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国家创新能力形成的系统动力学模型及应用 被引量:20

A system dynamics model of the formation of national innovative capacity and its applications
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摘要 本文从分析国家创新能力形成机理入手,建立基于过程导向的国家创新能力概念框架。首先,通过将国家创新体系划分为载体、环境和成果三个子功能模块,绘制国家创新体系各要素间的一般因果关系图。其次,运用径向基神经网络模型对各个功能模块之间关系的基本假设进行检验,并在此基础上建立以政府政策对创新成果影响为主线的系统动力学模型。最后,通过向创新系统内输入延时、脉冲、阶跃函数,进一步探讨政府科技投入、人才培养、知识产权保护以及税收优惠等对国家创新体系产出的影响。 The formation mechanism of national innovative capacity is analyzed and the process - oriented conceptual framework of national innovative capacity is designed. Firstly, by dividing the national innovation system into three basic functional modules including resources, environment, and output, the general cause - effect feedback loops of the NIS are designed. Secondly, the RBF neural - network is used to testify the basic assumptions on the relationship between different function modules, and based on the testing results, the System Dynamics (SD) model which is aimed at to show how government policies affect the innovation is set up. Finally, by introducing input delay, pulse and step function into the NIS, how S&T investment, personnel training, intellectual property protection, tax incentives, and other factors affect the output of the NIS is discussed.
出处 《科研管理》 CSSCI 北大核心 2011年第8期17-25,共9页 Science Research Management
基金 国家自然科学基金项目"国家创新能力形成机理与中国路径选择" 编号(70973012) 期限:2010.1-2012.12 国家自然科学基金项目"政府R&D投入绩效分析的理论模型及其应用研究" 编号(70773014) 期限:2008.1-2010.12
关键词 国家创新能力 神经网络 系统动力学 national innovative capacity neural network SD
作者简介 刘凤朝(1954-),男,吉林通化人,教授,博士生导师。主要从事科技评价与科技政策研究。 冯婷婷(1984-),女,辽宁大连人,大连理工大学经济系硕士研究生,研究方向为创新体系分析。
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