【作者】 张华伦；

【导师】 宋伟；

【作者基本信息】 中国科学技术大学 ， 公共管理， 2014， 博士

【摘要】 进入21世纪,企业与企业之间、国家与国家之间的竞争越来越多依赖科学技术的发展和进步,经济的知识化和知识的经济化趋势日益显著。1978年,我国实施对内改革和对我开放的政策。此后,我国经济持续高速发展,取得了举世瞩目的非凡成就。然而,先前的经济增长模式如今已经无法为继。特别是,2008年美国的金融危机引发了全球金融风暴,导致我国沿海地区加工贸易型企业的倒闭狂潮,敲响了我国粗放型经济发展模式的警钟。近年来世界范围的整体经济形势不明朗,经济持续低迷。我国经济在不确定、不稳定的环境下持续深度调整,经济系统和创新系统都面临着前所未有的考验。面对复杂的国际经济形势以及我国经济结构转型升级等诸多困难因素,以符合知识自身发展规律的视角,重新审视当前我国科技政策以及国家创新系统的运行情况十分必要。现有关于科技政策绩效的研究,主要利用数据包络分析方法开展定量分析。特别是近年来,学者们借鉴创新系统效率评价的经验,将创新系统划分为研发子系统和经济子系统,深入考查两阶段的政策绩效,并为科技政策绩效的提升提供了有针对性的建议和对策。然而,这虽然弥补了传统上将创新系统视为“黑箱”处理进而忽略其内部结构及相互关系的不足,但经济子系统中的科技成果转移与应用仍处于混沌状态,无法全面的考察创新全过程的绩效问题,这显然不利于进一步深入分析科技政策绩效DEA非有效的问题所在。本文依据知识在创新系统中流动的过程——知识创造、知识扩散和知识应用,基于Fare和Grosskopf (2000)提出的网络DEA模型,并考虑了非期望产出,构建基于网络DEA的三阶段评价模型,对我国28个省市在2002-2011年间的整体效率以及知识创造、知识扩散和知识应用的效率进行实证分析。结果显示,各省市在2002-2011年间整体效率均值为DEA无效,说明这期间我国投入巨大的人力物力和财力并没有得到充分的利用,国家科技政策出现了系统失灵。在各个阶段的分析中,我们可以发现,整体上,知识创造效率均值>知识扩散效率均值>知识应用效率均值,这与我国长期重视研发而忽视科技成果转移转化的历史有很大关系。经济越发达的地区,其科技投入越大,其科技产出也越多,但是知识应用的效率随着投入、产出的增加,不增反降,即知识应用系统的运行效率随着产出的增长,呈下降趋势。这反映出,我国创新系统尤其是东部地区的创新系统问题在于知识应用阶段效率值拉了其创新系统整体效率。因此,东部地区亟需调整科技政策,促进科技成果的转移和转化,西部地区则需要根据自身经济的现状适度增加研发投入。最后,主要从提升科技投入产出质量,促进知识转移和科技成果转化方面给出相应的对策和建议。更多还原

【Abstract】 In the21st century, the competition between countries and countries, enterprises and enterprises, is more and more relying on technology progress. The trend of economy knowledgelization and knowledge economization is increasingly significant. Since the reform and opening, our country economy has realized the continuous rapid development. However, previous economic growth pattern dies. In particular, as a result of the global financial storm, the coastal areas of processing trade type enterprise have collapsed. This sounded the alarm extensive economic development pattern in our country. In recent years, the world is in a period of continuous economic downturn. In the face of difficult factors in many aspects, including complicated international economic situation and our country economic transformation and upgrading of economic structure, we need to review the current country science and technology policy and the operation of national innovation system following the perspective of knowledge development rule.Existing research on the performance of science and technology policy mainly uses the method of data envelopment analysis (DEA) to carry out quantitative analysis. Especially in recent years, based on the experience of the innovation system efficiency evaluation, scholars put innovation system into R&D subsystem and economic subsystem. This helps to explore the deep reasons of DEA invalid region, and can provide better suggestions and countermeasures. This makes up for the traditional general decision making units as the whole of input and output. Because this method treated the innovation system as a "black-box", yet ignored the internal structure and mutual relations. However, this makes no contribution to comprehensively review the whole process of innovation performance.This paper based on the process flow of knowledge innovation system, namely, the knowledge creation, knowledge diffusion and application of knowledge in three stages. Then, we follow Fare and Grosskopf (2000) proposed a network DEA model under the influence of Fare and Grosskopf (2000), considering undesirable output and building a three-stage network DEA evaluation model, meanwhile based on the overall efficiency of China’s28provinces and cities between2002-2011and knowledge creation, knowledge diffusion and knowledge of effective efficiency empirical analysis applications. Then, using the model estimates the value of China’s 28provinces and cities in the efficiency of the overall efficiency and knowledge creation, knowledge diffusion and knowledge application stage of the2002-2011years. The results showed that among the provinces between2002-2011mean overall efficiency DEA invalid, this shows that China invested enormous human and material resources and financial resources have not been fully utilized, the national science and technology policies of system failure. In various stages of the analysis, we can see that, on the whole, the average efficiency of knowledge creation, knowledge application and knowledge diffusion efficiency mean average efficiency in descending order, which is our long-standing neglect of important research results of scientific and technological achievements transfer transformation. More economically developed regions, the greater its technology investment is, the more its scientific output is, but the efficiency of knowledge into applications with increased output, is reduced rather than increased, namely the operating efficiency of the system declines as the application of knowledge outputs grows. This reflects our innovation system, especially the eastern part of the innovation system problem that knowledge application stage efficiency values pulled the overall efficiency of their innovation systems, and knowledge application stage efficiency relatively promote the values of the western region, therefore, it is needed to adjust the eastern and technology policy inprove the transfer and transformation of scientific and technological achievements, the western region will need a modest increase in R&D investment according to the status of their economies. Finally, the main technological investment to enhance the quality of output from promoting knowledge transfer and scientific and technological achievements into the corresponding countermeasures and suggestions as are given below.更多还原