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Are Fast Responses More Random? Testing the Effect of Response Time on Scale in an Online Choice Experiment

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  • Tobias Börger

    (Plymouth Marine Laboratory)

Abstract

Scepticism over stated preference surveys conducted online revolves around the concerns over “professional respondents” who might rush through the questionnaire without sufficiently considering the information provided. To gain insight on the validity of this phenomenon and test the effect of response time on choice randomness, this study makes use of a recently conducted choice experiment survey on ecological and amenity effects of an offshore windfarm in the UK. The positive relationship between self-rated and inferred attribute attendance and response time is taken as evidence for a link between response time and cognitive effort. Subsequently, the generalised multinomial logit model is employed to test the effect of response time on scale, which indicates the weight of the deterministic relative to the error component in the random utility model. Results show that longer response time increases scale, i.e. decreases choice randomness. This positive scale effect of response time is further found to be non-linear and wear off at some point beyond which extreme response time decreases scale. While response time does not systematically affect welfare estimates, higher response time increases the precision of such estimates. These effects persist when self-reported choice certainty is controlled for. Implications of the results for online stated preference surveys and further research are discussed.

Suggested Citation

  • Tobias Börger, 2016. "Are Fast Responses More Random? Testing the Effect of Response Time on Scale in an Online Choice Experiment," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 65(2), pages 389-413, October.
  • Handle: RePEc:kap:enreec:v:65:y:2016:i:2:d:10.1007_s10640-015-9905-1
    DOI: 10.1007/s10640-015-9905-1
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    More about this item

    Keywords

    Attribute non-attendance; Choice experiment; Generalised multinomial logit; Offshore windfarm; Online survey; Response time; Scale heterogeneity;
    All these keywords.

    JEL classification:

    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • Q51 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Valuation of Environmental Effects
    • H43 - Public Economics - - Publicly Provided Goods - - - Project Evaluation; Social Discount Rate

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