Comparative performance of the FSCL neural net and K-means algorithm for market segmentation

European Journal of Operational Research

Volumn 93, Issue 2, 1996, Pages 346-357

  Balakrishnan, P V ^a   Cooper, Martha C ^b   Jacob, Varghese S ^b   Lewis, Phillip A ^c  

^a UNIVERSITY OF WASHINGTON BOTHELL   (United States)

^b OHIO STATE UNIVERSITY   (United States)

^c The College of New Jersey   (United States)

Author keywords

Brand choice; Comparative performance; Data quality; K means; Marketing; Neural networks; Segmentation

Indexed keywords

DATA ACQUISITION; DATA REDUCTION; DECISION MAKING; LEARNING ALGORITHMS; MARKETING; MEASUREMENT ERRORS; PERFORMANCE;

BRAND CHOICE; DATA QUALITY; FREQUENCY SENSITIVE COMPETITIVE LEARNING ALGORITHM; MARKET SEGMENTATION;

NEURAL NETWORKS;

EID: 0030572650     PISSN: 03772217     EISSN: None     Source Type: Journal    
DOI: 10.1016/0377-2217(96)00046-X     Document Type: Article

References (35)

1. Ahalt, S.C., Krishnamurthy, A.K., Chen, P., and Melton, D.E. (1990), "Competitive learning algorithms for vector quantization", Neural Networks 3, 277-290.
2. Balakrishnan, P.V. (Sundar), Cooper, M.C., Jacob, V.S., and Lewis, P.A. (1992), "A cluster analysis of brand choice data using neural networks", in: V.S. Jacob and H. Pirkul (eds.), Proceedings of the Twentieth International Business School Computer Users Group, Columbus, OH, 365-375.
3. Balakrishnan, P.V. (Sundar), Cooper, M.C., Jacob, V.S., and Lewis, P.A. (1994), "A study of the classification capabilities of neural networks using unsupervised learning: A comparison with K-means clustering", Psychometrika 59/4, 509-525.
4. Bezdek, J.C. (1991), "Pattern recognition, neural networks, and artificial intelligence", in: M. Trivedi (ed.), Proceedings of the Society of Photo Optical Instrumentation Engineers Applications of Artificial Intelligence VIII, 1-12.
5. Bezdek, J.C and Hathaway, R.J. (1990), "Generalized regression and clustering", Proceedings of the International Conference on Fuzzy Logistic and Neural Networks, Iisuka, Japan, 575-578.
6. Bucklin, R.E., and V. Srinivasan (1991), "Determining interbrand substitutability through survey measurement of consumer preference structures", Journal of Marketing Research XXVII (February), 58-71.
7. Cooper, M.C., and Milligan, G.W. (1988), "The effect of measurement error on determining the number of clusters in cluster analysis", Data Analysis, Decision Support and Expert Knowledge Representation in Marketing and Related Areas of Research, Karlsruhe, Germany, 319-328.
8. Cormack, R.M. (1971), "A review of classification", Journal of the Royal Statistical Society, Series A 134, 321-367.
9. Dubes, R.C. (1987), "How many clusters are best? - An experiment", Pattern Recognition 20/6, 645-663.
10. Fort, J.C. (1991), "Kohonen algorithm and the traveling salesman problem", in: F. Murtagh (ed.), Neural Networks for Statistical and Economic Data, Munotec Systems Ltd, Dublin (supported by the Statistical Office of the European Communities, Luxembourg), 113-118.
11. Gath, I., and Geva, A.B. (1988), "Unsupervised optimal fuzzy clustering", IEEE Transactions on Pattern Analysis and Machine Intelligence 11/7, 773-781.
12. Grossberg, S. (1976), "Adaptive pattern classification and universal receding: I. Parallel development and coding of neural feature detectors", Biological Cybernetics 23, 121-134.
13. Hecht-Nielsen, R. (1988), "Application of counterpropogation networks", Neural Networks 1/2, 131-141.
14. Hecht-Nielsen, R. (1990), Neurocomputing, Addison-Wesley, Reading, MA.
15. Kangas, J.A., Kohonen, T.K., and Laaksonen, J.T. (1990), "Variants of self-organizing maps", IEEE Transactions on Neural Networks 1/1, 93-99.
16. Kohonen, T. (1982a), "Self-organized formation of topologically correct feature maps", Biological Cybernetics 43, 59-69.
17. Kohonen, T. (1982b), "Analysis of a simple self organizing process", Biological Cybernetics 44, 135-140.
18. Kohonen, T. (1989), Self Organization and Associative Memory, 3rd edn., Springer-Verlag, New York.
19. Krishnamurthy, A.K., Ahalt, S.C., Melton, D.E., and Chen, P. (1990), "Neural networks for vector quantization of speech and images", IEEE Journal on Selected Areas in Communications 8, 1449-1457.
20. Linde, Y., Buzo, A., and Gray, R.M. (1980), "An algorithm for vector quantization design", IEEE Transactions on Communications 28/1, 84-95.
21. Lippmann, R. R. (April, 1987), "An introduction to computing with neural nets", IEEE Acoustics, Speech and Signal Processing Magazine 4/2, 4-22.
22. Milligan, G.W. (1980), "An examination of the effect of six types of error perturbation on fifteen clustering algorithms", Psychometrika 45, 325-342.
23. Milligan, G.W. (1985), "An algorithm for generating artificial test clusters", Psychometrika 50, 123-127.
24. Milligan, G.W., and Cooper, M.C. (1985), "An examination of procedures for determining the number of clusters in a data set", Psychometrika 50, 159-179.
25. Milligan, G.W., and Cooper, M.C. (1987), "Methodology review: Clustering methods", Applied Psychological Measurement 11/4, 329-354.
26. Murtagh, F. (1991a), "A short survey of neural networks for forecasting", in: F. Murtagh (ed.), Neural Networks for Statistical and Economic Data, Munotec Systems Ltd, Dublin (supported by the Statistical Office of the European Communities, Luxembourg), 87-94.
27. Naylor, J., and Li, K.P. (1988), "Analysis of a neural network algorithm for vector quantization of speech parameters", Proceedings of the First Annual INNS Meeting, Pergamon, new York, 310.
28. Nelson, M.M., and Illingworth, W.T. (1991), A Practical Guide to Neural Networks, Addison-Wesley, Reading, MA.
29. Openshaw, S., and Wymer, C. (1991), "A neural net classifier system for handling census data", in: F. Murtagh (ed.), Neural Networks for Statistical and Economic Data, Munotec Systems Ltd, Dublin (supported by the Statistical Office of the European Communities, Luxembourg), 73-86.
30. Osipenko, V.V. (1988), "Solution of a double clusterization problem with the use of self-organization", Soviet Journal of Automation and Information Sciences 21/3, 77-82.
31. Rowher, R. (1991), "Neural networks for time-varying data", in: F. Murtagh (ed.), Neural Networks for Statistical and Economic Data, Munotec Systems Ltd, Dublin (supported by the Statistical Office of the European Communities, Luxembourg), 59-69.
32. Rumelhart, D.E., McClelland, J.L., and the PDP Research Group (1987), Parallel Distributed Processing: Explorations in the Microstructure of Cognition, Volume 1: Foundations, MIT Press, Cambridge, MA.
33. SAS (1990), SAS User's Guide: Statistics, (Version 5 Edition) SAS Institute Inc., Cary, NC.
34. Wilson, R.L., and Sharda, R. (1994), "Bankruptcy prediction using neural networks", Decision Support Systems 11/3, 545-557.
35. Winters, J.H., and Rose, C. (1989), "Minimum distance automata in parallel networks for optimum classification", Neural Networks 127-132.