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When and Why Do Supervisors’ Evaluations Overweight Subordinates’ Performance Outcomes? Evidence from a Team Setting in the Field

The Accounting Review 2025 100(2), 133-159 open access
ABSTRACT To better understand supervisors’ outcome bias, I use a regression discontinuity design that compares coaches’ performance assessments of professional football players involved in narrow wins and losses. I document that supervisors over-react to negative outcomes, sharply lowering performance ratings and tripling subordinate turnover. I find that supervisors’ evaluations that subjectively incorporate information from more incomplete objective performance measures are more prone to outcome bias than those that draw on less incomplete objective measures. I also document that supervisors’ evaluations of high-performing team members are more prone to outcome bias than supervisors’ evaluations of low performers. Finally, I find that outcomes affect supervisors’ ex post information collection. My findings, consistent with predictions that I derive from the theory of cognitive reconstruction, shed light on supervisors’ outcome bias in team settings and how effectively firms’ use of objective performance measures, direct monitoring, and information gathering can mitigate this bias. JEL Classifications: M50; D91; Z20.

Less Information, More Comparison, and Better Performance: Evidence from a Field Experiment

Journal of Accounting Research 2021 59(2), 657-711 open access
ABSTRACT We use a field experiment in professional sports to compare effects of providing absolute, relative, or both absolute and relative measures in performance reports for employees. Although studies have documented that the provision of these types of measures can benefit performance, theory from economic and accounting literature suggests that it may be optimal for firms to direct employees’ attention to some types of measures by omitting others. In line with this theory, we find that relative performance information alone yields the best performance effects in our setting—that is, that a subset of information (relative performance information) dominates the full information set (absolute and relative performance information together) in boosting performance. In cross‐sectional and survey‐data analyses, we do not find that restricting the number of measures shown per se benefits performance. Rather, we find that restricting the type of measures shown to convey only relative information increases involvement in peer‐performance comparison, benefitting performance. Our findings extend research on weighting of and responses to measures in performance reports.