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R&D项目投资风险预警控制模型与实证研究
引用本文:盛淑凯,刘宇.R&D项目投资风险预警控制模型与实证研究[J].科技与经济,2012,25(3):71-75.
作者姓名:盛淑凯  刘宇
作者单位:1. 安徽理工大学土木建筑学院,安徽淮南,232001
2. 北京信息科技大学经济管理学院,北京,100085
基金项目:国家自然科学基金,安徽省高校自然科学研究项目
摘    要:中国加入WTO后,企业为获得更高的市场竞争能力,急需通过R&D活动来提高其技术水平.随着产业技术创新动力机制模式和创新政策的完善,企业R&D投入必将大幅增加.企业R&D活动存在大量不确定性,尤其是技术的外部性极有可能导致其R&D投资失败.因此企业需要对R&D项目投资风险进行预警控制.在定量测量企业R&D项目投资风险的基础上,利用系统独立性原理和休哈特控制图建立预警控制界限,事前判断企业多R&D项目投资风险值是否受控;并采用时间回归方法判断企业决策者的心理趋势是否有变动;最后以某企业为案例验证了该方法的有效性.

关 键 词:R&D  风险预警  时间序列回归判别

Model of Risk Forewarning Control of R&D Investment Projects and Empirical Study in Chinese construction enterprises
SHENG Shu-kai , LIU yu.Model of Risk Forewarning Control of R&D Investment Projects and Empirical Study in Chinese construction enterprises[J].Science & Technology and Economy,2012,25(3):71-75.
Authors:SHENG Shu-kai  LIU yu
Institution:1 School of Civil Enigneering,AnHui University of Scienc & Technology,HuaiNan 232001,China; 2 School of Economics and Management,Beijing University of Information and Technology,Beijing 100085,China)
Abstract:After the entry of WTO,enterprises acutely need to improve the technology level through R&D activities for the market competitive ability.With the perfection of the mode of technology innovation dynamic mechanism and policy in the industry,its enterprises will add the input of R&D extremely.Because of the uncertainties of R&D activity in enterprises,especially the character of easy-used of construction technology,the investment of R&D is extremely likely to fail.So,the enterprises need to forewarn the risk of R&D investment projects.This paper prescribes the risk measurement of R&D investment projects in enterprises and builds the forewarning limitation based on the principle of system dependence and Shewhart control charts to warn the fluctuation of risk values of R&D investment projects in enterprises early.Then the mental trend of decision-makers in enterprises is correctly judged by the method of time series regression.In the last,the validity of the model is proved by a case.
Keywords:R&D  Risk Forewarning  Judgment of Time Series Regression
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