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Designing pareto-optimal systems for complex selection decisions

Celina Druart (UGent) and Wilfried De Corte (UGent)
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Abstract
Complex selection decisions handle situation involving multiple jobs and an applicant pool where some of the applicants simultaneously apply for several of the available jobs. Practitioners and researchers interested in the outcomes of such complex selection decisions, based on specific predictors and their characteristics, are provided with two decision aids for designing predictor composites that offer a Pareto-optimal balance between the goals of quality and work force diversity. As shown in the illustrative applications, these developments provide a coherent set of tools for addressing both practical and substantive issues related to the selection uality/adverse impact quandary.
Keywords
Personnel selection, I-O Psychology, Complex selection systems

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Chicago
Druart, Celina, and Wilfried De Corte. 2011. “Designing Pareto-optimal Systems for Complex Selection Decisions.” In 26th Annual Society for Industrial and Organizational Psychology Conference (SIOP), Abstracts. Ghent, Belgium: Ghent University, Department of Data Analysis.
APA
Druart, Celina, & De Corte, W. (2011). Designing pareto-optimal systems for complex selection decisions. 26th Annual Society for Industrial and Organizational Psychology Conference (SIOP), Abstracts. Presented at the 26th Annual Society for Industrial and Organizational Psychology Conference (SIOP), Ghent, Belgium: Ghent University, Department of Data Analysis.
Vancouver
1.
Druart C, De Corte W. Designing pareto-optimal systems for complex selection decisions. 26th Annual Society for Industrial and Organizational Psychology Conference (SIOP), Abstracts. Ghent, Belgium: Ghent University, Department of Data Analysis; 2011.
MLA
Druart, Celina, and Wilfried De Corte. “Designing Pareto-optimal Systems for Complex Selection Decisions.” 26th Annual Society for Industrial and Organizational Psychology Conference (SIOP), Abstracts. Ghent, Belgium: Ghent University, Department of Data Analysis, 2011. Print.
@inproceedings{1220776,
  abstract     = {Complex selection decisions handle situation involving multiple jobs and an applicant pool where some of the applicants simultaneously apply for several of the available jobs. Practitioners and researchers interested in the outcomes of such complex selection decisions, based on specific predictors and their characteristics, are provided with two decision aids for designing predictor composites that offer a Pareto-optimal balance between the goals of quality and work force diversity. As shown in the illustrative applications, these developments provide a coherent set of tools for addressing both practical and substantive issues related to the selection uality/adverse impact quandary.},
  author       = {Druart, Celina and De Corte, Wilfried},
  booktitle    = {26th Annual Society for Industrial and Organizational Psychology Conference (SIOP), Abstracts},
  keyword      = {Personnel selection,I-O Psychology,Complex selection systems},
  language     = {eng},
  location     = {Chicago, IL, USA},
  publisher    = {Ghent University, Department of Data Analysis},
  title        = {Designing pareto-optimal systems for complex selection decisions},
  year         = {2011},
}