Cube model: Predictions and account for best–worst choice situations with three choice alternatives

Adele Diederich and Keivan Mallahi-Karai

Journal of choice modelling, 2023, vol. 49, issue C

Abstract: The Cube model (Mallahi-Karai and Diederich, 2019) is a dynamic-stochastic approach for decision making situations including multiple alternatives. The underlying model is a multivariate Wiener process with drift, and its dimension is related to the number of alternatives in the choice set. Here we modify the model to account for Best–Worst settings. The choices are made in a number of episodes allowing the alternatives to be ranked from best to worst or from worst to best. The model makes predictions with respect to choice probabilities and (mean) choice response times. We show how the model can be implemented using Markov chains and test the model and a simpler variation of it on data from Hawkins et al. (2014b).

Keywords: Best–worst setting; Cube model; Geometric models in higher dimensions; Multivariate Wiener process; Markov chain; Model fit (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:eee:eejocm:v:49:y:2023:i:c:s1755534523000490

DOI: 10.1016/j.jocm.2023.100448

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