Running head: PREVENTING BIASES IN 360-DEGREE FEEDBACK Preventing Rater Biases in 360-Degree Feedback by Forcing Choice

We examined the effects of response biases on 360-degree feedback using a large sample (N=4,675) of organizational appraisal data. Sixteen competencies were assessed by peers, bosses and subordinates of 922 managers, as well as self-assessed, using the Inventory of Management Competencies (IMC) administered in two formats – Likert scale and multidimensional forced choice. Likert ratings were subject to strong response biases, making even theoretically unrelated competencies correlate highly. Modeling a latent common method factor, which represented non-uniform distortions similar to those of “ideal-employee” factor in both selfand other assessments, improved validity of competency scores as evidenced by meaningful second-order factor structures, better inter-rater agreement, and better convergent correlations with an external personality measure. Forced-choice rankings modelled with Thurstonian IRT yielded as good construct and convergent validities as the bias-controlled Likert ratings, and slightly better rater agreement. We suggest that the mechanism for these enhancements is finer differentiation between behaviors in comparative judgements, and advocate the operational use of the multidimensional forced-choice response format as an effective bias prevention method.