Designing Pareto-Optimal Selection Systems: Formalizing the Decisions Required for Selection System Development

Wilfried De Corte, Paul R. Sackett, Filip Lievens

Research output: Contribution to journalArticlepeer-review

31 Scopus citations

Abstract

The article presents an analytic method for designing Pareto-optimal selection systems where the applicants belong to a mixture of candidate populations. The method is useful in both applied and research settings. In an applied context, the present method is the first to assist the selection practitioner when deciding on 6 major selection design issues: (1) the predictor subset, (2) the selection rule, (3) the selection staging, (4) the predictor sequencing, (5) the predictor weighting, and (6) the stage retention decision issue. From a research perspective, the method offers a unique opportunity for studying the impact and relative importance of different strategies for reducing adverse impact.

Original languageEnglish (US)
Pages (from-to)907-926
Number of pages20
JournalJournal of Applied Psychology
Volume96
Issue number5
DOIs
StatePublished - Sep 2011

Keywords

  • Adverse impact
  • Pareto-optimal
  • Personnel selection
  • Selection design

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