Probabilistic Polyhedral Methods for Adaptive Choice-Based Conjoint Analysis: Theory and Application

References

• Ailawadi K. L., Kopalle P. K., Neslin S. A. Predicting competitive response to a major policy change: Combining game-theoretic and empirical analyses. Marketing Sci. (2005) 24(1):12–24Link, Google Scholar
• Allenby G. M., Arora N., Ginter J. L. Incorporating prior knowledge into the analysis of conjoint studies. J. Marketing Res. (1995) 32(May):152–162Crossref, Google Scholar
• Arora N., Huber J. Improving parameter estimates and model prediction by aggregate customization in choice experiments. J. Consumer Res. (2001) 28(September):273–283Crossref, Google Scholar
• Belloni A., Freund R., Selove M., Simester D. Optimizing product line designs: Efficient methods and comparisons. Management Sci. (2005) . ForthcomingGoogle Scholar
• Courtney S. Screwcap wine seals: Has Kiwi ingenuity gone too far? Wine of the Week (2001) August). http://www.wineoftheweek.com/screwcaps/history.htmlGoogle Scholar
• Evgeniou T., Boussious C., Zacharia G. Generalized robust conjoint estimation. Marketing Sci. (2005) 24(3):415–429Link, Google Scholar
• Hauser J. R., Toubia O. The impact of utility balance and endogeneity in conjoint analysis. Marketing Sci. (2005) 24(3):498–507Link, Google Scholar
• Huber J., Zwerina K. The importance of utility balance in efficient choice designs. J. Marketing Res. (1996) 33(August):307–317Crossref, Google Scholar
• Kanninen B. J. Optimal design for multinomial choice experiments. J. Marketing Res. (2002) 36(May):214–227Crossref, Google Scholar
• Liechty J. C., Fong D. K. H., DeSarbo W. Dynamic models incorporating individual heterogeneity: Utility evolution in conjoint analysis. Marketing Sci. (2005) 24(2):285–293Link, Google Scholar
• Liu Q., Otter T., Allenby G. M. Investigating endogeneity bias in marketing. Marketing Sci. (2006) 26(5):640–648Google Scholar
• Lockshin L., Quester P., Spawton T. Segmentation by involvement or nationality for global retailing: A cross-national comparative study of wine shopping behavior. J. Wine Res. (2001) 12(December):223–236Crossref, Google Scholar
• Rossi P. E., Allenby G. M. Bayesian statistics and marketing. Marketing Sci. (2003) 22(3):304–328Link, Google Scholar
• Rust R. T., Verhoef P. C. Optimizing the marketing interventions mix in intermediate-term CRM. Marketing Sci. (2005) 24(3):477–489Link, Google Scholar
• Spall J. C.Introduction to Stochastic Search and Optimization: Estimation, Simulation, and Control (2003) (Wiley-Interscience, Hoboken, NJ) Crossref, Google Scholar
• Toubia O., Hauser J. R., Simester D. I. Polyhedral methods for adaptive choice-based conjoint analysis. J. Marketing Res. (2004) 41(February):116–131Crossref, Google Scholar
• Toubia O., Simester D., Hauser J. R., Dahan E. Fast polyhedral adaptive conjoint estimation. Marketing Sci. (2003) 22(3):273–303Link, Google Scholar