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How many choice sets and alternatives are optimal? Consistency in choice experiments

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  • Chanjin Chung
  • Tracy Boyer
  • Sungill Han

Abstract

This article focuses on two important issues faced by researchers working on choice experiments: how to find the optimal number of alternatives in each choice set and the number of choice sets in each survey. The authors first develop survey instruments with different numbers of choice sets and alternatives. Then, a heteroscedastic logit model is developed to relate the varying number of alternatives and choice sets to changes in the error term by parameterizing the scale factor of the heteroscedastic logit model. The authors study the effects of two simultaneous forms of complexity on the consistency of respondents' choices, i.e., the number of choice sets per questionnaire and the number of options per choice set. Their findings suggest that respondents' choices do vary with the amount of information given resulting in an optimal five options and six choice sets per survey. Results from the marginal effects and willingness to pay (WTP) estimates indicate that varying the number of alternatives and choice sets can also affect consumers' marginal WTP estimates. [EconLit citations: Q110; Q130; Q180]. (C) 2010 Wiley Periodicals, Inc.

Suggested Citation

  • Chanjin Chung & Tracy Boyer & Sungill Han, 2011. "How many choice sets and alternatives are optimal? Consistency in choice experiments," Agribusiness, John Wiley & Sons, Ltd., vol. 27(1), pages 114-125, Winter.
    • Handle: RePEc:wly:agribz:v:27:y:2011:i:1:p:114-125
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    File URL: http://hdl.handle.net/10.1002/agr.20252
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    Cited by:

    1. Jürgen Meyerhoff & Malte Oehlmann & Priska Weller, 2015. "The Influence of Design Dimensions on Stated Choices in an Environmental Context," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 61(3), pages 385-407, July.
    2. Mikołaj Czajkowski & Marek Giergiczny & William H. Greene, 2012. "Learning and Fatigue Effects Revisited. The Impact of Accounting for Unobservable Preference and Scale Heterogeneity on Perceived Ordering Effects in Multiple Choice Task Discrete Choice Experiments," Working Papers 2012-08, Faculty of Economic Sciences, University of Warsaw.
    3. Mikolaj Czajkowski & Marek Giergiczny & William H. Greene, 2014. "Learning and Fatigue Effects Revisited: Investigating the Effects of Accounting for Unobservable Preference and Scale Heterogeneity," Land Economics, University of Wisconsin Press, vol. 90(2), pages 324-351.
    4. Anna Kollerup & Jacob Ladenburg, 2021. "Willingness to pay for accommodating job attributes when returning to work after cancer treatment: A discrete choice experiment with Danish breast cancer survivors," LABOUR, CEIS, vol. 35(3), pages 378-411, September.
    5. Liao, Feixiong & Tian, Qiong & Arentze, Theo & Huang, Hai-Jun & Timmermans, Harry J.P., 2020. "Travel preferences of multimodal transport systems in emerging markets: The case of Beijing," Transportation Research Part A: Policy and Practice, Elsevier, vol. 138(C), pages 250-266.
    6. Francesca Colantuoni & Gianni Cicia & Teresa Del Giudice & Daniel Lass & Francesco Caracciolo & Pasquale Lombardi, 2016. "Heterogeneous Preferences for Domestic Fresh Produce: Evidence from German and Italian Early Potato Markets," Agribusiness, John Wiley & Sons, Ltd., vol. 32(4), pages 512-530, November.
    7. Cash, Sean B. & Slade, Peter & Cranfield, John, 2013. "The Chicken Wears No Skin: Ordering Effects in Elicitation of Willingness to Pay for Multiple Credence Attributes in Ethical and Novel Food Products," 2013 Annual Meeting, August 4-6, 2013, Washington, D.C. 150364, Agricultural and Applied Economics Association.
    8. Ms. Chie Aoyagi & Alistair Munro, 2019. "Guilt, Gender, and Work-Life Balance in Japan: A Choice Experiment," IMF Working Papers 2019/261, International Monetary Fund.

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