Differences in self- and managerial-ratings on generic performance dimensions
Open Access
- 29 November 2022
- journal article
- research article
- Published by AOSIS in SA Journal of Industrial Psychology
- Vol. 48, 10
- https://doi.org/10.4102/sajip.v48i0.2045
Abstract
Orientation: The 360-degree performance assessments are frequently deployed. However, scores by different performance reviewers might erroneously be aggregated, without a clear understanding of the biases that are inherent to different rating sources. Research purpose: The purpose of this study was to determine whether there are conceptual and mean score differences between self- and managerial-ratings on performance dimensions. Motivation for the study: Combining self- and managerial-ratings may lead to incorrect decisions about the development, promotion, and/or remuneration of employees. Understanding the effects of rating sources may aid thoughtful decisions about the applications of self- versus managerial-ratings in low- and high-stakes decisions. Research approach/design and method: A cross-sectional design was implemented by asking 448 managers to evaluate their subordinates’ performance, and 435 employees to evaluate their own performance. The quantitative data were analysed by means of multi-group factor analyses and robust t-tests. Main findings: There was a satisfactory degree of structural equivalence between self- and managerial-ratings. Practically meaningful differences emerged when the means of self- and managerial-ratings were compared. Practical/managerial implications: It might be meaningful to uncouple self- and managerial-ratings, when providing performance feedback. Managerial ratings might be a more conservative estimate, which could be used for high-stakes decisions, such as remuneration or promotion. Contribution/value-add: This study is the first to investigate the effect of rating sources on a generic model of performance in South Africa. It provides valuable evidence regarding when different rating sources should be used in predictive studies, performance feedback, or high-stakes talent decisions.Keywords
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