IDEAS home Printed from https://ideas.repec.org/a/kap/mktlet/v17y2006i4p295-310.html
   My bibliography  Save this article

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

Author

Listed:
  • 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

Suggested Citation

  • 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
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s11002-006-8632-3
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s11002-006-8632-3?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. 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.
    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, Journal of Consumer Research Inc., vol. 28(1), pages 135-148, June.
    5. Brownstone, David & Bunch, David S. & Train, Kenneth, 2000. "Joint mixed logit models of stated and revealed preferences for alternative-fuel vehicles," Transportation Research Part B: Methodological, Elsevier, vol. 34(5), pages 315-338, June.
    6. Bettman, James R & Luce, Mary Frances & Payne, John W, 1998. "Constructive Consumer Choice Processes," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 25(3), pages 187-217, December.
    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. 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 419-440, June.
    9. 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.
    10. Brownstone, David & Bunch, David S. & Train, Kenneth, 2000. "Joint mixed logit models of stated and revealed preferences for alternative-fuel vehicles," Transportation Research Part B: Methodological, Elsevier, vol. 34(5), pages 315-338, June.
    11. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521747387, January.
    12. Bockenholt, Ulf & Albert, Dietrich & Aschenbrenner, Michael & Schmalhofer, Franz, 1991. "The effects of attractiveness, dominance, and attribute differences on information acquisition in multiattribute binary choice," Organizational Behavior and Human Decision Processes, Elsevier, vol. 49(2), pages 258-281, August.
    13. Chandra R. Bhat, 2000. "Incorporating Observed and Unobserved Heterogeneity in Urban Work Travel Mode Choice Modeling," Transportation Science, INFORMS, vol. 34(2), pages 228-238, May.
    14. Louviere, Jordan J, 2001. "What If Consumer Experiments Impact Variances as Well as Means? Response Variability as a Behavioral Phenomenon," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 28(3), pages 506-511, December.
    15. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Deka, Devajyoti & Carnegie, Jon, 2021. "Predicting transit mode choice of New Jersey workers commuting to New York City from a stated preference survey," Journal of Transport Geography, Elsevier, vol. 91(C).
    2. Haghani, Milad & Bliemer, Michiel C.J. & Hensher, David A., 2021. "The landscape of econometric discrete choice modelling research," Journal of choice modelling, Elsevier, vol. 40(C).
    3. Fosgerau, Mogens & Bierlaire, Michel, 2007. "A practical test for the choice of mixing distribution in discrete choice models," Transportation Research Part B: Methodological, Elsevier, vol. 41(7), pages 784-794, August.
    4. Paleti, Rajesh, 2018. "Generalized multinomial probit Model: Accommodating constrained random parameters," Transportation Research Part B: Methodological, Elsevier, vol. 118(C), pages 248-262.
    5. Stephane Hess & John W. Polak, 2004. "An analysis of parking behaviour using discrete choice models calibrated on SP datasets," ERSA conference papers ersa04p60, European Regional Science Association.
    6. repec:ehu:biltok:5564 is not listed on IDEAS
    7. Yang, Chih-Wen & Sung, Yen-Ching, 2010. "Constructing a mixed-logit model with market positioning to analyze the effects of new mode introduction," Journal of Transport Geography, Elsevier, vol. 18(1), pages 175-182.
    8. Haghani, Milad & Sarvi, Majid & Shahhoseini, Zahra, 2015. "Accommodating taste heterogeneity and desired substitution pattern in exit choices of pedestrian crowd evacuees using a mixed nested logit model," Journal of choice modelling, Elsevier, vol. 16(C), pages 58-68.
    9. Mariel, Petr & Ayala, Amaya de & Hoyos, David & Abdullah, Sabah, 2013. "Selecting random parameters in discrete choice experiment for environmental valuation: A simulation experiment," Journal of choice modelling, Elsevier, vol. 7(C), pages 44-57.
    10. Swait, Joffre, 2023. "Distribution-free estimation of individual parameter logit (IPL) models using combined evolutionary and optimization algorithms," Journal of choice modelling, Elsevier, vol. 47(C).
    11. 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.
    12. Ben-Elia, Eran & Shiftan, Yoram, 2010. "Which road do I take? A learning-based model of route-choice behavior with real-time information," Transportation Research Part A: Policy and Practice, Elsevier, vol. 44(4), pages 249-264, May.
    13. 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.
    14. Martin Achtnicht, 2012. "German car buyers’ willingness to pay to reduce CO 2 emissions," Climatic Change, Springer, vol. 113(3), pages 679-697, August.
    15. David Hensher & William Greene, 2003. "The Mixed Logit model: The state of practice," Transportation, Springer, vol. 30(2), pages 133-176, May.
    16. Hu, Wuyang & Adamowicz, Wiktor L. & Veeman, Michele M., 2004. "Decomposing Unobserved Choice Variability In The Presence Of Consumers' Taste Heterogeneity," 2004 Annual meeting, August 1-4, Denver, CO 19954, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    17. Frick, Bernd & Barros, Carlos Pestana & Prinz, Joachim, 2010. "Analysing head coach dismissals in the German "Bundesliga" with a mixed logit approach," European Journal of Operational Research, Elsevier, vol. 200(1), pages 151-159, January.
    18. Axsen, Jonn & Mountain, Dean C. & Jaccard, Mark, 2009. "Combining stated and revealed choice research to simulate the neighbor effect: The case of hybrid-electric vehicles," Resource and Energy Economics, Elsevier, vol. 31(3), pages 221-238, August.
    19. Koo, Yoonmo & Kim, Chang Seob & Hong, Junhee & Choi, Ie-Jung & Lee, Jongsu, 2012. "Consumer preferences for automobile energy-efficiency grades," Energy Economics, Elsevier, vol. 34(2), pages 446-451.
    20. Michael P. Keane & Nada Wasi, 2013. "The Structure of Consumer Taste Heterogeneity in Revealed vs. Stated Preference Data," Economics Papers 2013-W10, Economics Group, Nuffield College, University of Oxford.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:kap:mktlet:v:17:y:2006:i:4:p:295-310. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.