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Research On Urban Scientific And Technological Innovation Ability And Innovation Efficiency In China

Posted on:2020-09-07Degree:MasterType:Thesis
Country:ChinaCandidate:D Y WangFull Text:PDF
GTID:2439330623960029Subject:Management Science and Engineering
Abstract/Summary:PDF Full Text Request
China's innovation resources are mainly concentrated in cities.Cities play a pivotal role in regional innovation-driven development.The improvement of urban innovation capability and innovation efficiency directly affects the regional and national technological and economic competitiveness.However,there are great regional differences in China's economic development.In order to narrow regional differences in the new round of innovation-driven development,it is necessary to reduce the gap between urban innovation capabilities and levels.To this end,this thesis is based on regional innovation systems,innovation management and other theories,the factor analysis method,the three-stage DEA-Malmquist method and convergence analysis method are used to analyze and evaluate the innovation ability and innovation efficiency of major cities in China and Jiangsu.Firstly,the thesis defines the concepts of technological innovation,regional innovation system,innovation capability and innovation efficiency,clarifies the purpose of analysis and corresponding analysis content,and discusses the choice of analytical methods.Secondly,factor analysis are used to analyze and evaluate the innovation ability of major cities in China and Jiangsu Province.This method is used to summarize the selected innovation capability indicators,and the main components that influence the city's innovation ability are innovation input and economic level factors,innovation output factors,education level and population quality factors,then calculate the innovation ability scores of each city according to the weight of the factor analysis method.The results show that the innovation ability between the sub-provincial cities in China and the cities in Jiangsu Province is quite different,appearing a distinct regional distribution feature.Moreover,the rankings of different cities in different main components are very different,and the factors affecting the innovation ability of each city are very different.Thirdly,using the three-stage DEA method and the Malmquist method,the innovation efficiency of urban and sub-provincial cities in Jiangsu Province is analyzed from both dynamic and static perspectives.The results show that the innovation efficiency of different regions in Jiangsu Province and sub-provincial cities has not been effective before and after adjustment,and there are obvious differences between different cities.The regional innovation efficiency is not completely consistent with its innovation ability level and economic development level.From a dynamic perspective,the TFP index in Jiangsu Province has increased by 0.1% and the Technology Progress Index has been 1.The overall TFP index of the sub-provincial cities is 1,while the technical efficiency has declined by 0.2%.Technological progress is the main factor to promote regional production efficiency.At the same time,the analysis found that urban innovation efficiency is affected by environmental factors.Finally,the ? convergence and ? convergence methods are used to analyze the convergence of innovation efficiency in cities in Jiangsu Province and sub-provincial cities.The results show that the difference in innovation efficiency of cities in Jiangsu Province is gradually narrowing,but there are differences in the convergence trends of the three major regions in the province,and the efficiency convergence of each region is mainly affected by government support and labor quality.The overall efficiency fluctuations of the sub-provincial cities are more stable than those in Jiangsu Province,but the innovation efficiency among the various internal regions shows different convergence trends,and the factors affecting the efficiency convergence of each region are quite different.
Keywords/Search Tags:innovation ability, innovation efficiency, factor analysis method, three-stage DEA, Malmquist index, convergence analysis
PDF Full Text Request
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