- Title
- Small-to-medium enterprises and economic growth : A comparative study of clustering techniques
- Creator
- Mardaneh, Karim
- Date
- 2012
- Type
- Text; Journal article
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/69002
- Identifier
- vital:4937
- Identifier
- http://www.scopus.com/inward/record.url?eid=2-s2.0-84875275120&partnerID=40&md5=cd27ee5304e548796c5b30de3f3388cd
- Identifier
- ISSN:1538-9472
- Abstract
- Small-to-medium enterprises (SMEs) in regional (non-metropolitan) areas are considered when economic planning may require large data sets and sophisticated clustering techniques. The economic growth of regional areas was investigated using four clustering algorithms. Empirical analysis demonstrated that the modified global k-means algorithm outperformed other algorithms. © 2012 JMASM, Inc.
- Relation
- Journal of Modern Applied Statistical Methods Vol. 11, no. 2 (2012), p. 469-478
- Rights
- Copyright 2012 JMASM, Inc.
- Rights
- Open Access
- Rights
- This metadata is freely available under a CCO license
- Subject
- Clustering; Firm size; Industry structure; K-means; Regional economy; Ward's clustering; 0104 Statistics
- Full Text
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