Acta Oeconomica Pragensia 2013, 21(4):3-19 | DOI: 10.18267/j.aop.407

Hybrid Approach to Choice-Based Conjoint Analysis

Ondřej Vilikus
University of Economics, Prague, Faculty of Informatics and Statistics (ondrej.vilikus@vse.cz).

Conjoint analysis is a popular tool for analysing consumer preferences in market research which has undergone rapid development throughout history. It is now generally agreed that choice-based conjoint (CBC) has a stronger theoretical background than traditional conjoint methods and that it mimics the real decision-making process of consumers more closely. When hierarchical Bayesian models allowed robust estimation of consumer preferences from sparse data available from choice-based conjoint tasks, formerly popular self-explicated or hybrid approaches lost their popularity. In this article, it is shown that hybrid approaches can be a useful alternative to pure CBC design. A hybrid approach to CBC that combines self-explicated questions on attribute levels with individualised choice tasks is suggested and illustrated on a real example and its efficiency is compared to traditional CBC and adaptive CBC. The results of the study support the hypothesis that this approach can be beneficial under certain circumstances and yield higher model fit while keeping the questionnaire length and respondent fatigue at an acceptable level.

Keywords: hybrid approach, choice-based conjoint, Bayesian models, adaptive conjoint
JEL classification: C35, C91

Published: August 1, 2013  Show citation

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Vilikus, O. (2013). Hybrid Approach to Choice-Based Conjoint Analysis. Acta Oeconomica Pragensia21(4), 3-19. doi: 10.18267/j.aop.407
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References

  1. ALLENBY, G. M.; GINTER, J. L. Using Extremes to Design Products and Segment Markets. Journal of Marketing Research. 1995, Vol. 32, No. 4, p. 392-403. Go to original source...
  2. BUNCH, D. S.; LOUVIERE, J. J.; ANDERSON D. A Comparison of Experimental Design Strategies for Multinomial Logit Models: The Case of Generic Attributes. [Working paper UCDGSMWP# 11.96]. Davis: Graduate School of Management, University of California, 1996. faculty.gsm.ucda-vis.edu/~bunch/bla_wp_1996.pdf.
  3. CHRZAN, K.; ORME, B. An Overview and Comparison of Design Strategies for Choice-Based Conjoint Analysis. [Sawtooth Software Research Paper Series]. Sequim : Sawtooth Software, 2000. www. sawtoothsoftware.com/download/techpap/desgncbc.pdf.
  4. GREEN, P E.; RAO, V. R. Conjoint Measurement for Quantifying Judgmental Data. Journal of Marketing Research. 1971, Vol. 8, p. 355-363. Go to original source...
  5. GREEN, P E.; WIND, Y New Way to Measure Consumers' Judgements. Harvard Business Review. 1975, July-August, p. 107-117.
  6. HEBÁK, P Srovnání klasické a bayesovské pravděpodobnosti a statistiky (1.). Acta Oeconomica Pragensia. 2012, No. 1, p. 69-87. Go to original source...
  7. HUBER, J.; ZWERINA, K. The Importance of Utility Balance in Efficient Choice Designs. Journal of Marketing Research. 1996, Vol. 33, p. 307-317. Go to original source...
  8. JOHNSON, R. M.; ORME, B. K. A New Approach to Adaptive CBC. In Sawtooth Software (ed.) 2007 Sawtooth Software Conference Proceedings. 2007, p. 67-84.
  9. LAZARI, A. G.; ANDERSON D. A. Designs of Discrete Choice Experiments for Estimating Both Attribute and Availability Cross Effects. Journal of Marketing Research. 1994, Vol. 31, p. 375-383. Go to original source...
  10. LENK, P J.; DESARBO, W. S.; GREEN P E.; YOUNG, M. R. Hierarchical Bayes Conjoint Analysis: Recovery of Partworth Heterogeneity from Reduced Experimental Designs. Marketing Science. 1996, Vol. 15, p. 173-191. Go to original source...
  11. MCFADDEN, D. Conditional Logit Analysis of Qualitative Choice Behavior. Frontiers in Econometrics. 1974, Vol. 1, No. 2, p. 105-142.
  12. ORME, B. K. Task Order Effects in Menu-Based Choice. [Sawtooth Software Technical Paper Series]. Sequim, WA : Sawtooth Software, 2010. www.sawtoothsoftware.com/ download/techpap/mbcorder2010.pdf.
  13. SAWTOOTH SOFTWARE. ACBC Technical Paper. Sequim, WA : Sawtooth Software, 2009. www.sawto-othsoftware.com/download/techpap/acbctech.pdf.
  14. VILIKUS, O. Analýza heterogenních preferencí pomocí hierarchických modelů. In DOUCEK, P; NEDO-MOVÁ, L. (ed.). Sborník prací účastníků vědeckého semináře doktorského studia FIS VŠE. Praha : Nakladatelství Oeconomica, 2012, s. 259-268.

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