广东省大中型工业企业技术创新效率及影响因素研究

发布时间：2018-05-04 22:22

本文选题：广东省 + 大中型工业企业　；参考：《华南理工大学》2013年硕士论文

【摘要】：大中型工业企业是我国经济发展中的重要支柱力量，而广东又是我国第一经济大省，伴随着各个地区的经济在金融危机中逐渐复苏，技术创新已成为决定地区大中型工业企业持续快速发展，影响区域经济增长与区域综合竞争力的关键因素。如何才能认清广东技术创新效率的现状，加快技术创新的步伐，提高技术创新效率，使广东从制造大省转变为以科技进步为依托的创新强省，转变广东大中型工业企业的经济增长方式，已经成为目前要研究的重要课题。论文在深入分析前人研究和相关理论的基础上，主要在两个方面有所创新：一是建立了针对技术创新系统的混联网络DEA模型，打开了技术创新过程这个“黑箱”；二是设计出针对混联创新系统的一整套分阶段的投入产出指标体系对广东省技术创新效率进行了评价。然后，本文以算出的技术创新效率结果为基础分别从创新资源配置、市场结构和制度环境三方面提出了影响广东大中型工业企业技术创新效率的八个测度变量，，并运用Tobit回归模型对影响技术创新效率的八个主要因素进行了测度和分析。本文实证结果表明：混联网络DEA模型在效率评价上鉴别能力更强，也能更好的反映混联创新系统的前沿生产能力；广东的技术转化效率要高于技术研发效率，而导致技术研发效率较低的原因在于规模效率较低，导致技术转化效率不高的原因是由于纯技术效率较低；在本文模型下测算的广东的系统效率值相对于传统模型，排名出现了下滑，究其原因主要是两个子系统间的协调效率较低。研发投资强度、企业成长能力、市场集中度、对外开放程度、政府的科技投入增加对技术创新效率的提高起促进作用；企业资产规模、国有企业比重的增加实际上却对技术创新效率的提高起到了反作用；人力资本投入存在浪费并且效率低下，没有对技术创新效率的提升起到显著正向作用，人才的创新积极性和作用并没有被有效发挥。
[Abstract]:Large and medium-sized industrial enterprises are an important pillar in the economic development of our country, and Guangdong is also the largest economic province in China. With the gradual recovery of the economy in various regions in the financial crisis, Technological innovation has become a key factor that determines the sustained and rapid development of regional large and medium-sized industrial enterprises and affects regional economic growth and regional comprehensive competitiveness. How can we recognize the present situation of Guangdong's technological innovation efficiency, speed up the pace of technological innovation, improve the efficiency of technological innovation, and transform Guangdong from a major manufacturing province into a strong province of innovation based on scientific and technological progress? Changing the economic growth mode of Guangdong large and medium-sized industrial enterprises has become an important subject to be studied. On the basis of in-depth analysis of previous studies and related theories, this paper mainly innovates in two aspects: first, a hybrid network DEA model for technological innovation system is established, which opens the "black box" of technological innovation process; The second is to design a set of input-output index system to evaluate the efficiency of technological innovation in Guangdong province. Then, based on the calculated results of technological innovation efficiency, this paper puts forward eight measurement variables that affect the technological innovation efficiency of Guangdong large and medium-sized industrial enterprises from three aspects: the allocation of innovative resources, the market structure and the institutional environment. Tobit regression model is used to measure and analyze the eight main factors that affect the efficiency of technological innovation. The empirical results show that: The DEA model of hybrid network is more effective in efficiency evaluation and can better reflect the advanced production capacity of hybrid innovation system, and the efficiency of technology transformation in Guangdong is higher than that of technology research and development. The reason for the low efficiency of technology research and development lies in the low efficiency of scale, and the reason of the low efficiency of technology transformation is the low efficiency of pure technology. Ranking has declined, the main reason for the two subsystems between the coordination efficiency is low. The intensity of R & D investment, the ability of enterprise growth, the degree of market concentration, the degree of opening to the outside world, and the increase of government investment in science and technology play an important role in improving the efficiency of technological innovation. In fact, the increase of the proportion of state-owned enterprises is counterproductive to the improvement of the efficiency of technological innovation; the investment of human capital is wasteful and inefficient, and it does not play a significant positive role in improving the efficiency of technological innovation. The innovative enthusiasm and role of talents have not been effectively brought into play.
【学位授予单位】：华南理工大学
【学位级别】：硕士
【学位授予年份】：2013
【分类号】：F273.1;F427

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