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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

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    1. Guney, Begum, 2014. "A theory of iterative choice in lists," Journal of Mathematical Economics, Elsevier, vol. 53(C), pages 26-32.
    2. 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.
    3. Swait, Joffre, 2001. "A non-compensatory choice model incorporating attribute cutoffs," Transportation Research Part B: Methodological, Elsevier, vol. 35(10), pages 903-928, November.
    4. Campbell, Danny & Hensher, David A. & Scarpa, Riccardo, 2014. "Bounding WTP distributions to reflect the ‘actual’ consideration set," Journal of choice modelling, Elsevier, vol. 11(C), pages 4-15.
    5. Eran Dayan & Maya Bar-Hillel, 2011. "Nudge to nobesity II: Menu positions influence food orders," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 6(4), pages 333-342, June.
    6. Stephane Hess & Amanda Stathopoulos & Danny Campbell & Vikki O’Neill & Sebastian Caussade, 2013. "It’s not that I don’t care, I just don’t care very much: confounding between attribute non-attendance and taste heterogeneity," Transportation, Springer, vol. 40(3), pages 583-607, May.
    7. Seda Erdem & Danny Campbell & Arne Risa Hole, 2015. "Accounting for Attribute‐Level Non‐Attendance in a Health Choice Experiment: Does it Matter?," Health Economics, John Wiley & Sons, Ltd., vol. 24(7), pages 773-789, July.
    8. Lusk, Jayson L. & Briggeman, Brian C., 2008. "AJAE appendix for “Food Values”," American Journal of Agricultural Economics APPENDICES, Agricultural and Applied Economics Association, vol. 91(1), pages 1-12, February.
    9. Danny Campbell & W. Hutchinson & Riccardo Scarpa, 2008. "Incorporating Discontinuous Preferences into the Analysis of Discrete Choice Experiments," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 41(3), pages 401-417, November.
    10. Jayson L. Lusk & Brian C. Briggeman, 2009. "Food Values," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 91(1), pages 184-196.
    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.
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    15. Paul Rozin & Sydney Scott & Megan Dingley & Joanna K. Urbanek & Hong Jiang & Mark Kaltenbach, 2011. "Nudge to nobesity I: Minor changes in accessibility decrease food intake," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 6(4), pages 323-332, June.
    16. Carlsson, Fredrik & Raun Mørkbak, Morten & Bøye Olsen, Søren, 2010. "The first time is the hardest: A test of ordering effects in choice experiments," Working Papers in Economics 470, University of Gothenburg, Department of Economics.
    17. Inman, J Jeffrey & McAlister, Leigh & Hoyer, Wayne D, 1990. "Promotion Signal: Proxy for a Price Cut?," Journal of Consumer Research, Oxford University Press, vol. 17(1), pages 74-81, June.
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    19. Riccardo Scarpa & Raffaele Zanoli & Viola Bruschi & Simona Naspetti, 2013. "Inferred and Stated Attribute Non-attendance in Food Choice Experiments," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 95(1), pages 165-180.
    20. 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, Foundation for the European Review of Agricultural Economics, vol. 36(2), pages 151-174, June.
    21. Swait, Joffre & Ben-Akiva, Moshe, 1987. "Incorporating random constraints in discrete models of choice set generation," Transportation Research Part B: Methodological, Elsevier, vol. 21(2), pages 91-102, April.
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    23. Seda Erdem & Dan Rigby, 2013. "Investigating Heterogeneity in the Characterization of Risks Using Best Worst Scaling," Risk Analysis, John Wiley & Sons, vol. 33(9), pages 1728-1748, September.
    24. Eran Dayan & Maya Bar-Hillel, 2011. "Nudge to nobesity II: Menu positions influence food orders," Discussion Paper Series dp581, The Federmann Center for the Study of Rationality, the Hebrew University, Jerusalem.
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    Cited by:

    1. Campbell, Danny & Boeri, Marco & Doherty, Edel & George Hutchinson, W., 2015. "Learning, fatigue and preference formation in discrete choice experiments," Journal of Economic Behavior & Organization, Elsevier, vol. 119(C), pages 345-363.
    2. Erdem, Seda, 2018. "Who do UK consumers trust for information about nanotechnology?," Food Policy, Elsevier, vol. 77(C), pages 133-142.
    3. Matthews, Yvonne & Scarpa, Riccardo & Marsh, Dan, 2017. "Using virtual environments to improve the realism of choice experiments: A case study about coastal erosion management," Journal of Environmental Economics and Management, Elsevier, vol. 81(C), pages 193-208.
    4. Vincenzina Caputo & Jayson L. Lusk, 2020. "What agricultural and food policies do U.S. consumers prefer? A best–worst scaling approach," Agricultural Economics, International Association of Agricultural Economists, vol. 51(1), pages 75-93, January.
    5. He, Ke & Zhang, Junbiao & Zeng, Yangmei, 2020. "Households’ willingness to pay for energy utilization of crop straw in rural China:Based on an improved UTAUT model," Energy Policy, Elsevier, vol. 140(C).
    6. Ivan Sever & Miroslav Verbič & Eva Klaric Sever, 2020. "Estimating Attribute-Specific Willingness-to-Pay Values from a Health Care Contingent Valuation Study: A Best–Worst Choice Approach," Applied Health Economics and Health Policy, Springer, vol. 18(1), pages 97-107, February.
    7. Soto, José R. & Adams, Damian C. & Escobedo, Francisco J., 2016. "Landowner attitudes and willingness to accept compensation from forest carbon offsets: Application of best–worst choice modeling in Florida USA," Forest Policy and Economics, Elsevier, vol. 63(C), pages 35-42.
    8. Erlend Dancke Sandorf & Danny Campbell, 2019. "Accommodating satisficing behaviour in stated choice experiments," European Review of Agricultural Economics, Foundation for the European Review of Agricultural Economics, vol. 46(1), pages 133-162.
    9. Huang, Lijuan & Mou, Jian & See-To, Eric W.K. & Kim, Jongki, 2019. "Consumer perceived value preferences for mobile marketing in China: A mixed method approach," Journal of Retailing and Consumer Services, Elsevier, vol. 48(C), pages 70-86.
    10. Campbell, Danny & Mørkbak, Morten Raun & Olsen, Søren Bøye, 2018. "The link between response time and preference, variance and processing heterogeneity in stated choice experiments," Journal of Environmental Economics and Management, Elsevier, vol. 88(C), pages 18-34.
    11. Lusk, Jayson L. & Crespi, John M. & McFadden, Brandon R. & Cherry, J. Bradley C. & Martin, Laura & Bruce, Amanda, 2016. "Neural antecedents of a random utility model," Journal of Economic Behavior & Organization, Elsevier, vol. 132(PA), pages 93-103.
    12. Shaosheng Jin & Bashiru Mansaray & Xin Jin & Haoyang Li, 2020. "Farmers’ preferences for attributes of rice varieties in Sierra Leone," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 12(5), pages 1185-1197, October.
    13. Phillips, Yvonne & Marsh, Dan, 2015. "Virtual Reality and Scope Sensitivity in a Choice Experiment About Coastal Erosion," 2015 Conference (59th), February 10-13, 2015, Rotorua, New Zealand 202571, Australian Agricultural and Resource Economics Society.
    14. Hajji, Assma & Trukeschitz, Birgit & Malley, Juliette & Batchelder, Laurie & Saloniki, Eirini & Linnosmaa, Ismo & Lu, Hui, 2020. "Population-based preference weights for the Adult Social Care Outcomes Toolkit (ASCOT) for service users for Austria: Findings from a best-worst experiment," Social Science & Medicine, Elsevier, vol. 250(C).
    15. Soto, José R. & Escobedo, Francisco J. & Khachatryan, Hayk & Adams, Damian C., 2018. "Consumer demand for urban forest ecosystem services and disservices: Examining trade-offs using choice experiments and best-worst scaling," Ecosystem Services, Elsevier, vol. 29(PA), pages 31-39.
    16. Mansaray, B. & Jin, S. & Yuan, R. & Li, H., 2018. "Farmers Preferences for Attributes of Seed Rice in Sierra Leone: A Best-Worst Scaling Approach," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 277552, International Association of Agricultural Economists.
    17. Erdem, Seda & McCarthy, Tony, 2016. "The effect of front-of-pack nutrition labelling formats on consumers’ food choices and decision-making: merging discrete choice experiment with an eye tracking experiment," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 235864, Agricultural and Applied Economics Association.
    18. 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.
    19. Seda Erdem & Danny Campbell, 2017. "Preferences for public involvement in health service decisions: a comparison between best-worst scaling and trio-wise stated preference elicitation techniques," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 18(9), pages 1107-1123, December.
    20. Matthews, Yvonne & Scarpa, Riccardo & Marsh, Dan, 2017. "Stability of Willingness-to-Pay for Coastal Management: A Choice Experiment Across Three Time Periods," Ecological Economics, Elsevier, vol. 138(C), pages 64-73.
    21. Danny Campbell & Seda Erdem, 2019. "Including Opt-Out Options in Discrete Choice Experiments: Issues to Consider," The Patient: Patient-Centered Outcomes Research, Springer;International Academy of Health Preference Research, vol. 12(1), pages 1-14, February.
    22. Logar, Ivana & Brouwer, Roy & Campbell, Danny, 2020. "Does attribute order influence attribute-information processing in discrete choice experiments?," Resource and Energy Economics, Elsevier, vol. 60(C).
    23. Alberto Longo & Danny Campbell, 2017. "The Determinants of Brownfields Redevelopment in England," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 67(2), pages 261-283, June.
    24. Yeongmin Kwon & Suji Kim & Hyungjoo Kim & Jihye Byun, 2020. "What Attributes Do Passengers Value in Electrified Buses?," Energies, MDPI, Open Access Journal, vol. 13(10), pages 1-14, May.

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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

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