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W. Moore (1980)
Levels of Aggregation in Conjoint Analysis: An Empirical ComparisonJournal of Marketing Research, 17
Philippe Cattin, D. Wittink (1982)
Commercial Use of Conjoint Analysis: A SurveyJournal of Marketing, 46
W. DeSarbo, R. Oliver, A. Rangaswamy (1989)
A simulated annealing methodology for clusterwise linear regressionPsychometrika, 54
D. Roberts (1987)
The statistical program SYSTAT : Wilkinson, L. (1986). SYSTAT, The System for Statistics. SYSTAT, Inc. 2902 Central Street, Evanston, IL 60201.Journal of School Psychology, 25
A. Dempster, N. Laird, D. Rubin (1977)
Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper
D. Titterington, A. Smith, U. Makov (1986)
Statistical analysis of finite mixture distributions
P. Green, V. Srinivasan (1978)
Conjoint Analysis in Consumer Research: Issues and OutlookJournal of Consumer Research, 5
K. Ogawa (1987)
An Approach to Simultaneous Estimation and Segmentation in Conjoint AnalysisMarketing Science, 6
(1991)
A Latent Pooling Methodology for Regression Analysis with Limited Time Series of Cross Sections: A PIMS Data Application," Under Revision
W. DeSarbo, W. Cron (1988)
A maximum likelihood methodology for clusterwise linear regressionJournal of Classification, 5
H. Spath (1985)
The Cluster Dissection and Analysis Theory FORTRAN Programs ExamplesMathematics of Computation, 47
W. Kamakura (1988)
A Least Squares Procedure for Benefit Segmentation with Conjoint ExperimentsJournal of Marketing Research, 25
D. Stewart (1981)
The Application and Misapplication of Factor Analysis in Marketing ResearchJournal of Marketing Research, 18
D. Hand (1986)
Cluster dissection and analysis: Helmuth SPATH Wiley, Chichester, 1985, 226 pages, £25.00European Journal of Operational Research, 25
S. Addelman (1962)
Orthogonal Main-Effect Plans for Asymmetrical Factorial ExperimentsTechnometrics, 4
H. Akaike (1974)
A new look at the statistical model identificationIEEE Transactions on Automatic Control, 19
P. Green (1984)
Hybrid Models for Conjoint Analysis: An Expository ReviewJournal of Marketing Research, 21
M. Wedel, J. Steenkamp (1991)
A Clusterwise Regression Method for Simultaneous Fuzzy Market Structuring and Benefit SegmentationJournal of Marketing Research, 28
P. Green, Kristiaan Helsen (1989)
Cross-Validation Assessment of Alternatives to Individual-Level Conjoint Analysis: A Case StudyJournal of Marketing Research, 26
J. Hartigan (1975)
Clustering Algorithms
D. Wittink, Philippe Cattin (1989)
Commercial Use of Conjoint Analysis: An UpdateJournal of Marketing, 53
W. DeSarbo, K. Jedidi, Karel Cool, D. Schendel (1991)
Simultaneous multidimensional unfolding and cluster analysis: An investigation of strategic groupsMarketing Letters, 2
H. Bozdogan (1987)
Model selection and Akaike's Information Criterion (AIC): The general theory and its analytical extensionsPsychometrika, 52
P. Green (1977)
A new approach to market segmentationBusiness Horizons, 20
M. Wedel, J. Steenkamp (1989)
A fuzzy clusterwise regression approach to benefit segmentationInternational Journal of Research in Marketing, 6
H. Spath (1985)
Cluster Dissection and Analysis
P. Green, A. Krieger (1991)
Segmenting Markets with Conjoint AnalysisJournal of Marketing, 55
(1991)
SYSTAT: The System for Statistics
P. Green, V. Srinivasan (1990)
Conjoint Analysis in Marketing: New Developments with Implications for Research and PracticeJournal of Marketing, 54
M. Hagerty (1985)
Improving the Predictive Power of Conjoint Analysis: The use of Factor Analysis and Cluster AnalysisJournal of Marketing Research, 22
A. P. Dempster, N. M. Laird, D. B. Rubin (1977)
Maximum Likelihood from Incomplete data Via the E. M. AlgorithmJournal of the Royal Statistical Society, B39
P. Green, V. Srinivasan (1990)
Conjoint Analysis in Marketing Research: New Developments and Directions
W. DeSarbo, Daniel Howard, K. Jedidi (1991)
Multiclus: A new method for simultaneously performing multidimensional scaling and cluster analysisPsychometrika, 56
M. Wedel, C. Kistemaker (1989)
Consumer benefit segmentation using clusterwise linear regressionInternational Journal of Research in Marketing, 6
A. Rao (1980)
Quantity Discounts in Today's MarketsJournal of Marketing, 44
A latent class methodology for conjoint analysis is proposed, which simultaneously estimates market segment membership and part-worth utilities for each derived market segment using mixtures of multivariate conditional normal distributions. An E-M algorithm to estimate the parameters of these mixtures is briefly discussed. Finally, an application of the methodology to a commercial study (pretest) examining the design of a remote automobile entry device is presented.
Marketing Letters – Springer Journals
Published: Dec 31, 2004
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