摘要
考虑随机因素干扰的情形下,运用HJB方程和动态规划方法分别求解Nash非合作博弈和协同创新博弈模型下大学与企业的知识共享策略。结果表明:(1)两种博弈情形下,知识共享的成本越高,共享的知识量越少,知识共享边际收益越高;(2)协同创新博弈模式下的知识共享量、系统总收益均高于Nash非合作博弈,更易于达到Pareto最优,即推动产学研协同创新有助于提升系统总收益;(3)在合作情形下,大学与企业的决策目标定位于整体收益最大化,使得双方在知识共享努力程度与整体收益情况均优于Nash非合作博弈,在对知识共享行为有效协调下,合作策略是大学与企业构建协同创新系统,促进系统内知识共享的最优选择。
In this paper, the HJB equation and dynamic programming method are used to solve the knowledge sharing strategies of university and enterprise under the Nash non-cooperative game and collaborative innovation game model respectively. The results show:(1) In the two game situations, the higher the cost of knowledge sharing, the less the amount of knowledge shared, the higher the marginal benefit of knowledge sharing.(2) The amount of knowledge sharing and total system revenue under the collaborative innovation game model is higher than that of Nash non-cooperative game, and it is easier to achieve Pareto optimization. Promoting collaborative innovation of industry, universities, and research helps to increase total system revenue.(3)Under the cooperation situation, the decision-making objectives of universities and enterprises aim at maximizing the overall benefits, making the two parties better than the Nash non-cooperative game in the degree of knowledge-sharing efforts and overall benefits. Under the effective coordination of knowledge-sharing behaviors, the cooperation strategy is the universities build a collaborative innovation system with the company to promote the optimal choice of knowledge sharing within the system.
作者
王庆金
袁壮
蒋天峰
Wang Qingjin;Yuan Zhuang;Jiang Tianfeng(Business School, Qingdao University, Qingdao 266100, China)
出处
《科技管理研究》
CSSCI
北大核心
2019年第10期139-145,共7页
Science and Technology Management Research
基金
山东省自然科学基金项目“众创空间生态系统协同演化路径及治理机制研究”(2017RZB01006)
山东省软科学研究计划重点项目“‘政产学研金服用’相结合的技术创新体系研究”(2017RZB01006)
关键词
随机微分博弈
Nash非合作博弈
协同创新
知识共享
stochastic differential game
Nash non-cooperative game
collaborative innovation
knowledge sharing
