Organizations often use competencies to drive human capital initiatives such as recruitment, selection, training, and promotion. To serve such organizations, practitioners now offer various competency-based research solutions incorporating personality assessments to predict these competencies. Each approach begins by mapping competencies from an organization’s model to scientific models backed by synthetic and content validity evidence to align personality dimensions with each competency. This helps determine which personality dimensions drive performance for each competency. In this paper, we compare scale-based profiles, subscale-based algorithms, and scale-based algorithms to investigate the consistency of scores across methods and how effective each method is in predicting competency-based performance.
Gaddis, Blaine and Ferrell, Brandon
"Investigating Three Approaches of Using Personality to Predict Competency-Based Performance,"
Personnel Assessment and Decisions: Vol. 4
, Article 3.
Available at: https://scholarworks.bgsu.edu/pad/vol4/iss1/3
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