随机因素干扰下协同创新系统知识共享策略研究
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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.
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.
引文
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[22]赵黎明,孙健慧,张海波.基于微分博弈的军民融合协同创新体系技术共享行为研究[J].管理工程学报,2017,31(3):183-191.
[23]朱怀念,刘贻新,张成科,等.基于随机微分博弈的协同创新知识共享策略[J].科研管理,2017,38(7):17-25.
[2]陈劲,阳银娟.协同创新的理论基础与内涵[J].科学学研究,2012,30(2):161-164.
[3]涂振洲,顾新.基于知识流动的产学研协同创新过程研究[J].科技进步与对策,2013,31(15):133-137.
[4]KOSCHATZKY K.Networking and knowledge transfer between research and industry in transition countries:empirical evidence from the Slovenian innovation system [J].The Journal of Technology Transfer,2002,27 ( 1) :27-38.
[5]ROBIN V,ROSE B,GIRARD P.Modeling collaborative knowledge to support engineering design project manager[J].Computers in Industry,2007,58(2):188-198.
[6]SAMADDAR S,KADUYALA S S.An analysis of interorganizational resource sharing decisions in collaborative knowledge creation[J].European Journal of Operational Research,2006,170(1):192-210.
[7]刘怡君,唐锡晋.一种支持协作与知识创造的“场”[J].管理科学学报,2006,9(1):79-85.
[8]吴悦,顾新.产学研协同创新的知识协同过程研究[J].中国科技论坛,2012(10):17-23.
[9]翁莉,仲伟俊,鲁芳.供应链知识共享的决策行为及影响因素研究[J].管理学报,2009,6(12):1648-1652.
[10]刘建设.基于静态博弈分析的组织知识共享激励策略研究[J].经济研究导刊,2010(16):126-128.
[11]张廷海,韩玮.产业集群协同创新的博弈均衡研究[J].科学管理研究,2014(3):64-67.
[12]李高扬,刘明广.产学研协同创新的演化博弈模型及策略分析[J].科技管理研究,2014,34(3):197-203.
[13]张华.协同创新、知识溢出的演化博弈机制研究[J].中国管理科学,2016,24(2):92-99.
[14]朱卫未,施琴芬.隐性知识转移过程中个体间的博弈纳什均衡[J].研究与发展管理,2011,23(5):128-134.
[15]蒋樟生,胡珑瑛.技术创新联盟知识转移决策的主从博弈分析[J].科研管理,2011,32(4):19-25.
[16]商淑秀,张再生.虚拟企业知识共享演化博弈分析[J].中国软科学,2015(3):150-157.
[17]YUQIN Z,GUIJUN W,ZHENQIANG B,et al.A game between enterprise and employees about the tacit knowledge transfer and sharing[J].Physics Procedia,2012,24(Part C):1789-1795.
[18]KOESSLER F.Strategic knowledge sharing in Bayesian games[J].Games & Economic Behavior,2004,48(2):292-320.
[19]LI Y M.Knowledge sharing in communities of practice:a game theoretic analysis[J].European Journal of Operational Research,2010,207(2):1052-1064.
[20]李煜华,刘洋,胡瑶瑛.科技型小微企业与科技型大企业协同创新策略研究:基于动态演化博弈视角[J].科技进步与对策,2015(3):90-93.
[21]李保林,王娟茹,杨丽华,等.考虑政府补贴的产业共性技术协同创新博弈分析[J].科技管理研究,2017,37(16):152-157.
[22]赵黎明,孙健慧,张海波.基于微分博弈的军民融合协同创新体系技术共享行为研究[J].管理工程学报,2017,31(3):183-191.
[23]朱怀念,刘贻新,张成科,等.基于随机微分博弈的协同创新知识共享策略[J].科研管理,2017,38(7):17-25.