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Conjoint Choice Experiments: General Characteristics and Alternative Model Specifications

In: Conjoint Measurement

Author

Listed:
  • Rinus Haaijer

    (University of Groningen)

  • Michel Wedel

    (University of Groningen)

Abstract

Conjoint choice experimentation involves the design of product profiles on the basis of product attributes specified at certain levels, and requires respondents to repeatedly choose one alternative from different sets of profiles offered to them, instead of ranking or rating all profiles, as is usually done in various forms of classic metric conjoint studies. The Multinomial Logit (MNL) model has been the most frequently used model to analyze the 0/1 choice data arising from such conjoint choice experiments (e.g., Louviere and Woodworth 1983; Elrod, Louviere and Davey 1992). One of the first articles describing the potential advantages of a choice approach for conjoint analysis was by Madanski (1980). His conclusion was that conjoint analysts could adopt the random utility model approach to explain gross trends or predilections in decisions instead of each person's specific decision in each choice presented. The real breakthrough for conjoint choice came with the Louviere and Woodworth (1983) article in which they integrated the conjoint and discrete choice approaches.

Suggested Citation

  • Rinus Haaijer & Michel Wedel, 2007. "Conjoint Choice Experiments: General Characteristics and Alternative Model Specifications," Springer Books, in: Anders Gustafsson & Andreas Herrmann & Frank Huber (ed.), Conjoint Measurement, edition 0, chapter 11, pages 199-229, Springer.
    • Handle: RePEc:spr:sprchp:978-3-540-71404-0_11
    DOI: 10.1007/978-3-540-71404-0_11
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    Citations

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    Cited by:

    1. Kim, Hyunggeun & Park, Sangkyu & Lee, Jongsu, 2021. "Is renewable energy acceptable with power grid expansion? A quantitative study of South Korea's renewable energy acceptance," Renewable and Sustainable Energy Reviews, Elsevier, vol. 139(C).
    2. Hyunjoo Lee & Misuk Lee & Sesil Lim, 2018. "Do Consumers Care about the Energy Efficiency of Buildings? Understanding Residential Choice Based on Energy Performance Certificates," Sustainability, MDPI, vol. 10(11), pages 1-18, November.
    3. Moser, Nataliya, 2009. "Untersuchung Der Präferenzen Russischer Fachbesucher Für Ausgewählte Messeleistungen," IAMO Discussion Papers 91768, Institute of Agricultural Development in Transition Economies (IAMO).
    4. Brian Innes & John Cranfield, 2009. "Consumer preference for production-derived quality: analyzing perceptions of premium chicken production methods," Agribusiness, John Wiley & Sons, Ltd., vol. 25(3), pages 395-411.
    5. repec:zbw:iamodp:91768 is not listed on IDEAS
    6. Möser, Nataliya, 2009. "Untersuchung der Präferenzen russischer Fachbesucher für ausgewählte Messeleistungen [Analysis of preferences of Russian trade visitors for selected exhibit attributes]," IAMO Discussion Papers 124, Leibniz Institute of Agricultural Development in Transition Economies (IAMO).
    7. Sung-Yoon Huh & JongRoul Woo & Chul-Yong Lee, 2019. "What Do Potential Residents Really Want When Hosting a Nuclear Power Plant? An Empirical Study of Economic Incentives in South Korea," Energies, MDPI, vol. 12(7), pages 1-17, March.
    8. Kick, Markus & Littich, Martina, 2015. "Brand and Reputation as Quality Signals on Regulated Markets," EconStor Preprints 182503, ZBW - Leibniz Information Centre for Economics.
    9. Kick, Markus, 2015. "The Price Premium Induced by Branding: A Health Care Case Study," EconStor Preprints 182504, ZBW - Leibniz Information Centre for Economics.
    10. Jing Wang & Anocha Aribarg & Yves F. Atchadé, 2013. "Modeling Choice Interdependence in a Social Network," Marketing Science, INFORMS, vol. 32(6), pages 977-997, November.
    11. Rahel Renata Tanujaya & Chul-Yong Lee & JongRoul Woo & Sung-Yoon Huh & Min-Kyu Lee, 2020. "Quantifying Public Preferences for Community-Based Renewable Energy Projects in South Korea," Energies, MDPI, vol. 13(9), pages 1-13, May.

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