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What If Consumer Experiments Impact Variances as Well as Means? Response Variability as a Behavioral Phenomenon

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  • Louviere, Jordan J
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    Abstract

    This essay discusses the fact that in many cases means and variances of probability distributions are confounded and cannot be separated, which poses particular problems for analysis and interpretation of behavioral response data in consumer research. The discussion focuses on random utility theory to show that the confoundment of means and variances poses problems for published research in many areas of consumer behavior. Examples are provided to show why and how reported empirical differences in means may in fact be differences in variability. Ways to deal with the problem empirically are discussed. Copyright 2001 by the University of Chicago.

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    Bibliographic Info

    Article provided by University of Chicago Press in its journal Journal of Consumer Research.

    Volume (Year): 28 (2001)
    Issue (Month): 3 (December)
    Pages: 506-11

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    Handle: RePEc:ucp:jconrs:v:28:y:2001:i:3:p:506-11

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    Web page: http://www.journals.uchicago.edu/JCR/

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    Cited by:
    1. Vasquez Lavin, Felipe & Hanemann, W. Michael, 2008. "Taste Indicators and Heterogeneous Revealed Preferences for Congestion in Recreation Demand," Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series qt4rz5z706, Department of Agricultural & Resource Economics, UC Berkeley.
    2. Brett R. Gelso & John C. Whitehead, 2008. "Effect of US Policies on Offshore Oil Leasing, 1983-2006: A Random Parameter Logit Regression Analysis," Working Papers 08-03, Department of Economics, Appalachian State University.
    3. Kjaer, Trine & Gyrd-Hansen, Dorte, 2008. "Preference heterogeneity and choice of cardiac rehabilitation program: Results from a discrete choice experiment," Health Policy, Elsevier, vol. 85(1), pages 124-132, January.
    4. Teichert, Thorsten & Shehu, Edlira & von Wartburg, Iwan, 2008. "Customer segmentation revisited: The case of the airline industry," Transportation Research Part A: Policy and Practice, Elsevier, vol. 42(1), pages 227-242, January.
    5. Louviere, Jordan J. & Islam, Towhidul, 2008. "A comparison of importance weights and willingness-to-pay measures derived from choice-based conjoint, constant sum scales and best-worst scaling," Journal of Business Research, Elsevier, vol. 61(9), pages 903-911, September.
    6. Jens Hougaard & Tue Tjur & Lars Østerdal, 2012. "On the meaningfulness of testing preference axioms in stated preference discrete choice experiments," The European Journal of Health Economics, Springer, vol. 13(4), pages 409-417, August.
    7. Hu, Wuyang & Adamowicz, Wiktor L. & Veeman, Michele M., 2005. "Bayesian Analysis of Consumer Choices with Taste, Context, Reference Point and Individual Scale Effects," 2005 Annual meeting, July 24-27, Providence, RI 19296, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    8. Arne Risa Hole, 2006. "Small-sample properties of tests for heteroscedasticity in the conditional logit model," Health, Econometrics and Data Group (HEDG) Working Papers 06/04, HEDG, c/o Department of Economics, University of York.
    9. Rulleau, Bénédicte & Dachary-Bernard, Jeanne, 2012. "Preferences, rational choices and economic valuation: Some empirical tests," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 41(2), pages 198-206.
    10. Sackett, Hillary M., 2011. "Consumer Perceptions of Sustainable Farming Practices: A Best-Worst Scenario," Graduate Research Masters Degree Plan B Papers 115966, Michigan State University, Department of Agricultural, Food, and Resource Economics.

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