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Proceedings Paper

Network-based spatial clustering technique for exploring features in regional industry
Author(s): Tien-Yin Chou; Pi-Hui Huang; Lung-Shih Yang; Wen-Tzu Lin
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Paper Abstract

In the past researches, industrial cluster mainly focused on single or particular industry and less on spatial industrial structure and mutual relations. Industrial cluster could generate three kinds of spillover effects, including knowledge, labor market pooling, and input sharing. In addition, industrial cluster indeed benefits industry development. To fully control the status and characteristics of district industrial cluster can facilitate to improve the competitive ascendancy of district industry. The related researches on industrial spatial cluster were of great significance for setting up industrial policies and promoting district economic development. In this study, an improved model, GeoSOM, that combines DBSCAN (Density-Based Spatial Clustering of Applications with Noise) and SOM (Self-Organizing Map) was developed for analyzing industrial cluster. Different from former distance-based algorithm for industrial cluster, the proposed GeoSOM model can calculate spatial characteristics between firms based on DBSCAN algorithm and evaluate the similarity between firms based on SOM clustering analysis. The demonstrative data sets, the manufacturers around Taichung County in Taiwan, were analyzed for verifying the practicability of the proposed model. The analyzed results indicate that GeoSOM is suitable for evaluating spatial industrial cluster.

Paper Details

Date Published: 5 November 2008
PDF: 10 pages
Proc. SPIE 7144, Geoinformatics 2008 and Joint Conference on GIS and Built Environment: The Built Environment and Its Dynamics, 714419 (5 November 2008); doi: 10.1117/12.812740
Show Author Affiliations
Tien-Yin Chou, Feng Chia Univ. (Taiwan)
Pi-Hui Huang, Feng Chia Univ. (Taiwan)
Lung-Shih Yang, Feng Chia Univ. (Taiwan)
Wen-Tzu Lin, Ming Dao Univ. (Taiwan)


Published in SPIE Proceedings Vol. 7144:
Geoinformatics 2008 and Joint Conference on GIS and Built Environment: The Built Environment and Its Dynamics
Lin Liu; Xia Li; Kai Liu; Xinchang Zhang; Xinhao Wang, Editor(s)

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