A methodology for incorporating prior information into choice models

In this paper, we propose a method which facilitates the way a modeler or manager can include subjective information (such as judgment or intuition) into a choice model. The major contribution and focus of this research is on the way this prior information can be incorporated in a logit model. An important advantage of our approach is that, unlike the standard Bayesian approach, the prior information is incorporated using exogenous variables. We contend that it is easier for a manager or modeler to think in terms of market share and exogenous variables rather than in terms of unobservable parameter distributions. Two empirical illustrations are provided of our model: (i) showing the impact of a change in marketing strategy by including informative prior through subjective judgments, (ii) parameter estimation and sales forecasting when limited information is available. The results indicate that incorporating subjective prior information may lead to a significant improvement of parameter estimates and sales forecasts. r 2004 Elsevier Ltd. All rights reserved.