Marketing Letters

, Volume 16, Issue 3–4, pp 197–208 | Cite as

Adjusting Choice Models to Better Predict Market Behavior

  • Greg Allenby
  • Geraldine Fennell
  • Joel Huber
  • Thomas Eagle
  • Tim Gilbride
  • Dan Horsky
  • Jaehwan Kim
  • Peter Lenk
  • Rich Johnson
  • Elie Ofek
  • Bryan Orme
  • Thomas Otter
  • Joan Walker


The emergence of Bayesian methodology has facilitated respondent-level conjoint models, and deriving utilities from choice experiments has become very popular among those modeling product line decisions or new product introductions. This review begins with a paradox of why experimental choices should mirror market behavior despite clear differences in content, structure and motivation. It then addresses ways to design the choice tasks so that they are more likely to reflect market choices. Finally, it examines ways to model the results of the choice experiments to better mirror both underlying decision processes and potential market choices.


Bayesian analysis extended model of behavior motivating conditions 


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Copyright information

© Springer Science + Business Media, Inc. 2005

Authors and Affiliations

  • Greg Allenby
    • 1
  • Geraldine Fennell
    • 2
  • Joel Huber
    • 3
  • Thomas Eagle
    • 4
  • Tim Gilbride
    • 5
  • Dan Horsky
    • 6
  • Jaehwan Kim
    • 7
  • Peter Lenk
    • 8
  • Rich Johnson
    • 9
  • Elie Ofek
    • 10
  • Bryan Orme
    • 11
  • Thomas Otter
    • 12
  • Joan Walker
    • 13
  1. 1.Ohio State University
  2. 2.ConsultantDublinIreland
  3. 3.Duke UniversityUSA
  4. 4.Eagle AnalyticsUSA
  5. 5.Notre Dame UniversityUSA
  6. 6.University of RochesterUSA
  7. 7.Korea UniversityKorea
  8. 8.University of Michigan
  9. 9.Sawtooth SoftwareUSA
  10. 10.Harvard UniversityUSA
  11. 11.Sawtooth SoftwareUSA
  12. 12.Ohio State University
  13. 13.Boston UniversityBoston

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