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Attribute level overlap (and color coding) can reduce task complexity, improve choice consistency, and decrease the

Marcel F Jonker1,2,3, Bas Donkers1,4, Esther de Bekker-Grob1,3

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Attribute level overlap and color coding in discrete choice experiments (DCEs) significantly improve respondent choice consistency and reduce dropout rates. Combining these strategies offers the most effective approach for DCE design.

Keywords:
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Area of Science:

  • Behavioral economics
  • Survey methodology
  • Experimental design

Background:

  • Discrete choice experiments (DCEs) are widely used for preference elicitation.
  • Task complexity and respondent engagement can influence DCE data quality.
  • Optimizing DCE design is crucial for reliable results.

Purpose of the Study:

  • To evaluate the impact of attribute level overlap and color coding on DCE outcomes.
  • To assess the individual and combined effects of these design strategies.
  • To provide evidence-based recommendations for DCE design.

Main Methods:

  • A randomized controlled discrete choice experiment (DCE) involving 3,320 respondents.
  • Comparison of study arms with varying levels of attribute overlap and color coding.
  • Analysis using a heteroskedastic mixed logit model for choice consistency.

Main Results:

  • Attribute level overlap alone reduced dropout rates by 30% and increased choice consistency by 30%.
  • The combination of level overlap and color coding reduced dropout rates by 40-50% and increased choice consistency by over 60%.
  • These strategies simplified task complexity and reduced learning effects.

Conclusions:

  • Attribute level overlap is a valuable design strategy for DCEs.
  • Color coding amplifies the positive effects of attribute level overlap.
  • Recommending attribute level overlap, with color coding, as a standard DCE design strategy.