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首页> 外文期刊>Journal of Applied Psychology >Forced Distribution Rating Systems: When Does 'Rank and Yank' Lead to Adverse Impact?
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Forced Distribution Rating Systems: When Does 'Rank and Yank' Lead to Adverse Impact?

机译：强制分配评级系统：“排名和猛击”何时会导致不利影响？

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摘要

Despite widespread use of forced distribution rating systems (FDRSs), the potential for this performance appraisal method to lead to adverse impact (AI) in a layoff context has yet to be examined empirically. Thus, the current study uses a Monte Carlo simulation to examine the likelihood of encountering AI violations when an FDRS is used in the context of layoffs. The primary research questions included an examination of how AI violations change depending on the definition of the employment action (i.e., retention vs. layoff), the length of the repeated layoffs, and whether or not laid off employees are replaced each year. The current study also examined the impact of the size of the organization, the percentage of the workforce laid off, and the type of AI calculation method used on the likelihood of AI violations. Results suggest that defining the employment action as layoffs (rather than as retentions) may result in a greater likelihood of AI violations, and AI violations are likely to peak in the 1st year of use. Further, replacing laid off employees may result in higher levels of AI over time as compared with not replacing layoffs. Additionally, the greatest risk for AI occurs when the organization size is large (i.e., N = 10,000) and when certain AI calculation methods are used. Results are discussed in terms of their practical and legal implications for organizations.
机译：尽管强制分配评级系统（FDRS）的广泛使用，但这种绩效评估方法在裁员中导致不利影响（AI）的潜力尚未得到经验检验。因此，当前的研究使用蒙特卡洛模拟来检验在裁员中使用FDRS时遇到AI违规的可能性。主要的研究问题包括检查AI违规行为如何根据雇佣行动的定义（即保留与裁员），重复裁员的时间长短以及是否每年更换员工而变化。当前的研究还检查了组织规模，裁员人数的影响以及使用AI计算方法的类型对AI违规可能性的影响。结果表明，将雇佣行为定义为裁员（而不是保留），可能会导致违反AI的可能性更大，并且AI违规行为可能会在使用的第一年达到顶峰。此外，与不裁员相比，随着时间的推移，替换下岗员工可能会导致更高水平的AI。另外，当组织规模较大（即N = 10,000）并且使用某些AI计算方法时，发生AI的最大风险。根据结果​​对组织的实际和法律意义进行讨论。

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