Research On R&D Output Efficiency Of China's Manufacturing Industry

The research on the efficiency of R&D input and out put has been a topic of increasing concern to many scholars in recent years,With the rapid development of manufacturing,various industries,especially high-tech industries,have played a significant role in China's economic development.Output efficiency is an embodiment of industrial technology and business capabilities,and is an important indicator for measuring industrial competitiveness.Therefore,it is necessary to analyze and evaluate the efficiency of manufacturing R&D input and output.This paper uses the data envelopment analysis method to measure and analyze the comprehensive technical efficiency,pure technical efficiency,and scale effect of China manufacturing industry.First,the super efficiency SBM model is used to analyze the data of31sub-categories of China's manufacturing industry for 2012 to 2015.Each year,the static value of the comprehensive technical efficiency of each industry understands the current status of R&D input-output efficiency.At the same time,the super-efficiency SBM model is used to compare and analyze the 2015 test results that consider undesired output and do not consider undesired output.The amount of slack in the variable is analyzed,and the amount of slack in the inefficiency evaluation object can be analyzed,and suggestions for improving efficiency can be proposed for each variable.Since the actual process of research anddevelopment is accompanied by the generation of innovation losses,the models used in this paper all consider non-efficiency,Expected output SBM model.As the lag effect of new product R&D investment will generally be reflected in a longer period of time,the reverse lag effect of new product sales revenue is correspondingly due to the diversification of the sensitivity of new product R&D in the industry.Therefore,this trend also needs to he reflected in a longer time interval.Therefore,this paper uses the VAR model and impulse response function based on long-term sequences as analysis tools to ensure the reliability and scientificity of the analysis results.The research in this paper shows that the overall efficiency values of the 31 manufacturing industries in 2015 are quite different,indicating that the overall performance of the manufacturing industry has experienced a two-level differentiation phenomenon.The overall technical efficiency values of most manufacturing industries in2012-2015 were relatively low,low,indicating that most manufacturing industries have low output efficiency in the R&D investment process,and need to improve resource allocation and scientific research capabilities.The impulse response analysis method is used to invest in new product research and development and new product sales in high-tech industries and traditional manufacturing industries,The analysis of the two-way lag effect between them shows that the R&D investment of high-techindustry manufacturing industry has a relatively obvious relationship with the sales revenue of new products,while the relationship between R&D investment and output of traditional manufacturing industry is not significant.The effective allocation of input resources and the transformation of new product research and development results promote the efficiency of manufacturing research and development inputs and outputs.