地理与认知邻近对高技术产业集群创新影响——以我国软件产业集群为典型案例

doi:10.11821/yj2011090005

地理研究 ›› 2011, Vol. 30 ›› Issue (9): 1592-1605.doi: 10.11821/yj2011090005

地理与认知邻近对高技术产业集群创新影响——以我国软件产业集群为典型案例

李琳, 韩宝龙

湖南大学经济与贸易学院,长沙 410079

收稿日期:2011-03-02 修回日期:2011-06-01 出版日期:2011-09-20 发布日期:2011-09-20
作者简介:李琳(1965-)女,湖南涟源人,教授,博士,主要从事产业集群与区域创新研究。 E-mail: lilin963@vip.sina.com 韩宝龙(1986-)男,河南信阳人,硕士生,专业方向为区域经济与产业集群。 E-mail: baronhan@foxmail.com
基金资助:
教育部人文社会科学规划课题(08JA790038);湖南省社科基金课题(2010YBA049)

An empirical research on how geographic proximity and cognitive proximity work on the innovation performance of high-tech industrial cluster

LI Lin, HAN Bao-long

College of Economics and Trade, Hunan University, Changsha 410079, China

Received:2011-03-02 Revised:2011-06-01 Online:2011-09-20 Published:2011-09-20

摘要/Abstract

摘要： 多维邻近性是近些年国际学术界在区域创新及产业集群方向新的研究视角。本文首先从多维邻近视角出发探讨了地理邻近、认知邻近对高技术产业集群创新的影响机制,并据此提出4个待验假设;进而以我国国家级软件产业园产业集群为典型案例进行实证分析,并创造性地使用人工神经网络为前导的OLS回归分析方法对待验假设进行双重递进检验。实证结果显示:在高技术产业集群的发展和成熟阶段,地理邻近对集群创新绩效产生负的影响,但负影响递减;认知邻近对集群创新绩效产生正影响;集群外部知识的获取有利于集群创新绩效提升;集群直接创新投入也促进创新绩效的提高,但边际报酬递减。

关键词: 高技术产业集群, 地理邻近, 认知邻近, 创新绩效, 人工神经网络

Abstract: With the rise of knowledge-based economy, high-tech industry clusters and their ability to innovate become the key reason for regional development. According to the tacit knowledge and knowledge spillover theory proposed, more and more academia begin to pay attention to the new view of Dimensions of Proximity in order to explore the essential factors to the innovation of high-tech industry cluster. From the view of Dimensions of Proximity, this article analyzes how those proximities usually work on the innovation of high-tech industrial cluster, and serve a theoretical mechanism for this process. After a discussion on the mechanism between high-tech industry cluster innovation and proximities, this article proposes four hypotheses of the relationships between the geographical proximity, cognitive proximity and cluster innovation, and each of these relations is transformed into mathematical formula expression. Based on the data of national software industrial parks of China in recent five years, two methods are used in the empirical tests: artificial neural network and ordinary least squares (OLS). According to the comparison among theoretical mechanism and two empirical analysis results, this paper finally draws four conclusions as follows. Firstly, during the development period and mature period of high-tech industrial cluster development, geographic proximity has a positive influence on innovation performance of high-tech industrial cluster, but the marginal effects for this are decreasing with the development of cluster. Secondly, cognitive proximity has an active influence on cluster innovation. Moreover, the learning on external knowledge can promote the increase of innovation very much. Fourthly, the direct investment on research and development can enforce the capacity of innovation, but the marginal return for this is decreasing.

Key words: high-tech industrial cluster, geographic proximity, cognitive proximity, innovation performance, artificial neural network

李琳, 韩宝龙. 地理与认知邻近对高技术产业集群创新影响——以我国软件产业集群为典型案例[J]. 地理研究, 2011, 30(9): 1592-1605.

LI Lin, HAN Bao-long. An empirical research on how geographic proximity and cognitive proximity work on the innovation performance of high-tech industrial cluster[J]. GEOGRAPHICAL RESEARCH, 2011, 30(9): 1592-1605.

参考文献

[1] Torre A,Gilly J P.On the analytical dimension of proximity dynamics.Regional Studies,2000,34:169~180.

[2] Torre A, Rallet A.Proximity and location. Regional Studies,2005,39:47~59.

[3] Torre A.Cluster and temporary geographical proximity.IKINET Working Paper,2007.

[4] Torre A.On the role played by temporary geographical proximity in knowledge transmission.Regional Studies,2008,42:869~889.

[5] Boschma R.Proximity and innovation::A critical assessment.Regional Studies,2005,39:61~74.

[6] 王缉慈.产业集群和工业园区发展中的企业邻近与集聚辨析.中国软科学,2005,(12):91~98.

[7] 王孝斌,李福刚.地理邻近在区域创新中的作用机理及其启示.经济地理,2007,14(4):543~546.

[8] 汪涛,曾刚.地理邻近与上海浦东高技术企业创新活动研究.世界地理研究,2008,17(1):47~53.

[9] 李琳,韩宝龙.组织合作中的多维邻近性:西方文献评述与思考.社会科学家,2009,(7):108~112.

[10] Ponds R,Frank V O.The geographical and institutional proximity of scientific collaboration networks.Regional Studies,2007,3:79~91.

[11] Marja H,Mika K.Dimensions of proximity in relationships between knowledge intensive business service firms and their clients:Theoretical considerations with empirical observations from a study in Helsinki Region,Finland.Regional Studies Association International Conference on Regional Growth Agendas, 2005.

[12] 魏欣仪.厂商跨界学习能力——"邻近性"观点回顾与研究途径的建议.世界地理研究,2005,27(12):1~8.

[13] Lee C Y.Do firms in clusters invest in R&D more intensively？Theory and evidence from multi-country data.Research Policy,2009,38:1159~1171.

[14] Romans R,Nicolas J V.Schelling’s spatial proximity model of segregation revisited.Journal of Public Economics,2007,91:1~24.

[15] Callois J M.The two sides of proximity in industrial clusters:The trade-off between process and product innovation.Journal of Urban Economics,2008,63:146~162.

[16] Ajay A,Devesh K,Mchale J.How do spatial and social proximity influence knowledge flows？Evidence from patent data. Journal of Urban Economics,2008,64:258~269.

[17] Andrew J,Paul S.Proximity and power within investment relationships:The case of UK private equity industry.Geoforum,2009,40:809~819.

[18] Takeda Y,Kajikawa Y,Sakata I,Matsushima K.An analysis of geographical agglomeration and modularized industrial networks in a regional cluster:A case study at Yamagata prefecture in Japan.Technovation,2008,28:531~539.

[19] Tura T,Harmaakorpi V.Social capital in building regional innovative capability.Regional Studies,2005,39:1111~1125.

[20] 万陆.外部知识源下的集群创新能力培育路径.科技进步与对策,2009,26(2):169~173.

[21] 刘华容,曹休宁.产业集群中集群企业的合作创新问题研究.科技进步与对策, 2009,26(3):98~100.

[22] 范太胜.基于产业集群创新网络的协同创新机制研究.中国科技论坛,2008,(7):26~30.

[23] 苗长虹,魏也华.分工深化、知识创造与产业集群成长——河南鄢陵县花木产业的案例研究.地理研究,2009,28(4):853~865.

地理与认知邻近对高技术产业集群创新影响——以我国软件产业集群为典型案例

An empirical research on how geographic proximity and cognitive proximity work on the innovation performance of high-tech industrial cluster

PDF (PC)

赞

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 8

Metrics

本文评价

推荐阅读 0

[1]	欧定华,夏建国. 城市近郊区景观格局变化特征,潜力与模拟----以成都市龙泉驿区为例[J]. 地理研究, 2016, 35(3): 534-550.
[2]	葛淼, 薛然尹, 何进伟, 胡燕宇. 中国男性儿童呼气高峰流量参考值地理分布[J]. 地理研究, 2014, 33(3): 451-466.
[3]	李琳, 熊雪梅. 产业集群生命周期视角下的地理邻近对集群创新的动态影响——基于对我国汽车产业集群的实证[J]. 地理研究, 2012, 31(11): 2017-2030.
[4]	李裕瑞, 刘彦随, 龙花楼. 黄淮海地区乡村发展格局与类型[J]. 地理研究, 2011, 30(9): 1637-1647.
[5]	王铮, 吴健平, 邓悦, 王凌云, 熊云波. 城市土地利用演变信息的数据挖掘——以上海市为例[J]. 地理研究, 2002, 21(6): 675-681.
[6]	刘继生, 陈彦光. 基于GIS的细胞自动机模型与人地关系的复杂性探讨[J]. 地理研究, 2002, 21(2): 155-162.
[7]	王为, 吴正. 应用人工神经网络识别华南沿海全新世海滩岩和海岸沙丘岩[J]. 地理研究, 1999, 18(4): 382-390.
[8]	李双成, 高伟明, 刘濂. 河北省环渤海地区生态经济协调发展的人工神经网络分析[J]. 地理研究, 1998, 17(4): 352-359.