Estimating decision rule differences between ‘best’ and ‘worst’ choices in a sequential best worst discrete choice experiment

نویسندگان

چکیده

Since the introduction of Discrete Choice Analysis, countless efforts have been made to enhance efficiency data collection through choice experiments and improve behavioural realism models. One example development in are best-worst discrete (BWDCE), which benefit obtaining a larger number observations per respondent, allowing for reliably estimating models even with smaller samples. In SWDCE, respondents asked alternatingly select ‘best’/‘worst’ alternatives, until set is exhausted. The use BWDCE raises question decision-rule consistency stages experiment. We challenge notion that same fully compensatory decision rule utilised throughout hypothesize may utilise one selecting ‘best’ another ‘worst’ alternatives. To test our hypothesis, we developed model combines SBWMNL modelling μRRM can account variations rules. Our results show heterogeneity does seem be present BWDCE: it more likely choices using (maximising utility), whereas non-compensatory (minimising regret). Such behaviour largely similar how image theory describes decision-making process complex situations. findings give modellers new insight into allows them represent their accurately. • Adapted heterogeneity. Respondents do not experiments. Successive lower reliability. produce significantly different parameter estimates.

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ژورنال

عنوان ژورنال: Journal of choice modelling

سال: 2021

ISSN: ['1755-5345']

DOI: https://doi.org/10.1016/j.jocm.2021.100307