科研管理

科研管理 ›› 2011, Vol. 32 ›› Issue (11): 1-6,17.

• 论文 •    下一篇

大中型工业企业技术创新投资演化行为分析

李梅芳1, 赵永翔2   

  1. 1. 福州大学 管理学院,福建 福州 350108;
    2. 福州大学 八古物流学院,福建 福州 350108
  • 收稿日期:2010-04-16 修回日期:2010-08-19 出版日期:2011-11-27 发布日期:2011-11-22
  • 作者简介:李梅芳(1979-),女(汉),湖北监利人,福州大学讲师,研究方向:创新工程与管理。
    赵永翔(1978-),男(汉),湖北监利人,福州大学讲师,研究方向:物流工程、人工智能。
  • 基金资助:

    2007年国家自然基金项目"分布式创新的机理及其效应研究"(70772074)。

The evolution behavior of technological innovative investmentin large and medium-sized industrial enterprises

Li Meifang1, Zhao Yongxiang2   

  1. 1. School of Management, Wuhan University of Technology, Wuhan 430070, China;
    2. State Key Laboratory of Advanced Technology for Materials Synthesis and Processing,Wuhan University of Technology, Wuhan 430070, China
  • Received:2010-04-16 Revised:2010-08-19 Online:2011-11-27 Published:2011-11-22

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摘要： 为了揭示大中型工业企业技术创新投资的演化行为与规律,构建了一个以差分形式表示的企业技术创新投资经济增长非线性动力学模型。采用差分演化算法对模型进行了参数优化并进行了计算机模拟。主要结论是:1企业的人均研发经费投入与科技活动人员比率对企业技术创新投资系统经济增长的演化行为有着决定性的影响,可以通过调节二者的值来改变系统的演化特性;2对二者的调节应在一定范围内进行;3并不是二者的值越大就必然导致企业人均工业增加值的上升;4当二者的值增大到一定条件会出现系统演化行为的分岔,分岔后会出现两种决然不同的结果,并最终进入混沌状态;5随着二者的值不断增大,系统进入分岔与走向混沌的速度也不断加快。

关键词: 技术创新投资, 非线性动力学模型, 演化行为, 计算机模拟, 大中型工业企业

Abstract: In order to reveal the evolution behavior and law of Enterprises Technological Innovative Investment (ETII), an economic growth nonlinear dynamic model of ETII expressed in a differential form was constructed. A differential evolution algorithm was used to optimize the parameters of the model, and then the computer simulation has been carried out. The main conclusions are as follows: (1) R&D investment per person and the ratio of R&D personnel have the decisively influence on the evolution behavior of economic growth of ETII system in enterprises, and the evolution characteristics of the system could be changed by adjusting the value of these two impact factors. (2) The factors should be adjusted in a certain range by taking the scientific theory as the guideline and foundation. (3) Value increasing of these two impact factors might not inexorably lead to the raise of industrial value per person. (4) When the value of the two factors is increased to some conditions, the bifurcation will be appeared; and following with two totally different results, and finally the system will enter into a chaotic state. (5) With the R&D investment and/or the R&D personnel ratio increasing, the speed for system entering bifurcation and going into chaotic state is faster.

Key words: technological innovative investment, nonlinear dynamic model, evolution behavior, computer simulation, large and medium-sized industrial enterprises

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