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知识流动视角下科技政策绩效评价研究
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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。
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.
引文
OECD. National Innovation Systems [R]. Paris:OECD,1997:7-11.
    Teece D. Technology Transfer by Multinational Firms:the Resource Cost of Tran sferring Technological Know-How [J]. The Economic Journal,1977 (87):242-261.
    M ax H Boisot. Is Your Firm a Creative Destroyer Competitive learning and Knowledge Flows in the T echnol ogical S trategies of Firm [J]. Research Policy,1995 (24):489-506.
    Sofia Liberman, KurtBernardo Wolf. The Flow of Knowledge:Scientific Contacts in Formal Meet-ings [J]. Social Networks,1997 (19):271-283.
    H ai Zhuge. A Knowledge Flow Model for Peer-to-Peer Team Knowledge Sharing and Management [J]. Expert Systems With Applications,2002 (23):23-30.
    KIM L. Imitation to innovation [M]. Boston:Harvard Business School Press,1997.
    BENN STEIL, DAVID G.VICTOR, RICHARD R.NELSON. Technological innovation and economic performance [M]. Princeton University Press,2002.
    NAUSHAD FORBES, DAVIDW IELD. From technology and innovation:managing technology and innovation [M]. Routledge,2002.
    Grace T. R. Lin, Yung-Chi Shen. James Chou.National innovation policy and performance: Comparing the small island countries of Taiwan and Ireland [J]. Technology in Society, Vol32, 2010 (2):161-172.
    Nasierowski W., Arcelus F. On the efficiency of national innovation systems [J]. Socioeconomic Planning Sciences,2003 (37):215-234.
    Jorg C. Mahlich, Thomas Roediger-Schluga. The Determinants of Pharmaceutical R&D Expenditures:Evidence from Japan[J]. Review of Industrial Organization,2006,28(2):145-164.
    Nonaka, I. A Dynamic Theory of Organizational Knowledge Creation [J]. Organization Science, 1994 (5):14-37.
    Nonaka, I. and Takeuchi, H. The Knowledge- creating Company:How Japanese Companies Create the Dynamics of Innovation [M]]. New York:Oxford University Press,1995.
    Nonaka, I. SECI Ba and Leadership a Unified Model of Dynamic Knowledge Creation [J]. Long Range Planning,2000 (33):5-34.
    Song Wei, Zhang Hualun. Evaluate the Investment Efficiency by Using Data Envelopment Analysis:the Case of China. American Journal of Operations Research(AJOR).2012(2):174-182.
    Beckmann, M. Knowledge networks:The case of scientific interaction at a distance [J]. The Annals of Regional Science,1993,27 (1):5-9.
    Beckmann, M. On knowledge networks in science:Collaboration among equals [J]. The Annals of Regional Science,1994 (28):233-242.
    Grabher, G. Trading routes, bypasses and risky intersections:Mapping the travels of 'Networks' between economic sociology and economic geography [J]. Progress in Human Geography,2006, 30 (2):163-189.
    Abemathy W. J, Utterback LM. Patterns of Industrianl Innovation [J], Technology Review,1978 (80):41-47.
    A. Gerybadze, Greger. Globalization of R&D:Recent Changes in the Management of Innovation in Transnational Corporations [J]. Research Policy,1999 (28):251-274.
    B. Carlsson. Internationalization of innovation systems:A survey of the literature [J]. Research Policy,2006(35):56-67.
    Bartholomew. National systems of biotechnology innovation:complex interdependence in the global system [J]. Journal of International Bvsiness Studies,1997 (2):241-266.
    Bruce Kogut, Anca Metiu. Open-Source Software Development and Distributed Innovation [J]. Oxford Review of Economic Policy,2001 (2):248-264.
    Carlsson, B. Internationalization of innovation systems:A survey of the literature [J]. Research Policy,2006 (35):56-67.
    Cooke, Philip. Regionally asymmetric knowledge capabilities and open innovation:exploring Globalisation 2-a new model of industry organization [J]. Research Policy,2005 (34): 1128-1149.
    David J. Teece. Profiting from technological innovation[J]. Research Policy,1986 (6):286-305.
    Edquist, C. Systems of Innovation:Technologies, Institutions and Organizations [M]. Pinter, London,1997.
    Freeman C. Technology Policy and Economic Performance:Lessons from Japan [M]. London: Printer Publishers,1987.
    Farrell, M. J., The measurement of productive efficiency[J]. Journal of the Royal Statistical Society, 1957, Series A, Vol.120,253-281.
    Farrell, M. J. and M. Fieldhouse, Estimating efficiency pruoduction under increasing return to scale [J]. Journal of the Royal Statistical Society,1962 (18):252-267.
    A. Charnes, W. W. Cooper. E. Rhodes..Measuring the efficiency of decision makingunits [J]. European Journal Operational Research,1978 (2):429-444.
    A. Charnes, W. W. Cooper. B. Colany, L. Seiford, J. Stutz. Foundations of data envelopment analys is for pareto koopmans efficient empirical production [J].1985 (30):91-107.
    Michael Fritsch. Measuring the Quality of Regional Innovation Systems-A Knowledge Production Function Approach [J]. International Regional Science Review, 2002 (25):86-101.
    Baumert, Pellitero MM. Analyzing Regional Innovation Systems through A Multi-Perspective Econometric Approach:The Spanish Case[J]. Paper Presented at the 7th INFER Annual Conference in Economic Research,2005 (10):7-9.
    Phene, A., Tallman, S.. Knowledge flows and geography in biotechnology [J]. Journal of Medical Marketing,2002 (2):241-254.
    Mauro Silva Ruiz, Paulo Lauro Correa de Oliveira, Rosa Maria Lima Alves et. An Analysis of the Supple and Demand of Specialized Technical Services in the Landline Region Envisaging the Strengthening of the Technological Competencies and the Structuring of A Regional Innovation System [C]. International Conference on Technology and Innovation,2000.
    Furman, J. L, Porter, M. E., Stern, S. The Determinants of National Innovative Capacity [J]. Research Policy,2002 (31):899-933.
    Schartinger. D., Schibany, A., Gassier, H.. Interactive relations between university and firms: empirical evidence for Austria [J]. Journal of Technology Transfer,2001 (26):255-268.
    Antonio Gutier rez Gracia, Peter Voigt, JonMikel Zabala Iturriagagoitia. Evaluating the Performance of Regional Innovation Systems [C].5th Triple Helix Conference on "The Capitalization of Knowledge:Cognitive. Economic, Social &Cultural aspects" Turin,2005:18-21.
    Nasierowski W, Arcelus FJ. On the Efficiency of National Innovation Systems [J]. Socioeconomic Planning Sciences,2003 (37):215-234.
    Maria A. The Evaluation of Regional Innovation and Cluster Policies:Looking for New Approaches [C]. Conferencepaper on "decentralization and Evaluation", Lausanne,2000.
    Bhutto, A.. Rashdi. P. I., & Abro, Q. M.. Indicators for science and technology policy in Pakistan:Entering the science, technology and innovation paradigm[J]. Science and Public Policy, 2012 (39):1-12.
    Feller, I.. Performance measures as forms of evidence for science and technology policy decisions [J]. Journal of Technology Transfer,2013,38 (5):565-576.
    Jung, H. J., & Lee, J.. The impacts of science and technology policy interventions on university research:Evidence from the US National Nanotechnology Initiative [J]. Research Policy,2014, 43 (1):74-91.
    Kun, L.. Complexity in Science and Technology Policy... Symptoms or Disease? [J]. Ieee Technology and Society Magazine,2012,31 (1):11-14.
    Mayer, H.. Catching Up:The Role of State Science and Technology Policy in Open Innovation [J]. Economic Development Quarterly,2010,24 (3):195-209.
    Mugunieri, G. L., Omamo, S. W., & Obare, G. A.. Agricultural Science and Technology Policy System Institutions and Their Impact on Efficiency and Technical Progress in Kenya and Uganda [J]. Journal of Agricultural Science and Technology,2011,13 (1):1-15.
    Parthasarathy, S.. Breaking the expertise barrier:understanding activist strategies in science and technology policy domains [J]. Science and Public Policy,2010,37 (5):355-367.
    Sarewitz, D., & Rip, A.. Special Issue:An Agenda for Science and Technology Policy Studies? Emerging Themes from the Work of Young Scholars A Forward Look [J]. Minerva,2012,50 (2): 143-148.
    Su, H. N.. Visualization of Global Science and Technology Policy Research Structure [J]. Journal of the American Society for Information Science and Technology,2012,63 (2):242-255.
    Thomas, H., Fressoli, M., & Becerra, L.. Science and technology policy and social ex/inclusion: Analyzing opportunities and constraints in Brazil and Argentina [J]. Science and Public Policy, 2012,39 (5):579-591.
    Moenaert. R. K, et al. Communication Flows in International Product Innovation Teams[J]. Journal of Product Innovation Management,2000 (17):360-377.
    Wu, Y. C., Lin, B. W., Shih, C., & Chen, C. J.. Communicating and prioritizing science and technology policy using AHP [J]. Innovation-Management Policy & Practice,2013,15 (4): 437-451.
    Ringuest J. L. Lp-metric Sensitivity Analysis for Single and Multi Attribute Decision Analysis [J]. European Journal of Operations Research,1997 (98):563-570.
    MasudaT. Hierarchical Sensitivity Analysis of the Priorities Used in Analytic Hierarchy Process [J]. Systems Science,1990,21 (2):415-427.
    PENNINGS E. LINT O·Market entry, phased roll out or abandonment? A real option approach [J]. Euro J Operational Res,2000 (124):125-138.
    Fare R, Grosskopf S. Network dea[J]. Socio-economic planning sciences,2000,34 (1):35-49.
    K P Sycara. Multi-Agent Systems [J]. A IMagazine,1998,19 (2):79-92.
    Ian McBriar, Colin Smith, Geoff Bain, et al. Risk, Gap and Strength:Key Concep ts in KnowledgeManagement [J]. Knowledge-Based Systems,2003,16 (1):29-36.
    Von Hippel E. "Sticky Information" and the Locus of Problem Solving:Implication for Innovation [J]. Management Science,1994, (40):429-439.
    Marjolein C J. Canids and Bart Verspagen. Barriers to Knowledge and Regional Convergence in an Evolutionary modal [J]. Journal of Evolutionary Economies,2001 (11):307-329.
    Bauer, K ath leen. Trend s in Electronic Content at the Crushing/Whitney Medical Library: 1999-2003 [J]. Journal of Electronic Resources in Medical Libraries,2004,1 (4):31-43.
    Max Hoisot. Is Your Firm a Creative Destroyer Competitive Learning and Knowledge Flows in the Technological Strategies of Firm [J]. Research Policy,1995 (24):489-506.
    Jeffrey L Cummings, Bing-Sheng Teng. Transferring R&D Knowledge:the Key Factors Affecting Knowledge Transfer Success [J]. Manage,2003, (20):39-68.
    F Re R, Grosskopf S, Norris M, et al. Productivity growth, technical progress, and efficiency change in industrialized countries [J]. The American Economic Review,1994,84 (1):66-83.
    Caves D W, Christensen L R, Diewert W E. The economic theory of index numbers and the measurement of input, output, and productivity [J]. Econometrica:Journal of the Econometric Society,1982,50 (6):1393-1414.
    F Re R, Grosskopf S, Lovell C A K, et al. Multilateral productivity comparisons when some outputs are undesirable:a nonparametric approach [J]. The review of economics and statistics,1989,71 (2):90-98.
    Chesbrough, H. Managing open innovation [J]. Research Technology Management,2004,47(1): 23-26.
    Christensen, Clayton M. & Overdorf, Michael. Meeting the Challenge of Disruptive Change [M]. Harvard Business Review,2000.
    Cohendet. P, Meyer-Krahmer. F. The Theoretical and Policy Implications of Knowledge Codification [J]. Research Policy,2001 (30):1563-1591.
    肖士恩,雷家篌等.科技创新政策评估的理论与方法初探[J].中国科技论坛,2003(5):24-27.
    肖士恩.基于创新型社会的地方科技创新政策评估理论研究[J].科技进步与对策,2010(1):103-105.
    赵峰,张晓丰.科技政策评估的内涵与评估框架研究[J].北京化工大学学报:社会科学版,2011(1):25-31.
    张晓丰,赵峰.科技政策评估的方法论体系及相关性研究[J].北京化工大学学报(社会科学版),2012(2):1-6.
    拉雷·N·格斯顿.公共政策的制定:程序和原理[M].朱子文译.重庆:重庆出版社,2001.
    高兴武.公共政策评估:体系与过程[J].中国行政管理,2008(2):58-62.
    托马斯·戴伊.理解公共政策[M].北京:华夏出版社,2004.
    弗兰克·费希尔.公共政策评估[M].北京:中国人民大学出版社,2003.
    威廉·N,邓恩.公共政策分析导论[M].北京:中国人民大学出版社,2002.
    陈振明.政策科学—公共政策分析导论[M].北京:中国人民大学出版社,2003.
    张金马.公共政策分析:概念·过程·方法[M].北京:人民出版社,2004.
    和经纬.中国公共政策评估研究的方法论取向:走向实证主义[J].中国行政管理,2009(9):118-124.
    赵修卫.现代科技创新政策发展的四个特点[J].科学学研究,2006(6):895-899.
    任锦鸾,吕永波等.提高我国创新政策水平的综合思考[J].科技进步与对策,2007(2):1-4.
    石先珏,薛慧.我国科技创新法律制度存在的问题及其完善研究[J].科技进步与对策,2009(23):119-122.
    赵新力,仪德刚.建国以来党的三代中央领导集体的科技理论与政策创新及其启示[J].党的文献,2006(5):61-64.
    连燕华.关于技术创新政策评估的探索—鼓励企业加大技术开发投入的财税优惠政策评估[J].中国青年科技,2007(2):4-8.
    彭富国.中国科技政策发展阶段研究[J].湖南社会科学,2006(6):25-28.
    王伟宜.新中国50年科技政策的发展[J].科技管理研究,2000(6):49-53.
    李晓轩,杨国梁等.科技政策学(SoSP):科技政策研究的新阶段[J].中国科学院院刊,2012(6):538-544.
    杨国梁,肖小溪等.美国STARMETRICS项目及对我国科技评价的启示[J].科学学与科学技术管理,2011(12):12-25.
    肖小溪,杨国梁等.美国科技政策方法学及其对我国的启示[J].科学学研究,2011(7):961-964.
    樊春良,马小亮.美国科技政策学的发展及其对中国的启示[J].中国软科学,2013(10):168-181.
    周华东,王海燕等.推进科学政策的决策科学化——解读美国科学政策学建设工作[J].科学学研究,2012(11):1601-1606.
    牟杰,杨成虎.公共政策评估:理论与方法[M].北京:中国社会科学出版社,2006.
    李洁.我国公共科技政策制定及其评估体系的建立研究[D].燕山大学,2008.
    陈尧.重庆市科技政策效果评估与建议[D].重庆大学,2005.
    段君伟.广东省技术创新政策实施效果评估研究[D].暨南大学,2007.
    郑启军.浙江省自主创新政策的绩效评估及优化路径研究[D].浙江大学,2013.
    郝莹莹.欧盟科技政策及其区域效应研究[D].华东师范大学,2007.
    邹林全.科技创新政策绩效评估指标体系的设计[J].中国管理信息化,2010(1):50-53.
    彭富国.中国地方技术创新政策效果分析[J].研究与发展管理,2003(3):17-21.
    李国平,陈福明等.地方科技政策法规绩效评估与建议[J].科技进步与对策,2009(2):87-90.
    仲为国,彭纪生等.政策测量、政策协同与技术绩效:基于中国创新政策的实证研究(1978-2006)[J].科学学与科学技术管理,2009(3):54-60.
    庞宇,崔玉亭.日本的政策评估体系和实践及其对中国科技评估的启示[J].中国科技论坛,2012(3):148-155.
    欧阳进良,张俊清等.我国科技评估与评价实践的分析与探讨[J].中国科技论坛,2010(5):5-8.
    阮守武,陈来.关于构建公共政策评估机制的理论思考[J].经济研究参考,2009(29):55-65.
    叶胡,宋伟等.基于两阶段集中式CCR-DEA模型的科技政策绩效评估分析[J].中国科技论坛,2012(12):27-33.
    程华,钱芬芬.政策力度、政策稳定性、政策工具与创新绩效——基于2000—2009年产业面板数据的实证分析[J].科研管理,2013(10):103-108.
    冯锋,汪良兵.协同创新视角下的区域科技政策绩效提升研究——基于泛长三角区域的实证分析[J].科学学与科学技术管理,2011(12):109-115.
    李伟铭,崔毅等.技术创新政策对中小企业创新绩效影响的实证研究——以企业资源投入和组织激励为中介变量[J].科学学与科学技术管理,2008(9):61-65.
    刘世锦等.通过体制改革和政策调整为创新提供动力[C]//激励创新:政策选择和案例研究.北京:知识产权出版社,2008.
    江静.公共政策对企业创新支持的绩效:基于直接补贴与税收优惠的比较分析[J].科研管理.2011(4):1-8.
    颜莉.我国区域创新效率评价指标体系实证研究[J].管理世界,2012(5):174-175.
    苏靖.关于国家创新系统的基本理论、知识流动和研究方法[J].中国软科学,1999(1):59-61.
    刘顺忠,官建成.区域创新系统创新绩效的评价[J].中国管理科学,2002(1):75-78.
    成良斌.论科技政策的本质和目的[J].科技管理研究,2002(4):1-4.
    张永安,李晨光.创新科技政策及其三阶段周期研究[J].科学学与科学技术管理,2012(4):20-26.
    罗伟,连燕华等.技术创新与政府政策[M].北京:人民出版社,1996.
    陈勇鸣,陈辉等.创新的瓶颈与突破:上海自主创新的体制、环境和政策研究[M].上海:上海人民出版社,2010.
    董书礼,齐琪.区域创新体系中的知识流动及其政策涵义[J].西安财经学院学报,2004(17):85-87.
    宋伟,张华伦.知识流动视角下我国国家创新系统的演进历程[J].科技管理研究,2013(14):6-9.
    张华伦,宋伟等.先进技术研究院探析——政产学研用协同新模式研究[J].中国高校科技,2014(3):64-66.
    范丹宇,金峰.创新系统中的知识流动与转化分析[J].科技管理研究,2006(10):224-228.
    范丹宇,金峰.创新系统中知识流动的机理及其影响因素[J].科技管理研究,2006(6):92-95.
    李久平.国家创新系统中知识流动的有效组织模式:知识联盟[J].情报科学,2003(21):266-268.
    曾德明,王业静等.基于知识流动视角的国家创新系统与创新政策体系互动关系研究[J].湖南大学学报(社会科学版),2009(23):39-43.
    高鹏.论区域创新系统中的知识流动[J].产业与科技论坛,2007(6):87-89.
    李顺才,邵凤英.区域创新系统中的知识流动障碍及其化解[J].管理学报,2006(3):109-112.
    汪涛,任瑞芳等.知识网络结构特征及其对知识流动的影响[J].科学学与科学技术管理,2010(5):150-155.
    张晓丰,赵峰.科技政策评估的方法论体系及相关性研究[J].北京化工大学学报(社会科学版),2012(2):1-6.
    劳伦斯·纽曼.社会研究方法:定量与定性的取向[M].郝大海,译.北京:中国人民出版社,2007.
    李永生.我国科技政策评:作用、问题及其对策[J].科技管理研究,2011(21):24-26.
    王婧漪.科技全球化背景下的我国科技政策创新发展研究[D].成都理工大学,2011.
    陈伟.区域创新系统绩效评价研究[D].华中科技大学,2012.
    白俊红.中国区域创新效率的实证研究[D].南京航空航天大学,2010.
    杨锋.含有多个子系统的决策单元的DEA效率评估研究[D].中国科学技术大学,2006.
    陈岑.中国国家创新系统的效率评价与机制改进研究[D].武汉大学,2010.
    吕明洁.我国自主创新政策绩效评价的DEA分析——以上海市高新技术产业为例[J].经济论坛,2009(20):63-65.
    鲁贵宝,曾繁华.我国建设创新型国家的科技创新政策研究综述[J].科技进步与对策,2007(8):1-4.
    李正风,曾国屏.OECD国家创新系统研究及其意义——从理论走向政策[J].科学学研究,2004(2):206-211.
    万钢,李学勇等.中国科技改革开放30年[M].北京:科学出版社,2008.
    李石柱,李冬梅等.影响我国区域科技资源配置效率要素的定量分析[J].科学管理研究,2003(2):60-63.
    刘洪伟,和金生等.知识发酵——知识管理的仿生学理论初探[J].科学学研究,2003(5):514-518.
    和金生,唐建生.基于知识发酵理论的知识管理系统框架研究[J].工业工程,2004(7):10-13.
    陈劲,柳卸林.自主创新与国家强盛[M].北京:科学出版社,2008.
    樊春良.全球化时代的科技政策[M].北京:北京理工大学出版社,2005.
    胡志坚.国家创新系统:理论分析与国际比较[M].北京:社会科学文献出版社,2000.
    克里斯托夫·弗里曼.日本:一个新国家创新系统[M].北京:经济科学出版社,1991.
    刘云,常青.中国基础研究国际合作的科学计量测度与评价[J].管理科学学报,2011(1):37-47.
    涂振洲,顾新.基于知识流动的产学研协同创新过程研究[J].科学学研究,2013(9):1381-1390..
    熊小刚.跨区域创新系统的协同发展研究[J].科技与管理,2013(1):39-42.
    崔禄春.建国以来中国共产党科技政策研究[M].北京:华夏出版社,2002.
    顾建光.公共政策分析学[M].上海:上海人民出版社,2004.
    徐士钮.宏观科技政策研究——中国R&D投资国际比较分析[M].上海:同济大学出版社,1993.
    经济合作与发展组织.弗拉斯卡蒂研究与发展手册[M].北京:新华出版社,2000.
    叶茂林.科技评价理论与方法[M].北京:社会科学文献出版社,2007.
    李永生.我国科技政策评估:作用、问题及其对策[J].科技管理研究,2011(21):24-26.
    李正风,曾国屏.创新研究的“系统范式”[J].自然辩证法通讯,1999(5):29-34.
    顾新,李久平等.知识流动、知识链与知识链管理[J].软科学,2006(2):10-16.
    马旭军.区域创新系统中知识流动的重要性分析[J].经济问题,2007(5):19-20.
    谢守美.知识生态系统知识流动的生态学分析[J].图书馆学研究,2009(5):7-10.
    王兴成.日本的科技政策[J].国外社会科学,1978(6):54-60.
    杨沛霆.外国技术引进政策的比较分析[J].世界经济,1978(4):50-59.
    余佩馄,林水山.基于分形理论的中国区域创新系统绩效研究[J].技术经济与管理研究,2005(4):25-29.
    王海盛,郑立群.区域创新系统创新绩效测度研究[J].安徽工业大学学报(社会科学版),2005(11):39-40.
    刘顺忠,官建成.区域创新系统创新绩效的评价[J].中国管理科学,2002(1):75-78.
    韩振海,李国平.国家创新系统理论的演变评述[J].科学管理研究,2004(2):24-26.
    刘朝马.国家创新系统的研究现状与展望[J].科技进步与对策,2006(4):5-7.
    曹洋,陈士俊.科技中介组织在国家创新系统中的功能定位及其运行机制研究[J].科学学与科学技术管理,2007(4):20-24.
    连燕华,国家创新系统的一种新的分析框架[J].科学学研究,2000(4):71-75.
    郭淑芬.我国国家创新系统的演进历程[J].自然辩证法研究,2010(11):551-62.
    周元,王海燕.关于我国创新体系研究的几个问题[J].中国软科学,2006(10):15-19.
    赵兰香,方新.模块重构:构建我国国家创新系统的新思路[J].科学学与科学技术管理,2005(11):64-68.
    陈丽娜,胡树华.知识创新与国家创新系统[J].科技与经济,2004(5):9-12.
    吴颖,钟海粒.国家创新系统中知识产权战略作用机制研究[J].知识产权,2012(8):73-76.
    周毓萍,郭庆.我国国家创新系统的结构和特点[J].科技管理研究,2000(4):6-8.
    魏权龄,庞立永.链式网络DEA模型[J].数学的实践与认识,2010,40(1):213-221.
    李凌,刘建永.综合网络DEA模型有效性理论分析[J].系统工程,2010,28(1):53-57.
    魏权龄.论“打开黑箱评价”的网络DEA模型[J].数学的实践与认识,2012,42(24):184-195.
    顾新,李久平等.知识流动、知识链与知识链管理[J].软科学,2006,20(2):10-12.
    胡延平,刘晓敏.基于SECI模型的知识创新过程的再认识[J].管理纵横,2009(3):45-48.
    夏敬华,金昕.知识管理[M].北京:机械工业出版社,2003.
    应力,钱省三.知识管理的内涵[J].科学学研究,2001,19(1):64-69.
    华连连,张悟移.知识流动及相关概念辨析[J].情报杂志,2010,29(10):112-116.
    聂鹏,王向.协同创新视角下环渤海区域科技政策绩效优化研究[J].经济问题探索,2013(3):69-72.
    李建民.中日两国科技政策绩效差异分析[J].国家行政学院学报,2009(4):97-102.
    蒋栋,李婷.自主创新科技政策在河北省的实施效果评价[J].中国软科学(增刊上),2009:88-92.
    管书华.科技政策制定与评价的研究[D].武汉理工大学,2004.
    匡跃辉.科技政策评估:标准与方法[J].科学管理研究,2005,(12):62-65.
    王春明,黄宁.完善广西公共科技政策实施效果评估的制度研究[J].2009(20):4-8.
    金振辉,汪善荣等.浅谈我国科技评价的理论、方法和实践[J].改革与探索,2006(4):20-23.
    丁福虎.科技评价指标设置的误区[J].科学管理研究,2002(3):38-41.
    李阳成.科技评价管理与区域创新体系建设[J].发展研究,2007(3):4546.
    刘继芬.国外科技评估机构、方法的比较研究及对我国的科技成果管理工作的启示[J].农 业科技管理,2001(1):50-53.
    王琳娜.基于“第三方”视角的中国特色科技评价体系研究[D].济南大学,2012.
    项杨雪.基于知识三角的高校协同创新过程机理研究[D].浙江大学,2013.
    张子刚,周永红.知识管理对企业技术创新过程的能动效应及其机理分析[J].科学学与科学技术管理,2004(3):45-49.
    徐芳,杨国梁等.基于知识创新过程的科技政策方法论研究[J].科学学研究,2013,31(4):510-517.

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