知识流动空间的城市关系建构与创新网络模拟

doi:10.11821/dlxb202004004

Abstract

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.

Key words: flow space, innovative space, knowledge flow, intercity interactions, relationship construction, network simulation method

MA Haitao. The theoretical construction and network simulation of intercity innovative relationships in knowledge flow space[J].Acta Geographica Sinica, 2020, 75(4): 708-721.

Figures/Tables 11

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References 57

[1]	Xu Xueqiang, Zhou Yixing, Ning Yuemin. Urban Geography Beijing: Higher Education Press, 1997.
	[ 许学强, 周一星, 宁越敏 . 城市地理学. 北京: 高等教育出版社, 1997.]
[2]	Harris C D, Ullman E L . The nature of cities. The Annals of the American Academy of Political and Social Science, 1945,242(1):7-17. doi: 10.1177/000271624524200103
[3]	Smith D A, Timerlake M . Conceptualising and mapping the structure of the world system's city system. Urban Studies, 1995,32(2):287-302.
[4]	Friedmann J. Where We Stand: A Decade of World City Research. New York: Cambridge University Press, 1995: 21-47.
[5]	Taylor P J . World Cities Network: A Global Urban Analysis. London: Routledge, 2004.
[6]	Zhou Y X, Yang Q . Changes in the urban hierarchy in China and the territorial types by province. Chinese Sociology and Anthropology, 1987,19(3):137-159. doi: 10.2753/CSA0009-4625190304137
[7]	Bourne L S. Urban Systems: Strategies for Regulation. Oxford: Oxford University Press, 1975.
[8]	Castells M . The Information City. Oxford: Basil Blackwell, 1989.
[9]	Neal Z . Refining the air traffic approach to city networks. Urban Studies, 2010,47(10):2195-2215. doi: 10.1016/j.injury.2016.07.029 pmid: 27496724
[10]	Esparza A X, Krmenec A J . Large city interaction in the US urban system. Urban Studies, 2000,37(4):691-709.
[11]	Camagni R, Capello R . The city network paradigm: Theory and empirical evidence. Contributions to Economic Analysis, 2004,26(6):495-529.
[12]	Derudder B, Witlox F . An appraisal of the use of airline data in assessing the world city network: A research note on data. Urban Studies, 2005,42(13):2371-2388. doi: 10.1080/00420980500379503
[13]	Choi J H, Barnett G A, Chon B S . Comparing world city networks: A network analysis of internet backbone and air transport intercity linkages. Global Networks, 2006,6(1):81-99. doi: 10.1111/glob.2006.6.issue-1
[14]	Wu L F, Wang D, Evans J A . Large teams develop and small teams disrupt science and technology. Nature, 2019,566:378-382. doi: 10.1038/s41586-019-0941-9 pmid: 30760923
[15]	Li Y C, Phelps N . Megalopolis unbound: Knowledge collaboration and functional polycentricity within and beyond the Yangtze River Delta Region in China, 2014. Urban Studies, 2018,55(2):443-460. doi: 10.1177/0042098016656971
[16]	Wang Xingping, Feng Miao, Gu Hui . A study of discriminative characteristics of intercity innovation linkage at different scales: A case study of Yangtze River Delta. Journal of Southeast University (Philosophy and Social Science), 2015,17(6):108-116.
	[ 王兴平, 冯淼, 顾惠 . 城际创新联系的尺度差异特征分析: 以长三角核心区为例. 东南大学学报(哲学社会科学版), 2015,17(6):108-116.]
[17]	Hoekman J, Frenken K, Oort F V . The geography of collaborative knowledge production in Europe. Annals of Regional Science, 2009,43(3):721-738. doi: 10.1007/s00168-008-0252-9
[18]	Li Dandan, Wang Tao, Wei Yehua , et al. Spatial and temporal complexity of scientific knowledge network and technological knowledge network on China's urban scale. Geographical Research, 2015,34(3):525-540.
	[ 李丹丹, 汪涛, 魏也华 , 等. 中国城市尺度科学知识网络与技术知识网络结构的时空复杂性. 地理研究, 2015,34(3):525-540.]
[19]	Ma H T, Fang C L, Pang B , et al. The effect of geographical proximity on scientific cooperation among Chinese cities from1990 to 2010. Plos One, 2014,9(11):1-11. doi: 10.1371/journal.pone.0111705 pmid: 25365449
[20]	Li Y C, Phelps N . Knowledge polycentricity and the evolving Yangtze River Delta megalopolis. Regional Studies, 2017,51(7):1035-1047. doi: 10.1080/00343404.2016.1240868
[21]	Ma H T, Fang C L, Lin S N , et al. Hierarchy, clusters, and spatial differences in Chinese intercity networks constructed by scientific collaborators. Journal of Geographical Sciences, 2018,28(12):1793-1809. doi: 10.1007/s11442-018-1579-5
[22]	Ma Haitao, Huang Xiaodong, Li Yingcheng . The evolution and mechanisms of megalopolitan knowledge polycentricity of Guangdong-Hong Kong-Macao Greater Bay Area. Acta Geographica Sinica, 2018,73(12):2297-2314. doi: 10.11821/dlxb201812003
	[ 马海涛, 黄晓东, 李迎成 . 粤港澳大湾区城市群知识多中心的演化过程与机理. 地理学报, 2018,73(12):2297-2314.] doi: 10.11821/dlxb201812003
[23]	Proff S V, Brenner T . The dynamics of interregional collaboration: An analysis of co-patenting. Annals of Regional Science, 2011,52(1):41-64.
[24]	Niu Xin, Chen Xiangdong . The cooperation innovation across city boundary and radiation distance based on the cross city cooperation patent application data. Scientia Geographica Sinica, 2013,33(6):659-667.
	[ 牛欣, 陈向东 . 城市创新跨边界合作与辐射距离探析: 基于城市间合作申请专利数据的研究. 地理科学, 2013,33(6):659-667.]
[25]	Ma H T, Fang C L, Pang B . Structure of Chinese city network as driven by technological knowledge flows. Chinese Geographical Science, 2015,25(4):498-510. doi: 10.1007/s11769-014-0731-0
[26]	Duan Dezhong, Du Debin, Chen Ying , et al. Technology transfer in China's city system: Process, pattern and influencing factors. Acta Geographica Sinica, 2018,73(4):738-754. doi: 10.11821/dlxb201804011
	[ 段德忠, 杜德斌, 谌颖 , 等. 中国城市创新技术转移格局与影响因素. 地理学报, 2018,73(4):738-754.] doi: 10.11821/dlxb201804011
[27]	Lyu Lachang, Liang Zhengji, Huang Ru . The innovation linkage among Chinese major cities. Scientia Geographica Sinica, 2015,35(1):30-37.
	[ 吕拉昌, 梁政骥, 黄茹 . 中国主要城市间的创新联系研究. 地理科学, 2015,35(1):30-37. ]
[28]	Ma Haitao . Triangle model of Chinese returnees: A tentative method for city networks based on talent flows. Geographical Research, 2017,36(1):161-170.
	[ 马海涛 . 基于人才流动的城市网络关系构建. 地理研究, 2017,36(1):161-170.]
[29]	Duan Dezhong, Du Debin, Gui Qinchang , et al. The geography of Chinese entrepreneurial development. Human Geography, 2018,33(4):102-112.
	[ 段德忠, 杜德斌, 桂钦昌 , 等. 中国企业家成长路径的地理学研究. 人文地理, 2018,33(4):102-112.]
[30]	Lyu Lachang, Li Yong . A research on Chinese renovation urban system based on urban renovation function. Acta Geographica Sinica, 2010,65(2):177-190.
	[ 吕拉昌, 李勇 . 基于城市创新职能的中国创新城市空间体系. 地理学报, 2010,65(2):177-190.]
[31]	Camagni R P, Salone C . Network urban structures in northern Italy: Elements for a theoretical framework. Urban Studies, 1993,30(6):1053-1064.
[32]	Malecki E J . Hard and soft networks for urban competitiveness. Urban Studies, 2002,39(5):929-945.
[33]	Ma Haitao . Research progress and prospects of city networks based on knowledge flow in China. Economic Geography, 2016,36(11):207-213.
	[ 马海涛 . 基于知识流动的中国城市网络研究进展与展望. 经济地理, 2016,36(11):207-213.]
[34]	Amin A, Thrift N , et al. Globalization, Institution, and Regional Development in Europe. New York: Oxford University Press, 1994: 1-22.
[35]	Florida R . Toward the learning region. Futures, 1995,27(5):527-536. doi: 10.1016/0016-3287(95)00021-N
[36]	Asheim B . Industrial Districts as 'learning regions': A condition for prosperity. European Planning Studies, 1995,4(4):379-400.
[37]	Storper M . The Regional World: Territorial Development in a Global Economy. New York: Guilford Press, 1997: 3-25.
[38]	Cooke P . Regional innovation systems, clusters, and the knowledge economy. Industrial and Corporate Change, 2001,10(4):945-974. doi: 10.1038/s41586-019-1545-0 pmid: 31619795
[39]	Scott A J . The cultural economy: Geography and the creative field. Media Culture & Society, 1999,21(6):807-817.
[40]	Miao C H, Wei D Y H, Ma H T . Technological learning and innovation in China in the context of globalization. Eurasian Geography & Economics, 2007,48(6):713-732.
[41]	Castells M, Hall P G . Technopoles of the World: The Making of Twenty-First-Century Industrial Complexes. London: Routledge, 1994.
[42]	Bathelt H, Malmberg A, Maskell P . Clusters and knowledge: Local buzz, global pipelines and the process of knowledge creation. Progress in Human Geography, 2004,28(1):31-56. doi: 10.1191/0309132504ph469oa
[43]	Ma Haitao, Fang Chuanglin, Wu Kang . Links and drive: Key nodes impel the evolution of national innovation networks. China Soft Science, 2012(2):88-95.
	[ 马海涛, 方创琳, 吴康 . 链接与动力: 核心节点助推国家创新网络演进. 中国软科学, 2012(2):88-95.]
[44]	Matthiessen C W, Schwarz A W, Find S . World cities of scientific knowledge: Systems, networks and potential dynamics. An analysis based on bibliometric indicators. Urban Studies, 2010,47(9):1879-1897. doi: 10.1177/0042098010372683
[45]	Liu Chengliang, Gui Qinchang, Duan Dezhong , et al. Structural heterogeneity and proximity mechanism of global scientific collaboration network based on co-authored papers. Acta Geographica Sinica, 2017,72(4):737-752. doi: 10.11821/dlxb201704014
	[ 刘承良, 桂钦昌, 段德忠 , 等. 全球科研论文合作网络的结构异质性及其邻近性机理. 地理学报, 2017,72(4):737-752.] doi: 10.11821/dlxb201704014
[46]	Williams A M . Lost in translation? International migration, learning and knowledge. Progress in Human Geography, 2006,30(5):588-607. doi: 10.1177/0309132506070169
[47]	Menzel M P . Dynamic proximities-changing relations by creating and bridging distances. Papers in Evolutionary Economic Geography, 2008(8):1-26.
[48]	Yeung Wai-chung . Global production networks and regional development in East and Southeast Asia. Tropical Geography, 2017,37(5):628. doi: 10.13284/j.cnki.rddl.002992
	[ 杨伟聪 . 全球生产网络、价值捕捉轨迹与区域发展. 热带地理, 2017,37(5):628.] doi: 10.13284/j.cnki.rddl.002992
[49]	Miao Changhong . Global-local nexus and technological learning in industrial cluster: A case study of hair-goods industry in Xuchang, Henan Province. Acta Geographica Sinica, 2006,61(4):425-434. doi: 10.11821/xb200604009
	[ 苗长虹 . 全球—地方联结与产业集群的技术学习: 以河南许昌发制品产业为例. 地理学报, 2006,61(4):425-434.] doi: 10.11821/xb200604009
[50]	Dicken P, Thrift N . The organization of production and the production of organization: Why business enterprises matter in the study of geographical industrialization. Transactions of the Institute of British Geographers, 1992,17(3):279-291.
[51]	Zhang Huixuan, Li Qing, Li Guicai . Spatial structure change and optimization strategies of innovation linkage among the cities in Guangdong Province. Progress in Geography, 2016,35(8):952-962.
	[ 张惠璇, 刘青, 李贵才 . 广东省城市创新联系的空间格局演变及优化策略. 地理科学进展, 2016,35(8):952-962.]
[52]	Wang Fenglong, Zeng Gang, Ye Qin , et al. Analysis of city network based on innovation cooperation: Case study of Yangtze River Economic Belt. Resources and Environment in the Yangtze Basin, 2017,26(6):797-805.
	[ 王丰龙, 曾刚, 叶琴 , 等. 基于创新合作联系的城市网络格局分析: 以长江经济带为例. 长江流域资源与环境, 2017,26(6):797-805.]
[53]	Zhou Can, Zeng Gang, Cao Xianzhong . Chinese intercity innovation networks structure and city innovation capability. Geographical Research, 2017,36(7):1297-1308.
	[ 周灿, 曾刚, 曹贤忠 . 中国城市创新网络结构与创新能力研究. 地理研究, 2017,36(7):1297-1308.]
[54]	Fang Chuanglin, Liu Yi, Lin Yueran , et al. Report on the Development of Innovative Cities in China. Beijing: Science Press, 2013.
	[ 方创琳, 刘毅, 林跃然 , 等. 中国创新型城市发展报告. 北京: 科学出版社, 2013.]
[55]	Beaverstock J V . Rethinking skilled international labour migration: World cities and banking organizations. Geoforum, 1994,25(3):323-338. doi: 10.1016/0016-7185(94)90034-5 pmid: 12320415
[56]	Alderson A S, Beckfield S . Power and position in the world city system. American Journal of Sociology, 2004,109(4):811-851.
[57]	Taylor P J, Walker D R F . Measurement of the world city network. Urban Studies, 2002,39(39):2367-2376.

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

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)

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

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

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