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Position bias in best-worst scaling surveys: a case study on trust in institutions

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  • Campbell, Danny
  • Erdem, Seda

Abstract

This paper investigates the effect of physical position on ‘best’ and ‘worst’ choices in the bestworst scaling technique. Although the best-worst scaling technique has been used widely in many fields, the phenomenon of consumers’ adoption of processing strategies while making choices has been largely overlooked. We examine this issue in the context of consumers’ perception of trust in institutions to provide information about a new food technology, namely nanotechnology, and its use in food processing. Our results show that around half of the consumers used position as a schematic cue when making choices. We find the position bias is particularly strong when consumers chose their most trustworthy institution compared to their least trustworthy institution. In light of our findings, we recommend researchers in the field to be aware of the possibility of position bias when designing best-worst scaling surveys. We also encourage researchers who have already collected best-worst data to investigate whether their data shows such heuristics.

Suggested Citation

  • Campbell, Danny & Erdem, Seda, 2014. "Position bias in best-worst scaling surveys: a case study on trust in institutions," 2014 Annual Meeting, July 27-29, 2014, Minneapolis, Minnesota 177167, Agricultural and Applied Economics Association.
  • Handle: RePEc:ags:aaea14:177167
    DOI: 10.22004/ag.econ.177167
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    References listed on IDEAS

    as
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    16. Erdem, Seda & Campbell, Danny & Thompson, Carl, 2014. "Elimination and selection by aspects in health choice experiments: Prioritising health service innovations," Journal of Health Economics, Elsevier, vol. 38(C), pages 10-22.
    17. 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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    24. Inman, J Jeffrey & McAlister, Leigh & Hoyer, Wayne D, 1990. "Promotion Signal: Proxy for a Price Cut?," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 17(1), pages 74-81, June.
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    26. Riccardo Scarpa & Timothy J. Gilbride & Danny Campbell & David A. Hensher, 2009. "Modelling attribute non-attendance in choice experiments for rural landscape valuation," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 36(2), pages 151-174, June.
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    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Consumer/Household Economics; Research Methods/ Statistical Methods;

    JEL classification:

    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • Q18 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Agricultural Policy; Food Policy; Animal Welfare Policy

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