The Impact of Utility Balance and Endogeneity in Conjoint Analysis
Published Online:1 Aug 2005https://doi.org/10.1287/mksc.1040.0108
References
- . Incorporating prior knowledge into the analysis of conjoint studies. J. Marketing Res. (1995) 32(2):152–163Crossref, Google Scholar
- . Improving parameter estimates and model prediction by aggregate customization in choice experiments. J. Consumer Res. (2001) 28(September):273–283Crossref, Google Scholar
- Competitive bidding in high-risk situations. J. Petroleum Tech. (1971) 23(June):641–653Crossref, Google Scholar
- Psychometric methods in marketing research: Part I, Conjoint analysis. J. Marketing Res. (1995) 32(November):385–391Crossref, Google Scholar
- A conjoint-based product designing procedure incorporating price competition. J. Product Innovation Management (1994) 11:451–459Crossref, Google Scholar
- . Generalized robust conjoint estimation. Marketing Sci. (2004) 24(3):415–429Link, Google Scholar
- . Attribute importance weights modification in assessing a brand’s competitive potential. Marketing Sci. (1995) 14(3, Part 1 of 2):253–270Link, Google Scholar
- Adaptive conjoint analysis: Some caveats and suggestions. J. Marketing Res. (1991) 28(2):215–222Crossref, Google Scholar
- Econometric Analysis (1993) 2nd ed.(Prentice-Hall, Inc., Englewood Cliffs, NJ) Google Scholar
- . Response latencies in the analysis of conjoint choice experiments. J. Marketing Res. (2000) 37(August):376–382Crossref, Google Scholar
- Intensity measures of consumer preference. Oper. Res. (1980) 28(2, March–April):278–320Link, Google Scholar
- , Wallendorf Melanie, Anderson Paul. Testing the impact of dimensional complexity and affective differences of paired concepts in adaptive conjoint analysis. Advances in Consumer Research (1986) 14(Associations of Consumer Research, Provo, UT) 159–163Google Scholar
- . The importance of utility balance in efficient choice designs. J. Marketing Res. (1996) 33(August):307–317Crossref, Google Scholar
- . The effectiveness of alternative preference elicitation procedures in predicting choice. J. Marketing Res. (1993) 30(1):105–114Crossref, Google Scholar
- . Measuring heterogeneous reservation prices for product bundles. Marketing Sci. (2003) 22(1, Winter):107–130Link, Google Scholar
- . Comment on adaptive conjoint analysis: Some caveats and suggestions. J. Marketing Res. (1991) 28(May):223–225Crossref, Google Scholar
- . Adaptive choice-based conjoint. (2003) (Sawtooth Software, Sequim, WA) Google Scholar
- The Theory and Practice of Econometrics (1985) (John Wiley and Sons, New York) Google Scholar
- . The winner’s curse and public information in common value auctions. Amer. Econom. Rev. (1986) 76(5, December):894–920Google Scholar
- Optimal design for multinomial choice experiments. J. Marketing Res. (2002) 39(May):214–227Crossref, Google Scholar
- . Efficient experimental design with marketing research applications. J. Marketing Res. (1994) 31(4, November):545–557Crossref, Google Scholar
- Hierarchical Bayes conjoint analysis: Recovery of partworth heterogeneity from reduced experimental designs. Marketing Sci. (1996) 15(2):173–191Link, Google Scholar
- The evolution of consumer utility functions in conjoint analysis. Marketing Sci. (2005) 24(2):285–293Link, Google Scholar
- A unified approach to conjoint analysis models. J. Amer. Statist. Assoc. (2002) 97(459, September):674–682Crossref, Google Scholar
- . ACA, CBC, or both: Effective strategies for conjoint research. (1999) . Working paper, Sawtooth Software, Sequim, WAGoogle Scholar
- . Improving the value of conjoint simulations. Marketing Res. (2000) 12(4, Winter):12–20Google Scholar
- . Improving ACA algorithms: Challenging a twenty-year-old approach. Advance Res. Tech. Conf. (2002) (American Marketing Association, Vail, Co) Google Scholar
- . Designing conjoint choice experiments using managers’ prior beliefs. J. Marketing Res. (2001) 38(4, November):430–444Crossref, Google Scholar
- . Profile construction in experimental choice designs for mixed logit models. Marketing Sci. (2002) 21(4, Fall):455–475Link, Google Scholar
- . Differentiated Bayesian conjoint choice designs, April 29, 2003. (2003) . ERIM Report Series Reference No. ERS-2003-016-MKT. http://ssrn.com/abstract=41161Google Scholar
- Sawtooth Software The ACA/hierarchical Bayes technical paper. (2001) (Sawtooth Software, Inc., Sequim, WA) Google Scholar
- Sawtooth Software ACA 5.0 technical paper. (2002) (Sawtooth Software, Inc., Sequim, WA) Sawtooth Software Technical Paper SeriesGoogle Scholar
- Sawtooth Software Update on relative conjoint analysis usage. Sawtooth Solutions (2004) Summer). http://www.sawtoothsoftware.com/productforms/ssolutions/ss20.shtml#ss20usageGoogle Scholar
- The cost of thinking. J. Consumer Res. (1980) 7(2, September):99–111Crossref, Google Scholar
- Enriching scanner panel models with choice experiments. Marketing Sci. (2003) 22(4):442–460Link, Google Scholar
- The Winner’s Curse: Paradoxes and Anomalies of Economic Life (1992) (Princeton University Press, Princeton, NJ) Google Scholar
- Polyhedral methods for adaptive choice-based conjoint analysis. J. Marketing Res. (2004) 41(1):116–131Crossref, Google Scholar
- . Fast polyhedral adaptive conjoint estimation. Marketing Sci. (2003) 22(3):273–303Link, Google Scholar

