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Presentation matters: Number of attributes presented impacts estimated preferences

Author

Listed:
  • Elizabeth S. Byrd
  • Nicole J. Olynk Widmar
  • Benjamin M. Gramig

Abstract

Best–worst scaling is an increasingly employed methodology in which both the number of attributes shown in each choice task and the number of tasks can vary. Researchers face a tradeoff between the number of attributes shown per question and the total number of questions. U.S. residents (n = 818) were randomly assigned to see one of two best–worst presentations of the same six meat attributes (taste, convenience, safety, animal welfare, price, and nutrition). Significant differences were found in the estimated preference shares when respondents were shown two versus three attributes at a time. Both presentations ranked safety as the most important, taste as the second most important, and convenience as the least important meat purchasing attribute. However, the distributions of most of the preference share estimates were statistically different. Differences in preferences share estimates resulting from the presentation of questions has the potential to influence marketing, retailing, and other decisions. [EconLit citations: C83, M31, Q13]

Suggested Citation

  • Elizabeth S. Byrd & Nicole J. Olynk Widmar & Benjamin M. Gramig, 2018. "Presentation matters: Number of attributes presented impacts estimated preferences," Agribusiness, John Wiley & Sons, Ltd., vol. 34(2), pages 377-389, March.
  • Handle: RePEc:wly:agribz:v:34:y:2018:i:2:p:377-389
    DOI: 10.1002/agr.21527
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    File URL: https://doi.org/10.1002/agr.21527
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    References listed on IDEAS

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    1. Sackett, Hillary M. & Shupp, Robert & Tonsor, Glynn, 2013. "Consumer Perceptions of Sustainable Farming Practices: A Best-Worst Scenario," Agricultural and Resource Economics Review, Cambridge University Press, vol. 42(2), pages 275-290, August.
    2. Maynard, Leigh J. & Hartell, Jason G. & Meyer, A. Lee & Hao, Jianqiang, 2004. "An experimental approach to valuing new differentiated products," Agricultural Economics, Blackwell, vol. 31(2-3), pages 317-325, December.
    3. Pat Auger & Timothy Devinney & Jordan Louviere, 2007. "Using Best–Worst Scaling Methodology to Investigate Consumer Ethical Beliefs Across Countries," Journal of Business Ethics, Springer, vol. 70(3), pages 299-326, February.
    4. Loureiro, Maria L. & Dominguez Arcos, Fernando, 2012. "Applying Best–Worst Scaling in a stated preference analysis of forest management programs," Journal of Forest Economics, Elsevier, vol. 18(4), pages 381-394.
    5. Arne Risa Hole, 2007. "A comparison of approaches to estimating confidence intervals for willingness to pay measures," Health Economics, John Wiley & Sons, Ltd., vol. 16(8), pages 827-840, August.
    6. Jordan Louviere & Terry Flynn, 2010. "Using Best-Worst Scaling Choice Experiments to Measure Public Perceptions and Preferences for Healthcare Reform in Australia," The Patient: Patient-Centered Outcomes Research, Springer;International Academy of Health Preference Research, vol. 3(4), pages 275-283, December.
    7. Holland, Jacqueline K. & Olynk Widmar, Nicole J. & Widmar, David A. & Ortega, David L. & Gunderson, Michael A., 2014. "Understanding Producer Strategies: Identifying Key Success Factors of Commercial Farms in 2013," 2014 Annual Meeting, February 1-4, 2014, Dallas, Texas 162422, Southern Agricultural Economics Association.
    8. Widmar, Nicole J. Olynk & Ortega, David L., 2014. "Comparing Consumer Preferences for Livestock Production Process Attributes Across Products, Species, and Modeling Methods," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 46(3), pages 375-391, August.
    9. Tonsor, Glynn T. & Olynk, Nicole & Wolf, Christopher, 2009. "Consumer Preferences for Animal Welfare Attributes: The Case of Gestation Crates," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 41(3), pages 713-730, December.
    10. Malone, Trey & Lusk, Jayson L., 2017. "Taste Trumps Health And Safety: Incorporating Consumer Perceptions Into A Discrete Choice Experiment For Meat," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 49(1), pages 139-157, February.
    11. Erdem, Seda & Rigby, Dan & Wossink, Ada, 2012. "Using best–worst scaling to explore perceptions of relative responsibility for ensuring food safety," Food Policy, Elsevier, vol. 37(6), pages 661-670.
    12. Lusk, Jayson L. & Parker, Natalie, 2009. "Consumer Preferences for Amount and Type of Fat in Ground Beef," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 41(1), pages 75-90, April.
    13. Marisa J. Mazzotta & James J. Opaluch, 1995. "Decision Making When Choices Are Complex: A Test of Heiner's Hypothesis," Land Economics, University of Wisconsin Press, vol. 71(4), pages 500-515.
    14. Olynk, Nicole J. & Tonsor, Glynn T. & Wolf, Christopher A., 2010. "Consumer Willingness to Pay for Livestock Credence Attribute Claim Verification," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 35(2), pages 1-20, August.
    15. Brooks, Kathleen R. & Ellison, Brenna, 2014. "Which Livestock Production Methods Matter Most to Consumers?," 2014 Annual Meeting, July 27-29, 2014, Minneapolis, Minnesota 173517, Agricultural and Applied Economics Association.
    16. Danny Campbell & Seda Erdem, 2015. "Position Bias in Best-worst Scaling Surveys: A Case Study on Trust in Institutions," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 97(2), pages 526-545.
    17. Krinsky, Itzhak & Robb, A Leslie, 1986. "On Approximating the Statistical Properties of Elasticities," The Review of Economics and Statistics, MIT Press, vol. 68(4), pages 715-719, November.
    18. Gregory L. Poe & Kelly L. Giraud & John B. Loomis, 2005. "Computational Methods for Measuring the Difference of Empirical Distributions," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 87(2), pages 353-365.
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    1. West, Grant H. & Snell, Heather & Kovacs, Kent & Nayga, Rodolfo M., 2020. "Estimation of the preferences for the intertemporal services from groundwater," 2020 Annual Meeting, July 26-28, Kansas City, Missouri 304220, Agricultural and Applied Economics Association.

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