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Development, Implementation, and Evaluation of a More Efficient Method of Best-Worst Scaling Data Collection

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  • Bir, Courtney
  • Delgado, Michael
  • Widmar, Nicole

Abstract

Discrete choice experiments are used to collect data that facilitates measurement and understanding of consumer preferences. A sample of 750 respondents was employed to evaluate a new method of best-worst scaling data collection. This new method decreased the number of attributes and questions while discerning preferences for a larger set of attributes through self-stated preference “filter” questions. The new best-worst method resulted in overall equivalent rates of transitivity violations and lower incidences of attribute non-attendance than standard best-worst scaling designs. The new method of best-worst scaling data collection can be successfully employed to efficiently evaluate more attributes while improving data quality.

Suggested Citation

  • Bir, Courtney & Delgado, Michael & Widmar, Nicole, 2022. "Development, Implementation, and Evaluation of a More Efficient Method of Best-Worst Scaling Data Collection," Agricultural and Resource Economics Review, Cambridge University Press, vol. 51(1), pages 178-201, April.
    • Handle: RePEc:cup:agrerw:v:51:y:2022:i:1:p:178-201_9
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