease to follow the changing geography of trade. Accordingly, this article argues that EET studies should pay closer attention to regional development from a "glocalization" perspective to: (1) consider the expanding trade-induced regional inequality; (2) adapt to the coexistence of intra-and inter-industry trade; and (3) produce a proper scale for the coordination between trade policy and environmental regulation.

[ 毛熙彦, 贺灿飞.

“全球—国家—地方”尺度下的国际贸易环境效应研究进展

地理科学进展, 2016, 35(8): 1027-1038.]

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Dicken P.

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[ 张云伟, 曾刚, 程进.

基于全球通道与本地蜂鸣的张江IC产业集群演化

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He Canfei, Mao Xiyan.

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Progress in Geography, 2015, 34(9): 1073-1083.

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Time-space compression in the context of globalization leads to declining costs of communication and transportation and increasing transnational activities. The emergence of multi-national firms and international organizations, in accordance with increasing boundary-crossing activities, has simultaneously weaken the power of state on economic, political, and cultural processes within its territory. Under such circumstances, some researchers assert globalization as "the end of geography", which sounds like an argument of hyper-globalist. In light of scale construction, human geographers are engaged in reconstructing the global scale and relating it to other scales. It turns out that space matters in the process of globalization. Two key points emerge: (1) Scale construction is not necessarily with hierarchical structures. Relation-based scales provide a better model for globalization, which is featured with horizontal communication rather than vertical regulation. (2) Global shifting exhibits trends both towards globalization and localization simultaneously, much of which appears to be global-local nexus rather than simplex globalizing process. These findings introduce new perspectives into globalization research in human geography: framework based on relational network makes it possible to conduct a trans-territorial analysis and to depict a big picture of the reshaping pattern of global economic landscape. On the other hand, in light of localized globalization, researchers set out to refer regional development to global-local interactions other than local embeddedness and endogenous factors, which offers insight into urban and regional governance in the context of globalization.

[ 贺灿飞, 毛熙彦.

尺度重构视角下的经济全球化研究

地理科学进展, 2015, 34(9): 1073-1083.]

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Mao Xiyan, He Canfei.

A review of global-local interactions for regional development

Progress in Geography, 2019, 38(10): 1449-1461.

DOI:10.18306/dlkxjz.2019.10.001      [本文引用: 2]

Extra-regional linkages can benefit regional development by introducing supplement resources and technologies. They also enrich the local knowledge base, keeping regions away from depression due to lock-in effects. Global-local interaction (GLI) research represents the academic effort to theorize this process by examining the interplay between a wide array of actors at multi-scales within particular territorial confines. It raises four critical questions regarding the conditions, regional differences, channels, and actors for interaction. The literature has documented that the relatedness between local and nonlocal inputs determines the probability of GLI. Local capabilities determine the extent of GLI. The literature also reveals that the leading and most lagging behind regions tend to benefit from GLI. Knowledge diffusion, foreign investment, and international trade are primary elements that support GLI. As one region continues to develop, the immigrants and nonlocal institutions may enrich the GLI. Conventionally, the literature on GLI is firm-centric. Recent advances highlight the role of individuals, such as entrepreneurs and employees. There is also increasing awareness of the non-economic agency, especially the institutional agency. Overall, an in-depth examination is still required for understanding the scales, dynamics, and agencies of GLI for regional development. Grounded in the context of China's regional restructuring and opening-up, this study proposes a framework to model GLI in China and discusses its potential for future studies.

[ 毛熙彦, 贺灿飞.

区域发展的“全球—地方”互动机制研究

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[ 殷德生, 吴虹仪, 金桩.

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Spatio-temporal evolution of interurban technological flow network in the Yangtze River Delta Urban Agglomeration: From the perspective of patent transaction network

Geographical Research, 2018, 37(5): 981-994.

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Taking the Yangtze River Delta Urban Agglomeration as an example, based on the perspective of patent transaction network and applying the big-data mining technology, social network analysis and GIS, this paper describes the regular laws of the spatiotemporal evolution of the interurban technological flow network systemically. The results are obtained as follows: First, enterprise is the main body of interurban technological transfer, while universities and institutes play a minor role in the patent transferring relationship. Besides, technological transfer tends to generate in an internal system, instead of spillovers outside. What's more, the patent related to appearance designs is less than innovative patent and utility-oriented patent. Second, as the diffusion centers of the interurban technological flow network under a hub-and-spoke organization, Shanghai, Hangzhou, Nanjing and Suzhou make a transfer from technical convergences to technical centers. Furthermore, Hefei, Nantong and Jiaxing become the main technological absorbers. Third, two diffusion models in the interurban technological flow network are observed. One is hierarchical diffusion model from hubs towards lower-tier cities or sub-centers. The other is contacting diffusion models and technological flows have emerged between those neighboring city pairs because of spatial proximity. Fourth, interurban technological transfers are not well distributed. Under the Matthew Effect, the dynamics of the technological flow network is self-organized with the coupling mechanism including place dependence and path creation. Finally, the spatial evolution of the network presents an evolutionary law from discrete homogeneity with single core (e.g., Shanghai) to dual-hub driven pattern (i.e., Shanghai and Suzhou) to multi-core network with a hub-and-spoke system (e.g., Shanghai, Suzhou, Hangzhou and Nanjing).

[ 刘承良, 管明明.

基于专利转移网络视角的长三角城市群城际技术流动的时空演化

地理研究, 2018, 37(5): 981-994.]

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Liu Chengliang, Niu Caicheng.

Spatial evolution and factors of interurban technology transfer network in Northeast China from national to local perspectives

Acta Geographica Sinica, 2019, 74(10): 2092-2107.

DOI:10.11821/dlxb201910010      [本文引用: 1]

Interurban technology transfer becomes an essential channel for regions or cities to obtain external knowledge. Based on patent transaction data among cities during 2005-2015, this study investigates the interurban technology transfer network of Northeast China, aiming to explore spatial evolution of technology transfer network in this region from national to local perspectives based on social network analysis (SNA). A negative binomial regression analysis further reveals the factors of interurban technology transfer network. The results of the study are as follows: (1) From the national perspective, the interurban technology transfer network of Northeast China presents a core-periphery structure. The spatial pattern of "divergence in the northeast region" and "convergence in the coastal areas" has been formed. (2) From the local perspective, the technology transfer network of Northeast China shows a centripetal contraction situation, and its four hubs, namely, Harbin, Changchun, Shenyang and Dalian, play the role of technology gatekeeper. The interurban technology transfer flows present the characteristic of strengthening nationalization and weakening localization, which are more likely to emerge between the Northeast-Southeast China rather than among the Northeast China. (3) Both path-dependence and path-creation exist in the spatial dynamics of intercity technology flows in Northeast China. From the national perspective, technology flows from Northeast China to the Beijing-Tianjin-Hebei, Yangtze River Delta and Pearl River Delta urban agglomerations with Beijing, Shanghai and Shenzhen as the core respectively, while the local intercity technology transfer in Northeast China presents a mixed diffusing mode including hierarchical, contagious and jump diffusions. In addition, the local network mainly focuses on intra-provincial technology flows which centered on Haibin, Changchun, Shenyang and Dalian. (4) Some drivers, such as geographical proximity, the similarity of industrial structure, economic differences, the similarity of innovation capability, technology absorptive capacity, foreign direct investment, are evidenced to play a significant or determining role in interurban technology transfer of Northeast China.

[ 刘承良, 牛彩澄.

东北三省城际技术转移网络的空间演化及影响因素

地理学报, 2019, 74(10): 2092-2107.]

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Fang Wei, Zheng Liming, Wang Lili.

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[ 方炜, 郑立明, 王莉丽.

改革开放40年: 中国技术转移体系建设之路

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DOI:10.1007/s40804-019-00163-x      [本文引用: 1]

US corporate law and, in particular, Delaware law, which leaves ample room to freedom of contract, has been one of the reasons for the successful creation and financing of startups in Silicon Valley. We analyze the Italian attempt to modernize company law in order to promote startup creation within the wider movement of company law simplification and modernization around Europe. In Italy a suitable corporate law statute for early stage startups was missing. Italy is a dual system jurisdiction. The SPA (public company type) has at least part of the required financial flexibility, but it is still burdened by European rules on legal capital and inflexible rules concerning management and controls. The SRL (private company type) offered a lot of leeway as to the management of the company, but left no room for freedom of contract with regard to financing, since it was not imagined as a vehicle for investors. In response to competitive pressure, economic aspirations and social changes, and to general demands from European institutions for some forms of facilitation of firm creation and venture capital, the Italian lawmaker has slowly transformed the SRL and created what is basically a new type of company (the SME SRL), which lies in between the two original types but whose borders are not fully clear. The ambiguous character of this company form makes it a problematic model for venture-funded startups. On the basis of our analysis, we argue that Italian corporate law is under competitive pressure from Delaware rather than from inter-European competition on corporate charters, and that path-dependance and remaining limits to freedom of contract burden Italian company law and prevent economic growth. We make some policy suggestions, among which the introduction of a counter-Satzungsstrenge principle for private companies.

Buckley P J, Sutherland D, Voss H, et al.

The economic geography of offshore incorporation in tax havens and offshore financial centres: The case of Chinese MNEs

Journal of Economic Geography, 2015, 15(1): 103-128.

DOI:10.1093/jeg/lbt040      URL     [本文引用: 1]

Shi S, Wall R, Pain K.

Exploring the significance of domestic investment for foreign direct investment in China: A city-network approach

Urban Studies, 2019, 56(12): 2447-2464.

DOI:10.1177/0042098018795977      URL     [本文引用: 1]

Zhang G P, Duan H B, Zhou J H.

Investigating determinants of inter-regional technology transfer in China: A network analysis with provincial patent data

Review of Managerial Science, 2016, 10(2): 345-364.

DOI:10.1007/s11846-014-0148-2      URL     [本文引用: 1]

Link A N, Morris C A, van Hasselt M.

The impact of public R&D investments on patenting activity: Technology transfer at the US Environmental Protection Agency

Economics of Innovation and New Technology, 2019, 28(5): 536-546.

DOI:10.1080/10438599.2018.1542772      URL     [本文引用: 1]

Si Yuefang, Wang Dai, Wang Fenglong.

Geographical patterns and determinants of transnational technology transfer to China

Scientia Geographica Sinica, 2019, 39(2): 259-266.

DOI:10.13249/j.cnki.sgs.2019.02.010      [本文引用: 1]

In this article, we analyze the geographical distribution of the countries which transfer technology to China via technology introduction contracts and the factors influencing the amount of technology introduction contracts from 2003 to 2016, based on a large database compiled from World Bank, USPTO and China Statistical Bureau. We find out that, 1) Historically, the total amount of transnational technology introduction contracts to China showed a U-shape development trajectory: it increased dramatically from 2003 to 2013, and then decreases gradually due to the implementation of national endogenous innovation policy from 2013. 2) Geographically, the Gini index fluctuated between 0.85 and 0.90, indicating a high spatial concentration of transnational technology introduction contracts. Among all the source countries, the United States, Japan, Germany, Finland, the UK and France have been the main sources in the whole period; while India, Malaysia, Thailand and other Asian countries are becoming increasingly important in recent 5 years. 3) Three main aspects, namely technical capability gap, geographical distance and technology pipeline, influence the amount of transnational technology transfer to China. Countries geographically closer and of the greater the technical capability are more important sources which transfer technology to China. The transnational technology pipeline in terms of overseas Chinese community and multinational companies also facilitate the technology transfer to China. However, the imports of goods show a negative relationship with transnational technology introduction contact, because the countries which import low-tech goods to China usually have comparatively low technical competitiveness. It is reasonable that China avoids importing technology from those countries.

[ 司月芳, 王岱, 王丰龙.

对华跨境技术转移影响因素研究

地理科学, 2019, 39(2): 259-266.]

[本文引用: 1]

Yang Longzhi, Liu Xia.

Is there "Matthew Effect" in regional technology transfer? The driving orientation of inter-regional technology transfer

Studies in Science of Science, 2014, 32(12): 1820-1827, 1858.

[本文引用: 1]

[ 杨龙志, 刘霞.

区域间技术转移存在“马太效应”吗? 省际技术转移的驱动机制研究

科学学研究, 2014, 32(12): 1820-1827, 1858.]

[本文引用: 1]

Zeng Qinghui, Wang Guoshun.

An empirical study on the relations between network capability of industrial network and innovation performance

Economic Geography, 2014, 34(10): 111-118.

[本文引用: 1]

[ 曾庆辉, 王国顺.

基于产业网络的企业网络能力与创新绩效关系实证研究

经济地理, 2014, 34(10): 111-118.]

[本文引用: 1]

Cheng Kaiming, Wang Yali.

Mechanism and evidence of the promotion of city network on technological innovation

Studies in Science of Science, 2013, 31(9): 1399-1411, 1440.

[本文引用: 2]

[ 程开明, 王亚丽.

城市网络激发技术创新的机理及证据

科学学研究, 2013, 31(9): 1399-1411, 1440.]

[本文引用: 2]

Zhou Can, Cao Xianzhong, Zeng Gang.

Cluster networks and evolution path of China's electronic information industry innovation

Geographical Research, 2019, 38(9): 2212-2225.

[本文引用: 1]

[ 周灿, 曹贤忠, 曾刚.

中国电子信息产业创新的集群网络模式与演化路径

地理研究, 2019, 38(9): 2212-2225.]

[本文引用: 1]

Liu Chengliang, Guan Mingming, Duan Dezhong.

Spatial pattern and influential mechanism of interurban technology transfer network in China

Acta Geographica Sinica, 2018, 73(8): 1462-1477.

DOI:10.11821/dlxb201808006      [本文引用: 1]

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.

[ 刘承良, 管明明, 段德忠.

中国城际技术转移网络的空间格局及影响因素

地理学报, 2018, 73(8): 1462-1477.]

[本文引用: 1]

Xiao Sa, Liu Jun.

The coordinated development analysis about the science-technology innovation ability of regional higher education

Economic Geography, 2018, 38(8): 124-131.

[本文引用: 1]

[ 肖洒, 刘君.

区域高等教育科技创新能力协同发展测度分析

经济地理, 2018, 38(8): 124-131.]

[本文引用: 1]

Xu Chun.

Universities' patents, technology transfer and firms' innovation in China: Based on the accumulation innovation

Science of Science and Management of S.&T., 2013, 34(12): 78-86.

[本文引用: 1]

[ 许春.

中国大学专利、技术转移与企业创新: 基于累积创新视角

科学学与科学技术管理, 2013, 34(12): 78-86.]

[本文引用: 1]

Zhang Jianqing, Sun Yuanyuan.

An comparative study on technology spillovers from FDI and import

World Economy Study, 2011, (12): 51-58, 85-86.

[本文引用: 1]

[ 张建清, 孙元元.

进口贸易和FDI技术溢出的比较研究: 基于技术溢出内生性的实证检验

世界经济研究, 2011, (12): 51-58, 85-86.]

[本文引用: 1]

Zhou Rongjun.

The impact of intellectual property protection and technology spillover of import trade on innovation

Statistics & Decision, 2019, 35(14): 90-94.

[本文引用: 1]

[ 周荣军.

知识产权保护、进口贸易技术溢出对创新的影响

统计与决策, 2019, 35(14): 90-94.]

[本文引用: 1]

Li Bing, Yue Yunsong, Chen Ting.

Export and innovation: Empirical evidence from patent data at firm level

The Journal of World Economy, 2016, 39(12): 72-94.

[本文引用: 1]

[ 李兵, 岳云嵩, 陈婷.

出口与企业自主技术创新: 来自企业专利数据的经验研究

世界经济, 2016, 39(12): 72-94.]

[本文引用: 1]

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