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Fast algorithms to generate individualized designs for the mixed logit choice model

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  • Crabbe, Marjolein
  • Akinc, Deniz
  • Vandebroek, Martina

Abstract

The mixed logit choice model has become the common standard to analyze transport behavior. Moreover, more and more transport studies start to make use of stated preference data to obtain precise knowledge on travelers’ preferences. Accounting for the individual-specific coefficients in the mixed logit choice model, this research advocates an individualized design approach to generate these stated choice experiments. Individualized designs are sequentially generated for each person separately, using the answers from previous choice sets to select the next best set in a survey. In this way they are adapted to the specific preferences of an individual and therefore more efficient than an aggregate design. In order for individual sequential designs to be practicable, the speed of designing an additional choice set in an experiment is obviously a key issue. This paper introduces three design criteria used in optimal test design, based on Kullback–Leibler information, and compares them with the well known D-efficiency criterion to obtain individually adapted choice designs for the mixed logit choice model. Being equally efficient to D-efficiency and at the same time much faster, the Kullback–Leibler criteria are well suited for the design of individualized choice experiments.

Suggested Citation

  • Crabbe, Marjolein & Akinc, Deniz & Vandebroek, Martina, 2014. "Fast algorithms to generate individualized designs for the mixed logit choice model," Transportation Research Part B: Methodological, Elsevier, vol. 60(C), pages 1-15.
    • Handle: RePEc:eee:transb:v:60:y:2014:i:c:p:1-15
    DOI: 10.1016/j.trb.2013.11.008
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    as
    1. Bhat, Chandra R., 1998. "Accommodating variations in responsiveness to level-of-service measures in travel mode choice modeling," Transportation Research Part A: Policy and Practice, Elsevier, vol. 32(7), pages 495-507, September.
    2. Bliemer, Michiel C.J. & Rose, John M., 2010. "Construction of experimental designs for mixed logit models allowing for correlation across choice observations," Transportation Research Part B: Methodological, Elsevier, vol. 44(6), pages 720-734, July.
    3. Yu, Jie & Goos, Peter & Vandebroek, Martina, 2011. "Individually adapted sequential Bayesian conjoint-choice designs in the presence of consumer heterogeneity," International Journal of Research in Marketing, Elsevier, vol. 28(4), pages 378-388.
    4. Espino, Raquel & Martín, Juan Carlos & Román, Concepción, 2008. "Analyzing the effect of preference heterogeneity on willingness to pay for improving service quality in an airline choice context," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 44(4), pages 593-606, July.
    5. Chun Wang & Hua-Hua Chang, 2011. "Item Selection in Multidimensional Computerized Adaptive Testing—Gaining Information from Different Angles," Psychometrika, Springer;The Psychometric Society, vol. 76(3), pages 363-384, July.
    6. Hess, Stephane & Adler, Thomas & Polak, John W., 2007. "Modelling airport and airline choice behaviour with the use of stated preference survey data," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 43(3), pages 221-233, May.
    7. Greene, William H. & Hensher, David A. & Rose, John, 2006. "Accounting for heterogeneity in the variance of unobserved effects in mixed logit models," Transportation Research Part B: Methodological, Elsevier, vol. 40(1), pages 75-92, January.
    8. Jie Yu & Peter Goos & Martina Vandebroek, 2009. "Efficient Conjoint Choice Designs in the Presence of Respondent Heterogeneity," Marketing Science, INFORMS, vol. 28(1), pages 122-135, 01-02.
    9. Zsolt Sándor & Michel Wedel, 2002. "Profile Construction in Experimental Choice Designs for Mixed Logit Models," Marketing Science, INFORMS, vol. 21(4), pages 455-475, February.
    10. Hess, Stephane & Hensher, David A., 2010. "Using conditioning on observed choices to retrieve individual-specific attribute processing strategies," Transportation Research Part B: Methodological, Elsevier, vol. 44(6), pages 781-790, July.
    11. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521747387.
    12. David Hensher & William Greene, 2003. "The Mixed Logit model: The state of practice," Transportation, Springer, vol. 30(2), pages 133-176, May.
    13. John M. Rose & Michiel C. J. Bliemer, 2008. "Constructing Efficient Stated Choice Experimental Designs," Transport Reviews, Taylor & Francis Journals, vol. 29(5), pages 587-617, October.
    14. Axhausen, Kay W. & Hess, Stephane & König, Arnd & Abay, Georg & Bates, John J. & Bierlaire, Michel, 2008. "Income and distance elasticities of values of travel time savings: New Swiss results," Transport Policy, Elsevier, vol. 15(3), pages 173-185, May.
    15. A. Jourdan & J. Franco, 2010. "Optimal Latin hypercube designs for the Kullback–Leibler criterion," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 94(4), pages 341-351, December.
    16. Vishva Danthurebandara & Jie Yu & Martina Vandebroek, 2011. "Sequential choice designs to estimate the heterogeneity distribution of willingness-to-pay," Quantitative Marketing and Economics (QME), Springer, vol. 9(4), pages 429-448, December.
    17. David Revelt & Kenneth Train, 1998. "Mixed Logit With Repeated Choices: Households' Choices Of Appliance Efficiency Level," The Review of Economics and Statistics, MIT Press, vol. 80(4), pages 647-657, November.
    18. Ben-Akiva, M. & Bolduc, D. & Bradley, M., 1993. "Estimation of Travel Choice Models with Randomly Distributed Values of Time," Papers 9303, Laval - Recherche en Energie.
    19. Yu, Jie & Goos, Peter & Vandebroek, Martina, 2010. "Comparing different sampling schemes for approximating the integrals involved in the efficient design of stated choice experiments," Transportation Research Part B: Methodological, Elsevier, vol. 44(10), pages 1268-1289, December.
    20. Hess, Stephane & Train, Kenneth E., 2011. "Recovery of inter- and intra-personal heterogeneity using mixed logit models," Transportation Research Part B: Methodological, Elsevier, vol. 45(7), pages 973-990, August.
    21. Hess, Stephane & Bierlaire, Michel & Polak, John W., 2005. "Estimation of value of travel-time savings using mixed logit models," Transportation Research Part A: Policy and Practice, Elsevier, vol. 39(2-3), pages 221-236.
    22. Peter J. Lenk & Wayne S. DeSarbo & Paul E. Green & Martin R. Young, 1996. "Hierarchical Bayes Conjoint Analysis: Recovery of Partworth Heterogeneity from Reduced Experimental Designs," Marketing Science, INFORMS, vol. 15(2), pages 173-191.
    23. Bhat, Chandra R., 2012. "Recent developments in discrete choice model formulation, estimation, and inference," Transportation Research Part B: Methodological, Elsevier, vol. 46(2), pages 273-275.
    24. Ying Cheng, 2009. "When Cognitive Diagnosis Meets Computerized Adaptive Testing: CD-CAT," Psychometrika, Springer;The Psychometric Society, vol. 74(4), pages 619-632, December.
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