Publication Type
Journal Article
Version
acceptedVersion
Publication Date
7-2020
Abstract
In case that both the goals of selection quality and diversity are important, a selection system is Pareto-optimal (PO) when its implementation is expected to result in an optimal balance between the levels achieved with respect to both these goals. The study addresses the critical issue whether PO systems, as computed from calibration conditions, continue to perform well when applied to a large variety of different validation selection situations. To address the key issue, we introduce two new measures for gauging the achievement of these designs and conduct a large simulation study in which we manipulate 10 factors (related to the selection situation, sensitivity/robustness, and the selection system) that cumulate in a design with 3,888 cells and 24 selection systems. Results demonstrate that PO systems are superior to other, non-PO systems (including unit weighed system designs) both in terms of the achievement measures as well as in terms of yielding more often a better quality/diversity trade-off. The study also identifies a number of conditions that favor the achievement of PO systems in realistic selection situations.
Keywords
adverse impact, personnel selection, Pareto-optimal, selection design, robustness, sensitivity, sampling variability
Discipline
Human Resources Management | Organizational Behavior and Theory
Research Areas
Organisational Behaviour and Human Resources
Publication
Organizational Research Methods
Volume
23
Issue
3
First Page
535
Last Page
568
ISSN
1094-4281
Identifier
10.1177/1094428118825301
Publisher
SAGE Publications (UK and US)
Citation
DE CORTE, Wilfried; SACKETT, Paul; and LIEVENS, Filip.
Robustness, sensitivity and sampling variability of Pareto-optimal selection system solutions to address the quality-diversity trade-off. (2020). Organizational Research Methods. 23, (3), 535-568.
Available at: https://ink.library.smu.edu.sg/lkcsb_research/6425
Copyright Owner and License
Authors
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1177/1094428118825301