| As China is in the period of economic transformation and upgrading,economic growth is increasingly dependent on technological innovation.Known as the most active technology innovation industry in the knowledge economy era,high-tech industry has become a new driving force and key point for China's economic growth during the transition period,and it is also of great importance for international technology and economic competition.Improving the innovation efficiency of high-tech industries and enhancing industrial competitiveness have a major impact on increasing China's innovation capabilities,adjusting industrial structure,and transforming economic development methods.In recent years,China has invested a large amount of labour and funds and introduced a series of policy measures to support the development of high-tech industries.The Outline of the National Medium-and Long-Term Science and Technology Development Plan(2006-2020)clearly states that “it is of great significance to promote the efficient allocation and comprehensive integration of science and technology resources in the whole society”.Therefore,the important and urgent task for improving the innovation capability of China's high-tech industry under the new situation is to judge the actual efficiency level,clarify the factors affecting the innovation efficiency,in order to adjust and optimize the allocation of resources in a targeted manner.In recent years,China has invested a large amount of labour and funds and introduced a series of policy measures to support the development of high-tech industries.The Outline of the National Medium-and Long-Term Science and Technology Development Plan(2006-2020)clearly states that “it is of great significance to promote the efficient allocation and comprehensive integration of science and technology resources in the whole society”.Therefore,the important and urgent task for improving the innovation capability of China's high-tech industry under the new situation is to clarify the factors affecting the innovation efficiency,judge the actual efficiency level,in order to adjust and optimize the allocation of resources in a targeted manner.This thesis attempts to evaluate the current situation of China's high-tech industry innovation efficiency,and find out the main direction of improving the innovation efficiency by clarifying relevant influencing factors.Specifically,based on the theory of technological innovation and efficiency evaluation,related literatures on high-tech industries are sourted out and summarized,technological innovation,and efficiency analysis both in China and abroad.First,a reasonable research framework is established,along with a two-stage DEA model with additional intermediate inputs;Then,the innovation efficiency of China's high-tech industry is measured and analyzed by region;Afterwards,under the same efficiency level,the Bayesian model averaging method is used to analyze the main factors affecting the innovation efficiency of high-tech industries,explore the causes of efficiency differences and establish the direction of improvement;Finally,the corresponding policy recommendations are proposed to the analysis results of the two-stage DEA model and the Bayesian model averaging method.The main work and conclusions are as follows:First,based on domestic and foreign theories and literatures,this thesis starts with the concept and definition of high-tech industry,and analyzes the relevant literatures on innovation efficiency evaluation,Bayesian model averaging method and their applied researches.The focal point of this part is applied research of the DEA model and the Bayesian model averaging method,which sets the theoretical foundation of the empirical analysis.Secondly,model construction and empirical research is carried out.By constructing a two-stage efficiency analysis framework for high-tech industries,a two-stage high-tech industrial innovation efficiency evaluation DEA model based on the framework is build,and then use the model to measure and evaluate the innovation efficiency of China's high-tech industries.The analysis results show that the innovation efficiency of China's high-tech industry is not very satisfactory,the overall average is only 0.501,and the innovation efficiency between regions is significantly different;Therefore,there is an inconsistency in the efficiency of the technology R&D stage and the achievement transformation stage in the high-tech industry.Since 2008,the efficiency of the technology research and development stage is higher than the production efficiency,and the comprehensive innovation efficiency is mainly dominated by production.With the inconsistency between the efficiency of the technology R&D stage and the achievement transformation stage,the high-tech industry in most parts of China belongs to the development mode of High-tech R&D efficiency and low efficiency of transformation.Third,based on the measurement and evaluation of innovation efficiency,the uncertainty of the model is introduced At the same level of efficiency,the Bayesian Model Average(BMA)method is used to analyze the main factors affecting the innovation efficiency of high-tech industries,explore the causes of the differences in efficiency and the direction of improvement,and set the different models of prior hypotheses to conduct a robustness test in empirical results.The analysis results show that R&D capital investment,enterprise scale and government support are the most influential factors.R&D capital investment and enterprise scale have a significant positive impact on the comprehensive innovation efficiency of high-tech industries,and the degree of government support has the opposite impact.Finally,according to the relevant theoretical and empirical analysis results,this thesis put forward some specific countermeasures and suggestions,and the prospect of further research from the perspective of R&D investment,resource allocation,enterprise scale,etc.The research results of this thesis are part of the National Natural Science Foundation's “study on the model,path & organization of industry transfer under the constrains & guidance of new-type urbanization”(71473037).The research results of “The influencing Factors Analysis of Chinese High-tech Industry Innovation Performance——Based on the Bayesian Model Averaging(BMA)Method” were presented at the 5th Global Innovation and Entrepreneurship Conference(GEIC)held at the University of Amsterdam,Netherlands in October 2018.The report was praised by the host and scholars during the meeting. |
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