A Three-stage DEA Study on The Efficiency of Global Intelligent Innovation Based on Big Data

Abstract

With the global intelligent technology coming, governments and organizations of various countries are speeding up the strategic layout of intelligent technology and competing to occupy the strategic commanding heights in global intelligent innovation. In this study, 101 countries from 18 regions were selected as samples. Based on the spiral collaborative innovation theory, from the perspectives of politics, industry, research, study and application, the number of Top 600 universities in the world majoring in computer science, R&D investment of hightech enterprises, and e-government investment level were selected as the input variables of intelligent innovation. Intelligence number of published papers linked with intelligent innovation, national high-tech exports, the government maturity level of artificial intelligence as the output variables. We use those input and output data to do the first stage DEA. Then, we choose the set up the number of national science and technology award, the average GDP growth rate nearly three years, intelligent technology industry in compensation levels, ICT development level as 4 environment variables, to figure out SFA analysis as the second stage DEA. Next we use three-stage DEA method to research global intelligent innovation efficiency with and without environment variables, and we find intelligent innovation efficiency presents obvious space characteristic: North America, Oceania and other regions to eliminate environment variables before and after the intelligent innovation efficiency is very high, West Africa, South Asia and other regions in the environment variable influences intelligent innovation efficiency improved significantly, and finally this study to provide path for intelligent innovation low efficiency region to improve their innovative efficiency of intelligent innovation development.