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Conjoint Measurement with Constraints on Attribute Levels: A Mixture–Amount Model Approach

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  • Damaraju Raghavarao
  • James B. Wiley

Abstract

Traditional and choice‐based conjoint analyses (CAs) have used full or fractional factorial designs to generate concept profile descriptions. However, these designs confound two factors when costs are associated with attributes: first is the total cost of the concept profile, and second is the allocation of costs among the attributes. Both factors may influence consumers' preferences. So far, these issues have not been separated in the CA literature. The present paper shows how mixture–amount designs used in industrial experiments may be used to separate amount and mixture effects in traditional CA. The extension to choice‐based CA using balance incomplete block (BIB) designs is also given. L'analyse conjointe, classique ou basée sur les choix (CBC), a utilisé des plans factoriels complets ou fractionnés pour générer des descriptions de profils de concepts. Toutefois, ces plans confondent deux facteurs lorsque les coûts sont associés aux attributs: le premier est le coût total du profil de concept et le second est la répartition des coûts entre les attributs. Ces deux facteurs peuvent influencer les préférences des consommateurs. Jusqu'à présent, la littérature sur l'analyse conjointe n'a pas traité séparément ces problèmes. Cet article montre comment des plans de mélange mixture–amount utilisés dans des expériences en milieu industriel peuvent être utilisés pour séparer des effets de type montant et des effets de type mélange dans une analyse conjointe traditionnelle. Une extension à l'analyse conjointe CBC fondée sur des plans en blocs incomplets équilibrés (BIB) est également proposée.

Suggested Citation

  • Damaraju Raghavarao & James B. Wiley, 2009. "Conjoint Measurement with Constraints on Attribute Levels: A Mixture–Amount Model Approach," International Statistical Review, International Statistical Institute, vol. 77(2), pages 167-178, August.
    • Handle: RePEc:bla:istatr:v:77:y:2009:i:2:p:167-178
    DOI: 10.1111/j.1751-5823.2009.00077.x
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    References listed on IDEAS

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    1. Carol Propper, 1995. "The Disutility of Time Spent on the United Kingdom's National Health Service Waiting Lists," Journal of Human Resources, University of Wisconsin Press, vol. 30(4), pages 677-700.
    2. H Oppewal & H J P Timmermans & J J Louviere, 1997. "Modelling the Effects of Shopping Centre Size and Store Variety on Consumer Choice Behaviour," Environment and Planning A, , vol. 29(6), pages 1073-1090, June.
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    1. Zijlstra, Toon & Goos, Peter & Verhetsel, Ann, 2019. "A mixture-amount stated preference study on the mobility budget," Transportation Research Part A: Policy and Practice, Elsevier, vol. 126(C), pages 230-246.
    2. Dujuan Yang & Gamze Dane & Harry J.P. Timmermans, 2013. "Mixture–amount experiments for measuring consumer preferences of energy-saving adaptation strategies: principles and illustration," Chapters, in: Thomas Vanoutrive & Ann Verhetsel (ed.), Smart Transport Networks, chapter 10, pages 208-223, Edward Elgar Publishing.
    3. Boonaert, Eva & Hoyweghen, Kaat Van & Feyisa, Ashenafi Duguma & Goos, Peter & Maertens, Miet, 2021. "Twofold Gendered Preferences in the Quantity-Quality Trade-Off Impact the Demographic Transition in Ethiopia," 2021 Conference, August 17-31, 2021, Virtual 315224, International Association of Agricultural Economists.
    4. Dujuan Yang & Harry Timmermans & Aloys Borgers, 2016. "The prevalence of context-dependent adjustment of activity-travel patterns in energy conservation strategies: results from a mixture-amount stated adaptation experiment," Transportation, Springer, vol. 43(1), pages 79-100, January.
    5. Dujuan Yang & Harry Timmermans & Aloys Borgers, 2016. "The prevalence of context-dependent adjustment of activity-travel patterns in energy conservation strategies: results from a mixture-amount stated adaptation experiment," Transportation, Springer, vol. 43(1), pages 79-100, January.

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