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Unraveling the Impact of Employee Traits and Organizational Structure on Continuous Peer Evaluation: An Empirical Investigation
Yuan Zhang, Michael Rivera, Liangfei Qiu, Subodha Kumar
In a rapidly changing tech environment, organizations must adapt quickly, making precise performance evaluations essential. However, the increasing complexity of organizations and their evaluation systems complicates fair peer evaluations. Issues like team size and diversity in competencies can bias evaluations, posing a challenge to effective performance management. Our research explores ways to enhance fairness and accuracy in evaluations using data from DevelapMe, a real-time feedback tool. We analyze over 18,100 team-level and 1,200 employee-level feedback instances, discovering that smaller teams and those aligned with organizational values tend to give higher ratings. In contrast, employees within the same department rate each other lower. Our findings also show that employee traits such as competitiveness and leadership skills influence ratings. This research offers strategies to improve performance evaluations by considering organizational structures and individual characteristics, providing leaders with tools to foster better collaboration and productivity.
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