知识流动空间的城市关系建构与创新网络模拟

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The theoretical construction and network simulation of intercity innovative relationships in knowledge flow space

MA HaitaoKey Laboratory of Regional Sustainable Development Modeling, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China

收稿日期:2018-12-17修回日期:2019-12-3网络出版日期:2020-04-25

基金资助:

国家自然科学基金项目.41971209
国家自然科学基金项目.41590842
国家自然科学基金项目.41571151
国家自然科学基金项目.41201128

Received:2018-12-17Revised:2019-12-3Online:2020-04-25

Fund supported:

National Natural Science Foundation of China.41971209
National Natural Science Foundation of China.41590842
National Natural Science Foundation of China.41571151
National Natural Science Foundation of China.41201128

作者简介 About authors
马海涛(1979-),男,山东滕州人,博士,副研究员,硕士生导师,中国地理学会会员(S110008167M),主要从事城市网络与创新研究E-mail:maht@igsnrr.ac.cn。

摘要
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。
关键词： 流动空间;创新空间;知识流;城市间相互作用;关系建构;网络模拟方法

Abstract

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.

Keywords：flow space;innovative space;knowledge flow;intercity interactions;relationship construction;network simulation method

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本文引用格式
马海涛. 知识流动空间的城市关系建构与创新网络模拟. 地理学报[J], 2020, 75(4): 708-721 doi:10.11821/dlxb202004004
MA Haitao. The theoretical construction and network simulation of intercity innovative relationships in knowledge flow space. Acta Geographica Sinice[J], 2020, 75(4): 708-721 doi:10.11821/dlxb202004004

1 引言

城市间相互作用关系是城市地理研究的传统内容^[1],其关系内涵随着时代的发展而发展,关注热点也随之变化。Harris等在1945年提出“城市本质”是“城市的内部组织关系”^[2]。然而,任何一个城市都不可能是孤立存在的,为了保障城市的正常运行,城市之间总是在不断地进行着物质、能量、人员和信息的交换^[3]。城市是作为多种要素流动的中心存在于全球、国家或区域的经济系统之中的,是整个经济系统的重要节点^[4]。因此,将城市看作空间中的点,研究一系列城市间的相互作用和联系状况（即所谓的城市系统思维）,应是城市地理研究的另一个重要方面。城市之间的关系问题被Taylor称之为“城市的第二本质”^[5]。早期,城市间相互作用关系研究主要集中在城市体系研究上^[6],城市职能结构、等级规模结构和空间网络结构是城市体系研究的三大支柱。受中心地理论的影响,一个国家的城市体系往往被解读为是由处于中心的大城市所主导的、呈现出一种阶梯状的层级结构^[7]。随着通讯和信息技术的突破,经济全球化和区域经济一体化程度不断提高,流动空间（Space of Flows）逐渐取代地方空间（Space of Places）成为主导性空间组织形式^[8],城市的网络地位相比规模地位更为重要^[9],城市之间的水平联系（城市间的合作和互补关系）受到研究者广泛关注^[10];城市网络成为了一种能够更好地解释城市空间组织结构的新范式^[11]。当前影响最广泛的是全球化与世界城市研究组（Globalization and World Cities Study Group and Network, GaWC）的研究,他们运用高级生产性服务企业的机构分布数据构建世界城市网络,探讨了世界城市之间的现代服务关系。也有****运用城市间的铁路流、航空流、港口流、互联网和电讯流等数据开展城市间交通信息联系研究^[12,13]。21世纪已经进入了知识经济时代,创新发展成为时代主题,世界各国都在积极推动创新发展和创新研究,城市间的知识流动与科技分工合作愈来愈强,城市之间的创新联系正在成为重塑区域关系的重要动力,探讨城市间的知识流动与协同创新关系成为了新的社会需求与研究话题^[14,15]。

城市间创新联系是创新活动的重要表现形式,是指城市之间基于创新要素的交换、创新活动的协同等而产生的联系^[16]。现有对城市间知识流动关系与创新网络的研究,主要有以下3个方面：① 关系建构方面：多数研究利用城市间科技合作成果数量来模拟城市间的创新关系^[17,18],常以科技论文库和专利数据库为数据源,挖掘城市间的合作发表论文数量^{[19,20,21,22]}、合作申请专利数量^[23,24,25]和专利转移转让数量^[26],建立城市间创新联系矩阵,构建城市创新网络;也有****借助引力模型间接测度城市间创新关系水平^[27],还有****尝试运用人才流动^[28,29]等新的数据构建城市间创新关系。② 结构分析方面：运用多种网络分析方法,对所构建的城市创新网络进行结构分析,研究城市创新网络的空间结构、组成结构、等级结构、组群结构和控制结构^[21,22],揭示城市在创新网络中的地位作用、城市之间的创新合作关系、以及不同类型知识在城市间流动的差异化特征^[18],从城市的角度理解区域创新网络的结构特征。③ 影响机制方面：分析城市的个体属性对城市转出和接收知识能力的影响程度,探讨空间的、技术的和社会的距离对城市间发生创新联系的作用机制;相关研究发现地理空间隔离和技术认知距离都会对城市间创新合作产生影响^[24];也有研究认为是技术需求与供给决定了城市间技术转移能力^[26]。

总体来看,探讨知识经济时代下的城市关系研究已经成为热点话题,研究数量大大增加,研究内容多样化,但是仍有一些问题缺乏深入考虑。① 理论层面,为什么可以用创新行动者跨城市的科技合作行为构建城市间的创新关系?目前研究较多的是区域创新网络,然而区域创新网络与城市创新网络存在关键不同。区域创新研究的主体是科技人才、科研单位和创新企业等创新行动者,这些行动者虽有地点属性并根植于城市,但它们只是城市的构成部分,并不能将行动者之间的关系归结为城市间的关系。如果城市间创新网络研究自然地把相同城市的个体当作这个城市,缺乏代表性和精确度的论证,会不可避免的对实证结果产生影响。吕拉昌等提出了城市创新职能概念,认为知识经济时代的城市应具备为城市之外的区域和城市提供创新产品和服务的能力^[30],但如何将创新职能转化成城市间创新关系尚缺乏讨论。② 方法层面,怎样用创新行动者跨城市的科技合作行为构建城市间的创新关系?城市间的创新关系本是城市间客观存在的关系,在知识经济时代不断增强,但是这种关系并不像交通联系、人口流动、投资关系等可以直接测度,而是一种隐含在各种直接、非直接联系中的相对抽象的关系。目前已经有多种方法,但缺少梳理和探讨这些方法之间的关系和适用性问题,甚至出现了简单粗暴的模仿套用,研究结果展示很漂亮,但缺少可信度。③ 数据层面,选择什么样的数据来模拟什么样的城市间创新网络?知识的范畴非常广泛,创新的概念也非常丰富,虽然本文所指是与科学技术紧密相关的知识与创新,但在实际研究中却是很难给予精确界定,这种情况下就需要明确数据所能代表的创新领域和内涵,以提高研究结果的科学性,避免以偏概全。

综上,本文旨在探讨构建城市间创新关系的理论和方法问题,思考建立城市间知识流动/创新关系的理论基础,设计知识流动空间中城市关系网络的构建方法,并选择几种数据进行案例模拟与分析,以期为城市间知识流动网络研究提供新思路,为城市间协同创新发展提供理论支撑。

2 城市间创新关系的理论建构

为什么可以用创新行动者跨城市的科技合作行为构建城市间的创新关系?这是开展城市间创新网络研究应首先思考的问题。一方面要明确城市间创新网络属于主观构建出来的“软网络”,需要考虑如何将主观构建更加趋近客观实际;另一方面要理清创新主体与创新城市的嵌套关系,这是理解运用创新主体跨城市联系构建城市网络的关键。

2.1 论本底：本质上是“软网络”

城市网络是通过城市间的人流、物流、资金流、信息流和知识流等多种形式的“流”实现的。Castells的流空间理论为理解城市网络提供了理论基础,他认为流空间由3个层次构成：网络的物质基础（如航空网络和因特网基础结构）,构成网络节点的地点,和以工作、运动等方式在空间上组织起来的全球精英^[8]。城市网络中的城市节点就属于流空间的中间层次;城市间各种形式的“流”就是建立在城市间“硬网络”（如公路、铁路、机场、电讯等基础设施）基础上的“软网络”（可区分为经济的、政治的、社会的和文化的等多种联系功能,表现为人、物质和信息多种联系形式）,分属流空间的第一和第三层次^{[3, 5, 31-32]}。“硬网络”的基础数据相对容易获得,但它却仅仅提供了一种对网络的描述而不是解释^[12];“软网络”虽比较抽象,而且缺乏反映城市间关系的数据,但这一网络无疑具有很强的实际意义^[5]。城市间创新网络就属于“软网络”的一种^[33],并没有任何客观的数据可以直接反映城市间创新关系,现有的研究都是主观建构出来的网络,这些研究都试图能够反映客观存在的城市间创新关系,但都与客观现实存在偏差。如何认知偏差,如何缩小偏差,如何从主观构建的城市关系结果中更加精准地解读城市间客观的真实的创新关系,是应首先思考的理论问题。

2.2 论内因：关系的尺度转换

城市间的创新关系建立是一种关系建构的过程,最终要运用具体的、可统计、可量化的数据来实现,不能脱离诸如科技企业、科研院所和大学等创新主体的创新行为及其创新成果;但是运用城市的创新主体来构建城市间的创新关系,属于从点—点关系（包括创新机构和人才）向城—城关系的尺度转换,是用个体层面的微观关系反映城市层面的宏观关系,转换过程容易发生夸大（用某类创新主体反映整个城市,以偏概全）或偏离（用一种创新行为的关系数据解释另一种创新行为的关系）的问题。

理解这一过程需要厘清3个方面的关系,才能减少上述问题对结果的客观性和有效性带来的可能影响。① 创新主体与所在城市的关系。地方创新环境和创新氛围的理论讨论同样适用于城市创新,关系资产（Relational Assets）、制度厚度（Institutional Thickness）、创新氛围（Innovative Milieus）、学习型区域（Learning Regions）、学习场（Learning Field）、创意场（Creative Fields）等概念都从不同视角探讨了创新行动者之间及其与地方（包含城市）的关系^{[34,35,36,37,38,39,40]}。每个城市在发展过程中都在积累积淀知识,并会形成自身特色的知识本垒和创新氛围,这其中创新主体发挥着至关重要的作用。创新主体主要有科技企业、科研院所和大学等,这些创新主体同所在城市的创新制度、创新文化、科技设施和创新空间存在多重交互关系,最终使创新主体拥有了“城市名片”,具有了城市属性。② 创新主体与其他城市创新主体的关系。Castells等认为创新过程的关键在于不同区域（城市）、不同类型创新主体所建立的创新链^[41]。Bathlet等提出了“地方传言—全球通道”模型,认为要想获得有价值的新异知识（Nonredundant Knowledge）来促进地方学习创新,除了充分利用地方传言（Local Buzz）获得默许知识（Tacit Knowledge）之外,还应借助全球通道（Global Pipelines）获取新异知识^[42]。同样,对城市而言,创新主体在创新过程中并不是孤立的、封闭的,在进行综合集成创新的过程中往往需要同具有异质性知识的城市创新主体开展合作。③ 城市之间的知识流动与创新关系。依据城市在创新链条中的分工,创新型城市可以划分成基础研究型、技术应用型、产业创新型和综合创新型城市^[43];探讨这些城市的关系是城市地理学的重点,目的是为了发现知识经济时代背景下城市间围绕知识创新所形成的新的关系（图1）。

图1

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图1城市内及城市间知识流动与创新联系示意图

Fig. 1A schematic diagram to illustrate knowledge flows and innovation links inside, and between cities

从3个方面的关系看,用创新主体的城市间关系来构建城市间的创新关系是可行的,因为创新主体与所在城市之间存在密切关系,一定程度上可以代表城市;但是,需要注意的是创新主体的跨城关系并不等于城市之间的创新关系。转换的关键点在于选择什么样的创新主体来反映城市间什么方面的创新关系。

2.3 论关系：4种关系的建构

基于上述分析,选择科研成果的异城合作、科技成果的转让转移、高端人才的跨城移动和创新企业的多城分布4种方式分别阐述城市间创新关系的构建。

（1）科技成果的异城合作与城市关系建构。知识有隐性和显性之分,隐性和显性知识相互作用、相互转换即是知识的创造过程^[44]。显性知识与隐性知识无法真正区分,往往相伴而生,而且隐性知识难以测度,常以显性知识为载体探讨知识联系。合著论文和专利是测量显性知识合作最常用的指标。合著科研论文是科研合作最直接的体现形式,随着期刊数据库的完善和文献计量方法的发展,运用合著论文数据开展科学知识流的研究越来越多^[45];专利数据库提供的大量合作专利信息也被用来测度技术知识流。由于论文和专利信息中含有作者的单位及地址信息,可以通过这些地址信息将个人层面的知识合作整合到城市层面,通过大量合著论文和专利数据可以模拟出城市间科学技术合作网络,开展城市间创新关系的研究。科技成果的合作不能体现知识流方向,一般用于研究无向网络。运用城市间合作论文或专利构建城市关系时,要注意结果解释的准确性,合作论文仅能反映科学知识联系,合作专利仅能反映技术知识联系。

（2）科技成果的转让转移与城市关系建构。专利转让是指专利权人将其发明专利的所有权或持有权转给受让方,包括专利申请权的转让和专利权的转让。专利权的转移是技术交易最直接的体现形式,因而成为研究技术知识流动、扩散和转移的主要途径之一^[26]。专利的跨城市转移受到转出城市属性、接收城市属性和城市关系属性的影响,转出城市的技术发明能力和技术扩散动力,接收城市的技术转化能力和技术吸收动力,城市间的地理距离、技术接近、制度隔阂和产业关联等,都影响专利的城市间转移。因此专利的跨城市转移能够体现城市间知识流方向,可以用来研究有向网络。

（3）高端人才的跨城移动与城市关系建构。关系和演化经济地理学的相关研究对人才迁移促进城市间知识/创新联系奠定了理论基础。关系经济地理的相关研究阐述了人才及其移动性与知识创新的关系,强调将“基于个人的关系建构”纳入网络分析^{[28, 46]}。演化经济地理的相关研究提出了“动态接近”思想及“行动者空间移动带来的空间动力”这一全新的视角,用来解释网络的形成,认为高技术人才的流动是城市间协同创新网络形成的重要动因^[47]。人才是创新的核心要素,是城市创新的第一资源,但是用什么样的人才能更为准确的反映城市间的创新关系?相关研究发现高端人才能够为所居城市（生活、学习或工作过较长一段时间的城市）建立起重要的知识联系,并用中国“****”人才和重要企业家的城市间迁移来构建城市间创新关系网络^[28,29]。用人才移动构建城市间创新关系相比论文和专利更能反映隐性知识的联系,而高端人才又能反映隐性知识中的高端部分,对模拟城市间的高端知识流动和创新联系有重要价值。

（4）创新企业的多城分布与城市关系建构。创新企业对外设立分支机构意味着部分企业职能在本地城市的脱嵌,及在外部城市的再嵌入^[48]。创新企业分支机构的嵌入一方面为城市注入了创新活力,另一方面也深深受到城市制度文化的影响。分支机构本身承载着总部企业的资本流、技术流和信息流,其地方嵌入可为当地城市的产业升级、技术创新带来机遇。例如跨国公司的地方嵌入,所产生的源自总部城市的技术扩散和溢出效应,为中国一些城市实现从“低端发展道路”向“高端发展道路”的跨越提供了重要驱动力^[49]。创新企业在多城布局分支机构是一种关系嵌入过程^[50],企业在来源城市的组织文化和实践惯例通过分设机构扩散到新的城市,分支机构也会将所在城市收集到的技术信息反馈给总部城市。选择一定数量的具有较强创新实力的大型企业,可以建立起由创新企业主导的城市间创新关系网络。

3 城市间创新网络的模拟方法

城市间创新网络的模拟方法主要有两类,一种是借用牛顿万有引力定律,通过构建空间相互作用模型^[51]和修正的引力模型^[27]等方法测度城市间的创新关系,但这种方法属于间接模拟,对城市间创新联系的解释力并不高^[52]。另一种是运用城市间知识流动的载体,测度城市间创新的直接联系程度,更能反映城市间创新关系的内涵。本文系统梳理了城市间创新网络的直接模拟方法,除了常用的论文专利等科技成果的模拟方法之外,还给出了用高端人才跨城移动和创新企业机构多城分布模拟城市间创新网络的方法设计、数据选择和模拟案例。

3.1 科技成果异城合作的城市间无向网络构建方法

3.1.1 方法设计用两个或多个城市共同发表的论文数量和共同申请的专利数量来表征两个城市之间的创新联系程度。通常有两种计数方式来计算两个城市间的合作次数：① 全部计数法,认为所有作者构成了一个研究小组,所有作者之间会充分交流和协作,计数时只要在一个成果的单位中出现了这一对城市,就表示这两个城市有1次合作^[19];② 部分计数法,认为第一作者与其他作者间的交流更为重要,而不能将所有作者的联系同等看待,计数时只计算第一作者和其他作者之间合作对,非第一作者之间的合作不统计^[53]。两种方式都无法体现知识的流向,只能用做无向网络的模拟。有研究认为这两种计数方式的研究结果很接近^[16],因此多数研究选择全部计数法,公式为：

（1）

T_{i} = \overset{n}{\sum_{j}} T_{ij} (i \neq j)

式中：T_i为城市i在城市网络中的中心度（常做百值化处理）;T_ij代表城市i与城市j之间的联系量,用两个城市的合作论文或专利数量表达。

3.1.2 数据选择数据来自国际和国内期刊论文库。可以从国际期刊数据库（如Web of Science（WOS）核心合集数据库）获取全球尺度的城市间合作论文数据,从国内期刊数据库（如中国知网和万方数据知识服务平台等）获取中国城市间合作论文数据。目前数据库的建设已经非常完善,几乎历史上的所有发表论文都被电子化入库;但是数据库类型很多,需要根据研究需要选择适宜的数据库,在结果分析和结论提炼过程中需要结合所选数据库进行论述,并指出运用这一数据库可能存在的问题,避免得出以偏概全的结论。

3.1.3 模拟案例本文分别选择WOS期刊库、万方期刊库和两个期刊库之和,测度中国100个主要创新型城市间^①(^①选择方创琳等著《中国创新型城市发展报告》^[54]中城市创新能力评价排名前100位的城市。)2014—2016年的论文合作关系（图2~图4）,可以看出3幅图的网络结构类似,但结果却有差别。不管是国内期刊还是国际期刊,北京、上海、南京和广州都在论文合作网络中排名前四,而香港和杭州在国际期刊合作中的地位较高,西安和济南在国内期刊合作中的地位较高（表1）。这种差别产生的原因是选择期刊库不同造成的,后续网络分析需要重视这种差别可能带来的影响。

图2

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图2基于WOS数据库的2014—2016年中国城市间论文合作网络模拟

Fig. 2A Chinese intercity network based on WOS co-publications between 2014 and 2016

图3

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图3基于万方数据库的2014—2016年中国城市间论文合作网络模拟

Fig. 3A Chinese intercity network based on ChinaInfo co-publications between 2014 and 2016

图4

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图4基于WOS和万方数据库的2014—2016年中国城市间论文合作网络模拟

Fig. 4A Chinese intercity network based on WOS and ChinaInfo co-publications between 2014 and 2016

Tab. 1
表1
表1基于不同数据库的中国城市间论文合作网络的城市中心度排名(2014—2016年平均值)
Tab. 1City centrality rank within the Chinese intercity network based on co-publications from different databases between 2014 and 2016

名次	WOS数据库		万方数据库		WOS和万方数据库
名次	城市名	中心度	城市名	中心度	城市名	中心度
1	北京	100	北京	100	北京	100
2	上海	47	上海	42	上海	44
3	南京	40	南京	35	南京	37
4	广州	34	广州	27	广州	30
5	武汉	26	西安	25	武汉	25
6	香港	25	济南	22	杭州	20
7	杭州	22	深圳	18	成都	19
8	成都	20	武汉	18	深圳	18
9	深圳	19	成都	17	天津	15
10	天津	16	长沙	16	西安	14

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3.2 科技成果转移转让的城市间有向网络构建方法

3.2.1 方法设计全球约90%~95%的R&D产出包含在专利中。专利作为知识产权的主要体现形式,是创新研究广泛使用的数据。可以用城市间专利转移数量来表征城市间技术流动或扩散程度^[26],属于有向网络的一种。城市分为源地城市和汇地城市两类,每个城市既可是源地城市,也可是汇地城市;城市间的技术关系也包括转出和接收两种形式。每个城市也有两种技术转移规模：技术转出量和技术接收量,公式为：

（2）

P_{i} = \overset{n}{\sum_{j}} P_{ij} (i \neq j)

式中：P_i为城市i在城市网络中的中心度（分为技术转出度或技术转入度）;P_ij代表城市间的连通度（包括城市i向城市j的专利转出量和城市j向城市i的专利转入量）,用专利转移数量表达。

3.2.2 数据选择专利文献库是世界上最大的技术信息源,具有公开性和及时性的优点,成为研究技术知识生产和创新活动的重要数据源^[55]。目前多个国家都建设有技术转移公共服务平台,能整合世界各国的专利技术并可快速更新,这些技术平台为研究提供了充足的数据支撑。可以利用国家知识产权局专利检索及分析数据库,通过挖掘专利的位置信息,来模拟城市间技术转移网络。

3.2.3 模拟案例运用国家知识产权局专利文献库挖掘的城市间专利转让数据,模拟中国100个主要城市间2016年的专利转移网络图（图5）,对比前6位核心城市的中心度和出、入度,发现虽然北京是全国技术转移网络的首位中心城市,但深圳却在技术转出度的排名中名列第一,广州在技术转入度的排名中名列第一（表2）,反映出粤港澳大湾区的技术流动活跃度非常高。

图5

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图52016年中国城市间专利转移网络模拟

Fig. 5A Chinese intercity network based on patent transfers between cities in 2016

Tab. 2
表2
表22016年中国城市间专利转移网络的城市出入度特征
Tab. 2Measures of in-degree, out-degree, and centrality for the Chinese intercity patent transfer network in 2016

城市	技术转出度	技术转入度	网络中心度(百值化)
北京	2684	2506	5190(100)
深圳	2973	1794	4767(92)
广州	1695	2671	4366(84)
上海	1791	1624	3415(66)
重庆	481	956	1437(28)
武汉	357	370	727(14)

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3.3 高端人才跨城移动的城市间创新网络建构方法

3.3.1 方法设计高端人才往往具有很大的移动性,常会给一个城市带来外部新异知识。相关研究表明高端移动性人才有能力将所履历的城市联系在一起^[56]。选择一定数量的能对城市间创新合作产生重要影响的高端移动性人才,通过对人才进行履历分析,将每位人才所经历的城市（一般居住超过2年）视作一个关系社团,假设每个城市间都存在一条由这个人才所建立的关系,大量高端人才所建立的城市关系累积起来就可以形成城市间知识流动和创新关系网络^[24]。公式为：

（3）

C_{i} = \overset{n}{\sum_{j}} C_{ij} (i \neq j)

（4）

C_{ij} = \sum R_{ij} (i \neq j)

式中：C_i为城市i在城市网络中的中心度;C_ij为城市i和城市j之间的创新连通度;R_ij代表由一个高端人才为城市i与城市j建立的一条创新关系。

3.3.2 数据选择高端人才库的选择是有效模拟城市对外创新联系网络的关键。首先要求所选人才的确有能力建立起履历城市间的创新联系;其次需要对高端人才所经历的城市进行筛选,仅保留理论上能建立关系的城市;第三人才数量要达到一定规模,在保证人才选择合适的情况下,数量越多效果越好。2008年中央开始实施海外高层次人才引进计划简称“****”,有重点地支持一批能够突破关键技术、发展高新产业、带动新兴学科的战略科学家和领军人才。截至2018年底,“****”已分14批共引进7680余名高层次人才。“****”库是模拟中国高端跨国人才构建中国城市对外知识联系和创新合作关系的优质数据。

3.3.3 模拟案例运用“****”库4464名人才的有效履历信息,模拟中国城市与国外城市之间的知识流动和创新网络（图6）,计算中国城市与国外城市间的联系度,发现北京和上海无疑是中国参与全球创新网络的枢纽城市,美国的波士顿、纽约、华盛顿和洛杉矶等城市是与中国联系最紧密的城市（表3）。该网络图是中国高端人才构建起来的世界城市网络,可以一定程度上反映中国城市参与全球创新网络的状况。

图6

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图6基于国家“****”人才移动的城市间创新网络模拟

Fig. 6An intercity innovation network based on Chinese national 'Thousand Talent Programme' talent flow

Tab. 3
表3
表3基于“****”人才移动的城市创新网络中的最强城市对(前20名)
Tab. 3The top 20 strongest ties within intercity innovation networks based on Chinese national 'Thousand Talent Programme' talent flow

名次	城市对	名次	城市对	名次	城市对	名次	城市对
1	北京—波士顿	6	上海—纽约	11	北京—伯克利	16	北京—圣地亚哥
2	北京—纽约	7	北京—圣何塞	12	上海—洛杉矶	17	北京—奥斯汀
3	上海—波士顿	8	上海—华盛顿	13	北京—旧金山	18	南京—波士顿
4	北京—华盛顿	9	北京—新加坡	14	北京—东京	19	上海—新加坡
5	北京—洛杉矶	10	北京—芝加哥	15	北京—普林斯顿	20	武汉—波士顿

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3.4 创新企业机构多城分布的城市间创新网络建构方法

3.4.1 方法设计位于不同城市的创新企业总部与分支机构之间的知识传播与反馈,推动了城市间知识流动与创新联系。企业总部与分支机构之间传递的知识既有显性知识,也有隐性知识。显性知识表现在企业总部将制定的创新战略、技术章程和设计说明等编码知识下发给分支机构,分支机构将所属技术业务以书面形式反馈给总部。除此之外,企业内部还会通过公司员工之间的非正式的交流,传播公司的技术知识和创新文化,属于隐性知识传播。基于此考虑,设计了两种网络构建方法。

（1）借鉴世界城市网络的跨国公司总部—分支构建方法^[57],构建创新企业机构多城分布的城市间创新网络,反映以显性知识为主的城市间联系,公式为：

（5）

B C_{ij} = \sum B_{ij} (i \neq j)

式中：BC_ij为城市i和城市j的创新关联度,表示所有创新企业机构建立的城市i和城市j之间的创新关系总和;B_ij代表创新企业总部所在城市i同分支机构所在城市j建立的一条知识联系或创新关系。

（2）借鉴GaWC的互锁网络模型^[57],构建创新企业机构多城分布所建立的、反映包含显性和隐性知识联系的城市间创新网络。模型首先建立由n家创新企业和m个城市排列所得的n×m的矩阵V,矩阵中的元素V_ij被定义为创新价值,反映企业j在城市i的重要程度。由此可以得到基于创新企业j所引发的城市a和城市b之间的创新关联度：

（6）

r_{abj} = V_{aj} \times V_{bj}

那么由所有创新企业所形成的城市a和城市b之间创新关联度为：

（7）

r_{ab} = \sum^{} r_{abj}

3.4.2 数据选择创新企业库的选择是有效模拟城市间创新网络的基础。为了确保所选创新企业的数量和质量,综合考虑了多家权威机构对中国创新型企业的认定,包括中国科技部、国资委、总工会在2006—2012年间评选出来的5批676家“创新型企业试点”,工信部、财政部在2011—2017年评选出来的7批495家“国家技术创新示范企业”,中国人民大学所评选出来的“中国企业创新能力1000强”,国际著名科学服务商Clarivate Analytic评选出来的2016年和2017年“中国大陆创新企业百强”,国际咨询机构Strategy评选出来“2017 Global Innovation 1000”（全球创新1000强）中的113家中国大陆企业;最后共确定了1796家国内（不含港澳台）最具创新实力的企业。以此为基础,通过查询企业官网、企业年报、企业信息服务平台和大数据挖掘手段,获取企业总部和分支机构的地址信息。

3.4.3 模拟案例使用1796家创新企业数据,分别运用互锁网络模型和总部—分支方法模拟了中国城市间的创新网络,可以看出用互锁网络模型构建的城市创新网络因为涵盖了隐性知识的流动,相比总部—分支方法所构建的城市创新网络（主要反映显性知识）更加稠密;图7显示出以北京为核心的放射状网络,图8则显示出了菱形结构,城市中心度总体上增加明显。

图7

新窗口打开|下载原图ZIP|生成PPT
图7基于公司总部—分支方法模拟的中国城市间创新网络

Fig. 7A Chinese intercity innovation network constructed using the headquarters-subsidiaries method

图8

新窗口打开|下载原图ZIP|生成PPT
图8基于互锁网络模型模拟的中国城市间创新网络

Fig. 8A Chinese intercity innovation network constructed using the interlocking network model

4 结论与讨论

21世纪进入知识经济时代,创新发展成为时代主题,如何揭示创新的空间格局、模拟创新的空间组织,成为区域可持续发展分析与模拟研究的重要内容。本文讨论了从城市地理学城市间相互作用关系的视角构建城市间创新关系的思路,梳理了4种网络模拟方法,为知识经济时代的城市关系构建和城市间创新联系研究奠定了基础。结论如下：

（1）城市间创新网络区别于城市间交通基础设施联系的“硬网络”,属于“软网络”的一种,区别于城市间人口流和资金流等能够容易客观测度和表征的网络,本质上是一种城市关系的主观建构。由于并没有能够直接反映城市间创新关系的统计数据,城市间创新关系的建构往往借助城市间创新主体之间的联系,比如科研机构、大学、创新企业和人才的跨城市联系,来反映创新主体所在城市间的创新关系;这一过程存在尺度的转换,需要在选择创新主体和确定样本数量上进行充分论证,必须确保创新主体与所在城市存在很好的嵌入和被嵌入关系,确保创新主体的创新联系数量达到一定规模足以反映城市间的创新关系,并要对模拟和分析的结果给予精确度和局限性的说明,以便使主观建构的城市关系结果能更加趋近客观存在的城市关系。

（2）梳理了4种城市间创新关系网络的模拟方法,分别反映了不同方面的城市间创新关系。其中,科技成果异城合作的城市创新网络构建方法,可反映城市间科技协同发展的关系;专利成果转让转移的城市创新网络构建方法,可反映城市间技术转移的关系;高端人才跨城迁移的城市创新网络建构方法,可反映城市间高端的创新合作关系;创新企业机构多城分布的城市创新网络建构方法,可反映城市间的产业协同创新关系。这些关系既属于创新关系的不同方面,又存在紧密关联,共同揭示城市间创新关系特征。这些方法相比借助重力模型模拟的城市间创新关系更为客观,可为探讨全球、国家和区域的创新空间格局与组织研究提供新的思路。

然而,知识的范畴不易明确,创新的内涵太过宽泛,创新空间研究并非易事。虽然本研究强调城市间创新关系的理论建构,并梳理了4种城市间创新网络的模拟方法,但仍有很多问题待进一步研究。首先,创新联系复杂多样,而且随着新技术新手段的应用,城市间的创新联系方式不断更新,创新网络的构建方法有待于持续跟踪研究。其次,需要加强更加精细化的城市间创新网络研究,探讨不同学科、不同行业、不同类型的城市间创新网络,以更好地服务创新政策的制定。

致谢:

感谢河南大学与中国科学院地理科学与资源研究所联合培养硕士生张芳芳和黄晓东在数据整理和制图中给予的帮助。

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