随机因素干扰下协同创新系统知识共享策略研究

Research on Knowledge Sharing Strategy of Collaborative Innovation System under Random Factor Interference

摘要:

本文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。

Abstract:

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. That is, 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 are aimed 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 university. Build a collaborative innovation system with the company to promote the optimal choice of knowledge sharing within the system.