高专利密集度产业创新效率及影响因素研究——基于DEA-Malmquist指数和Tobit模型  

Research on the Innovation Efficiency and Affecting Factors of High Patent Intensity Industry Based on the DEA- Malmquist Index and Tobit Method

作　　者：陈伟[1] 刘锦志[1] 杨早立[1] 周文[1] 

机构地区：[1]哈尔滨工程大学经济管理学院,黑龙江哈尔滨150001

出　　处：《科技管理研究》2015年第21期1-6,共6页Science and Technology Management Research

基　　金：国家社科基金项目"区域知识产权战略管理系统协同与产业升级研究"(14BGL007);黑龙江省自然科学基金项目"军民结合企业持续创新能力形成机理及评价方法研究"(G201209)

摘　　要：高专利密集度产业的创新效率影响着高专利密集度产业的自主创新能力水平和产业竞争力。运用DEAMalmquist指数和Tobit模型对我国高专利密集度产业创新效率及其影响因素进行实证研究。研究发现,我国高专利密集度产业规模效率不高,但整体创新效率呈现上升趋势。在此基础上采用Tobit模型回归分析高专利密集度产业创新效率的影响因素,发现政府支持力度、产业科技水平、企业规模、从业人员素质与创新效率正相关,产业聚集度与高专利密集度产业创新效率高度负相关。结合上述分析,给出提高我国高专利密集度产业创新效率的对策及建议。The innovation efficiency of high patent intensity industry affects independent innovation ability and competitive- ness of the industry. This paper uses DEA - Malmquist index analysis method to make an empirical analysis on the innova- tion efficiency and the influencing factors of our national high patent intensity industry. From the analysis, we learn that the scale efficiency of the high patent intensity industry is not very high, but the innovation efficiency of the whole industry is improving. On this basis, we use the Tobit regression model method to analyze the influencing factors of innovation efficien- cy of high patent intensity industry. As a result, we find that the government support, the level of the industry＇ s technolo- gy, the scale of enterprises, the qualities of relative employees have positive correlations with the innovation efficiency. Be- sides, the industry agglomeration degree has a negative correlations with the innovation efficiency. Finally, combining of the above analysis, we make proposals to improve the innovation efficiency of high patent intensity industry.

关 键 词：高专利密集度产业 创新效率 DEA—Malmquist TOBIT模型 

分 类 号：F204[经济管理—国民经济] F224