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Latent variables in discrete choice experiments

Author

Listed:
  • Rungie, Cam M.
  • Coote, Leonard V.
  • Louviere, Jordan J.
Abstract
This paper describes and applies a general approach for incorporating factors with structural equations into models for discrete choice. The approach gives form to the covariance matrix in random coefficient models. The factors act directly on the random coefficients as unobserved attributes. The structural equations allow the factors to act on each other building structures that can represent a variety of concepts such as global heterogeneity and segmentation. The practical outcomes include parsimonious and identified models with rich covariances and better fit. Of greater interest is the ability to specify models that represent and test theory on the relationships between the taste heterogeneities for covariates and in particular between the attributes within a discrete choice experiment. The paper describes the general model and then applies it to a discrete choice experiment with seven attributes. Four competing specifications are evaluated, which demonstrates the ability of the model to be identified and parsimonious. The four specifications also demonstrate how competing a priori knowledge of the structure of the attributes used in the experiment can be empirically tested and evaluated. The outcomes include new behavioral insights and knowledge about choice and choice processes for the subject area of discrete choice experiments.

Suggested Citation

  • Rungie, Cam M. & Coote, Leonard V. & Louviere, Jordan J., 2012. "Latent variables in discrete choice experiments," Journal of choice modelling, Elsevier, vol. 5(3), pages 145-156.
    • Handle: RePEc:eee:eejocm:v:5:y:2012:i:3:p:145-156
    DOI: 10.1016/j.jocm.2013.03.002
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    References listed on IDEAS

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    Cited by:

    1. Schmidt, Alejandro & Ortúzar, Juan de Dios & Paredes, Ricardo D., 2019. "Heterogeneity and college choice: Latent class modelling for improved policy making," Journal of choice modelling, Elsevier, vol. 33(C).
    2. Rungie, Cam & Scarpa, Riccardo & Thiene, Mara, 2014. "The influence of individuals in forming collective household preferences for water quality," Journal of Environmental Economics and Management, Elsevier, vol. 68(1), pages 161-174.
    3. Joseph F. Hair & Christian M. Ringle & Siegfried P. Gudergan & Andreas Fischer & Christian Nitzl & Con Menictas, 2019. "Partial least squares structural equation modeling-based discrete choice modeling: an illustration in modeling retailer choice," Business Research, Springer;German Academic Association for Business Research, vol. 12(1), pages 115-142, April.
    4. Oluwagbenga Akinwehinmi & Kolawole Ogundari & Taye Timothy Amos, 2022. "Consumers’ food control risk perception and preference for food safety certification in emerging food markets," Journal of Agricultural Economics, Wiley Blackwell, vol. 73(3), pages 690-708, September.
    5. Akinwehinmi, Oluwagbenga & Ogundari, Kolawole & Amos, Taiwo, 2021. "Consumers' Food Control Risk Perception and Preference for Government-Controlled Safety Certification in Emerging Food Markets," 2021 Conference, August 17-31, 2021, Virtual 315312, International Association of Agricultural Economists.
    6. Brown, Zachary S. & Dickinson, Katherine L. & Paskewitz, Susan, 2015. "A generalized latent class logit model of discontinuous preferences in repeated discrete choice data: an application to mosquito control in Madison, Wisconsin," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 205613, Agricultural and Applied Economics Association.
    7. Maren Hein & Peter Kurz & Winfried J. Steiner, 2020. "Analyzing the capabilities of the HB logit model for choice-based conjoint analysis: a simulation study," Journal of Business Economics, Springer, vol. 90(1), pages 1-36, February.
    8. Johanna Lena Dahlhausen & Cam Rungie & Jutta Roosen, 2018. "Value of labeling credence attributes—common structures and individual preferences," Agricultural Economics, International Association of Agricultural Economists, vol. 49(6), pages 741-751, November.
    9. Wong, Melvin & Farooq, Bilal & Bilodeau, Guillaume-Alexandre, 2018. "Discriminative conditional restricted Boltzmann machine for discrete choice and latent variable modelling," Journal of choice modelling, Elsevier, vol. 29(C), pages 152-168.
    10. Lee, Jae Hyun & Davis, Adam W. & Goulias, Konstadinos G., 2017. "Triggers of behavioral change: Longitudinal analysis of travel behavior, household composition and spatial characteristics of the residence," Journal of choice modelling, Elsevier, vol. 24(C), pages 4-21.
    11. Hasselbach, Johanna Lena & Rungie, Cam & Roosen, Jutta, 2015. "The value of ethical concern - Willingness to pay for animal welfare, local origin and organic production," 143rd Joint EAAE/AAEA Seminar, March 25-27, 2015, Naples, Italy 202729, European Association of Agricultural Economists.
    12. Brown, Zachary & Dickinson, Katherine L. & Paskewitz, Susan, 2016. "Partially observable latent class analysis (POLCA): An application to serial participation in mosquito control in Madison, Wisconsin," CEnREP Working Papers 340062, North Carolina State University, Department of Agricultural and Resource Economics.
    13. Sever, Ivan & Verbič, Miroslav & Klarić Sever, Eva, 2019. "Cost attribute in health care DCEs: Just adding another attribute or a trigger of change in the stated preferences?," Journal of choice modelling, Elsevier, vol. 32(C), pages 1-1.
    14. Daziano, Ricardo A., 2015. "Inference on mode preferences, vehicle purchases, and the energy paradox using a Bayesian structural choice model," Transportation Research Part B: Methodological, Elsevier, vol. 76(C), pages 1-26.
    15. Brown, Zachary & Dickinson, Katherine L. & Paskewitz, Susan, 2016. "Partially observable latent class analysis (POLCA): An application to serial participation in mosquito control in Madison, WI," CEnREP Working Papers 264979, North Carolina State University, Department of Agricultural and Resource Economics.
    16. Magor, Thomas J. & Coote, Leonard V., 2014. "Latent variables as a proxy for inherent preferences: A test of antecedent volition," Journal of choice modelling, Elsevier, vol. 13(C), pages 24-36.

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