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本文构建了专利转化为新产品销售收入为产出变量的超越对数随机前沿模型,利用SFA方法对专利转化效率及其影响因素进行分析。通过对1995~2011年五个一级行业的面板数据进行分析,结果显示:(1)外资化程度、大规模企业、产业集聚等因素对专利转化效率有显著促进作用,而国有化程度、小规模企业却对专利转化效率有明显抑制作用,中型规模企业对专利转化效率影响并不显著;(2)电子计算机及办公设备制造业、电子及通信设备制造业效率值较高,航空航天器制造业效率值处于中下水平,医药制造业、医疗设备及仪器仪表制造业效率值较低;(3)各高技术产业效率值随时间发展有所改善,但速度缓慢,且各产业间的效率差异并无较大变化。基于上述结论,对我国高技术产业技术转化提出了一些建议。
In this paper, we build a transcendental logarithm stochastic frontier model of patent into new product sales revenue as output variable, and use SFA method to analyze patent transformation efficiency and its influencing factors. The panel data of five industry sectors from 1995 to 2011 are analyzed. The results show that: (1) The degree of foreign capital, large-scale enterprises and industrial agglomeration have a significant impact on patent conversion efficiency, while the degree of nationalization is small Scale enterprises have a significant inhibitory effect on the conversion efficiency of patents, and the effect of medium-sized enterprises on patent conversion efficiency is insignificant; (2) the manufacturing enterprises of electronic computers and office equipment, the manufacturing industry with high efficiency of electronics and communications equipment, the manufacturing of aerospace vehicles The efficiency value of the industry is in the middle and lower levels, and the manufacturing efficiency of the pharmaceutical manufacturing industry, medical equipment and instrumentation industries is low; (3) the efficiency values of various high-tech industries have improved over time, but at a slow pace; and the efficiency among industries There are no major changes in the difference. Based on the above conclusions, some suggestions are put forward for the technological transformation of high-tech industries in China.