中国电子信息产业创新网络演化——基于SAO模型的实证  

The Dynamics of China’s Electronic Information Industry Innovation Networks: An Empirical Research Based on SAO Model

作　　者：周灿[1] 曾刚[1] 辛晓睿 宓泽锋 ZHOU Can;ZENG Gang;XIN Xiaorui;MI Zefeng(Center for Modern Chinese City Studies ＆ School of City and Regional Science, East China Normal University, Shanghai 200062,China;School of Economics , Zhejiang Gongshang University , Hangzhou 310018 , Zhejiang , China)

机构地区：[1]华东师范大学中国现代城市研究中心/城市与区域科学学院,中国上海200062 [2]浙江工商大学经济学院,中国浙江杭州310018

出　　处：《经济地理》2018年第4期116-122,共7页Economic Geography

基　　金：国家自然科学基金面上项目(41071093、41371147);德国科学基金会项目(LI981/8–1AOBJ:595493)

摘　　要：采用国家知识产权局2009-2013年中国电子信息产业联合申请发明专利数据，运用SAO模型，借助Ucinet和Stocnet等分析工具，刻画中国电子信息产业创新网络演化特征，探讨创新网络演化影响因素。研究表明：中国电子信息产业合作创新日趋显著；创新网络演化处于活跃期，网络结构尚未稳定；创新网络趋向于具有较小的平均路径长度和较大的群集系数，逐渐向小世界网络演化。地理邻近有助于隐性知识交流，奠定了创新网络演化的基础；社会邻近增强了双方互信，成为促进创新网络演化的重要因素；根植性能够塑造知识循环，是创新网络演化的重要推动力；考虑到成本效应，网络地位对创新网络演化具有消极影响；创新能力强、合作创新经验丰富的创新主体更有可能吸引更多的合作伙伴。Although the growing interest in economic geography about innovation networks, there is still relatively little evidence of their dynamics, that is, how they form and change over time. Drawing on stochastic actor-oriented model and by using Ucinet and Stocnet, our paper aims to analyze the evolution of innovation networks and estimate three main mechanisms： proximity, network endogeneity and individual characteristics on the formation of innovation networks in China＇ s electronic information industry based on a unique co-patent dataset issued by the State Intellectual Propelty Office of P.R. China from 2009 to 2013. The main findings of this study are drawn as follows. Recognition of the importance of external sources of knowledge, collaborative innovation is becoming more and more significant. The innovation networks of China＇ s electronic information industry are currently experiencing the most active period and become more unstable over time. The dynamics of China＇ s electronic information industry innovation networks features ＇small-world＇ network properties, whereby dense clusters of network actors are linked to other clusters via a relatively small number of bridging links. Geographic proximity facilitates tacit knowledge communication and plays an important role in the dynamics of innovation networks. Social proximity enhance trust and we find a positive and significant of social proximity. Embeddedness plays an important role in shaping knowledge circulation and the dynamics of innovation networks was clearly driven by embeddedness. Network status measures the costs of linkages which inhibit actors to be fully connected and the effect of network status is negative and slgnificant. With respect to the individual characteristics, the positive and significant effects of innovation ability and collaborative innovation experience show that actors are more likely to partner with innovative and experienced actors.

关 键 词：创新网络演化 随机面向对象模型 电子信息产业 中国 

分 类 号：F129.9[经济管理—世界经济]