LAUSR

This paper contributes to the process of eliciting additive model scale constants in order to support choice problems, thereby reducing the effort a decision maker (DM) needs to make since partial information with regard to DM preferences can be used. Procedures related to eliciting weights without a tradeoff interpretation of weights are justified based on assumptions that DM is not able to specify fixed weight values or if DM is able to do so, this would not be reliable information. As long as partial information is provided, the flexible elicitation procedure performs dominance tests based on a linear programming problem to explore the DM’s preferences as a vector space which is built using the DM’s partial information. To provide evidence of the satisfactory performance of the flexible elicitation procedure, an empirical test is presented with results that indicate that this procedure requires less effort from DMs.