{"title":"基于系统动力学的南京规模以上工业企业创新网络绩效影响因素研究","authors":"Yibin Lu;Yexiang Fang","doi":"10.23919/CSMS.2021.0005","DOIUrl":null,"url":null,"abstract":"Based on the method of system dynamics, this paper simulates the cycle of collaborative innovation network, involving enterprises, government, research institutions, and science and technology intermediaries from the perspective of capital flow. The results of model analysis show that among the influencing factors, the number of innovation achievements is the most complex variable, and the influence of patent elimination rate is the most significant. The number of Research and Development (R&D) projects is most sensitive to the positive impact of the number of technology intermediaries, and with the passage of time, this kind of effect gradually increases. At the same time, the total industrial assets are positively affected by the intensity of enterprise innovation investment, but there is about three years delay in this effect.","PeriodicalId":65786,"journal":{"name":"复杂系统建模与仿真(英文)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2021-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.23919/CSMS.2021.0005","citationCount":"0","resultStr":"{\"title\":\"Research on Influencing Factors of Innovation Network Performance of Industrial Enterprises above Designated Size in Nanjing Based on System Dynamics\",\"authors\":\"Yibin Lu;Yexiang Fang\",\"doi\":\"10.23919/CSMS.2021.0005\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Based on the method of system dynamics, this paper simulates the cycle of collaborative innovation network, involving enterprises, government, research institutions, and science and technology intermediaries from the perspective of capital flow. The results of model analysis show that among the influencing factors, the number of innovation achievements is the most complex variable, and the influence of patent elimination rate is the most significant. The number of Research and Development (R&D) projects is most sensitive to the positive impact of the number of technology intermediaries, and with the passage of time, this kind of effect gradually increases. At the same time, the total industrial assets are positively affected by the intensity of enterprise innovation investment, but there is about three years delay in this effect.\",\"PeriodicalId\":65786,\"journal\":{\"name\":\"复杂系统建模与仿真(英文)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.23919/CSMS.2021.0005\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"复杂系统建模与仿真(英文)\",\"FirstCategoryId\":\"1089\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/9426463/\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"复杂系统建模与仿真(英文)","FirstCategoryId":"1089","ListUrlMain":"https://ieeexplore.ieee.org/document/9426463/","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Research on Influencing Factors of Innovation Network Performance of Industrial Enterprises above Designated Size in Nanjing Based on System Dynamics
Based on the method of system dynamics, this paper simulates the cycle of collaborative innovation network, involving enterprises, government, research institutions, and science and technology intermediaries from the perspective of capital flow. The results of model analysis show that among the influencing factors, the number of innovation achievements is the most complex variable, and the influence of patent elimination rate is the most significant. The number of Research and Development (R&D) projects is most sensitive to the positive impact of the number of technology intermediaries, and with the passage of time, this kind of effect gradually increases. At the same time, the total industrial assets are positively affected by the intensity of enterprise innovation investment, but there is about three years delay in this effect.