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The Shift Towards Innovation-driven Manufacturing:A Study On Its Stages,Influencing Factors And Paths

Posted on:2018-11-12Degree:MasterType:Thesis
Country:ChinaCandidate:M Y LiaoFull Text:PDF
GTID:2429330596954713Subject:Applied Economics
Abstract/Summary:PDF Full Text Request
Manufacturing industry is the main body of the national economy,the foundation of the country,showing self-evident importance.While manufacturing industries around the world have been on the intelligentialized and informationized way,with innovation as the core competitiveness of the industry,China's traditional manufacturing model cannot continue.On this background,the study on China's manufacturing industry's crrent driven stage and the Influencing factors and pathways of transformation to innovation-driven model are of great significance to accelerate the transformation of China's manufacturing industry to innovation-driven one.Based on Michael E.Porter's economically-driven stage and innovation-driven theory,this paper compares the gap between manufacturing industry in China and in the United States,Japan,Germany and Korea,and combines the innovation-driven requirements of "National Innovation-Driven Development Program" and "Manufacturing Industry 2025" to set the mark of the beginning stage of innovation-driven model.What's more,the paper not just divides the stages of innovation-driven model,and analyzes the difference between industries and areas,and tests the influencing factors of the transformation of China's manufacturing industry into an innovation-driven one by using the panel data,but also it does a further research on the road to the influencing factors of the transformation with the use of structural equation model,thus providing a theoretical basis for the transformation of China's manufacturing industry to an innovation-driven one.With the use of the input and output of China's manufacturing industry from 2000 to 2014,this paper calculates the contribution rate of scientific and technological progress of China's manufacturing industry and evaluates the stage of innovation-driven economy.It selects 24 Two-digit industries and 30 regions of China's manufacturing industry,calculates the contribution rate of scientific and technological progress and evaluates the stage of innovation-driven economy,so as to analyzes the difference between industries and areas,tests the influencing factors of the transformation of China's manufacturing industry into an innovation-driven one by using the panel data,but also it does a further research on the road to the influencing factors of the transformation with the use of structural equation model.Finally,according to the gap in manufacturing industry between China and powerful nations,the difference between industries and regions,the effect of the influencing factors and how they work,the paper makes proposals of relevant polices and suggestions.Main study conclusions:(1)From 2000 to 2014,China's manufacturing industry was at the investment-driven stage.Among the 24 Two-digit industries,20 industries were investment-driven,while the other 4 were factor-driven.Among the 30 regions selected,4 of them were factor-driven,24 were investment-driven,and 2 of them,Beijing and Shanghai,were stepping into innovation-driven stage.Since the difference between industries and regions were large,differential innovation-driven strategies should be employed.(2)Among the influencing factors,the effective patens are not very much and the technology transfer rate is low.Also,the openness imposes negative effect on the transformation to innovation-driven,attributing to the low exported products structure,“low-end” locking problems and the dependence on experts.(3)On the path of transformation to innovation-driven model,the best ways are to improve innovation input.Also,by improving enterprises' innovation willingness,institutional innovation and innovation policies are effective methods to increase the industrial innovation input.Human capital is a key factor in the transformation of manufacturing industry to innovation,which has a strong effect on all endogenous variables,and the total path coefficient is more significant.
Keywords/Search Tags:Innovation-driven, Driven stage, Influencing factors, Transition paths
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