Discrete choice experiments: An overview on constructing D-optimal and near-optimal choice sets

Discrete choice experiments (DCEs) are frequently used to estimate and forecast the behavior of an individual's choice. DCEs based on stated preference; therefore, underlying experimental designs required for this type study. According psychologists, DCE consist a small number sets with limited size in alternatives within set increase response efficiency questionnaire. Even though algorithmic constructions (known as efficient designs) become quite common practitioners, optimal (sometimes so-called orthogonal continue be experiment studies, particularly case that prior information about extent population preference is not available. Various approaches have been developed construct fewer sets. However, question many practitioners' minds which techniques perform better (i.e. given high efficiency) circumstance. In paper address these concerns, we conducted overview discrete literature models only main effects. The various ways constructing near-optimal were compared terms their ability minimize survey. Our findings shed light sample sizes needed experimentation then can help researchers design more effective area.