Characteristics Analysis of FPGA Industry Chain and Knowledge Transfer Network
XIAO Yao1, LI Shouwei2, WANG Yihan2
1. Nanjing University of Information Science and Technology,School of Management Science and Engineering, Nanjing 210044,China; 2. School of Business, Shandong Normal University, Ji′nan 250300, China
Abstract：To clarify the positioning of the industrial chain of FPGA (Field programmable gate array) during the localization process, and to optimize the knowledge transfer network, the article proposes has the analytical models in the industrial chains, and the creation of the knowledge transfer network using complex network analysis method and the analysis of network structural features. The results have demonstrated that China occupies a low share in the industrial chains and its development is also unbalanced. The knowledge transfer network mainly focuses on the core enterprises characterized by small world and following power-law distribution. Core nodes exert a significant impact on the industrial evolution. Based on the perspective of network optimization, this paper puts forward policy suggestions such as establishing a modern knowledge transfer network development system and forming a new international competitive advantage covering the whole industrial chain.
肖瑶, 李守伟, 王怡涵. FPGA芯片产业链及知识转移网络特征分析[J]. 复杂系统与复杂性科学, 2022, 19(3): 20-26.
XIAO Yao, LI Shouwei, WANG Yihan. Characteristics Analysis of FPGA Industry Chain and Knowledge Transfer Network[J]. Complex Systems and Complexity Science, 2022, 19(3): 20-26.
[1] 钱晓东,杨贝. 基于复杂网络模型的供应链企业合作演化研究[J].复杂系统与复杂性科学, 2018, 15(3): 1-10. QIAN X D, YANG B. Supply chain enterprise cooperation evolution based on complex network model[J]. Complex Systems and Complexity Science, 2018, 15(3): 1-10. [2] 阮平南,栾梦雪,魏云凤,等. 创新网络组织间知识转移影响因素元分析[J]. 科技进步与对策, 2019, 36(18): 7-14. RUAN P N, LUAN M X, WEI Y F, et al. The influencing factors of knowledge transfer in innovation network: a meta-analysis[J]. Science & Technology Progress and Policy, 2019, 36(18): 7-14. [3] 张梦晓,高良谋. 驱动与阻碍: 网络位置影响知识转移的系统动力学研究[J]. 科技进步与对策, 2019, 36(22): 135-142. ZHANG M X, GAO L M. Drivers and hindrances: system dynamics study of network position affecting knowledge transfer[J]. Science & Technology Progress and Policy,2019,36(22):135-142. [4] 向希尧,裴云龙. 基于情境的多维接近性与知识流动[J]. 管理学报, 2017, 14(4): 554-560. XIANG X Y, PEI Y L. Multi-dimensional proximity and knowledge flows: a context-based theoretical frame[J]. Chinese Journal of Management, 2017, 14(4): 554-560. [5] GRANT R M. Toward a knowledge-based theory of the firm[J]. Strategic Management Journal, 1996, 17(S2): 109-122. [6] SPENDER J C, GRANT R M. Knowledge and the firm: overview[J]. Strategic Management Journal, 1996, 17(S2): 5-9. [7] LIEBOWITZ J. Knowledge Retention: Strategies and Solutions[M]. Boca Raton: Auerbach Publications, 2008. [8] TEECE D J, PISANO G, SHUEN A. Dynamic capabilities and strategic management[J]. Strategic Management Journal, 1997, 18(7):509-533. [9] 王婷,杨建君.组织控制协同使用、知识转移与新产品创造力——被调节的中介研究[J].科学学与科学技术管理, 2018, 39(3): 34-49. WANG T, YANG J J. The combined use of organizational cintrols, knowledge transfer, new product creativity: a research of moderated mediator effects[J]. Science of Science and Management of S & T, 2018, 39(3): 34-49. [10] 张保仓,任浩. 虚拟组织知识资源获取对持续创新能力的作用机制研究[J].管理学报, 2018, 15(7): 1009-1017. ZHANG B C, REN H. An empirical study on mechanism of action of organization knowledge resource acquisition to continuous innovation capability[J]. Chinese Journal of Management, 2018, 15(7): 1009-1017. [11] 李丹,杨建君,赵璐.企业间知识库兼容性、知识转移与企业知识创造绩效:双边关系质量的调节机制[J]. 科技进步与对策, 2020, 37(5): 141-150. LI D, YANG J J, ZHAO L. Knowledge creation performance, knowledge transfer and new knowledge creation rerformance: moderation paths of inter-firm relational quality[J]. Science & Technology Progress and Policy, 2020, 37(5): 141-150. [12] 米捷,林润辉,董坤祥,等.OFDI企业与本土集群企业知识共享的演化博弈分析——基于知识位势的视角[J].管理评论, 2016, 28(9): 106-120. MI J, LIN R H, DONG K X, et al. An evolutionary game analysis on knowledge sharing among ofdi corporation and local cluster enterprises: based on the perspective of knowledge potential[J]. Management Review, 2016, 28(9): 106-120. [13] 康鑫,赵丹妮.知识势差、知识隐匿与知识进化:组织惰性的调节作用[J].科技进步与对策,2021,38(6):122-130. KANG X, ZHAO D N. Knowledge potential, knowledge hiding and knowledge evolution: the moderation role of organizational inertia[J]. Science & Technology Progress and Policy, 2021, 38(6): 122-130. [14] 郭韬,邢璐,黄瑶. 创新网络知识转移对企业创新绩效的影响——双元创新的中介作用[J].科技进步与对策, 2017, 34(15): 114-119. GUO T, XING L, HUANG Y. Study on the influence of knowledge transfer of innovation networks on firms′ innovation performance-the intermediary role of ambidextrous innovation[J]. Science & Technology Progress and Policy, 2017, 34(15): 114-119. [15] 陈伟,杨早立,张永超.网络结构与企业核心能力关系实证研究:基于知识共享与知识整合中介效应视角[J].管理评论, 2014, 26(6):74-82. CHEN W, YANG Z L, ZHANG Y C. The empirical research on the relationship among network structure and core capability: the mediating role of knowledge sharing and knowledge integration[J]. Management Review, 2014, 26(6): 74-82. [16] WANG L Y,WANG Y,LOU Y, et al. Impact of different patent cooperation network models on innovation performance of technology-based SMEs[J]. Technology Analysis & Strategic Management, 2020, 32(6): 724-738. [17] 李守伟. 知识转移对企业创新能力的影响研究——网络中心性的调节作用[J]. 科技管理研究, 2018, 38(18): 164-171. LI S W. Research on the influence of knowledge transfer on enterprise′s innovation capability: the moderating role of network centrality[J]. Science and Technology Management Research, 2018, 38(18): 164-171. [18] 杨宝莹,胡延庆.统计推断方法在复杂网络中的应用[J].复杂系统与复杂性科学,2014,11(1):67-76. YANG B Y, HU Y Q. The application of statistical inference in complex networks[J]. Complex Systems and Complexity Science, 2014, 11(1): 67-76.
