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Sequential choice designs to estimate the heterogeneity distribution of willingness-to-pay

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  • Vishva Danthurebandara
  • Jie Yu
  • Martina Vandebroek

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  • 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.
    • Handle: RePEc:kap:qmktec:v:9:y:2011:i:4:p:429-448
    DOI: 10.1007/s11129-011-9106-3
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    References listed on IDEAS

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    1. 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.
    2. Arora, Neeraj & Huber, Joel, 2001. "Improving Parameter Estimates and Model Prediction by Aggregate Customization in Choice Experiments," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 28(2), pages 273-283, September.
    3. Ramón Álvarez-Esteban, 2008. "Using discrete choice experiments to value health and health care," International Review on Public and Nonprofit Marketing, Springer;International Association of Public and Non-Profit Marketing, vol. 5(2), pages 201-203, December.
    4. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521766555.
    5. Banfi, Silvia & Farsi, Mehdi & Filippini, Massimo & Jakob, Martin, 2008. "Willingness to pay for energy-saving measures in residential buildings," Energy Economics, Elsevier, vol. 30(2), pages 503-516, March.
    6. Riccardo Scarpa & Mara Thiene & Kenneth Train, 2008. "Utility in Willingness to Pay Space: A Tool to Address Confounding Random Scale Effects in Destination Choice to the Alps," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 90(4), pages 994-1010.
    7. Joo Heon Park & Douglas L. MacLachlan, 2008. "Estimating Willingness to Pay with Exaggeration Bias-Corrected Contingent Valuation Method," Marketing Science, INFORMS, vol. 27(4), pages 691-698, 07-08.
    8. 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.
    9. Train, K. & Weeks, M., 2004. "Discrete Choice Models in Preference Space and Willingness-to Pay Space," Cambridge Working Papers in Economics 0443, Faculty of Economics, University of Cambridge.
    10. Toubia, Olivier & Hauser, John & Simester, Duncan, 2003. "Polyhedral Methods for Adaptive Choice-Based Conjoint Analysis," Working papers 4285-03, Massachusetts Institute of Technology (MIT), Sloan School of Management.
    11. 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.
    12. Scarpa, R. & Thiene, M. & Train, K., 2008. "Appendix to Utility in WTP space: a tool to address confounding random scale effects in destination choice to the Alps," American Journal of Agricultural Economics APPENDICES, Agricultural and Applied Economics Association, vol. 90(4), pages 1-9, January.
    13. Peter E. Rossi & Robert E. McCulloch & Greg M. Allenby, 1996. "The Value of Purchase History Data in Target Marketing," Marketing Science, INFORMS, vol. 15(4), pages 321-340.
    14. Cameron, Trudy Ann & James, Michelle D, 1987. "Efficient Estimation Methods for "Closed-ended' Contingent Valuation Surveys," The Review of Economics and Statistics, MIT Press, vol. 69(2), pages 269-276, May.
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    Cited by:

    1. Crabbe, M. & Vandebroek, M., 2012. "Improving the efficiency of individualized designs for the mixed logit choice model by including covariates," Computational Statistics & Data Analysis, Elsevier, vol. 56(6), pages 2059-2072.
    2. Vishva Danthurebandara & Jie Yu & Martina Vandebroek, 2015. "Designing choice experiments by optimizing the complexity level to individual abilities," Quantitative Marketing and Economics (QME), Springer, vol. 13(1), pages 1-26, March.
    3. 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.

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    More about this item

    Keywords

    Willingness-to-pay; Optimal experimental design; Sequential approach; Hierarchical Bayesian estimation; Panel mixed logit model; Heterogeneity distribution; C11; C25; C90;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • C90 - Mathematical and Quantitative Methods - - Design of Experiments - - - General

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