AbstractStudies concerning innovative behavior have applied many predictor variables, to the point where a purge to reduce redundancy now appears in order. Factor analysis with orthogonal varimax rotation was applied to product perception and demographic, socioeconomic, and predispositional variables in order to reduce their numbers without a significant loss of information. The derived rotated factors were then related by way of factor scores obtained from respondent data to a surrogate measure of innovative behavior using multiple regression equations. The resulting coefficients of determination, while smaller than those originally derived using all of the perceptual and predispositional variables individually, were not reduced by any massive amounts. Thus, the gain from reducing the number of predictor variables through the use of factor analysis seems to more than off‐set the modest reduction in explained variance. Moreover, the resulting factors and their item loadings suggest possible alternative predictor variables to those that have commonly been used in past studies concerning the diffusion of innovation