Research On Technology Innovation Efficiency Of Big Data Enterprises Based On Two-stage DEA

In the era of big data,all major big data developing countries in the world have formulated and issued a series of policies and strategic development policies to promote the development of big data in order to better grasp the opportunities of big data development in the new industrial revolution.The related research on big data in academia at home and abroad has also set off a wave of scientific research.General Secretary Xi pointed out that the globalization of the digital economy is the general trend and our important task of promoting the integration of the digital economy and the real economy.As a part of China’s digital economy,knowledge-and technology-intensive big data companies are an important driving force.Improving the technological innovation efficiency of big data companies has important socio-economic significance for promoting the quality of China’s digital economy.In order to further improve the efficiency of technological innovation in China’s big data companies,this article starts from the perspective of the internal stages of technological innovation,and divides the technological innovation efficiency of big data companies into two parts: the efficiency of technological research and development and the efficiency of commercialization of technological results.On this basis,the overall technological innovation efficiency evaluation is performed.In terms of research methods,the author follows the principle of combining qualitative research and quantitative research for analysis.This article first uses qualitative research methods such as literature research and expert interviews to initially select the respective inputs of big data companies in the technology research and development stage and the commercialization stage of technology results.Output indicators,and then screen the primary indicators from the perspective of the relative importance of the indicators to construct the technical innovation efficiency evaluation index system of the big data enterprise in this paper.This article uses a combination of subjective and objective weighting methods to select In terms of specific index selection methods,this article integrates the application of entropy method and analytic hierarchy process to build an evaluation index system for the technological innovation efficiency of big data companies in this article.Then,this paper uses the variable envelope data analysis method(BCC-DEA))Perform a static overall evaluation on the efficiency of technology R & D and commercialization of technical results of big data companies from 2014 to 2017.Based on this,perform a static evaluation of the overall technology innovation efficiency of big data companies during the inspection period,and then use Malmquist-DEA’s technology for big data enterprises during the inspection period Dynamic evaluation of innovation efficiency and its stage efficiency;Finally,Tobit regression model was used to analyze the scale of enterprises,government subsidies,human capital,and the importance of technological innovation in enterprises.The three levels of significance of pure technology efficiency and scale efficiency.Through empirical analysis,this article draws the following main conclusions:(1)the number of R & D personnel,R & D investment funds,fixed assets and other input factors have a more important role in improving the technological innovation level of big data companies;(2)big data companies during the inspection period The overall technological innovation efficiency,technological research and development efficiency,and commercialization efficiency of technological achievements are all relatively low.The commercialization efficiency of technological achievements is a short-term link in technological innovation efficiency.The overall efficiency of overall technological innovation and technology research and development is limited by its scale efficiency,and the overall efficiency of commercialization of technological results is greatly affected by its pure technical efficiency;(3)The overall technological innovation,technological research and development,and technological achievement business of big data companies The overall total factor productivity(TFP)has also been on the decline during the inspection period.The decline in technological progress is the main reason for the decline in overall technical innovation and the commercialization of commercialized TFP.The decline in TFP in technological research and development is mainly due to its pure technical efficiency.Downside impact.The overall technical innovation and technology research and development TFP fluctuated greatly during the inspection period,and the commercialization of technical results of TFP was in a slowly rising trend during the inspection period;(4)the pure technical efficiency,scale efficiency,and technology research and development of the overall technical innovation of the enterprise scale Significantly promote efficiency,etc.;(5)Government subsidies have a certain crowding-out effect on technological innovation of big data companies;(6)The technological innovation capabilities of employees in big data companies need to be further improved;(7)the importance of technological innovation and technology The overall efficiency of R & D has a significant positive impact.