An advantage of multiple attribute decision analysis is its capability of handling nomonetary factors in addition t o traditional monetary data. However, measurements o f nonmonetary attributes are often highly subjective and imprecise and most analytical m e t h o d s lack provisions for handling imprecise d a t a. In this paper we reex-amine t h e linear additive utility model, expand and adapt it to accommodate imprecise attribute ratings and weights.