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Means matter, but variance matter too: Decomposing response latency influences on variance heterogeneity in stated preference experiments

  • John Rose

    ()

  • Iain Black

    ()

Registered author(s):

    Response time latencies have been shown to influence consumer’s choice behaviour in choice-based-conjoint studies. The literature has shown that response time latencies affect the mean outputs of parameter estimates derived from models of discrete choice. In this paper, we add further insight into the influences response time latencies have on such models by modelling latent response information associated with the variance of random parameter distributions through parameterisation of variance heterogeneity (or heteroskedasticity). We demonstrate that response time latencies influence not only the means of random parameter distributions, but also the variances, and that failure to account for both may result in incorrect model inferences being drawn. Copyright Springer Science + Business Media, LLC 2006

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    File URL: http://hdl.handle.net/10.1007/s11002-006-8632-3
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    Article provided by Springer in its journal Marketing Letters.

    Volume (Year): 17 (2006)
    Issue (Month): 4 (December)
    Pages: 295-310

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    Handle: RePEc:kap:mktlet:v:17:y:2006:i:4:p:295-310
    Contact details of provider: Web page: http://www.springerlink.com/link.asp?id=100312

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    1. Kenneth Train, 2003. "Discrete Choice Methods with Simulation," Online economics textbooks, SUNY-Oswego, Department of Economics, number emetr2, September.
    2. Cooke, Alan D. J. & Mellers, Barbara A., 1995. "Attribute Range and Response Range: Limits of Compatibility in Multiattribute Judgment," Organizational Behavior and Human Decision Processes, Elsevier, vol. 63(2), pages 187-194, August.
    3. Brownstone, David & Bunch, David S & Train, Kenneth, 1999. "Joint mixed logit models of stated and revealed preferences for alternative-fuel vehicles," University of California Transportation Center, Working Papers qt45f996hh, University of California Transportation Center.
    4. Swait, Joffre & Adamowicz, Wiktor, 2001. " The Influence of Task Complexity on Consumer Choice: A Latent Class Model of Decision Strategy Switching," Journal of Consumer Research, University of Chicago Press, vol. 28(1), pages 135-48, June.
    5. 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.
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    7. Bettman, James R & Luce, Mary Frances & Payne, John W, 1998. " Constructive Consumer Choice Processes," Journal of Consumer Research, University of Chicago Press, vol. 25(3), pages 187-217, December.
    8. Daniel McFadden & Kenneth Train, 2000. "Mixed MNL models for discrete response," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(5), pages 447-470.
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    10. Bhat, Chandra & Zhao, Huimin, 2002. "The spatial analysis of activity stop generation," Transportation Research Part B: Methodological, Elsevier, vol. 36(6), pages 557-575, July.
    11. DeShazo, J. R. & Fermo, German, 2002. "Designing Choice Sets for Stated Preference Methods: The Effects of Complexity on Choice Consistency," Journal of Environmental Economics and Management, Elsevier, vol. 44(1), pages 123-143, July.
    12. de Palma, Andre & Myers, Gordon M & Papageorgiou, Yorgos Y, 1994. "Rational Choice under an Imperfect Ability to Choose," American Economic Review, American Economic Association, vol. 84(3), pages 419-40, June.
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