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基于知识积累的高技术产品研发项目学习双元最优顺序策略研究
引用本文:荣健,刘西林,佟泽华.基于知识积累的高技术产品研发项目学习双元最优顺序策略研究[J].科技进步与对策,2017,34(16):126-131.
作者姓名:荣健  刘西林  佟泽华
作者单位:1.西北工业大学 管理学院,陕西 西安 710072;2.山东理工大学 商学院,山东 淄博 255049
基金项目:国家社会科学基金项目(13CGL012)
摘    要:高技术产品是高新技术知识的集成,其研发状况成为知识经济增长的决定性因素之一。围绕组织学习-知识存量-研发绩效的作用链条,构建了高技术产品研发过程中学习双元平衡的最优控制模型,求解出探索式学习和利用式学习的最优终止点、最优转换点、最优投入强度,并从这3个方面给出了高技术产品研发过程中的学习双元最优顺序策略。研究结论可为高技术产品研发项目实施中研发节奏掌控、学习战略的制定、资源分配等方面提供参考。

关 键 词:研发项目  知识存量  组织学习  最优控制  
收稿时间:2017-06-06

The Optimal Sequential Strategy of Learning Ambidexterity for High-tech Product R&D Project Based on the Knowledge Accumulation
Rong Jian,Liu Xilin,Tong Zehua.The Optimal Sequential Strategy of Learning Ambidexterity for High-tech Product R&D Project Based on the Knowledge Accumulation[J].Science & Technology Progress and Policy,2017,34(16):126-131.
Authors:Rong Jian  Liu Xilin  Tong Zehua
Institution:1.School of Management, Northwestern Polytechnical University, Xi'an 710072,China;2.School of Business, Shandong University of Technology, Zibo 255049,China
Abstract:High-tech product is the integration of high-tech knowledge, and its R&D status has become one of the decisive factors in the growth of knowledge economy. Focused on the mechanism of organizational learning-knowledge stock-R&D performance, an optimal model of dynamic ambidexterity is introduced. After the model solving, results are obtained about the decision making of the optimal termination point, the optimal switching point, and the optimal input intensity of exploration and exploitation. Based on these results the optimal sequential ambidexterity strategy is given for the maximization of high-tech product's R&D performance. All of these conclusions can provide reference for the control of R&D rhythm, the formulation of learning strategy and the allocation of investment resources in the implementation of high-tech product development projects.
Keywords:R&D Project  Knowledge Stock  Organizational Learning  Optimal Control  
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