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作 者:吴赐联 朱斌 Wu Cilian;Zhu Bin(School of Economics and Management,Fuzhou University,Fuzhou 350116,Fujian,China)
机构地区:[1]福州大学经济与管理学院
出 处:《科研管理》2019年第11期111-122,共12页Science Research Management
基 金:教育部人文社会科学研究规划项目:“企业创新管理探索:主流与新流创新的冲突与协同”(15YJA630109,2015.12-2017.12);国家社会科学基金后期资助项目:“企业主流与新流创新协同演进的理论与实证研究”(17FGL001,2017.12-2019.12);福建省社会科学规划项目:“企业主流与新流创新资源优化配置研究”(FJ2017C019,2017.09-2019.09)
摘 要:将企业的创新活动细分为主流与新流创新,利用半结构性访谈法构建二元创新动态绩效评价体系,并绘制体现二元创新动态绩效演化的模糊认知图,利用群体专家意见与Hebbian权值学习共同确定反映指标间影响权重的邻接矩阵,以汽车企业作为研究案例,利用计算机模拟企业主流与新流创新动态绩效的演化进程和关键变量对创新动态绩效的影响机理。结果表明基于模糊认知图的创新动态绩效评价模型具备良好的信息反馈机制,有助于决策者把握创新绩效的变化趋势和影响创新绩效提升的关键因素。The action of"Made in China 2025"points out that innovation should be given a prominent position in the development of manufacturing industry and the path of innovation-driven development should be followed. Innovation is the foundation of enterprises’ survival as well as the guarantee of realizing the strategy of strengthening China through science and technology. In the face of the fierce competition,enterprises should not only improve and upgrade the traditional technology to extend the life cycle,but also strive to develop new technology to keep ahead before the decline of traditional technology. We can subdivide the enterprise’s innovation activities into traditional mainstream innovation and emerging new stream innovation. However,none of the existing studies have been able to subdivide the innovation activity before the performance evaluation,and almost all of the studies just focus on the static evaluation,which is not conducive to accurately grasp the advantages and disadvantages of traditional and emerging innovation fields and also lacks the ability of dynamic prediction of performance,and the ability to analyze the impact mechanism of key variables on dynamic performance.Therefore,this paper adopted the method of combining theoretical reasoning with empirical research. Firstly,the innovation activities were divided into mainstream and new stream innovation,and the semi-structural interview method was used to obtain the key variables which will affect the dynamic performance of mainstream and new stream innovation through open communication with the heads of scientific research department,senior managers of enterprise,experts and scholars of universities;secondly,according to the definition of the variables,qualitative clustering method was adopted to classify the variables,a dynamic performance evaluation system was constructed,the fuzzy cognitive maps were drawn to highlight the characteristics of mainstream and new stream innovation and to reflect the causal relationship between the evaluation v
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