Differentiated Bayesian Conjoint Choice Designs
Previous conjoint choice design construction procedures have produced a single design that is administered to all subjects. This paper proposes to construct a limited set of different designs. The designs are constructed in a Bayesian fashion, taking into account prior uncertainty about the parameter values. A computational procedure is developed that enables fast and easy implementation in practice. Even though the number of such different designs in the optimal set is small, it is demonstrated through a Monte Carlo study that substantial gains in efficiency are achieved over aggregate designs.