摘要
跨界创新联盟是企业创新过程中资源整合与共享的一种有效形式,但在带来企业创新资源共享效益的同时,联盟中复杂的关联关系也构成了联盟关联信用风险传染的新渠道。本文结合复杂网络理论与传染病模型,根据跨界创新联盟特点,在原有资产关联研究的基础上,综合考虑行业关联、资产关联和创新合作关联三种关联关系,改进了风险传播的传染病模型,并进行了数值仿真实验。结果表明:行业关联、资产关联和创新合作关联对跨界创新联盟关联信用风险传染阈值具有综合性影响,增加行业关联和创新合作关联因素,有利于提高关联信用风险传染阈值的精度。此外,资产关联度越高则感染成员密度越大;行业关联度越低,创新合作关联度越高则感染成员密度越小。
Cross-border innovation alliance is an effective form of resource integration and sharing in the process of enterprise innovation.However,while bringing benefits of enterprise innovation resource sharing,the complex association relationship in the alliance also constitutes a new channel to the credit risk contagion of alliance.This paper combines the complex network theory with the model of infectious disease,according to the characteristics of cross-border innovation alliance,and on the basis of the original asset correlation study,comprehensively considers three correlation relationships of industry correlation,asset correlation and innovation cooperation correlation,improves the infectious disease model of risk transmission,and carries out numerical simulation experiments.The results show that industry correlation,asset correlation and innovation cooperation correlation have a comprehensive impact on the threshold of associated credit risk contagion with cross-border innovation alliance.Increasing the factors of industry correlation and innovation cooperation correlation is conducive to improving the accuracy of the threshold of associated credit risk contagion.In addition,the lower the industry correlation degree,the higher the innovation cooperation correlation degree,the smaller the density of infected members.
作者
高长元
张逸琳
王京
GAO Chang-yuan;ZHANG Yi-lin;WANG Jing(School of Economics and Management, Harbin University of Science and Technology, Harbin 150040, China)
出处
《运筹与管理》
CSSCI
CSCD
北大核心
2022年第4期169-175,共7页
Operations Research and Management Science
基金
国家自然科学基金资助项目(71774044,71672050,71804035)
教育部人文社会科学研究项目(18yjc630177,19YJC630215)
黑龙江省普通高校基本科研业务费专项资金资助(LGYC2018JC058)。
关键词
跨界创新联盟
关联信用风险
复杂网络
关联关系
传染病模型
cross-border innovation alliance
associated credit risk
complex network
association relationship
infectious disease mode