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Designing pareto-optimal selection systems: formalizing the decisions required for selection system development

(2011) JOURNAL OF APPLIED PSYCHOLOGY. 96(5). p.907-926
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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.
Keywords
Pareto-optimal, selection design, personnel selection, adverse impact, REDUCE ADVERSE IMPACT, PREDICTOR COMPOSITE FORMATION, SIMULATION, INTEGRITY, METAANALYSIS, COGNITIVE-ABILITY, JOB-PERFORMANCE, STRATEGIES, VALIDITY, PERSONNEL-SELECTION

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Citation

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MLA
De Corte, Wilfried, et al. “Designing Pareto-Optimal Selection Systems: Formalizing the Decisions Required for Selection System Development.” JOURNAL OF APPLIED PSYCHOLOGY, vol. 96, no. 5, 2011, pp. 907–26, doi:10.1037/a0023298.
APA
De Corte, W., Sackett, P. R., & Lievens, F. (2011). Designing pareto-optimal selection systems: formalizing the decisions required for selection system development. JOURNAL OF APPLIED PSYCHOLOGY, 96(5), 907–926. https://doi.org/10.1037/a0023298
Chicago author-date
De Corte, Wilfried, Paul R Sackett, and Filip Lievens. 2011. “Designing Pareto-Optimal Selection Systems: Formalizing the Decisions Required for Selection System Development.” JOURNAL OF APPLIED PSYCHOLOGY 96 (5): 907–26. https://doi.org/10.1037/a0023298.
Chicago author-date (all authors)
De Corte, Wilfried, Paul R Sackett, and Filip Lievens. 2011. “Designing Pareto-Optimal Selection Systems: Formalizing the Decisions Required for Selection System Development.” JOURNAL OF APPLIED PSYCHOLOGY 96 (5): 907–926. doi:10.1037/a0023298.
Vancouver
1.
De Corte W, Sackett PR, Lievens F. Designing pareto-optimal selection systems: formalizing the decisions required for selection system development. JOURNAL OF APPLIED PSYCHOLOGY. 2011;96(5):907–26.
IEEE
[1]
W. De Corte, P. R. Sackett, and F. Lievens, “Designing pareto-optimal selection systems: formalizing the decisions required for selection system development,” JOURNAL OF APPLIED PSYCHOLOGY, vol. 96, no. 5, pp. 907–926, 2011.
@article{2007122,
  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.}},
  author       = {{De Corte, Wilfried and Sackett, Paul R and Lievens, Filip}},
  issn         = {{0021-9010}},
  journal      = {{JOURNAL OF APPLIED PSYCHOLOGY}},
  keywords     = {{Pareto-optimal,selection design,personnel selection,adverse impact,REDUCE ADVERSE IMPACT,PREDICTOR COMPOSITE FORMATION,SIMULATION,INTEGRITY,METAANALYSIS,COGNITIVE-ABILITY,JOB-PERFORMANCE,STRATEGIES,VALIDITY,PERSONNEL-SELECTION}},
  language     = {{eng}},
  number       = {{5}},
  pages        = {{907--926}},
  title        = {{Designing pareto-optimal selection systems: formalizing the decisions required for selection system development}},
  url          = {{http://dx.doi.org/10.1037/a0023298}},
  volume       = {{96}},
  year         = {{2011}},
}

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