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Designing Pareto-optimal selection systems: formalizing the decisions required for selection system development.
Wilfried De Corte1, Paul R Sackett, Filip Lievens
1Department of Data Analysis, Ghent University, Ghent, Belgium. wilfried.decorte@ugent.be
The Journal of Applied Psychology
|April 6, 2011
Summary
This study introduces a novel analytic method for designing optimal selection systems for diverse applicant groups. It aids practitioners in making key decisions to reduce adverse impact and improve fairness.
Area of Science:
- Decision Science
- Organizational Psychology
- Statistical Modeling
Background:
- Selection systems often face challenges with diverse applicant pools.
- Existing methods may not adequately address complex design decisions.
- Reducing adverse impact is a critical goal in personnel selection.
Purpose of the Study:
- To present an analytic method for designing Pareto-optimal selection systems for mixed candidate populations.
- To provide a framework for addressing six key selection design issues.
- To facilitate research on strategies for mitigating adverse impact.
Main Methods:
- Development of an analytic approach for Pareto-optimal selection system design.
- Integration of decision-making on predictor subsets, rules, staging, sequencing, weighting, and retention.
- Application in both applied and research contexts.
Main Results:
- The proposed method offers a systematic way to optimize selection systems.
- It provides practical guidance for selection practitioners on critical design choices.
- The method enables empirical study of adverse impact reduction strategies.
Conclusions:
- The analytic method is valuable for applied selection and research.
- It addresses a gap in current selection system design tools.
- It supports the development of fairer and more effective selection processes.
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