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The Self Selection of Complexity in Choice Experiments

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  • Michael Burton
  • Dan Rigby

Abstract

We investigate whether individuals will voluntarily increase the complexity of the tasks they complete within a discrete choice experiment (DCE). We do this via a 'self selection of complexity' design in which respondents choose whether to face choice sets comprising 3, 4 or 6 alternatives. We link this approach with the emerging Excessive Choice Effect (ECE) literature. We find that 30% of the sample opt for the largest sets. We test whether this choice of complexity reveals information about respondents' capability/commitment. We find that it does since those with lowest initial error variance levels are most likely to later select the highest level of task complexity. We argue that this result offers insights regarding the design of more cognitively efficient DCE designs. We consider the matching of respondents to the appropriate level of task complexity as analogous to the principal-agent problem with asymmetric information. Rather than trying to understand respondents' cognitive capability or commitment ex ante we propose that participants self-select designs that achieve the researcher's objective of minimizing error variance. Copyright 2012, Oxford University Press.

Suggested Citation

  • Michael Burton & Dan Rigby, 2012. "The Self Selection of Complexity in Choice Experiments," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 94(3), pages 786-800.
  • Handle: RePEc:oup:ajagec:v:94:y:2012:i:3:p:786-800
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    File URL: http://hdl.handle.net/10.1093/ajae/aas015
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    Cited by:

    1. Kelvin Balcombe & Michail Bitzios & Iain Fraser & Janet Haddock-Fraser, 2014. "Using Attribute Importance Rankings Within Discrete Choice Experiments: An Application to Valuing Bread Attributes," Journal of Agricultural Economics, Wiley Blackwell, vol. 65(2), pages 446-462, June.
    2. Shiwen Quan & Yinchu Zeng & Xiaohua Yu & Te Bao, 2018. "WTP for baby milk formula in China: Using attribute nonattendance as a priori information to select attributes in choice experiment," Agribusiness, John Wiley & Sons, Ltd., vol. 34(2), pages 300-320, March.
    3. Wiktor L. Adamowicz & Klaus Glenk & Jürgen Meyerhoff, 2014. "Choice modelling research in environmental and resource economics," Chapters, in: Stephane Hess & Andrew Daly (ed.), Handbook of Choice Modelling, chapter 27, pages 661-674, Edward Elgar Publishing.
    4. Robert J. Johnston & Kevin J. Boyle & Wiktor (Vic) Adamowicz & Jeff Bennett & Roy Brouwer & Trudy Ann Cameron & W. Michael Hanemann & Nick Hanley & Mandy Ryan & Riccardo Scarpa & Roger Tourangeau & Ch, 2017. "Contemporary Guidance for Stated Preference Studies," Journal of the Association of Environmental and Resource Economists, University of Chicago Press, vol. 4(2), pages 319-405.
    5. Chavez, Daniel & Palma, Marco, 2015. "Off the reservation: Pushing the bounds of rationality in experimental auctions," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 202164, Agricultural and Applied Economics Association.
    6. Hangjian Wu & Emmanouil Mentzakis & Marije Schaafsma, 2022. "Exploring Different Assumptions about Outcome-Related Risk Perceptions in Discrete Choice Experiments," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 81(3), pages 531-572, March.
    7. Daniel A. Brent & Lata Gangadharan & Anke Leroux & Paul A. Raschky, 2014. "Putting One's Money Where One's Mouth is: Increasing Saliency in the Field," Monash Economics Working Papers 43-14, Monash University, Department of Economics.
    8. Daniel E. Chavez & Marco A. Palma, 2019. "Pushing subjects beyond rationality with more alternatives in experimental auctions," Agricultural Economics, International Association of Agricultural Economists, vol. 50(2), pages 207-217, March.
    9. Pluske, Jo & Burton, Michael & Rigby, Dan & Vercoe, Phil, 2013. "Cattle breeding in Northern Australia: Revealing how consumers react to alternative technologies," Australasian Agribusiness Review, University of Melbourne, Department of Agriculture and Food Systems, vol. 21, pages 1-15.
    10. Dan Rigby & Michael Burton & Jo Pluske, 2016. "Preference Stability and Choice Consistency in Discrete Choice Experiments," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 65(2), pages 441-461, October.

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