产学合作网络的形成机理——基于中国人工智能技术的实证研究  

Formation Mechanism of Industry—University Collaboration Net⁃work:An Empirical Study of Chinese AI Technology

作　　者：廉翔鹏 苏竣[1,2,3] Lian Xiangpeng;Su Jun(School of Public Policy&Management,Tsinghua University,Beijing 100084,China;Center for Strategic Studies Science and Technology Committee of Ministry of Education:Center of Science,Technology&Education Policy,Tsinghua University,Beijing 100084,China;Center for Innovation Strategy of Research Institute of Tsinghua,Pearl River Delta,Guangzhou 510799,China)

机构地区：[1]清华大学公共管理学院,北京100084 [2]教育部科技委战略研究基地清华大学科教政策研究中心,北京100084 [3]清华珠三角研究院创新战略中心,广东广州510799

出　　处：《创新科技》2022年第11期1-11,共11页Innovation science and technology

基　　金：国家自然科学基金创新研究群体项目“中国公共政策理论与治理机制研究”(71721002);地方软科学项目“粤港澳大湾区科技制度创新系列专题研究”(2018B070715001);清华大学自主科研计划课题“人工智能赋能国家治理现代化社会实验研究”(20201080726)。

摘　　要：产学合作是实现创新驱动发展的重要途径,厘清产学合作网络的形成机理是推动科研与经济增长互动的重要前提。旨在从技术性、社会性和地理性3个维度探究产学合作网络的形成机理,并基于我国2000—2021年人工智能专利数据,采用指数随机图模型分析工具进行实证分析。实证结果表明:技术多样性、技术价值和技术相似性的提高有助于大学和企业间的合作,能够促进产学合作网络的生成;产学合作网络呈现反“核心—边缘”规律,大学和企业会选择少量合作伙伴进行深入合作;地理临近是促进产学合作的重要因素,省域内产学合作是产学合作网络生成的关键动力。研究结果丰富了产学合作网络演化的相关理论,也为政府有序引导和促进产学合作提供了思路和科学依据。Industry-university collaboration(IUC)has become an important element for the innovation-driven development strategy and transformation of scientific and technological achievements in China.With the continuous development of IUC,more and more innovative enterprises and research universities join in the technology collaboration through resource share and complement of each other's advantages,which form the IUC networks with multiplex actors,abundant relationships and complex structure.A part of present literature on IUC network focuses on the descriptive analysis of collaboration mode and identification of the key actors,and the other literature explores its effect on innovation outcomes.There is a lack of discussion on the dynamic mechanism of IUC network.Therefore,combining with network system dynamics,this paper explores the formation mechanism of IUC network from the technical,social and geographical dimensions.This paper takes IUC of Chinese artificial intelligence technology as a case.We measure the key indicators and construct IUC network based on the patent data of Chinese artificial intelligence technology.Specifically,this paper uses the information of patentee and international patent classification from 2000 to 2019 to measure the independent variables:three technical factors including technological diversity,technological value and technological similarity,social factors represented by structural embeddedness,geographical factors represented by geographical proximity.The IUC network was constructed using the patentee information from 2020 to 2021 as the dependent variable of this study.Finally,the Exponential Random Graph Model(ERGM)is adopted to analyze the influence of above mentioned endogenous and exogenous factors on the evolution of IUC network.The analysis tool is software Pnet.The empirical results show that diverse technology base and similar technology background will promote universities and enterprises to join the IUC network.The results also indicate that universities with higher technolo

关 键 词：产学合作网络 形成机理 人工智能技术 指数随机图模型 

分 类 号：G322[文化科学]