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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. Wiktor L. Adamowicz & Klaus Glenk & J├╝rgen Meyerhoff, 2014. "Choice modelling research in environmental and resource economics," Chapters,in: Handbook of Choice Modelling, chapter 27, pages 661-674 Edward Elgar Publishing.
    3. 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, Melbourne School of Land and Environment, vol. 21.
    4. 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;Western Agricultural Economics Association.
    5. 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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