德国汉堡生物医药集群研发和商务知识的网络结构与空间流动

doi:10.13249/j.cnki.sgs.2019.02.017

Abstract

Abstract:

Knowledge spillover driven by industrial clusters has been considered as a key underpinning for boosting regional innovation. This article takes a case study of the biomedical cluster in Hamburg, Germany, examining social networks and spatial flow of both R&D talents and business talents in order to discuss the geographical features and formation mechanisms of knowledge spillover based on different angles and knowledge bases respectively. Empirical results indicate that: 1) Sensitivity to spatial distance of knowledge spillover based on different perspectives are differentiated. In contrast to knowledge network, knowledge flow to a greater extent relies on geographical proximity. 2) Geographical requirements of knowledge spillover of different knowledge bases differ from each other. Scientific knowledge spillovers and business knowledge spillovers are remarkably different at multi-scales with respect to linking intensity and spatial structure. 3) Local Production-Study-Research cooperation system centered on universities, research institutes, industry associations, and leading enterprises, national balanced R&D-intensive urban system of bio-industry, and selective international research collaborations with global leading regions make a joint effort to the formation of scientific knowledge network. Local diversified industrial structure, national polycentric urban system, and widespread international business collaborations with countries based on geographical, social, and institutional proximity collectively shape business knowledge network. Educational streaming, geographically balanced national talent training system, widespread spatial flow of talents across the country, and circular flow of talents in Western Europe and North America jointly form knowledge flows.

Key words: industrial cluster, innovation, knowledge network, knowledge flow, knowledge base, Germany

CLC Number:

K902

Jili Xu, Fan Yang, Desheng Xue. Differentiated Knowledge Bases, Knowledge Networks, and Spatial Flows: Evidence from the Biomedical Cluster in Hamburg, Germany[J].SCIENTIA GEOGRAPHICA SINICA, 2019, 39(2): 325-333.

Figures/Tables 6

Table 1

Fig.1

Fig.2

Fig.3

Fig.4

Table 2

References 37

[1]	Feldman M.The geography of innovation[M]. Boston: Kluwer Academic Publishers, 1994.
[2]	吕拉昌,黄茹,廖倩.创新地理学研究的几个理论问题[J].地理科学,2016,36(5):653-661. doi: 10.13249/j.cnki.sgs.2016.05.002
	[Lyu Lachang, Huang Ru, Liao Qian.Several theoretical issues on innovation geography. Scientia Geographica Sinica, 2016, 36(5): 653-661.] doi: 10.13249/j.cnki.sgs.2016.05.002
[3]	Asheim B.The changing role of learning regions in the globalizing knowledge economy: A theoretical re-examination[J]. Regional Studies, 2012, 46(8): 993-1004. doi: 10.1080/00343404.2011.607805
[4]	Martin R, Sunley P.Conceptualizing cluster evolution: Beyond the life cycle model[J]. Regional Studies, 2011, 45(10): 1239-1318. doi: 10.1080/00343404.2011.622263
[5]	王缉慈. 关于中国产业集群研究的若干概念辨析[J].地理学报,2004,59(S1):47-52. doi: 10.3321/j.issn:0375-5444.2004.z1.007
	[Wang Jici.Some related concepts in China’s research of industrial cluster. Acta Geographica Sinica, 2004, 59(S1): 47-52.] doi: 10.3321/j.issn:0375-5444.2004.z1.007
[6]	Iammarino S, McCann P. The structure and evolution of industrial clusters: Transactions, technology and knowledgths[J]. Research Policy, 2006, 35(7): 1018-1036. doi: 10.1016/j.respol.2006.05.004
[7]	Ibert O.Relational distance:Sociocultural and time-spatial tensions in innovation practices[J]. Environment and Planning A, 2010, 42(1): 187-204. doi: 10.1068/a4247
[8]	Manniche J, Moodysson J, Testa S.Combinatorial knowledge bases: An integrative and dynamic approach to innovation studies[J]. Economic Geography, 2017, 93(5): 480-499. doi: 10.1080/00130095.2016.1205948
[9]	Polanyi M.The tacit dimension[M]. New York: Doubleday, 1966.
[10]	Gertler M, Levitte Y.Local nodes in global networks: The geography of knowledge flows in biotechnology innovation[J]. Industry and Innovation, 2005, 12(4): 487-507. doi: 10.1080/13662710500361981
[11]	Breschi S, Lissoni F.Knowledge spillovers and local innovation systems: A critical survey[J]. Industrial and Corporate Change, 2001, 10(4): 975-1005. doi: 10.1093/icc/10.4.975
[12]	Breschi S, Lissoni F.Mobility of skilled workers and co-invention networks:An anatomy of localized knowledge flows[J]. Journal of Economic Geography, 2009, 9(4): 439-468.
[13]	Capello R, Faggian A.Collective learning and relational capital in local innovation processes[J]. Regional Studies, 2005, 39(1): 75-87. doi: 10.1080/0034340052000320851
[14]	Jacobs W, Koster A, Van Oort F.Co-agglomeration of knowledge-intensive business services and multinational enterprises[J]. Journal of Economic Geography, 2014, 14(2): 443-475. doi: 10.1093/jeg/lbs055
[15]	胡曙红,黄丽,范蓓蕾,等.中国高校创新产出的空间溢出效应与区域经济增长——基于省域数据的空间计量经济分析[J].地理科学,2016,36(12):1767-1776.
	[Hu Shuhong, Huang Li, Fan Beilei et al. Spatial spillover effects of innovative outputs of university and its impacts on regional economic growth of China: Based on spatial econometrics analysis of provincial data. Scientia Geographica Sinica, 2016, 36(12): 1767-1776.]
[16]	Ibert O.Towards a geography of knowledge creation: The ambivalences between ‘knowledge as an object’ and ‘knowing in practice’[J]. Regional Studies, 2007, 41(1): 103-114. doi: 10.1080/00343400601120346
[17]	Amin A, Roberts J.Knowing in action: Beyond communities of practice[J]. Research Policy, 2008, 37(2): 353-369. doi: 10.1016/j.respol.2007.11.003
[18]	Grabher G, Ibert O.Distance as asset? Knowledge collaboration in hybrid virtual communities[J]. Journal of Economic Geography, 2014, 14(1): 97-123. doi: 10.1093/jeg/lbt014
[19]	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[J].地理学报,2006,61(4):425-434. doi: 10.3321/j.issn:0375-5444.2006.04.009
	[Miao Changhong.Global-local nexus and technological learning in industrial clutser: A case study of Hair-goods industry in Xuchang, Henan Province. Acta Geographica Sinica, 2006, 61(4):425-434.] doi: 10.3321/j.issn:0375-5444.2006.04.009
[20]	曾刚,文嫮.上海浦东信息产业集群的建设[J].地理学报, 2004,59(S1):59-66. doi: 10.3321/j.issn:0375-5444.2004.z1.009
	[Zeng Gang, Wen Hu.A study on the IT cluster in Pudong of Shanghai. Acta Geographica Sinica, 2004, 59(S1): 59-66.] doi: 10.3321/j.issn:0375-5444.2004.z1.009
[21]	Sunley P, Pinch S, Reimer S.Design capital: Practice and situated learning in London design agencies[J]. Transactions of the Institute of British Geographers, 2011, 36(3): 377-392. doi: 10.1111/j.1475-5661.2011.00431.x
[22]	汪涛,Hennemann S,Liefner I, 等.知识网络空间结构演化及对NIS建设的启示——以我国生物技术知识为例[J].地理研究,2011,30(10):1861-1872. doi: 10.11821/yj2011100012
	[Wang Tao, Hennemann S, Liefner I et al. Spatial structure evolution of knowledge network and its impact on the NIS: Case study of biotechnology in China. Geographical Research, 2011, 30(10): 1861-1872.] doi: 10.11821/yj2011100012
[23]	Vallance P.Relational and dialectical spaces of knowing: knowledge, practice, and work in economic geography[J]. Environment and Planning A, 2011, 43(5): 1098-1117. doi: 10.1068/a43186
[24]	Faulconbridge J R.Global architects:Learning and innovation through communities and constellations of practice[J]. Environment and Planning A, 2010, 42(12): 2842-2858. doi: 10.1068/a4311
[25]	Maskell P.Accessing remote knowledge-the roles of trade fairs, pipelines, crowdsourcing and listening posts[J]. Journal of Economic Geography, 2014, 14(5SI): 883-902. doi: 10.1093/jeg/lbu002
[26]	Asheim T, Gertler M.Regional innovation systems and the geographical foundations of innovation[M]//J Fagerberg, D Mowery, R Nelson. The Oxford Handbook of Innovation. Oxford:Oxford University Press, 2005.
[27]	Asheim T,Coenen L,Vang J.Face-to-face, buzz, and knowledge bases: Sociospatial implications for learning, innovation, and innovation policy[J]. Environment and Planning C: Government and Policy, 2007, 25(5): 655-670. doi: 10.1068/c0648
[28]	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[J].地理研究,2015,34(3):525-540. doi: 10.11821/dlyj201503011
	[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.] doi: 10.11821/dlyj201503011
[29]	周灿,曾刚,王丰龙,等.中国电子信息产业创新网络与创新绩效研究[J].地理科学,2017,35(5):661-671.
	[Zhou Can, Zeng Gang, Wang Fenglong et al. Innovation network structure and innovation performance: A study of China’s electronic information industry. Scientia Geographica Sinica, 2017, 37(5): 661-671.]
[30]	林兰,曾刚,吕国庆.基于创新“二分法”的中国装备制造业创新网络研究[J].地理科学,2017,37(10):1469-1477.
	[Lin Lan, Zeng Gang, Lyu Guoqing.Innovation network of the Chinese equipment manufacturing industry: Based on the dichotomy of innovation. Scientia Geographica Sinica, 2017, 37(10): 1469-1477.]
[31]	Shearmur R, Doloreux D.Knowledge-intensive business services (KIBS) use and user innovation: High-order services, geographic hierarchies and internet use in Quebec’s manufacturing sector[J]. Regional Studies, 2015, 49(10): 1654-1671. doi: 10.1080/00343404.2013.870988
[32]	Tether B S, Li Q C, Mian A.Knowledge-bases, places, spatial configurations and the performance of knowledge-intensive professional service firms[J]. Journal of Economic Geography, 2012(12): 969-1001. doi: 10.1093/jeg/lbs015
[33]	Bathelt H,Malmberg A,Maskell P.Clusters and knowledge:Local buzz, global pipelines and the process of knowledge creation[J]. Progress in Human Geography, 2004, 28(1): 31-56. doi: 10.1191/0309132504ph469oa
[34]	吕拉昌,梁政骥,黄茹.中国主要城市间的创新联系研究[J].地理科学,2015,35(1):30-37.
	[Lyu Lachang, Liang Zhengji, Huang Ru.The innovation linkage among Chinese major cities. Scientia Geographica Sinica, 2015, 35(1): 30-37.]
[35]	何舜辉,杜德斌,焦美琪,等.中国地级以上城市创新能力的时空格局演变及影响因素分析[J].地理科学,2017,37(7):1014-1022.
	[He Shunhui, Du Debin, Jiao Meiqi et al. Spatial-temporal characteristics of urban innovation capability and impact factors analysis in China. Scientia Geographica Sinica, 2017, 37(7): 1014-1022.]
[36]	Kraetke S.Global Pharmaceutical and biotechnology firms’ linkages in the world city network[J]. Urban Studies, 2014, 51(6): 1196-1213. doi: 10.1177/0042098013494420
[37]	Cooke P.Regional knowledge capabilities, embeddedness of firms and industry organisation: Bioscience megacentres and economic geography[J]. European Planning Studies, 2004, 12(5): 625-641. doi: 10.1080/0965431042000219987

空间尺度	研发知识网络		商务知识网络
空间尺度	联系强度	占比（%）	联系强度	占比（%）
集群内部	157	11.2	67	6.3
集群外部、城市内部	90	6.4	146	13.7
城市尺度（含集群内外部）	247	17.6	213	20.0
国家尺度	475	33.8	439	41.3
全球尺度	676	48.1	411	38.7

空间尺度	研发知识				商务知识
空间尺度	流动强度	占比（%）	节点数量	平均联系强度	流动强度	占比（%）	节点数量	平均联系强度
集群内部	333	20.0	45	7.4	105	15.0	45	2.5
集群外部,城市内部	78	4.7	48	1.6	88	12.5	74	1.2
城市尺度（包含集群内外部）	411	24.7	93	4,4	193	27.5	119	1.6
国家尺度	852	51.3	108	7.9	331	47.2	91	3.6
全球尺度	398	24.0	144	2.8	178	25.3	101	1.8

Differentiated Knowledge Bases, Knowledge Networks, and Spatial Flows: Evidence from the Biomedical Cluster in Hamburg, Germany

RichHTML

PDF (PC)

Like

Knowledge

Abstract

Cite this article

share this article

Figures/Tables 6

References 37

Related Articles 15

Metrics

Comments

Recommended 10

[1]	Shuang Ma,Gang Zeng. Regional Innovation Models of China's Ten Major Urban Agglomerations from the Perspective of Network [J]. SCIENTIA GEOGRAPHICA SINICA, 2019, 39(6): 905-911.
[2]	Shufeng Liu, Debin Du, Xionghe Qin, Chunguang Hou. Spatial-temporal Pattern and Influencing Factors of China's Innovation Efficiency Based on Innovation Value Chain [J]. SCIENTIA GEOGRAPHICA SINICA, 2019, 39(2): 173-182.
[3]	Yukang Sun, Guoping Li, Qiangmin Xi. Technical Opportunity, Industry Heterogeneity and Innovation Agglomeration in Metropolis: Taking the Manufacturing Industry of Beijing as an Example [J]. SCIENTIA GEOGRAPHICA SINICA, 2019, 39(2): 252-258.
[4]	Kunbo Shi,Yongchun Yang,Rui Shao,Enlong Li,Wei Zhang,Tian Yuan. Spatial Pattern of Urban Resident’s C2C Online Consumption in China: Feasibility of Innovation Diffusion Hypothesis and Efficiency Hypothesis [J]. SCIENTIA GEOGRAPHICA SINICA, 2019, 39(1): 107-115.
[5]	Xianzhong Cao, Gang Zeng, Yiwen Zhu. Influencing Factors of Shanghai High-tech Industry Innovation Networking [J]. SCIENTIA GEOGRAPHICA SINICA, 2018, 38(8): 1301-1309.
[6]	Yunda Liu, Lianjun Tong. Dynamic Analysis on the Performance of Industrial Competitiveness of the Three Major German Automotive Manufacturers [J]. SCIENTIA GEOGRAPHICA SINICA, 2018, 38(7): 1061-1068.
[7]	Chuansong Zhao, Jianlan Ren, Yanbin Chen, Kai Liu. Coupling Coordination and Spatio-temporal Differentiation of Scientific and Technological Innovation and Sustainable Development in China [J]. SCIENTIA GEOGRAPHICA SINICA, 2018, 38(2): 214-222.
[8]	Fei Su, Rongrong Ying, Jianyi Huang, Bo Li, Saiying Zhu, Xiaohang Mo. Progress and Implications in Livelihood Security Research [J]. SCIENTIA GEOGRAPHICA SINICA, 2018, 38(12): 2058-2065.
[9]	Dezhong Duan, Debin Du, Ying Chen, Qinghua Zhai. Spatial-temporal Complexity and Growth Mechanism of City Innovation Network in China [J]. SCIENTIA GEOGRAPHICA SINICA, 2018, 38(11): 1759-1768.
[10]	Chengli Tang, Jiamin Wu, Yanhua He, Guohua Zhou, Baowen Ma, Weiyang Chen. Theoretical Thinking on the Interaction of Urban-Agglomeration-Development Zone-Industrial Cluster [J]. SCIENTIA GEOGRAPHICA SINICA, 2018, 38(1): 49-57.
[11]	Shunhui He, Debin Du, Meiqi Jiao, Yu Lin. Spatial-Temporal Characteristics of Urban Innovation Capability and Impact Factors Analysis in China [J]. SCIENTIA GEOGRAPHICA SINICA, 2017, 37(7): 1014-1022.
[12]	Qin Ye, Gang Zeng, Shuting Yang, Hongting Chen. Innovation Network Evolution of Petroleum Equipment Manufacturing Industry in Dongying [J]. SCIENTIA GEOGRAPHICA SINICA, 2017, 37(7): 1023-1031.
[13]	Wenying Fu, Jinling Deng. Locational Choice of Start-ups and Spatial Evolution of Clusters in the Context of Industrial Restructuring [J]. SCIENTIA GEOGRAPHICA SINICA, 2017, 37(6): 833-840.
[14]	Can Zhou, Gang Zeng, Fenglong Wang, Yuefang Si, Zefeng Mi. Innovation Network Structure and Innovative Performance: A Study of China’s Electronic Information Industry [J]. SCIENTIA GEOGRAPHICA SINICA, 2017, 37(5): 661-671.
[15]	Rui Lyu, Peiji Shi, Xiaoying Nie, Xuebin Zhang. The Mechanism on Cluster Development of the Industrial Parks of the Hexi Corridor Based on the Grounded Theory [J]. SCIENTIA GEOGRAPHICA SINICA, 2017, 37(5): 718-727.