Please wait a minute...
文章检索
复杂系统与复杂性科学  2022, Vol. 19 Issue (2): 31-38    DOI: 10.13306/j.1672-3813.2022.02.004
  本期目录 | 过刊浏览 | 高级检索 |
网络结构、知识基础与企业创新绩效
李培哲1,2, 菅利荣2
1.山东政法学院商学院,济南 250014;
2.南京航空航天大学经济与管理学院,南京 210016
Network Structure, Knowledge Base and Enterprise Innovation Performance
LI Peizhe1,2, JIAN Lirong2
1. School of Business, Shan Dong University of Political science and Law, Ji'nan 250014, China;
2. College of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China
全文: PDF(1008 KB)  
输出: BibTeX | EndNote (RIS)      
摘要 为探究网络结构、知识基础等对企业创新绩效的影响,基于社会网络的视角构建产学研合作创新网络,并运用负二项回归模型进行实证分析。结果表明:产学研创新网络中心性对企业创新绩效有显著正向影响,网络结构洞与企业创新绩效没有呈现出显著的倒U型关系,知识基础对企业创新绩效具有显著正向影响,知识基础与网络中心性的交互作用对企业创新绩效有显著负向影响,知识基础与结构洞的交互作用对企业创新绩效有正向影响但不显著。
服务
把本文推荐给朋友
加入引用管理器
E-mail Alert
RSS
作者相关文章
李培哲
菅利荣
关键词 产学研合作网络结构创新绩效社会网络分析    
Abstract:In order to explore the impact of network structure and knowledge base on enterprise innovation performance, the cooperative innovation network of industry-university-research institute is constructed from the perspective of social network, and the negative binomial regression model is used for empirical analysis. The results show that the industry-university-research innovation network centrality has a significant positive impact on enterprise innovation performance, network structure hole does not show a significant inverted U-shaped relationship with enterprise innovation performance, knowledge base has a significant positive impact on enterprise innovation performance, and the interaction between knowledge base and network centrality has a significant negative impact on enterprise innovation performance, the interaction between knowledge base and structure hole has a positive effect on enterprise innovation performance, but it is not significant.
Key wordsindustry-university-research cooperation    network structure    innovation performance    social network analysis
收稿日期: 2021-01-30      出版日期: 2022-05-23
ZTFLH:  F270  
基金资助:国家自然科学基金(71573124,71503103);山东省社会科学规划项目(21BGLJO5);山东省人文社会科学项目(19-ZZ-GL-04)
通讯作者: 菅利荣(1968-),女,内蒙古集宁人,博士,教授,主要研究方向为知识管理、管理预测与决策。   
作者简介: 李培哲(1981-),男,山东滨州人,博士研究生,教授,主要研究方向为复杂系统、创新管理。
引用本文:   
李培哲, 菅利荣. 网络结构、知识基础与企业创新绩效[J]. 复杂系统与复杂性科学, 2022, 19(2): 31-38.
LI Peizhe, JIAN Lirong. Network Structure, Knowledge Base and Enterprise Innovation Performance. Complex Systems and Complexity Science, 2022, 19(2): 31-38.
链接本文:  
http://fzkx.qdu.edu.cn/CN/10.13306/j.1672-3813.2022.02.004      或      http://fzkx.qdu.edu.cn/CN/Y2022/V19/I2/31
[1] WANG C, RODAN S, FRUIN M, et al. Knowledge networks, collaboration networks, and exploratory innovation[J]. Academy of Management Journal, 2014,57(2): 484-514.
[2] 杨博旭,王玉荣,李兴光.多维邻近与合作创新[J].科学学研究,2019,37(1):154-164.
YANG B X, WANG Y R, LI X G. The impact of multidimensional proximity on cooperative innovation [J]. Studies in Science of Science, 2019,37(1): 154-164.
[3] ZAHEER A, BELL G G. Benefiting from network position: firm capabilities, structural holes, and performance[J]. Strategic Management Journal, 2005,26(9):809-825.
[4] SCHILLING M A, PHELPS C C. Inter firm collaboration networks: the impact of large-scale network structure on firm innovation[J]. Management Science, 2007,53(7):1113-1126.
[5] OBSTFELD D. Social networks, the tertius iungens orientation, and involvement in innovation[J]. Administrative Science Quarterly, 2005,50(1):100-130.
[6] 李晨蕾,柳卸林,朱丽.国际研发联盟网络结构对企业创新绩效的影响研究——基于社会资本视角[J].科学学与科学技术管理,2017,38(1):52-61.
LI C L, LIU X L, ZHU L. Influence of structural characteristics of international R&D alliance network on company's innovative performance: based on social capital theory[J]. Science of Science and Management of S & T,2017,38(1): 52-61.
[7] 高霞,其格其,高群婷.知识转移效果的结构性指标对企业创新绩效的影响[J].科学学与科学技术管理,2018,39(5):89-100.
GAO X, QI G Q, GAO Q T. The impact of structural indicators of knowledge transfer effect on firm innovation performance [J]. Science of Science and Management of S & T, 2018,39(5): 89-100.
[8] 刘岩,蔡虹.企业知识基础网络结构与技术创新绩效的关系——基于中国电子信息行业的实证分析[J].系统管理学报,2012,21(5):655-661.
LIU Y, CAI H. Structure of knowledge base and a firm's innovative performance: an empirical test in Chinese electrical & electronic industry [J]. Journal of Systems & Management, 2012,21(5): 655-661.
[9] GUAN J, LIU N. Exploitative and exploratory innovations in knowledge network and collaboration network: a patent analysis in the technological field of nano-energy[J]. Research Policy, 2016, 45(1): 97-112.
[10] LI H J, ZHAN B, WANG Z, et al. Dynamical clustering in electronic commerce systems via optimization and leadership expansion[J]. IEEE Transactions on Industrial Informatics, 2019,16(8): 5327-5334.
[11] HUGGINS R, PROKOP D. Network structure and regional innovation: a study of university-industry ties[J].Urban Studies,2017,54(4):931-952.
[12] OWEN-SMITH J, POWELL W W. Knowledge networks as channels and conduits: the effects of spillovers in the Boston biotechnology community[J]. Organization Science, 2004, 15(1): 5-21.
[13] 其格其,高霞,曹洁琼.我国ICT产业产学研合作创新网络结构对企业创新绩效的影响[J].科研管理, 2016,37(S1):110-115.
QI G Q, GAO X, CAO J Q. The impact of industry-university-research collaboration innovation network structure on firm innovation performance in China's ICT industry [J]. Science Research Management, 2016,37(S1): 110-115.
[14] BURT R S. Structural Holes: The Social Structure of Competition[M]. Boston: Harvard University Press, 1992.
[15] LIU C H. The effects of innovation alliance on network structure and density of cluster[J]. Expert Systems with Applications, 2011,38(1):299-305.
[16] CAPALDO A. Network structure and innovation: the lever aging of a dual network as a distinctive relational capability[J]. Strategic Management Journal, 2007,28(6):585-608.
[17] 马源培,杨卓璇,李慧嘉.结合Bass模型和LTV的创新产品扩散预测[J].聊城大学学报(自然科学版),2020,33(4):26-32.
MA Y P, YANG Z X, LI H J. Innovative product diffusion forecasting combined Bass model and LTV [J]. Journal of Liaocheng University(Natural Science Edition), 2020,33(4): 26-32.
[18] FREEMAN L C. Centrality in social networks: conceptual clarification[J]. Social Networks, 1979,1(3): 15-239.
[19] 单晓红,王春稳,刘晓燕,等.基于知识网络的开放式创新社区知识发现研究[J].复杂系统与复杂性科学, 2020,17(1):62-70,94.
SHAN X H, WANG C W, LIU X Y, et al. Research on knowledge discovery of open innovation community based on knowledge network [J]. Complex Systems and Complexity Science, 2020,17(1): 62-70, 94.
[20] 王朋飞,李守伟,林琳霖,等.产学研合作网络复杂性分析——以镇江市为例[J].复杂系统与复杂性科学,2013,10(1):60-67.
WANG P F, LI S W, LIN L L, et al. Complexity analysis of industry-university-institute cooperative network-a case study of Zhenjiang city [J]. Complex Systems and Complexity Science, 2013,10 (1): 60-67.
[21] 温忠麟,侯杰泰,张雷.调节效应与中介效应的比较和应用[J].心理学报,2005,37(2): 268-274.
WEN Z L, HOU J T, ZHANG L. A comparison of moderator andmediator and their applications [J]. Acta Psychologica Sinica, 2005,37(2): 268-274.
[1] 齐廉文, 吴洁, 庄蕾, 陈宇, 夏磊, 卢冬冬. 生态视域下创业生态系统异质企业间知识转移机理研究[J]. 复杂系统与复杂性科学, 2021, 18(4): 74-83.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed