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Temporal framing of stated preference experiments: does it affect valuations?

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  • Peer, Stefanie
  • Börjesson, Maria

Abstract

In this paper, we explore how valuations of trip attributes by train commuters differ between a short-run (departure time choice) and a long-run (travel routine choice) context using a unique SP experiment explicitly designed for this purpose. In the short-run version of the SP experiment, the respondents receive information about available travel options shortly before they had planned to travel. In the long-run version, the respondents receive information about available travel options one month ahead of the planned travel. The short-run context concerns temporary changes in available travel options, while the long-run context concerns permanent changes. We find significantly higher valuations of trip attributes in the long-run context. Moreover, our results indicate that the usual arrival time at work as well as the intrinsically preferred arrival time at work serve as reference points in the short-run as well as the long-run choice context, with the former dominating in the short-run context and the latter in the long-run context.

Suggested Citation

  • Peer, Stefanie & Börjesson, Maria, 2018. "Temporal framing of stated preference experiments: does it affect valuations?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 117(C), pages 319-333.
    • Handle: RePEc:eee:transa:v:117:y:2018:i:c:p:319-333
    DOI: 10.1016/j.tra.2018.08.027
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    References listed on IDEAS

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    Cited by:

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    4. Stephane Hess & Andrew Daly & Maria Börjesson, 2020. "A critical appraisal of the use of simple time-money trade-offs for appraisal value of travel time measures," Transportation, Springer, vol. 47(3), pages 1541-1570, June.

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    More about this item

    Keywords

    Long-run; Short-run; Scheduling; Departure time; Routine; Framing; Stated preference data;
    All these keywords.

    JEL classification:

    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior
    • D03 - Microeconomics - - General - - - Behavioral Microeconomics: Underlying Principles
    • D99 - Microeconomics - - Micro-Based Behavioral Economics - - - Other
    • R41 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Transportation: Demand, Supply, and Congestion; Travel Time; Safety and Accidents; Transportation Noise

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