Prior information bias refers to the influence of previous information on subsequent evaluations of an employee. In the present study, a cusp-catastrophe mathematical model of this bias was proposed. The catastrophe model predicts that there are two patterns by which the biasing effect of prior information diminishes over time. One pattern predicts a smooth, continuous decrement in the bias, whereas the other pattern predicts a sudden, catastrophic decrement. Raters' locus of causality attributions were predicted to differentiate between these two patterns.
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Hanges et al. (1991) studied this question.
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