Response Time Patterns in a Stated Choice Experiment

Börjesson, Maria and Fosgerau, Mogens (2015): Response Time Patterns in a Stated Choice Experiment. Forthcoming in: Journal of Choice Modelling

Abstract

This paper studies how response times vary between unlabeled binary choice occasions in a stated choice (SC) experiment, with alternatives differing with respect to in-vehicle travel time and travel cost. The pattern of response times is interpreted as an indicator of the cognitive processes employed by the respondents when making their choices. We find clear signs of reference-dependence in response times in the form of a strong gain-loss asymmetry. Moreover, different patterns of response times for travel time and travel cost indicate that these attributes are processed in different ways by respondents. This may be of particular relevance for choice experiments in the transportation field, where the travel time attribute is central.

• Item Type: MPRA Paper
• Language: English
• Keywords: Response Times; Stated Choice; Data collection; Value of time
• Subjects: C - Mathematical and Quantitative Methods > C8 - Data Collection and Data Estimation Methodology ; Computer Programs > C83 - Survey Methods ; Sampling Methods; D - Microeconomics > D8 - Information, Knowledge, and Uncertainty > D87 - Neuroeconomics; R - Urban, Rural, Regional, Real Estate, and Transportation Economics > R4 - Transportation Economics > R41 - Transportation: Demand, Supply, and Congestion ; Travel Time ; Safety and Accidents ; Transportation Noise

References

Bates, J., & Whelan, G. (2001). Size and sign of time savings. Working Paper. Institute of Transport Studies, University of Leeds , Leeds, UK. Retrieved from http://www.its.leeds.ac.uk/

Börjesson, M., & Eliasson, J. (2014). Experiences from the Swedish Value of Time study. Transportation Research A, 59, 144–158.

Cantillo, V., Heydecker, B., & Ortúzar, J. de D. (2006). A discrete choice model incorporating thresholds for perception in attribute values. Transportation Research Part B: Methodological, 40(9), 807–825. doi:10.1016/j.trb.2005.11.002

Daly, A., Tsang, F., & Rohr, C. (2011). The value of small time savings for non-business travel. Proceedings from the European Transport Conference, 2011.

De Borger, B., & Fosgerau, M. (2008). The trade-off between money and travel time: A test of the theory of reference-dependent preferences. Journal of Urban Economics, 64(1), 101–115. doi:16/j.jue.2007.09.001

Hess, S., & Rose, J. M. (2012). Can scale and coefficient heterogeneity be separated in random coefficients models? Transportation, 39(6), 1225–1239. doi:10.1007/s11116-012-9394-9

Hess, S., & Stathopoulos, A. (2013). Linking response quality to survey engagement: A combined random scale and latent variable approach. Journal of Choice Modelling, 7, 1–12. doi:10.1016/j.jocm.2013.03.005

Higgins, E. T. (1996). Knowledge activation: Accessibility, applicability, and salience. In E. T. Higgins & A. W. Kruglanski (Eds.), Social psychology: Handbook of basic principles (pp. 133–168). New York, NY, US: Guilford Press.

Hjorth, K., & Fosgerau, M. (2011). Loss Aversion and Individual Characteristics. Environmental and Resource Economics, 49(4), 573–596. doi:10.1007/s10640-010-9455-5

Hultkrantz, L., Mortazavi, R., & Hulkranz, L. (2001). Anomalies in the Value of Travel-Time Changes. Journal of Transport Economics and Policy, 35(2), 285–299. doi:10.2307/20053871

Kahneman, D. (2003). Maps of Bounded Rationality: Psychology for Behavioral Economics. The American Economic Review, 93(5), 1449–1475.

Klein, N. M., & Yadav, M. S. (1989). Context Effects on Effort and Accuracy in Choice: An Enquiry into Adaptive Decision Making. Journal of Consumer Research, 15(4), 411–421.

Louviere, J., & Eagle, T. (2006). Confound it! That pesky little scale constant messes up our convenient assumptions. Retrieved from http://epress.lib.uts.edu.au/research/handle/10453/7515

Louviere, J. J., Meyer, R. J., Bunch, D. S., Carson, R., Dellaert, B., Hanemann, W. M., … Irwin, J. (1999). Combining Sources of Preference Data for Modeling Complex Decision Processes. Marketing Letters, 10(3), 205–217. doi:10.1023/A:1008050215270

Louviere, J., Street, D., Carson, R., Ainslie, A., Deshazo, J. R., Cameron, T., … Marley, T. (2002). Dissecting the Random Component of Utility. Marketing Letters, 13(3), 177–193. doi:10.1023/A:1020258402210

Malhotra, N. (2008). Completion Time and Response Order Effects in Web Surveys. Public Opinion Quarterly, 72(5), 914–934. doi:10.1093/poq/nfn050

Pagan, A., & Ullah, A. (1999). Nonparametric Econometrics. Cambridge University Press.

Palmer, S. E. (1999). Vision science: Photons to phenomenology (Vol. xxii). Cambridge, MA, US: The MIT Press.

Rose, J. M., & Black, I. R. (2006). Means matter, but variance matter too: Decomposing response latency influences on variance heterogeneity in stated preference experiments. Marketing Letters, 17(4), 295–310. doi:10.1007/s11002-006-8632-3

Susilo, Y. (2005). The Short-term Variability and the Long-term Changes of Individual Spatial Behavior in Urban Areas (PhD Thesis). Kyoto University.

Swait, J., & Bernardino, A. (2000). Distinguishing taste variation from error structure in discrete choice data. Transportation Research Part B: Methodological, 34(1), 1–15. doi:10.1016/S0191-2615(99)00009-0

Tom, S. M., Fox, C. R., Trepel, C., & Poldrack, R. A. (2007). The Neural Basis of Loss Aversion in Decision-Making Under Risk. Science, 315(5811), 515–518. doi:10.1126/science.1134239

Tversky, A., & Kahneman, D. (1991). Loss Aversion in Riskless Choice: A Reference-Dependent Model. The Quarterly Journal of Economics, 106(4), 1039–1061. doi:10.2307/2937956