创新网络中基于结派行为的企业创新能力评价

科研管理 ›› 2014, Vol. 35 ›› Issue (7): 35-43.

创新网络中基于结派行为的企业创新能力评价

赵炎, 孟庆时

上海大学管理学院, 上海大学创新与知识管理研究中心, 上海 200444

修回日期:2013-12-10 出版日期:2014-07-25 发布日期:2014-07-15
作者简介:赵炎（1976-），男，（汉），重庆人，上海大学管理学院副教授，上海大学创新与知识管理研究中心主任，研究方向：创新与创业管理，创新网络，企业联盟。
孟庆时（1989-），男，（汉），山东东明人，上海大学管理学院硕士研究生，研究方向：创新网络。
基金资助:
国家自然科学基金：集群与联盟：复杂创新网络中企业嵌入与动态抉择的中国实证（基金编号：71003069；起止时间：2011.1-2013.12）；上海市教育委员会科研创新项目：知识密集型服务业的集群创新系统的复杂性：基于中国的实证研究（项目编号：10YZ23，起止时间：2010.1-2012.12）。

Evaluation of enterprise innovative capability based on cohesive behaviors in inter-firm innovation network

Zhao Yan, Meng Qingshi

School of Management, Shanghai University, Research Center for Innovation and Knowledge Management, Shanghai University, Shanghai 200444, China

Revised:2013-12-10 Online:2014-07-25 Published:2014-07-15

摘要/Abstract

摘要： 对于创新网络的研究多从网络整体或企业个体网络的角度出发，较少关注企业结派行为所形成的网络子群结构对企业创新能力的影响。本文基于中国11个高科技行业的联盟数据，使用派系过滤算法和负二项回归模型研究了创新网络中企业结派行为对高科技企业创新能力的影响。研究发现：对于不同规模的网络子群，子群内部联系密度和子群间的联系数量对企业创新能力影响不同，规模小或者结构较简单的子群内企业比子群外的企业创新能力更高，并且具有跨子群联系的企业创新能力较高；规模较大的子群间的联系反而不能提高企业创新能力；同时，网络中的子群数量越多，即企业结派行为越频繁，对网络中企业创新能力的促进作用越大。本研究考虑到了企业子群结构以及子群间的重叠特性，有助于揭示创新网络中企业结派行为的特点，增强对创新网络结构的了解，并为评价和提高我国高科技产业的企业创新能力提供借鉴。

关键词: 高科技行业, 创新网络, 结派行为, 创新能力评价

Abstract: Studies on innovation network mainly focus on the whole network or the firms' individual network, there are few studies on the influence of network subgroups formed by the cohesive behaviors on enterprise innovation capability. The inter-firm innovation networks of 11 high-tech industries in China are built based on alliances data and clique percolation algorithm and negative binomial regression model are applied to study the impact of the enterprise's cohesive behaviors on the innovation capacity of high-tech enterprises. It is found that for firms in small or simple subgroups, internal link density of subgroups and the number of the links between subgroups affect the enterprise's innovative capability positively. But for firms in big or complex subgroups, these characteristics of subgroups have no promoting effect to firms. Meanwhile, the number of subgroups, indicating the frequency of firms' cohesive behaviors, affects the enterprise's innovative capability positively. By taking the subgroup structures at middle level of innovation network into consideration, the results are helpful to uncover the characters of cohesive behaviors in innovation network, enhance the comprehension of innovation network structures and provide references for evaluating and improving enterprise innovative capability of high-tech industries in China.

Key words: high-tech industry, innovation network, cohesive behavior, evaluation of innovative capability

中图分类号:

F273.1

赵炎, 孟庆时. 创新网络中基于结派行为的企业创新能力评价[J]. 科研管理, 2014, 35(7): 35-43.

Zhao Yan, Meng Qingshi. Evaluation of enterprise innovative capability based on cohesive behaviors in inter-firm innovation network[J]. Science Research Management, 2014, 35(7): 35-43.

参考文献

[1] 陈劲,郑刚.创新管理[M].北京大学出版社,2009. [2] 党兴华,郑登攀.对《创新网络17年研究文献述评》的进一步述评——技术创新网络的定义,形成与分类[J].研究与发展管理,2011(6):9-15. [3] 孙耀吾,卫英平.高技术企业联盟知识扩散研究——基于小世界网络的视角[J].管理科学学报,2011,14(12):17-26. [4] 陈红川.高新技术产业技术创新能力评价实证研究[J].科技管理研究,2010(16):20-22. [5] 赵文彦,曾月明.创新型企业创新能力评价指标体系的构建与设计[J].科技管理研究,2011,31(1):14-17. [6] 曹萍,陈福集.基于ANP理论的企业技术创新能力评价模型[J].科学学与科学技术管理,2010(2):67-71. [7] 吕一博,苏敬勤."创新过程"视角的中小企业创新能力结构化评价研究[J].科学学与科学技术管理,2011,32(8):58-64. [8] Tvan der Valk T,Chappin M M H,Gijsbers G W.Evaluating innovation networks in emerging technologies[J].Technological Forecasting and Social Change,2011,78(1):25-39. [9] Duysters G,Lemmens C.Alliance group formation enabling and constraining effects of embeddedness and social capital in strategic technology alliance networks[J].International Studies of Management and Organization,2003,33(2):49-68 [10] Bell G G.Clusters,networks,and firm innovativeness[J].Strategic management journal,2005,26(3):287-295. [11] Lee C,Reid F,McDaid A,et al.Detecting highly overlapping community structure by greedy clique expansion[J].arXiv preprint arXiv:1002.1827,2010. [12] Palla G,Barabási A L,Vicsek T.Quantifying social group evolution[J].Nature,2007,446(7136):664-667. [13] Evans T S.Clique graphs and overlapping communities[J].Journal of Statistical Mechanics:Theory and Experiment,2010,2010(12):P12037. [14] Lovejoy W S,Sinha A.Efficient structures for innovative social networks[J].Management science,2010,56(7):1127-1145. [15] Duysters G M,Lemmens C,Letterie W,et al.The innovative performance of alliance block members:evidence from the microelectronics industry .United Nations University,Maastricht Economic and social Research and training centre on Innovation and Technology,2008. [16] Rowley T J,Baum J A C,Shipilov A V,et al.Competing in groups[J].Managerial and Decision Economics,2004,25(6-7):453-471. [17] 谭建,喻小军.基于派系过滤算法的企业集群模块化应用研究[J].科技进步与对策,2008,25(12):122-124. [18] 欧瑞秋,杨建梅,常静.企业——产品二分网络的社团结构分析[J].管理学报,2010,7(9). [19] Lerch F,Sydow J,Provan K G.Cliques within clusters—Multi-dimensional network integration and innovation activities . Annual colloquium of the European Group for Organizational Studies,Bergen,Norway.2006. [20] Yang J,Leskovec J.Community-affiliation graph model for overlapping network community detection . Data Mining (ICDM),2012 IEEE 12th International Conference on.IEEE,2012:1170-1175. [21] 刘凯,魏钧.组织派系中的"小世界"对知识扩散的影响研究评述[J].中国管理信息化,2009,12(15). [22] Knoke D,Yang S.Social network analysis[M].Sage,2008. [23] Tang L,Liu H.Graph mining applications to social network analysis[M]. Managing and Mining Graph Data.Springer US,2010:487-513. [24] Balasundaram B,Butenko S,Hicks I V.Clique relaxations in social network analysis:The maximum k-plex problem[J].Operations Research,2011,59(1):133-142. [25] Kumpula J M,Kivel M,Kaski K,et al.Sequential algorithm for fast clique percolation[J].Physical Review E,2008,78(2):026109. [26] Palla G,Derényi I,Farkas I,et al.Uncovering the overlapping community structure of complex networks in nature and society[J].Nature,2005,435(7043):814-818. [27] Ahuja G,Soda G,Zaheer A.The genesis and dynamics of organizational networks[J].Organization Science,2012,23(2):434-448. [28] Bendersky C,McGinn K L.Perspective—Open to Negotiation:Phenomenological Assumptions and Knowledge Dissemination[J].Organization Science,2010,21(3):781-797. [29] Hawe P,Webster C,Shiell A.A glossary of terms for navigating the field of social network analysis[J].Journal of Epidemiology and Community Health,2004,58(12):971-975. [30] Reagans R,McEvily B.Network structure and knowledge transfer:The effects of cohesion and range[J].Administrative science quarterly,2003,48(2):240-267. [31] Gomes-Casseres B.Competitive advantage in alliance constellations[J].Strategic organization,2003,1(3):327-335. [32] Gomes-Casseres B.Constellation strategy:Managing alliance groups[J].Ivey Business Journal,2003:1-6. [33] Singh J,Hansen M T,Podolny J M.The world is not small for everyone:Inequity in searching for knowledge in organizations[J].Management Science,2010,56(9):1415-1438. [34] Fang C,Lee J,Schilling M A.Balancing exploration and exploitation through structural design:The isolation of subgroups and organizational learning[J].Organization Science,2010,21(3):625-642. [35] Doreian P,Conti N.Social context,spatial structure and social network structure[J].Social networks,2012,34(1):32-46. [36] Lazzarini S G.The impact of membership in competing alliance constellations:Evidence on the operational performance of global airlines[J].Strategic Management Journal,2007,28(4):345-367. [37] Phelps C C.A longitudinal study of the influence of alliance network structure and composition on firm exploratory innovation[J].Academy of Management Journal,2010,53(4):890-913. [38] 赵剑波,杨震宁,王以华.政府的引导作用对于集群中企业创新绩效的影响:基于国内科技园区数据的实证研究[J].科研管理,2012,33(2). [39] Vanhaverbeke W,Gilsing V,Beerkens B,et al.The Role ofAlliance Network Redundancy in the Creation of Core and Non-core Technologies[J].Journal of Management Studies,2009,46(2):215-244.