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

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  • John Rose
  • Iain Black

Abstract

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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  • John Rose & Iain Black, 2006. "Means matter, but variance matter too: Decomposing response latency influences on variance heterogeneity in stated preference experiments," Marketing Letters, Springer, vol. 17(4), pages 295-310, December.
    • Handle: RePEc:kap:mktlet:v:17:y:2006:i:4:p:295-310
    DOI: 10.1007/s11002-006-8632-3
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    Cited by:

    1. Johnson, F. Reed & Ozdemir, Semra & Phillips, Kathryn A., 2010. "Effects of simplifying choice tasks on estimates of taste heterogeneity in stated-choice surveys," Social Science & Medicine, Elsevier, vol. 70(2), pages 183-190, January.
    2. Mikołaj Czajkowski & Marek Giergiczny & William H. Greene, 2012. "Learning and Fatigue Effects Revisited. The Impact of Accounting for Unobservable Preference and Scale Heterogeneity on Perceived Ordering Effects in Multiple Choice Task Discrete Choice Experiments," Working Papers 2012-08, Faculty of Economic Sciences, University of Warsaw.
    3. Börjesson, Maria & Fosgerau, Mogens, 2015. "Response time patterns in a stated choice experiment," Journal of choice modelling, Elsevier, vol. 14(C), pages 48-58.
    4. Richard Yao & Riccardo Scarpa & John Rose & James Turner, 2015. "Experimental Design Criteria and Their Behavioural Efficiency: An Evaluation in the Field," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 62(3), pages 433-455, November.
    5. Seda Erdem & Danny Campbell, 2017. "Preferences for public involvement in health service decisions: a comparison between best-worst scaling and trio-wise stated preference elicitation techniques," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 18(9), pages 1107-1123, December.
    6. Liebe, Ulf & Glenk, Klaus & Oehlmann, Malte & Meyerhoff, Jürgen, 2015. "Does the use of mobile devices (tablets and smartphones) affect survey quality and choice behaviour in web surveys?," Journal of choice modelling, Elsevier, vol. 14(C), pages 17-31.
    7. Bujosa, Angel & Torres, Cati & Riera, Antoni, 2018. "Framing Decisions in Uncertain Scenarios: An Analysis of Tourist Preferences in the Face of Global Warming," Ecological Economics, Elsevier, vol. 148(C), pages 36-42.
    8. Tobias Börger, 2016. "Are Fast Responses More Random? Testing the Effect of Response Time on Scale in an Online Choice Experiment," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 65(2), pages 389-413, October.
    9. Danny Campbell & Morten Raun Mørkbak & Søren Bøye Olsen, 2017. "Response time in online stated choice experiments: the non-triviality of identifying fast and slow respondents," Journal of Environmental Economics and Policy, Taylor & Francis Journals, vol. 6(1), pages 17-35, January.
    10. 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.
    11. Tobias Börger & Joseph Cook, 2016. "Giving respondents “time to think” reduces response randomness in repeated discrete choice tasks," Discussion Papers in Environment and Development Economics 2016-13, University of St. Andrews, School of Geography and Sustainable Development.
    12. Campbell, Danny & Mørkbak, Morten Raun & Olsen, Søren Bøye, 2018. "The link between response time and preference, variance and processing heterogeneity in stated choice experiments," Journal of Environmental Economics and Management, Elsevier, vol. 88(C), pages 18-34.
    13. Mikolaj Czajkowski & Marek Giergiczny & William H. Greene, 2014. "Learning and Fatigue Effects Revisited: Investigating the Effects of Accounting for Unobservable Preference and Scale Heterogeneity," Land Economics, University of Wisconsin Press, vol. 90(2), pages 324-351.
    14. Marsh, Dan & Phillips, Yvonne, 2012. "Difficult Choices: What Influences the Error Variance in a Choice Experiment," 2012 Conference, August 31, 2012, Nelson, New Zealand 139651, New Zealand Agricultural and Resource Economics Society.
    15. Jang, Sunghoon & Rasouli, Soora & Timmermans, Harry, 2022. "The effect of task complexity on stated choice processes: The moderating role of cognitive ability," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 163(C).
    16. Hess, Stephane & Stathopoulos, Amanda, 2013. "Linking response quality to survey engagement: A combined random scale and latent variable approach," Journal of choice modelling, Elsevier, vol. 7(C), pages 1-12.
    17. Hess, Stephane & Rose, John M., 2009. "Allowing for intra-respondent variations in coefficients estimated on repeated choice data," Transportation Research Part B: Methodological, Elsevier, vol. 43(6), pages 708-719, July.

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