Abstract
When designing stated-choice experiments modellers may consider offering respondents an “indifference” alternative to avoid stochastic choices when utility differences between alternatives are perceived as too small. By doing this, the modeller avoids adding white noise to the data and may gain additional information. This paper proposes a framework to model
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