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The Research On Innovation-driven Efficiency And Its Influencing Factors Of Guangdong Province

Posted on:2018-09-19Degree:MasterType:Thesis
Country:ChinaCandidate:X T HuangFull Text:PDF
GTID:2359330536477924Subject:Regional Economics
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In 2006,Chinese ? National Medium and Long-term Science and Technology Development Plan Outline(2006-2020)?opened a new era of independent innovation in our country.In the twelfh Five-year period,China proposed innovation-driven development strategy,planning to promote innovation and development with a global perspective,Guangdong Province shows a positive response to accelerate the implementation of innovation-driven development.Under the background of the new normal,Guangdong province is in a critical period of deepening reform and development,how to maintain leading position,to achieve sustained and healthy development of economy is a daunting task in this period.With the increase of innovation inputs,Guangdong province faces a question that how to take advantage of innovation resources scientifically and reasonably,and improve the innovation environment,to improve the innovation-driven efficiency.Recently,domestic scholars have carried out extensive research on innovation-driven.Existing research on innovation theory and innovation drive concept provides a certain theoretical support,but there are still insufficient.Firstly,the innovation-driven research primarily on the theory discussion,lack of empirical research;Secondly,the empirical study tend to equate innovation with input and output of innovation resources,without considering the effect of innovation of social and economic level,As we know,the ultimate aim of a country or region to increase R&D investment should be to promote social and economic development,but few studies take this into account.The main contents of this paper are as follows:(1)the construction of innovation-driven system model: Combining innovative "chain model" and "system model",constructs an innovation-driven development system with technological innovation as the main path,in which the development is divided into three stages: knowledge development,achievement transformation and innovation driven.(2)Measurement of innovation-driven efficiency: Based on the theory of innovation,defines the innovation-driven efficiency and its formula,then carry out empirical study on the temporal and spatial evolution of innovation-driven efficiency in Guangdong from 2006 to 2015,combing the stochastic frontier model of transcendental logarithm with decomposition of total factor productivity growth.(3)Analysis of influencing factors: Based on the system model,the factors of technology spillovers are introduced into the analysis framework of Furman.The factors are analyzed from four aspects containing innovation basic factor,innovation subject cooperation,industrial innovation environment and innovation technology spillover in province in whole province,the Pearl River Delta region and the non-Pearl River Delta region respectively.The results show that: firstly,the efficiency of innovation-driven in the whole province and sub-region shows a stable rise at first and then a trend of "W" fluctuation rise,and the cities of the Pearl River Delta and non-Pearl River Delta show obvious regional consistency.Second,the efficiency of knowledge development and the efficiency of outcome transformation show different impact on innovation-driven efficiency in different periods.Third,there is a little waste of innovation R&D investment;the collaboration between government and enterprise plays a important role;high-tech industry,market concentration,urbanization,economic level,financial development,government technology support,trade and technology market activity have showed a positive effect on innovation-driven efficiency,with significant differences in different regions.However,there might be a waste of innovation R&D investment,and foreign direct investment has an inhibitory effect on innovation-driven efficiency.
Keywords/Search Tags:Innovation-driven Efficiency, Stochastic Frontier Model, Total Factor Productivity, Influence Factors
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