Comparing the Efficacy of Policy-Capturing Weights and Direct Estimates for Predicting Job Choice

Abstract

When studying applicants' job attribute preferences, researchers have used either direct estimates (DE) of importance or regression-derived statistical weights from policy-capturing (PC) studies. Although each methodology has been criticized, no research has examined the efficacy of weights derived from either method for predicting choices among job offers. In this study, participants were assigned to either a DE or PC condition, and weights for 14 attribute preferences were derived. Three weeks later, the participants made choices among hypothetical job offers. As predicted, PC weights outperformed DE weights when a noncompensatory strategy was assumed, and DE weights outperformed PC weights when a compensatory strategy was assumed. Implications for researchers' choice of methodology when studying attribute preferences are discussed.