文章检索

生态视域下创业生态系统异质企业间知识转移机理研究

  • 齐廉文 ,
  • 吴洁 ,
  • 庄蕾 ,
  • 陈宇 ,
  • 夏磊 ,
  • 卢冬冬 ,
  • 齐廉文 ,
  • 吴洁 ,
  • 庄蕾 ,
  • 陈宇 ,
  • 夏磊 ,
  • 卢冬冬
展开
  • 1.江苏大学化学化工学院,江苏 镇江 212001;
    2.江苏科技大学经济管理学院,江苏 镇江 212003;
    3.江苏省大数据管理中心,南京 210036
齐廉文(1994-),男,甘肃庆阳人,硕士研究生,助教,主要研究方向为知识管理、思政教育。

收稿日期: 2020-05-17

  修回日期: 2021-04-15

  网络出版日期: 2021-11-30

基金资助

国家自然科学基金(71771161);江苏大学大学生思想政治教育专项课题(JDXGCB202002)

Research on the Mechanism of Knowledge Transfer Between Heterogeneous Enterprises in Entrepreneurial Ecosystem from the Ecological Perspective

  • QI Lianwen ,
  • WU Jie ,
  • ZHUANG Lei ,
  • cHEN Yu ,
  • XIA Lei ,
  • LU Dongdong ,
  • QI Lianwen ,
  • WU Jie ,
  • ZHUANG Lei ,
  • cHEN Yu ,
  • XIA Lei ,
  • LU Dongdong
Expand
  • 1. School of Chemistry and Chemical Engineering, Jiangsu University, Zhenjiang 212001, China;
    2. School of Economics and Management, Jiangsu University of Science and Technology, Zhenjiang 212003, China;
    3. Big Data Management Center of Jiangsu Province, Nanjing 210036, China

Received date: 2020-05-17

  Revised date: 2021-04-15

  Online published: 2021-11-30

摘要

知识转移对企业知识积累和知识创造具有积极促进作用,也是塑造创业生态系统竞争优势的关键路径之一。根据生态学理论将创业生态系统内企业划分为共生型和竞争型两类异质企业,构建异质企业间知识转移模型,通过模型推导得到知识再生数的一般表达式,并对知识转移平衡点的存在性与稳定性进行了验证。结合数值仿真发现:企业间接触频率、知识整合时间、两类企业比例均会影响知识再生数的大小,进而影响知识转移的平衡点,且在知识再生数大于1的情况下,共生型企业占比上升会带来知识再生数的增加,系统内知识转移的活跃性也将得到增强;系统开放程度的增加能够显著促进知识转移。

本文引用格式

齐廉文 , 吴洁 , 庄蕾 , 陈宇 , 夏磊 , 卢冬冬 , 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 . DOI: 10.13306/j.1672-3813.2021.04.009

Abstract

Knowledge transfer has a positive role in promoting the accumulation and creation of enterprise knowledge, and it is also one of the key ways to shape the competitive advantage of the entrepreneurial ecosystem. According to ecological theory, the enterprises in the entrepreneurial ecosystem are divided into two types of heterogeneous enterprises, symbiosis and competition, and a knowledge transfer model between heterogeneous enterprises is constructed. The general expression of the number of knowledge regeneration is derived from the model, and the balance point of knowledge transfer is obtained. The existence and stability of the system have been verified. Combined with numerical simulation, it is found that the frequency of inter-firm contact, the time of knowledge integration, and the proportion of the two types of enterprises will all affect the number of knowledge regeneration, which in turn affects the balance of knowledge transfer, and when the number of knowledge regeneration is greater than 1, the proportion of symbiotic enterprises will increase. As the number of knowledge reproduction increases, the activity of knowledge transfer within the system will also be enhanced; the increase in the degree of openness of the system can significantly promote knowledge transfer.

参考文献

[1]Adner R, Kapoor R.Value creation in innovation ecosystems:how the structure of technological interdependence affects firm performance in new technology generations[J].Strategic Management Journal, 2010, 31(3):306-333.
[2]Almirall E, Casadesus-Masanell R. Open versus closed innovation: a model of discovery and divergence[J]. Academy of Management Review, 2010, 35(1):27-47.
[3]Secundo G, Toma A, Schiuma G, et al.Knowledge transfer in open innovation: a classification framework for healthcare ecosystems[J]. Business Process Management Journal, 2018, 25(1):144-163.
[4]王发明,朱美娟.创新生态系统价值共创行为协调机制研究[J].科研管理,2019,40(5):71-79.
Wang Invention,Zhu Meijuan.Research on the coordination mechanism of value co-creation behavior of innovation ecosystem[J].Scientific Research Management,2019,40(5):71-79.
[5]陈衍泰,夏敏,李欠强,等.创新生态系统研究:定性评价、中国情境与理论方向[J].研究与发展管理,2018,30(4):37-53.
Chen Yantai, Xia Min, Li Qianqiang, et al. Research on innovation ecosystem: qualitative evaluation, Chinese situation and theoretical direction[J].Research and Development Management,2018,30(4):37-53.
[6]郑少芳,唐方成.高科技企业创新生态系统的知识治理机制[J].中国科技论坛,2018,1(8):11-13.
Zheng Shaofang, Tang Fangcheng.The knowledge governance mechanism of the innovation ecosystem of high-tech enterprises[J].China Science and Technology Forum,2018,1(8):11-13.
[7]王峥,龚轶.创新共同体:概念、框架与模式[J].科学学研究,2018,36(1):140-148,175.
Wang Zheng,Gong Yi. Innovation community: concept, framework and model[J].Studies in Science of Science,2018,36(1):140-148,175.
[8] Berg C, Alexander A T. The openness of open innovation in ecosystems-integrating innovation and management literature on knowledge linkages[J]. Journal of Innovation & Knowledge, 2018, 4(4):212-217.
[9]Hamer S. Developing an innovation ecosystem: a framework for accelerating knowledge transfer[J]. Journal of Management & Marketing in Healthcare, 2010, 3(4):248-255.
[10] Amitrano C C, Coppola M, Tregua M, et al. Knowledge sharing in innovation ecosystems: a focus on functional food industry[J]. International Journal of Innovation & Technology Management, 2017, 14(5): 1-18.
[11] Clarysse B, Wright M, Bruneel J, et al. Creating value in ecosystems: crossing the chasm between knowledge and business ecosystems[J]. Research Policy, 2014, 43(7):1164-1176.
[12] 陈菁菁, 张卓, 王文华. 企业创新团队隐性知识转移模式分析及选择——基于知识生态系统的视角[J]. 管理现代化, 2019, 39(1):102-105.
Chen Jingjing, Zhang Zhuo, Wang Wenhua. Analysis and selection of tacit knowledge transfer mode of enterprise innovation team——based on the perspective of knowledge ecosystem[J]. Management Modernization, 2019, 39(1):102-105.
[13] Miller K, Mcadam R, Moffett S, et al. Knowledge transfer in university quadruple helix ecosystems: an absorptive capacity perspective[J]. R&D Management, 2016, 46(2):383-399.
[14] Fransman M. Innovation in the new ICT ecosystem[J]. Social Science Electronic Publishing, 2009,68:89-110.
[15] 彭晓芳,吴洁,盛永祥,等.创新生态系统中多主体知识转移生态关系的建模与实证分析[J].情报理论与实践, 2019(9):111-116.
Peng Xiaofang, Wu Jie, Sheng Yongxiang, et al. Modeling and empirical analysis of the ecological relationship of multi-agent knowledge transfer in the innovation ecosystem[J]. Information Theory and Practice, 2019(9):111-116.
[16] 龙跃,顾新,张莉.开放式创新下组织间知识转移的生态学建模及仿真[J].科技进步与对策,2017,34(2):128-133.
Long Yue,Gu Xin,Zhang Li.Ecological modeling and simulation of knowledge transfer between organizations under open innovation[J].Science and Technology Progress and Policy,2017,34(2):128-133.
[17] 薛娟,丁长青,陈莉莎,等. 基于SIR的众包社区知识转移模型研究[J].科技进步与对策,2016,33(4):132-137.
Xue Juan, Ding Changqing, Chen Lisha, et al. Research on SIR-based crowdsourcing community knowledge transfer model[J].Science and Technology Progress and Policy,2016,33(4):132-137.
[18] 胡绪华,陈丽珍,吕魁.基于传染病模型的创新生态系统内异质企业间知识转移机理分析与仿真[J].运筹与管理,2015(3):248-257.
Hu Xuhua,Chen Lizhen,Lü Kui.Analysis and simulation of knowledge transfer mechanism between heterogeneous enterprises in innovation ecosystem based on infectious disease model[J].Operations Research and Management,2015(3):248-257.
[19] 吴小桔,吴洁,盛永祥,等.企业知识流动SIRS模型构建与仿真[J].统计与决策,2016(13):177-180.
Wu Xiaoju, Wu Jie, Sheng Yongxiang, et al. Construction and simulation of SIRS model for enterprise knowledge flow[J].Statistics and Decision,2016(13):177-180.
[20] Bengtsson M, Kock S. ”Coopetition” in business networks—to cooperate and compete simultaneously[J]. Industrial Marketing Management, 2000, 29(5):411-426.
[21] 丁玲,吴金希.核心企业与商业生态系统的案例研究:互利共生与捕食共生战略[J].管理评论,2017,29(7):244-257.
Ding Ling,Wu Jinxi.Case study of core enterprise and business ecosystem: mutually beneficial symbiosis and predator symbiosis strategy[J].Management Review,2017,29(7):244-257.
[22] 刘应麟. 传染病学[M].北京:人民卫生出版社,1997:26-61.
[23] 郭润萍,蔡莉,王玲.战略知识整合模式与竞争优势:高技术创业企业多案例研究[J].科研管理,2019,40(2):97-105.
Guo Runping, Cai Li, Wang Ling.Strategic knowledge integration model and competitive advantage: a multi-case study of high-tech entrepreneurial enterprises[J].Science Research Management,2019,40(2):97-105.
[24] 马知恩,周义仓.传染病动力学的数学建模与研究[M]. 北京:科学出版社,2004:193-248.
文章导航

/

〈 〉