Transportation

, Volume 32, Issue 3, pp 203–222 | Cite as

The implications on willingness to pay of respondents ignoring specific attributes

Abstract

Individuals processing the information in a stated choice experiment are typically assumed to evaluate each and every attribute offered within and between alternatives, and to choose their most preferred alternative. However, it has always been thought that some attributes are ignored in this process for many reasons, including a coping strategy to handle one’s perception of the complexity of the choice task. Nonetheless, analysts typically proceed to estimate discrete choice models as if all attributes have influenced the outcome to some degree. The cognitive processes used to evaluate trade-offs are complex with boundaries often placed on the task to assist the respondent. These boundaries can include prioritising attributes and ignoring specific attributes. In this paper we investigate the implications of bounding the information processing task by attribute elimination through ignoring one or more attributes. Using a sample of car commuters in Sydney we estimate mixed logit models that assume all attributes are candidate contributors, and models that assume certain attributes are ignored, the latter based on supplementary information provided by respondents. We compare the value of travel time savings under the alternative attribute processing regimes. Assuming that all attributes are not ignored and duly processed, leads to estimates of parameters which produce significantly different willingness to pay (WTP) to that obtained when the exclusion rule is invoked.

Keywords

complexity information processing relevance stated choice designs willingness to pay 

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References

  1. Aarts, H, Dijksterhuis, A 2000The automatic activation of goal-directed behaviour: The case of travel habitJournal of Environmental Psychology207582Google Scholar
  2. Aarts, H, Verplanken, B, Knippenberg, A 1997Habit and information use in travel mode choicesActa Psychologica96114Google Scholar
  3. Arentze, T, Borgers, A, Timmermans, H, Del Mistro, R 2003Transport stated choice responses: Effects of task complexity, presentation format and literacyTransportation Research39E229244Google Scholar
  4. Berlyne, DE 1960Conflict, arousal and curiosityMcGraw-HillNew YorkGoogle Scholar
  5. Carlsson, F, Martinsson, P 2003Design techniques for stated preference methods in health economicsHealth Economics.12281294Google Scholar
  6. Dellaert, BGC, Brazell, JD, Louviere, JJ 1999The effect of attribute variation on consumer choice consistencyMarketing Letters10139147Google Scholar
  7. DeShazo, JR, Fermo, G 2001Designing choice sets for stated preference methods: The effects of complexity on choice consistencyJournal of Environmental Economics and Management43360385Google Scholar
  8. DeShazo JR & Fermo G (2004) Implications of Rationally-Adaptive Pre-choice Behaviour for the Design and Estimation of Choice Models, Working paper, School of Public Policy and Social Research, University of California at Los Angeles.Google Scholar
  9. Greene, WH, Hensher, DA, Rose, J 2004Accounting for Heterogeneity in the Variance of Unobserved Effects in Mixed Logit ModelsNew York University: Department of EconomicsStern School of BusinessGoogle Scholar
  10. Heiner, RA 1983The origin of predictable behaviourAmerican Economic Review73560595Google Scholar
  11. Hensher DA (in press) Revealing differences in willingness to pay due to the dimensionality of stated choice designs: An initial assessment. Journal of Environmental and Resource Economics.Google Scholar
  12. Hensher, DA 2004Accounting for stated choice design dimensionality in willingness to pay for travel time savingsJournal of Transport Economics and Policy38425446Google Scholar
  13. Hensher DA (2004a) How do Respondents Handle Stated Choice Experiments? - Information Processing Strategies under Varying Information Load, Institute of Transport Studies, The University of Sydney.Google Scholar
  14. Hensher, DA, Greene, WH 2003Mixed logit models: State of practiceTransportation30133176Google Scholar
  15. Hensher DA, Greene W & Rose J (2003) Deriving Willingness to Pay Estimates from Observation Specific Parameters, Institute of Transport Studies, The University of Sydney.Google Scholar
  16. Hensher DA, Puckett S & Rose J (2004) Agency Decision Making in Freight Distribution Chains: Revealing a Parsimonious Empirical Strategy from Alternative Behavioural Structures, Institute of Transport Studies, The University of Sydney.Google Scholar
  17. Jacoby, L 1991A process dissociation framework: Separating automatic from intentional uses of memoryJournal of Memory and Language30513541CrossRefGoogle Scholar
  18. Jacoby, L 1998Invariance in automatic influence of memory: Toward a user’s guide for the process-dissociation procedureJournal of Experimental Psychology24326Google Scholar
  19. Jacoby, L, Toth, J, Yonelinas, A, Debner, J 1994The relationship between conscious and unconscious influences: Independence or redundancyJournal of Experimental Psychology123216219Google Scholar
  20. WA, Kamakura, B-D, Kim, J, Lee 1996Modelling preference and structural heterogeneity in consumer choiceMarketing Science15152172Google Scholar
  21. Khan, BE 1995Consumer variety-seeking among goods and services: An integrative reviewJournal of Retailing and Consumer Services2139148Google Scholar
  22. Louviere, J, Carson, R, Ainslie, A, Cameron, T, DeShazo, JR, Hensher, D, Kohn, R, Marley, T, Street, D 2002Dissecting the Random Component of Utility, Workshop Report for the Asilomar Invitational Choice SymposiumCalifornia; Marketing Letters13163176Google Scholar
  23. Malhotra, NK 1982Information load and consumer decision makingJournal of Consumer Research8419430Google Scholar
  24. Ohler, T, Li, A, Louviere, J, Swait, J 2000Attribute range effects in binary response tasksMarketing Letters11249260Google Scholar
  25. Revelt, D, Train, K 1998Mixed logit with repeated choices: Households’ choices of appliance efficiency levelReview of Economics and Statistics LXXX40647657Google Scholar
  26. Rose J, Hensher DA, Greene WH & Black IR (2004) Accounting for Exogenous Information on Decision Maker Processing Strategies in Models of Discrete Choice: Attribute Exclusion Strategies, Institute of Transport Studies, The University of Sydney.Google Scholar
  27. Swait, J, Adamowicz, W 2001aThe influence of task complexity on consumer choice: A latent class model of decision strategy switchingJournal of Consumer Research28135148Google Scholar
  28. Swait, J, Adamowicz, W 2001bChoice environment, market complexity, and consumer behavior: A theoretical and empirical approach for incorporating decision complexity into models of consumer choiceOrganizational Behavior and Human Decision Processes49127Google Scholar
  29. Train, K 2003Discrete Choice Methods with SimulationCambridge University PressCambridgeGoogle Scholar
  30. White PJ, Johnson RD & Louviere JJ (1998) The Effect of Attribute Range and Variance on Weighted Estimates, Unpublished paper, Department of Marketing, The University of Sydney.Google Scholar

Copyright information

© Springer 2005

Authors and Affiliations

  • David A. Hensher
    • 1
  • John Rose
    • 1
  • William H. Greene
    • 2
  1. 1.Institute of Transport Studies, School of Business, Faculty of Economics and BusinessThe University of SydneyAustralia
  2. 2.Department of Economics, Stern School of BusinessNew York UniversityNew YorkUSA

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