Opt-Out Forced Choice Effect in Combined Revealed and Stated Preference Discrete Choice Models: A Gender Perspective

Abstract

In this study, we assess the convergent validity of preferences and willingness-to-pay (WTP) values for beach quality improvements from a gender perspective by isolating opt-out forced-choice effect from the SP1 DCE data (that is a forced-choice situation when a respondent was asked to select among the competing labelled alternatives if they chose an opt-out). Following this approach, we combine the RP discrete choice model and SP1 DCE datasets by splitting them into female and male sub-samples and then investigate whether estimated preferences and WTP values are susceptible to this effect from a gender perspective. Using the multinomial logit (MNL) models, we find that female visitors’ preferences are compatible across RP and SP1 data if the forced-choice effect is isolated from SP1 data, whereas this is not true for the male visitors. However, WTP values appear similar for both the female and male RP and SP1 sub-samples. Also, the sources of opt-out forced choices appear more promising for females than those of male counterparts in the estimated binary logit models. Our results, therefore, suggest that preferences’ similarity is a gender-specific if the opt-out forced-choice effect is isolated, but WTP similarity is not

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