On the Consequences of Frequent Applicants in Adverse Impact Analyses: A demonstration study

Abstract

Electronic ré sumé s, online applications, and automated personnel systems have reduced the effort required for a candidate to apply for employment opportunities like selection and promotion. The nature of these systems may affect analyses of adverse impact. For example, candidates that can easily apply to many positions multiple times could strongly influence analyses of adverse impact under particular circumstances. This study demonstrates some potential consequences of including frequent applicants in adverse impact analyses. Using workforce simulation methodology, we illustrate some conditions where a lesser qualified frequent applicant substantially influences the statistical significance of adverse impact detection. In some cases, the adverse impact against a subgroup may be accounted for by a single frequent applicant; in other cases, statistically significant adverse impact may be disguised by a single frequent applicant. We also consider methods for identifying frequent applicants and present options for handling these cases in analyses.

Employee Selection in Times of Change

“…According to the four-fifths rule, there is adverse impact when the selection rate for one group is less than 80% of the more successful group. Dunleavy et al (2008) point out how in the age of online applications and automated personnel systems, adverse impact computations are skewed by frequent applicants (i.e., applicants who apply for multiple positions or the same position on multiple occasions). Adverse impact can also be inferred by comparing the hiring rates for a particular group within an organization with the hiring rates for that group within the relevant industry as a whole.…”

Ευφυή Και Έμπειρα Συστήματα Διαχείρισης Ανθρώπινων Πόρων

“…Πλούσια είναι η σχετική βιβλιογραφία κατά τη διάρκεια των τελευταίων ετών, εστιασμένη σε αυτό το χαρακτηριστικό κατά τη διαδικασία επιλογής (Adkins et al, 1994, Cable και Judge, 1997, Carless, 2005, Garcia, 2004a, b, Higgins και Judge, 2004, Karren και Graves, 1994, Kristof-Brown, 2000, McCulloch και Turban, 2007, Rynes και Gerhart, 1990. (Bartrarn, 1995, Dunleavy et al, 2008. Για παράδειγμα, υποθέτοντας ότι υπάρχουν 1000 υποψήφιοι από την υπο-ομάδα Α και 300 υποψήφιοι από την υπο-ομάδα Β. Αν τελικά επιλεγούν 100 υποψήφιοι από την υπο-ομάδα Α, το ποσοστό επιλογής είναι 10%.…”