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dc.contributor.authorTsai, Bi-Hueien_US
dc.date.accessioned2014-12-08T15:24:24Z-
dc.date.available2014-12-08T15:24:24Z-
dc.date.issued2009en_US
dc.identifier.isbn978-1-8908-4319-9en_US
dc.identifier.urihttp://hdl.handle.net/11536/16932-
dc.description.abstractIn this work, we for the first time utilize numerical methods to computationally clarify the clustering dynamics of integrated circuit (IC) industry from Taiwan to China. According to the relationship between the foreign direct investment (FDI) and the industrial clustering phenomenon, we first formulate a dynamic growth FDI model for studying the industrial clustering evolutions. The effects of the innovation, Imitation and potential investment factors on the clustering behaviors are systematically considered. This examination is further advanced to forecast the trend of Taiwan's IC industrial clustering to China, where the accuracy among the predicted data as well as the collected data is compared and validated. The results indicate the significant internal influence of intra-industry communications on the FDI evolution into China. Taiwan IC firms tend to successively imitate the experienced firms to engage in FDIs in China. Particularly, the internal impact is the strongest for IC manufacturing firms, revealing its greatest clustering effect. The Taiwan IC industrial FDI amount in China is cumulatively predicted increasing, which once again supports the clustering tendency of IC industries. Finally, the FDI prediction is more accurate for IC design, packaging and testing industries than for IC manufacturing industry due to the governmental FDI restrictions of IC manufacturing industry.en_US
dc.language.isoen_USen_US
dc.titleDynamic Modeling and Simulation of Taiwan's IC Industrial Clustering to Chinaen_US
dc.typeProceedings Paperen_US
dc.identifier.journalPROCEEDINGS OF PICMET 09 - TECHNOLOGY MANAGEMENT IN THE AGE OF FUNDAMENTAL CHANGE, VOLS 1-5en_US
dc.citation.spage3216en_US
dc.citation.epage3223en_US
dc.contributor.department管理科學系zh_TW
dc.contributor.departmentDepartment of Management Scienceen_US
dc.identifier.wosnumberWOS:000277502501129-
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