A generalized normative segmentation methodology employing conjoint analysis

Conjoint Measurement: Methods and Applications

Volumn , Issue , 2007, Pages 321-345

  Desarbo, Wayne S ^a   Desarbo, Christian F ^b  

^a PENNSYLVANIA STATE UNIVERSITY   (United States)

^b Analytika Marketing Sciences Inc   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 77958533003     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.1007/978-3-540-71404-0_16     Document Type: Chapter

References (45)

1. DeSarbo, W. S. and Mahajan, V (1984), Constrained Classification: The Use of A Priori Information Tn Cluster Analysis, Psychometrika, 49, 187-215.
2. De Sarbo, W. S. and Cron, W. (1988). A Conditional Mixture Maximum Likelihood Methodology for Clusterwise Linear Regression. Journal of Classification, 5, 249-289.
3. DeSarbo, W. S., Oliver, R. and Rangaswamy, A. (1989), A Simulated Annealing Methodology for Cluster-wise Linear Regression, Psychometrika, 54, 707-736.
4. DeSarbo, W. S., Wedel, M, Ramaswamy, V. and Vriens, M. (1992), Latent Class Metric Conjoint Analysis, Marketing Letters, 3, 273-288.
5. De Sarbo, W. S., Ramaswamy, V. and Cohen, S. H. (1995), Market Segmentation With Choice-Based Conjoint Analysis, Marketing Letters, 6. 137-47.
6. DeSarbo, W. S., Ramaswamy, V. and Chatterjee, R. (1995), Analyzing Constant Sum Multiple Criteria Data: A Segment Level Approach. Journal of Marketing Research, 32, 222-232.
7. De Sarbo, W. S. and Grisaffee, D. (1998), Combinatorial Optimization Approaches to Constrained Market Segmentation: An Application to Industrial Market Segmentation, Marketing Letters, 9, 115-134.
8. De Soete, G. and DeSarbo, W. S. (1991), A Latent Class Probit Model for Analyzing Pick Any/N Data, Journal of Classification, 8, 45-63.
9. Frank, R. E., Massy, W. F. and Wind, Y. (1972), Market Segmentation, Englewood Cliffs, NJ.
10. Green, P. E. (1977). A New Approach to Market Segmentation, Business Horizons, 20, 61- 73.
11. Green, P. E. and Srinivasan, V. (1978), Conjoint Analysis in Consumer Research: Issues and Outlook, Journal of Consumer Research, 5, 103-23.
12. Green, P. E. and Helson, C. (1989), Cross-Validation Assessment of Alternatives to Individual Level Conjoint Analysis: A Case Study, Journal of Marketing Research, 26, 346-350.
13. Green, P. E. and Srinivasan, V. (1990), Conjoint Analysis in Marketing: New Developments with Implications for Research and Practice, Journal of Marketing, 54. 3-19.
14. Green, P. E. and Krieger, A. M. (1991), Segmenting Markets with Conjoint Analysis, Journal of Marketing. 55. 20-31.
15. Hagerty, M. R. (1985), Improving the Predictive Power of Conjoint Analysis: The Use of Factor Analysis and Cluster Analysis, Journal of Marketing Research, 22, 168-84.
16. Hair, J.F., Anderson, R.E., Tatham, R.L. and Black, W.C. (1995), Multivariate Data Analysis, Englewood Cliffs, N.J.
17. Haley, R. I. (1968), Benefit Segmentation: A Decision-Oriented Research Tool, Journal of Marketing, 32, 30-35.
18. Hartigan, J. (1975), Clustering Algorithms, New York.
19. Kamakura, W. (1988), A Least Squares Procedure for Benefit Segmentation with Conjoint Experiments, Journal of Marketing Research, 25, 157-67.
20. Kamakura, W., Wedel, M. and Agrawal, J. (1994), Concomitant Variable Latent Class Models for Conjoint Analysis, International Journal of Research in Marketing, 11, 451-64.
21. Kotler, P. (1995), Marketing Management: Analysis, Planning, Implementation, and Control, 9th Edition, Englewood Cliffs, NJ.
22. Krieger, A. M. and Green, P.E. (1996), Modifying Cluster Based Segments to Enhance Agreement with an Exogenous Response Variable, Journal of Marketing Research, 33, 351-363.
23. Lawson, C. L. and Hanson, R. J. (1972), Solving Least Squares Problems. Engiewood CUffs, NJ.
24. Lin, S. and Kemighan, M. (1973), An Effective Heuristic Algorithm for the Traveling Salesman Problem, Operations Research, 21, 498-516.
25. Mahajan, V. and Jain, A. K. (1978). An Approach to Normative Segmentation, Journal of Marketing Research, 15. 338-345.
26. Moore, W. L. (1980), Levels of Aggregation in Conjoint Analysis: An Empirical Comparison. Journal of Marketing Research, 17, 516-523.
27. Ogawa, K. (1987), An Approach to Simultaneous Estimation and Segmentation in Conjoint Analysis. Marketing Science, 6. 66-81.
28. Punj, G. and Stewart, D. W. (1983), Cluster Analysis in Marketing Research: Review and Suggestions for Application, Journal of Marketing Research, 20, 134-48.
29. Rao, S. S. (1996), Engineering Optimization, Theory and Practice, 3rd Edition, New York. NY.
30. Smith, W. R. (1956), Product Differentiation and Market Segmentation as Alternative Marketing Strategies, Journal of Marketing. 21, 3-8.
31. Spath, H. (1985), Cluster Dissection and Analysis. New York.
32. Steenkamp, J.-B. and Wedel, M. (1992), Fuzzy Clusterwise Regression in Benefit Segmentation: Application and Investigation into its Validity, Journal of Business Research. 26, 237-49.
33. Stewart, D. (1981), The Application and Misapplication of Factor Analysis in Marketing Research, Journal of Marketing Research, 19, 51-62.
34. Vriens, M., Wedel, M. and Wilms, T. (1996), Metric Conjoint Segmentation Methods : A Monte Carlo Comparison. Journal of Marketing Research, 33. 73-85.
35. Wedel, M. and Kistemaker, C. (1989), Consumer Benefit Segmentation Using Clusterwise Linear Regression. International Journal of Research in Marketing., 6, 45-49.
36. Wedel, M. and Steenkamp, J.-B. (1989), Fuzzy Clusterwise Regression Approach to Benefit Segmentation. International Journal of Research in Marketing, 6, 241-58.
37. Wedel, M. and Steenkamp, J.-B. (1991), A Clusterwise Regression Method for Simultaneous Fuzzy Market Structuring and Benefit Segmentation, Journal of Marketing Research. 28, 385-96.
38. Wedel, M. and DeSarbo, W. S. (1994). A Rev iew of Latent Class Regression Models and Their Applications, in Advanced Methods for Marketing Research. R. P. Bagozzi (ed.), London, 353-388.
39. Wedel, M. and DeSarbo, W. S. (1995), A Mixture Likelihood Approach for Generalized Linear Models, Journal of Classification, 12. 1-35.
40. Wedel, M. and Kamakura, W. (2001), Market Segmentation: Conceptual and Methodological Foundations, 2nd Norwell, MA.
41. Wind, Y. (1978), Issues and Advances in Segmentation Research, Journal of Marketing Research, 15, 317-37.
42. Winter, F. W. (1979), A Cost-Benefit Approach To Market Segmentation, Journal of Marketing A3. 103-111.
43. Wittink, D. R. and Cattin, P. (1981). Alternative Estimation Methods for Conjoint Analysis, A Monte Carlo Study, Journal of Marketing Research. 28, 101-06.
44. Wittink, D. R. and Cattin, P. (1989), Commercial Use of Conjoint Analysis: An Update, Journal of Marketing. 53, 91 -96.
45. Wittink, D. R., Vriens, M. and Burhenne, W. (1994), Commercial Use of Conjoint Analysis in Europe. Results and Critical Reflections, International Journal of Research in Marketing, 11, 41-52.