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The Scientific World Journal
Volume 2014 (2014), Article ID 685495, 7 pages
http://dx.doi.org/10.1155/2014/685495
Research Article

Analyzing Patients’ Values by Applying Cluster Analysis and LRFM Model in a Pediatric Dental Clinic in Taiwan

1Department of Business Administration, National Changhua University of Education, Changhua City 500, Taiwan
2Department of Tourism, Leisure, and Hospitality Management, National Chi Nan University, Nantou 545, Taiwan

Received 24 January 2014; Accepted 26 May 2014; Published 19 June 2014

Academic Editor: Hyunchul Ahn

Copyright © 2014 Hsin-Hung Wu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. S. Y. Lin, J. T. Wei, C. C. Weng, and H. H. Wu, “A case study of using classification and regression tree and LRFM model in a pediatric dental clinic,” in International Proceedings of Economic Development and Research—Innovation, Management and Service, L. Dong, Ed., vol. 14, pp. 131–135, IACSIT Press, Singapore, 2011. View at Google Scholar
  2. J.-I. Shieh, H.-H. Wu, and K.-K. Huang, “A DEMATEL method in identifying key success factors of hospital service quality,” Knowledge-Based Systems, vol. 23, no. 3, pp. 277–282, 2010. View at Publisher · View at Google Scholar · View at Scopus
  3. J.-T. Wei, S.-Y. Lin, C.-C. Weng, and H.-H. Wu, “A case study of applying LRFM model in market segmentation of a children's dental clinic,” Expert Systems with Applications, vol. 39, no. 5, pp. 5529–5533, 2012. View at Publisher · View at Google Scholar · View at Scopus
  4. W.-I. Lee and B.-Y. Shih, “Application of neural networks to recognize profitable customers for dental services marketing-a case of dental clinics in Taiwan,” Expert Systems with Applications, vol. 36, no. 1, pp. 199–208, 2009. View at Publisher · View at Google Scholar · View at Scopus
  5. C. F. Lo, H. H. Wu, E. C. Chang, and Y. Y. Cheng, “Applying data mining to an outfitter’s customer loyalty and value analysis,” Journal of Quality, vol. 15, no. 4, pp. 293–303, 2008. View at Google Scholar
  6. S.-C. Huang, E.-C. Chang, and H.-H. Wu, “A case study of applying data mining techniques in an outfitter's customer value analysis,” Expert Systems with Applications, vol. 36, no. 3, pp. 5909–5915, 2009. View at Publisher · View at Google Scholar · View at Scopus
  7. Y. T. Kao, H. H. Wu, H. K. Chen, and E. C. Chang, “A case study of applying LRFM model and clustering techniques to evaluate customer values,” Journal of Statistics & Management Systems, vol. 14, no. 2, pp. 267–276, 2011. View at Google Scholar
  8. J.-T. Wei, M.-C. Lee, H.-K. Chen, and H.-H. Wu, “Customer relationship management in the hairdressing industry: an application of data mining techniques,” Expert Systems with Applications, vol. 40, no. 18, pp. 7513–7518, 2013. View at Publisher · View at Google Scholar · View at Scopus
  9. C. Marcus, “A practical yet meaningful approach to customer segmentation,” Journal of Consumer Marketing, vol. 15, no. 5, pp. 494–504, 1998. View at Google Scholar · View at Scopus
  10. H. H. Chang and S. F. Tsay, “Integrating of SOM and K-mean in data mining clustering: an empirical study of CRM and profitability evaluation,” Journal of Information Management, vol. 11, no. 4, pp. 161–203, 2004. View at Google Scholar
  11. J. Han and M. Kamber, Data Mining: Concepts and Techniques, Morgan Kaufmann, San Francisco, Calif, USA, 2nd edition, 2007.
  12. K. Fish and P. Ruby, “An artificial intelligence foreign market screening method for small businesses,” International Journal of Entrepreneurship, vol. 13, no. 1, pp. 65–91, 2009. View at Google Scholar · View at Scopus
  13. P. Hanafizadeh and M. Mirzazadeh, “Visualizing market segmentation using self-organizing maps and Fuzzy Delphi method—ADSL market of a telecommunication company,” Expert Systems with Applications, vol. 38, no. 1, pp. 198–205, 2011. View at Publisher · View at Google Scholar · View at Scopus
  14. S.-H. Hsu, J. P.-A. Hsieh, T.-C. Chih, and K.-C. Hsu, “A two-stage architecture for stock price forecasting by integrating self-organizing map and support vector regression,” Expert Systems with Applications, vol. 36, no. 4, pp. 7947–7951, 2009. View at Publisher · View at Google Scholar · View at Scopus
  15. M. Y. Kiang and D. M. Fisher, “Selecting the right MBA schools—an application of self-organizing map networks,” Expert Systems with Applications, vol. 35, no. 3, pp. 946–955, 2008. View at Publisher · View at Google Scholar · View at Scopus
  16. L. Churilov, A. Bagirov, D. Schwartz, K. Smith, and M. Dally, “Data mining with combined use of optimization techniques and self-organizing maps for improving risk grouping rules: application to prostate cancer patients,” Journal of Management Information Systems, vol. 21, no. 4, pp. 85–100, 2005. View at Google Scholar · View at Scopus
  17. H.-H. Wu, J.-I. Shieh, A. Y. H. Liao, and S.-Y. Lin, “An application of the generalised K-means algorithm in decision-making processes,” International Journal of Operational Research, vol. 3, no. 1-2, pp. 19–35, 2008. View at Publisher · View at Google Scholar · View at Scopus
  18. S. Wang, “Cluster analysis using a validated self-organizing method: cases of problem identification,” International Journal of Intelligent Systems in Accounting, Finance and Management, vol. 10, no. 2, pp. 127–138, 2001. View at Google Scholar
  19. E.-C. Chang, S.-C. Huang, and H.-H. Wu, “Using K-means method and spectral clustering technique in an outfitter's value analysis,” Quality and Quantity, vol. 44, no. 4, pp. 807–815, 2010. View at Publisher · View at Google Scholar · View at Scopus
  20. R. J. Kuo, L. M. Ho, and C. M. Hu, “Integration of self-organizing feature map and K-means algorithm for market segmentation,” Computers and Operations Research, vol. 29, no. 11, pp. 1475–1493, 2002. View at Publisher · View at Google Scholar · View at Scopus
  21. C.-Y. Chiu, Y.-F. Chen, I.-T. Kuo, and H. C. Ku, “An intelligent market segmentation system using k-means and particle swarm optimization,” Expert Systems with Applications, vol. 36, no. 3, pp. 4558–4565, 2009. View at Publisher · View at Google Scholar · View at Scopus
  22. J. T. Wei, S. Y. Lin, and H. H. Wu, “A review of the application of RFM model,” African Journal of Business Management, vol. 4, no. 19, pp. 4199–4206, 2010. View at Google Scholar
  23. A. M. Hughes, “Boosting response with RFM,” Marketing Tools, vol. 3, no. 3, pp. 4–10, 1996. View at Google Scholar
  24. I.-C. Yeh, K.-J. Yang, and T.-M. Ting, “Knowledge discovery on RFM model using Bernoulli sequence,” Expert Systems with Applications, vol. 36, no. 3, pp. 5866–5871, 2009. View at Publisher · View at Google Scholar · View at Scopus
  25. A. M. Hughes, Strategic Database Marketing, McGraw-Hill, New York, NY, USA, 1994.
  26. W. J. Reinartz and V. Kumar, “On the profitability of long-life customers in a noncontractual setting: an empirical investigation and implications for marketing,” Journal of Marketing, vol. 64, no. 4, pp. 17–35, 2000. View at Google Scholar · View at Scopus
  27. S. H. Ha and S. C. Park, “Application of data mining tools to hotel data mart on the Intranet for database marketing,” Expert Systems with Applications, vol. 15, no. 1, pp. 1–31, 1998. View at Google Scholar · View at Scopus