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Research On Subject Behavior And Cluster Evolution Dynamics Of Biomedical Innovation Clusters In The Yangtze River Delta

Posted on:2021-07-16Degree:MasterType:Thesis
Country:ChinaCandidate:Y F GeFull Text:PDF
GTID:2569306023462424Subject:Social Medicine and Health Management
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Objective:The development of regional integration in the Yangtze River Delta has become a national strategy,and the biomedical industry is one of the strategic emerging industries.The biomedical innovation cluster is an advanced form of industrial cluster.The evolution and development of the Yangtze River Delta biomedical innovation cluster has unique development characteristics.Therefore,the article studies the subject behavior of the biomedical innovation cluster in the Yangtze River Delta,builds a system dynamics model of the biomedical innovation cluster evolution dynamics for simulation analysis,and puts forward corresponding suggestions,aiming to understand the evolutionary development law of the biomedical innovation cluster,and provide guidance for the innovation ability of the Yangtze River Delta biopharmaceutical industry and the improvement of international competitiveness.Methods:Based on literature and theoretical analysis,the "stimulus-response" model and echo model of the behavior of the main body of the biomedical innovation cluster were constructed;Collect biomedical industry data from four provinces in the Yangtze River Delta,simple data processing was performed using Excel,and SPSS 22.0 software was used to perform variable Linear regression analysis.Finally,the system dynamics software Vensim PLE 7.3.5 was used to construct the evolution simulation model of the biomedical innovation cluster,draw the causeeffect diagram and system flow diagram,establish the structural equation,and run the simulation experiment.Results:The biomedical innovation cluster is a complex adaptation system,and the subject of biomedical innovation has adaptive learning behaviors and interactive behaviors.Based on the data analysis of the biomedical industries in Shanghai,Jiangsu Province,Zhejiang Province,and Anhui Province from 2011 to 2016,it was found that the adjustment of local fiscal expenditure growth rate,fixed asset investment growth rate,domestic main business income growth rate,foreign main business.The values of the five parameters of income growth rate and biomedical innovation cluster R&D investment growth rate have different effects on the evolution and development of biomedical innovation cluster.Set the basic scenario as the average annual growth rate of each parameter from 2011 to 2016,the high-speed development scenario is the maximum value of each parameter,the low-speed development scenario is the minimum value of each parameter,the growth rate of local fiscal expenditure,the growth rate of fixed asset investment,and the growth rate of R&D investment of biomedical innovation clusters have multiple impacts on the evolution and development of biomedical innovation clusters.The changes in the growth rate of the main business income at home and abroad have little change on the evolution and development of the biomedical innovation cluster.Conclusions:The research and development investment of the biomedical innovation cluster directly affects the new biomedical innovation cluster.Product sales income,local fiscal expenditures have a greater impact on local R&D personnel,domestic and foreign market demand and fixed asset investment have a greater impact on the evolution and development of biomedical innovation clusters.Local fiscal expenditure,investment in fixed assets,domestic and foreign market demand,and R&D investment in biomedical innovation clusters are important drivers of the evolution of biomedical innovation clusters.The article proposes corresponding countermeasures from three aspects:government,cluster innovation research and development investment,and market demand to promote the sustainable development of biomedical innovation clusters in the Yangtze River Delta.
Keywords/Search Tags:CAS theory, biomedicine, Innovation cluster, Subject behavior, Mechanical machine, System Dynamics
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