The “simulation approach,” or fraction of first choice aggregation method, is widely used for aggregating conjoint data. The authors compare preference-share estimates generated by the simulation approach with those generated by a logistic model using identical data. The share estimates obtained by the two methods generally are equivalent, especially for conditions of greatest interest to marketers, i.e., when the objective is to estimate the share captured by the most preferred of several differentiated concepts. However, the logistic model provides more efficient estimates than does the simulation approach, and also proves to be robust to violations of its theoretical underlying distribution.
Get full access to this article
View all access options for this article.
References
1.
BlattbergR. C. (1979), “Discussant's Comments,” in Advances in Consumer Research, Vol. 6, WilkieWilliam L., ed. Miami: Association for Consumer Research. 587–8.
2.
BockR. O. and JonesL. V. (1968), The Measurement and Prediction of Judgement and Choice.San Francisco: Holden-Day.
3.
ChurchillG. A. (1979), Marketing Research: Methodological Foundations, 2nd ed. Hinsdale, II: The Dryden Press.
4.
CoombsC. (1964), Theory of Data.New York: John Wiley & Sons, Inc.
5.
DixonW. J. and MassyF. J.Jr. (1957), Introduction to Statistical Analysis, 2nd ed. New York: McGraw-Hill Book Company, 124–7.
6.
FiedlerJ. A. (1972), “Condominium Design and Pricing: A Case Study in Consumer Trade-Off Analysis,” in Proceedings of the 3rd Annual Conference of Association for Consumer Research, VenkatesanM., ed., 279–93.
7.
GreenP. E., CarrollJ. D., and GoldbergS. M. (1979), “Modeling Consumer Choice Simulators—A New Approach to the Analysis of Trade-off Data,” working paper, University of Pennsylvania (September).
8.
GreenP. E., and DevitaM. T. (1974), “A Complementarity Model of Consumer Utility for Item Collections,” Journal of Consumer Research, 1 (December), 56–67.
9.
GreenP. E., and DevitaM. T. (1975), “An Interaction Model of Consumer Utility,” Journal of Consumer Research, 2 (September), 146–53.
10.
GreenP. E., and SrinivasanV. (1978), “Conjoint Analysis in Consumer Research: Issues and Outlook,” Journal of Consumer Research, 5 (September), 103–23.
11.
GreenP. E., WindY., and JainA. K. (1972), “Benefit Bundle Analysis,” Journal of Advertising Research, 12 (April), 31–6.
12.
GumbelE. J. (1961), “Bivariate Logistic Distributions,” Journal of the American Statistical Association, 56, 335–49.
13.
HastingsN. A. J. and PeacockJ. B. (1974), Statistical Distributions.New York: John Wiley & Sons, Inc.
14.
HuberJ. and MooreW. (1979), “A Comparison of Alternative Ways to Aggregate Individual Conjoint Analysis,” in Educators’ Conference Proceedings, LandonLaird, ed. Chicago: American Marketing Association, 64–8.
15.
JainA. K., MalhotraN. K., and MahajanV., (1979), “Aggregating Conjoint Data: Some Methodological Considerations and Approaches,” in Educators’ Conference Proceedings, LandonLaird, ed. Chicago: American Marketing Association, 74–7.
16.
JohnsonR. M. (1974), “Trade-off Analysis of Consumer Values,” Journal of Marketing Research, 11 (May), 121–27.
17.
MahajanV., GreenP. E., and GoldbergS. M. (1982), “A Conjoint Model for Measuring Self- and Cross-Price/Demand Relationships,” Journal of Marketing Research, 19 (August), 334–42.
18.
MorrisonD. F. (1976), Multivariate Statistical Methods, 2nd ed. New York: McGraw-Hill Book Company, 141–3.
19.
PearsonK. (1924), Tables for Statisticians and Biometricians, Part II.Cambridge, England: Cambridge University Press.
20.
PekelmanD. and SenS. K. (1979), “Measurement and Estimation of Conjoint Utility Functions,” Journal of Consumer Research, 5 (March), 263–71.
21.
TorgersonW. (1958), Theory and Methods of Scaling.New York: John Wiley & Sons, Inc.
22.
WileyJ. B. and BushnellR. (1979), “Market Share Estimates Based on Conjoint Analysis of Concepts,” in Advances in Consumer Research, Vol. 6, WilkieWilliam L., ed. Miami: Association for Consumer Research, 582–6.
23.
WileyJ. B. and LowJ. T. (1979), “A Generalized Logit Model to Aggregate Conjoint Data,” in Educators’ Conference Proceedings, LandonLaird, ed. Chicago: American Marketing Association, 78–82.
24.
WindY. (1976), “Preference of Relevant Others and Individual Choice Models,” Journal of Consumer Research, 3 (June), 50–7.
