How do respondents process stated choice experiments? Attribute consideration under varying information load
The popularity of stated choice (SC) experiments has produced many design strategies in which researchers use increasingly more 'complex' choice settings to study choice behaviour. When the amount of information to assess increases, we wonder how an individual handles such information in making a choice. Defining the amount of information as the number of attributes associated with each choice set, we investigate how this information is processed as we vary its 'complexity'. Four ordered heterogeneous logit models are developed, each for an SC design based on a fixed number of attributes, in which the dependent variable defines the number of attributes that are ignored. We find that the degree to which individuals ignore attributes is influenced by the dimensionality of the SC experiment, the deviation of attribute levels from an experienced reference alternative, the use of 'adding up' attributes where feasible, the number of choice sets evaluated, and the personal income of the respondent. The empirical evidence supports the view that individuals appear to adopt a range of 'coping' strategies that are consistent with how they process information in real markets, and that aligning 'choice complexity' with the amount of information to process is potentially misleading. Relevancy is what matters. Copyright © 2006 John Wiley & Sons, Ltd.
Volume (Year): 21 (2006)
Issue (Month): 6 ()
|Contact details of provider:|| Web page: http://www.interscience.wiley.com/jpages/0883-7252/|
|Order Information:|| Web: http://www3.interscience.wiley.com/jcatalog/subscribe.jsp?issn=0883-7252 Email: |
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Caussade, Sebastián & Ortúzar, Juan de Dios & Rizzi, Luis I. & Hensher, David A., 2005. "Assessing the influence of design dimensions on stated choice experiment estimates," Transportation Research Part B: Methodological, Elsevier, vol. 39(7), pages 621-640, August.
- Arentze, Theo & Borgers, Aloys & Timmermans, Harry & DelMistro, Romano, 2003. "Transport stated choice responses: effects of task complexity, presentation format and literacy," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 39(3), pages 229-244, May.
- Amos Tversky & Daniel Kahneman, 1979.
"Prospect Theory: An Analysis of Decision under Risk,"
Levine's Working Paper Archive
7656, David K. Levine.
- Kahneman, Daniel & Tversky, Amos, 1979. "Prospect Theory: An Analysis of Decision under Risk," Econometrica, Econometric Society, vol. 47(2), pages 263-91, March.
- Starmer, Chris & Sugden, Robert, 1993. "Testing for Juxtaposition and Event-Splitting Effects," Journal of Risk and Uncertainty, Springer, vol. 6(3), pages 235-54, June.
- 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.
- 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.
This item is featured on the following reading lists or Wikipedia pages:
When requesting a correction, please mention this item's handle: RePEc:jae:japmet:v:21:y:2006:i:6:p:861-878. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Wiley-Blackwell Digital Licensing)or (Christopher F. Baum)
If references are entirely missing, you can add them using this form.