Abstract
Cluster analysis is a frequently used technique in marketing as a method to develop partitions or classifications for market segmentation, product positioning, test market selection, etc. Because of the vast diversity in the assortment of clustering algorithms available, it is often times not obvious which algorithm or technique should be employed. It is often recommended that the marketer perform more than one cluster analysis on the same data set and compare representations as a reliability check. A methodology for evaluating the consistency of different clusterings is introduced via contingency table analysis by log-linear models. In addition, insight is provided as to selecting a “best” representative clustering by examining Stewart and Love's (1968) redundancy measures.
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References
Arabie, P. and Boorman, S. A. (1973), “Multidimensional Scaling of Measures of Distance between Partitions,”Journal of Mathematical Psychology, Vol. 10, No. 2, 148–203.
Baker, F. B. (1974), “Stability of Two Hierarchical Grouping Techniques Case I: Sensitivity to Data Errors,”Journal of the American Statistical Association, 69, 440–445.
Ball, G. H. and D. J. Hall (1965),Isodata, A Novel Method of Data Analysis and Pattern Classification, Menlo Park, California: Stanford Research Institute.
—, (1971),Classification Analysis, Menlo Park, California: Stanford Research Institute.
Boorman, S. A. and Arabie, P. (1972), “Structural Measures and the Method of Sorting,” In R. N. Shepard, A. K. Romney, and S. Nerlove (Eds.),Multidimensional Scaling: Theory and Applications in the Behavioral Sciences, Vol. 1, N.Y.: Seminar Press, 1972, 225–249.
Boorman, S. A. and Oliver, D. C. (1973), “Metrics on Spaces of Finite Trees,”Journal of Mathematical Psychology, Vol. 10, No. 1, 26–59.
Brown, Morton B. (1976), “Screening Effects in Multidimensional Contingency Tables,”Journal of the Royal Statistical Society, (Series C): Applied Statistics, 25 (March), 37–46.
DeSarbo, W. S. and Hildebrand, D. K. (1980), “A Marketer's Guide to Log-Linear Models,”Journal of Marketing, 44 (Summer) 40–51.
Dixon, W. J., ed., (1975),BMDP: Biomedical Computer Programs, Los Angeles, California: University of California Press.
Everitt, B. (1974),Cluster Analysis, London: Heinemann Educational Books Ltd.
Fowlkes, E. B. and Mallows, C. L. (1980), “A Method for Comparing Two Hierarchical Clusterings,”Working Paper, Bell Laboratories, Murray Hill, N.J.
Frank, R. E., W. F. Massy, and Y. Wind (1972),Market Segmentation, Englewood Cliffs, New Jersey: Prentice-Hall, Inc.
Gleason, T. C. (1976), “On Redundancy in Canonical Analysis,”Psychological Bulletin, 83 (December), 1004–1006.
Goodman, Leo, A. (1970), “The Multivariate Analysis of Qualitative Data: Interactions Among Multiple Classifications,”Journal of the American Statistical Association, 64 (March), 226–256.
— (1971). “The Analysis of Multidimensional Contingency Tables: Stepwise Procedures and Direct Estimation Methods for Building Models for Multi ple Classifications,”Technometrics, 13 (February), 33–61.
—, (1971), “Partitioning of Chi-Square, Analysis of Marginal Contingency Tables, and Estimation of Expected Frequencies in Multidimensional Contingency Tables,”Journal of the American Statistical Association, 66 (June), 339–344.
Green, Paul, E. and Ronald E. Frank, (1968), “Numerical Taxonomy in Marketing Analysis: A Review Article,”Journal of Marketing Research, 5 (February) 83–98.
—, and V. R. Rao, (1972),Applied Multidimensional Scaling: A Comparison of Approaches and Algorithms, Hinsdale, Illinois: The Dryden Press.
— (1978),Analyzing Multivariate Data, Hinsdale, Illinois: The Dryden Press.
Haberman, S. J. (1976), “Log-Linear Fit for Contingency Tables,”Journal of the Royal Statistical Society (Series C): Applied Statistics. 25 (March), 218–225.
Howard, N., and Harris, B., (1966). “A Hierarchical Grouping Routine, IBM 360/65 FORTRAN IV Program,”University of Pennsylvania Computer Center Publication, 5–12.
Johnson, S. C. (1967). “Hierarchical Clustering Schemes,”Psychometrika, 32 (September), 241–254.
Morrison, D. F. (1976),Multivariate Statistical Methods, New York: McGraw-Hill Book Co.
Rand, W. M. (1971), “Objective Criteria for Evaluation of Clustering Methods,” Journal of the American Statistical Association, 66, 1971, 846–850.
Sethi, S. P. (1971). “Comparative Cluster Analysis for World Markets,”Journal of Marketing Research, (August), 348–354.
Sexton, D. E., Jr, (1974), “Cluster Analytic Approach to Market Response Functions,”Journal of Marketing Research, 109 (February), 109–114.
Stewart, D. K., Love, W. A. (1968). “A General Canonical Correlation Index,”Psychological Bulletin, 70 (December), 160–163.
Waterman, M. S. (1978), “On the Similarity of Dendrograms,”Journal of Theoretical Biology, 73, 789–800.
Williams, W. T. and Clifford, H. T. (1971),Taxonomy, 20, 519.
Wind, Y., (1982 forthcoming),Product Policy Reading, Mass.: Addison-Wesley Publishing.
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De Sarbo, W.S. Clustering consistency analysis. JAMS 10, 217–234 (1982). https://doi.org/10.1007/BF02729964
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DOI: https://doi.org/10.1007/BF02729964