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Designing Pareto-Optimal Selection Systems: Formalizing The Decisions Required For Selection System Development, Wilfried De Corte, Paul R. Sackett, Filip Lievens
Designing Pareto-Optimal Selection Systems: Formalizing The Decisions Required For Selection System Development, Wilfried De Corte, Paul R. Sackett, Filip Lievens
Research Collection Lee Kong Chian School Of Business
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 …
Applicant Versus Employee Scores On Self-Report Emotional Intelligence Measures, Filip Lievens, Ute-Christine Klehe, Nele Libbrecht
Applicant Versus Employee Scores On Self-Report Emotional Intelligence Measures, Filip Lievens, Ute-Christine Klehe, Nele Libbrecht
Research Collection Lee Kong Chian School Of Business
There exists growing interest to assess applicants' emotional intelligence (EI) via self-report trait-based measures of EI as part of the selection process. However, some studies that experimentally manipulated applicant conditions have cautioned that in these conditions use of self-report measures for assessing EI might lead to considerably higher scores than current norm scores suggest. So far, no studies have scrutinized self-reported EI scores among a sample of actual job applicants. Therefore, this study compares the scores of actual applicants at a large ICT organization (n = 109) on a well-known self-report measure of EI to the scores of employees already …