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Research On The Configuration Effect Of Digital Economy On Regional Green Innovation Efficiency

Posted on:2024-01-31Degree:MasterType:Thesis
Country:ChinaCandidate:Y Q JiaFull Text:PDF
GTID:2531307052988559Subject:Technical Economics and Management
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“Greenization” and “Digitization” are the important directions of China’s future economic development.In the face of the dual pressure of serious resource consumption and intensified environmental pollution,how to realize the green development model of“not only golden mountains and silver mountains,but also green waters and green mountains” has become the main goal of regional economic development.Especially in2021,China put forward the goal of “reaching the peak of carbon and carbon neutrality”,which once again raised the road of green development to a new height.Green innovation has become the only way to promote sustainable and healthy economic development and green transformation.The enabling effect of digital economy on green innovation is increasingly prominent,and it plays an important role in promoting high-quality economic development and the construction of ecological civilization.How to improve the efficiency of regional green innovation by virtue of the “east wind”of rapid development of digital economy is urgent to be studied.Based on this,this paper studies the impact of digital economy on regional green innovation efficiency from the perspective of configuration,and makes chapter layout around four aspects: literature review,theoretical framework,variable measurement and configuration analysis.First of all,it summarizes the relevant literature on digital economy and green innovation efficiency;Secondly,it briefly expounds the digital economy theory,sustainable development theory and green innovation theory,and constructs a four-dimensional analysis framework of digital resources,digital technology,digital industry and digital environment based on relevant theories and literature review,and establishes a configuration model of the green innovation efficiency of the region affected by the digital economy;Thirdly,combined with the model in this paper and other scholars’ research,we build a relatively perfect indicator system to measure variables;Finally,based on the theoretical framework,taking 30 provinces in 2020 as the research object,using the qualitative comparative analysis method of fuzzy sets,the synergy mechanism of the eight antecedents of the digital economy is systematically investigated,the configuration of the green innovation efficiency in the regions affected by the digital economy and the potential substitution relationship between the antecedents are explored,and the development strategy of adapting measures to local conditions is proposed according to the research conclusions.Through empirical analysis,the research conclusions of this paper are as follows:(1)Digital talent,digital finance,underlying technology,practical technology,business model digitalization,industry digitalization,digital consumption,and digital government can not constitute the necessary conditions for high regional green innovation efficiency alone,while multiple condition configurations constitute the path to improve the efficiency of green innovation,indicating that the regional green innovation efficiency has “multiple concurrent causal relationships”.(2)There are five types of models to achieve high green innovation efficiency and three types of models that lead to non-high green innovation efficiency,which further verifies the “causal asymmetry” of regional green innovation efficiency.(3)Under the condition of determining the overlapping elements between the configuration paths,the potential substitution relationship between digital resources,digital technology,digital industry and digital environmental conditions can be obtained.Different combinations of conditions can improve the efficiency of regional green innovation in the way of“achieving the same goal by different ways” through equivalent substitution.
Keywords/Search Tags:digital economy, regional green innovation efficiency, super-efficiency SBM model, fuzzy set qualitative comparative analysis
PDF Full Text Request
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