{"title":"Growth path of industrial clusters embedded in global value chain from the perspective of knowledge transfer: A fuzzy game approach","authors":"B. He, W. Meng","doi":"10.3233/JIFS-189950","DOIUrl":null,"url":null,"abstract":"How local industrial clusters break through the lock-in status of low end of value chains and realize industrial upgrading in the development process of embedded global value chain is the central topic of current industrial development research. To explore how industrial clusters achieve the enhancement of their innovation capability and value chains when they are embedded in the global value chain, from the perspective of knowledge transfer and according to the differences in the knowledge levels of the local industrial clusters, three fuzzy game models of knowledge transfer paths were constructed, and the model of the realization mechanism of knowledge transfer and its stability condition was analyzed, which make clear the path of cluster growth under different embedding modes. Results show that although the mode of embedding and the path of knowledge transfer is different, the local industrial clusters can obtain external knowledge transfer by embedding in the global value chain; the knowledge transformation ability of local industrial clusters is the determining factor that the knowledge transfer can smoothly achieve and become stable. The conclusion also shows that the feasibility of the cross-sectional growth of industrial clusters by actively embed the global value chain and acquiring external knowledge transfer if the industrial clusters want to enhance their technology accumulation, their innovation ability, and their position in the global value chain.","PeriodicalId":44705,"journal":{"name":"International Journal of Fuzzy Logic and Intelligent Systems","volume":"7 1","pages":"1-10"},"PeriodicalIF":1.5000,"publicationDate":"2021-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Fuzzy Logic and Intelligent Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3233/JIFS-189950","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, THEORY & METHODS","Score":null,"Total":0}
引用次数: 0
Abstract
How local industrial clusters break through the lock-in status of low end of value chains and realize industrial upgrading in the development process of embedded global value chain is the central topic of current industrial development research. To explore how industrial clusters achieve the enhancement of their innovation capability and value chains when they are embedded in the global value chain, from the perspective of knowledge transfer and according to the differences in the knowledge levels of the local industrial clusters, three fuzzy game models of knowledge transfer paths were constructed, and the model of the realization mechanism of knowledge transfer and its stability condition was analyzed, which make clear the path of cluster growth under different embedding modes. Results show that although the mode of embedding and the path of knowledge transfer is different, the local industrial clusters can obtain external knowledge transfer by embedding in the global value chain; the knowledge transformation ability of local industrial clusters is the determining factor that the knowledge transfer can smoothly achieve and become stable. The conclusion also shows that the feasibility of the cross-sectional growth of industrial clusters by actively embed the global value chain and acquiring external knowledge transfer if the industrial clusters want to enhance their technology accumulation, their innovation ability, and their position in the global value chain.
期刊介绍:
The International Journal of Fuzzy Logic and Intelligent Systems (pISSN 1598-2645, eISSN 2093-744X) is published quarterly by the Korean Institute of Intelligent Systems. The official title of the journal is International Journal of Fuzzy Logic and Intelligent Systems and the abbreviated title is Int. J. Fuzzy Log. Intell. Syst. Some, or all, of the articles in the journal are indexed in SCOPUS, Korea Citation Index (KCI), DOI/CrossrRef, DBLP, and Google Scholar. The journal was launched in 2001 and dedicated to the dissemination of well-defined theoretical and empirical studies results that have a potential impact on the realization of intelligent systems based on fuzzy logic and intelligent systems theory. Specific topics include, but are not limited to: a) computational intelligence techniques including fuzzy logic systems, neural networks and evolutionary computation; b) intelligent control, instrumentation and robotics; c) adaptive signal and multimedia processing; d) intelligent information processing including pattern recognition and information processing; e) machine learning and smart systems including data mining and intelligent service practices; f) fuzzy theory and its applications.