Improving the value of conjoint simulations adding variability to choice models can help shine a light on market behavior

Marketing Research

Volumn 12, Issue 4, 2000, Pages 12-20

  Orme, Bryan ^a   Huber, Joel ^b  

^a Sawtooth Software Inc

^b DUKE UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 77449153522     PISSN: 10408460     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (9)

1. Arora, Neeraj, Greg Allenby, and James L. Ginter (1998), "A Hierarchical Bayes Model of Primary and Secondary Demand," Marketing Science, 17, 29-44.
2. Green, Paul E. and Abba M. Krieger (1988), "Choice Rules and Sensitivity Analysis in Conjoint Simulators," Journal of the Academy of Marketing Science, 16.1, 114-127.
3. Green, Paul E. and V. Srinivasan (1990), "Conjoint Analysis in Marketing: New Developments with Implications for Research and Practice," Journal of Marketing, 54, 3-19.
4. Hausman and Wise (1978), "A Conditional Probit Model for Quantitative Choice: Discrete Decision Recognizing Interdependence and Heterogeneous Preferences." Econometrica, 43, 402-426.
5. Huber, Joel and Klaus Zwerina (1996), "The Importance of Utility Balance in Efficient Choice Designs," Journal of Marketing Research, 23. 307-317.
6. Kamakura, Wagner A. and Gary I. Russell (1989), "A Probabilistic Choice Model for Market Segmentation and Elasticity Structure," Journal of Marketing Research, 26, 339-390.
7. McFadden, D. (1973), "Conditional Logit Analysis of Qualitative Choice Behavior," in Frontiers in Econometrics, P. Zarembka ed. New York: Academic Press.
8. Orme, Bryan K. and Michael Heft (1999), "Predicting Actual Sales with CBC: How Capturing Heterogeneity Improves Results," Sawtooth Software Conference Proceedings.
9. Revelt, David and Kenneth Train (1998), "Mixed Logit with Repeated Choices: Household's Choices of Appliance Efficiency Level," Review of Economics and Statistics, (Forthcoming).