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Using conditioning on observed choices to retrieve individual-specific attribute processing strategies

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  • Hess, Stephane
  • Hensher, David A.

Abstract

With the growing reliance on Stated Choice (SC) data, researchers are increasingly interested in understanding how respondents process the information presented to them in such surveys. Specifically, it has been argued that some respondents may simplify the choice tasks by consistently ignoring one or more of the attributes describing the alternatives, and direct questions put to respondents after the completion of SC surveys support this hypothesis. However, in the general context of issues with response quality in SC data, there are certainly grounds for questioning the reliability of stated attribute processing strategies. In this paper, we take a different approach by attempting to infer attribute processing strategies through the analysis of respondent-specific coefficient distributions obtained through conditioning on observed choices. Our results suggest that a share of respondents do indeed ignore a subset of explanatory variables. However, there is also some evidence that the inferred attribute processing strategies are not necessarily consistent with the stated attribute processing strategies. Additionally, there is some evidence that respondents who claim to have ignored a certain attribute may simply have assigned it lesser importance. The results produced by the inferring approach not only lead to slightly better fit but also more consistent results.

Suggested Citation

  • Hess, Stephane & Hensher, David A., 2010. "Using conditioning on observed choices to retrieve individual-specific attribute processing strategies," Transportation Research Part B: Methodological, Elsevier, vol. 44(6), pages 781-790, July.
  • Handle: RePEc:eee:transb:v:44:y:2010:i:6:p:781-790
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    References listed on IDEAS

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    1. Hensher, David A. & Rose, John & Bertoia, Tony, 2007. "The implications on willingness to pay of a stochastic treatment of attribute processing in stated choice studies," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 43(2), pages 73-89, March.
    2. Cantillo, Víctor & Heydecker, Benjamin & de Dios Ortúzar, Juan, 2006. "A discrete choice model incorporating thresholds for perception in attribute values," Transportation Research Part B: Methodological, Elsevier, vol. 40(9), pages 807-825, November.
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    6. Hess, Stephane & Rose, John M. & Hensher, David A., 2008. "Asymmetric preference formation in willingness to pay estimates in discrete choice models," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 44(5), pages 847-863, September.
    7. Rose, John M. & Bliemer, Michiel C.J. & Hensher, David A. & Collins, Andrew T., 2008. "Designing efficient stated choice experiments in the presence of reference alternatives," Transportation Research Part B: Methodological, Elsevier, vol. 42(4), pages 395-406, May.
    8. Hess, Stephane & Bierlaire, Michel & Polak, John W., 2005. "Estimation of value of travel-time savings using mixed logit models," Transportation Research Part A: Policy and Practice, Elsevier, vol. 39(2-3), pages 221-236.
    9. 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.
    10. Swait, Joffre, 2001. "A non-compensatory choice model incorporating attribute cutoffs," Transportation Research Part B: Methodological, Elsevier, vol. 35(10), pages 903-928, November.
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