The Effect of Cue Categorization and Modeling Technique on the Assessment of Cue Importance*

Abstract

A substantial amount of behavioral research in business has attempted to uncover the relative importance decision makers attach to different decision variables (cues) used in their decision processes. This paper reports on two experiments that examine methodological issues concerning the assessment of cue importance. The first experiment examined whether the categorical descriptions given to cues in many modeling studies affect the importance decision makers attach to those cues. Results revealed that the importance attributed was significantly affected by the categories used to define cues. Additionally, because different techniques have been utilized to model cue importance, the second experiment examined the level of agreement between importance measures derived from two commonly used modeling techniques (ANOVA and information boards) under varying levels of task complexity. Results indicated that cue importance measures generally exhibited a moderate level of agreement. However, the use of different modeling techniques appears to affect the importance attributed to cues for some decision makers. In addition, the level of agreement was not affected by changes in task complexity. Implications of these results for future research studies that model decision behavior are discussed.