Title: Fuzzy C-means clustering for the optimal portfolio of machinery industrial sustainable development strategies in Taiwan
Authors: Chiou, HK
Tzeng, GH
Yuan, BJC
Wang, CP
科技管理研究所
Institute of Management of Technology
Keywords: analytic hierarchy process;fuzzy C-mcans clustering;machinery industry
Issue Date: 2004
Abstract: Many products of machinery industry that produced in Taiwan ranked within top-ten exports Countries around the world. However, with the dynamic change in both the internal and external environment, production volume, imports and exports dropped simultaneously in 2001. In order to strengthen the industry's competitive advantage, we propose ten Sustainable strategies for machinery industry through focus opinions and employ fuzzy hierarchical analysis approach to find the order these strategies. Furthermore, we introduce fuzzy c-means Clustering to determine the optimal combination of these strategies for sustainable development. Finally, three clusters be extracted for enhancing the industrial promotion, improving national competitiveness and sustainable development, Through this research, we successfully demonstrate that fuzzy C-means clustering not only provides good discriminating power in pattern recognition, but also contribute to good portfolio selection for industry.
URI: http://hdl.handle.net/11536/18171
ISBN: 1-889335-23-1
Journal: Soft Computing with Industrial Applications, Vol 17
Volume: 17
Begin Page: 345
End Page: 350
Appears in Collections:Conferences Paper