The decisions job applicants must make: Insights from a Bayesian perspective

Abstract

The application/selection process can be thought of as a set of Bayesian opinion revision tasks, in which applicants obtain new information about the organization at each stage of the process and must integrate this information with their prior perceptions of the organization and the jobs. The Bayesian perspective provides useful insights for understanding serial decisions of this type. It suggests that real-world decision-makers are too sensitive to the valence and insufficiently sensitive to the diagnosticity of the information they obtain from interviewers, assessors, etc., and that the effects of information obtained early in the process depends on both the applicant's state of perceived uncertainty and on the relationship between the applicant's preconceptions and this early information.