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Impending-Exit Period and Employee Performance: Rethinking Human Capital Disruption
Journal of Management ( IF 9.3 ) Pub Date : 2025-03-13 , DOI: 10.1177/01492063251316464
Yea Hee Ko 1 , Charlie O. Trevor 2
Journal of Management ( IF 9.3 ) Pub Date : 2025-03-13 , DOI: 10.1177/01492063251316464
Yea Hee Ko 1 , Charlie O. Trevor 2
Affiliation
The well-established disruptive effects of employee turnover on firms have typically been attributed to post-exit dynamics, such as losses of human and social capital. Little is known, however, about leavers’ pre-exit job performance, which, if declining in sufficient magnitude as separation nears, may drive some of this disruption. Drawing on career concerns research, we argue that impending exit weakens incentives to improve future career prospects at the firm, thereby resulting in reduced performance. Our analysis reveals strikingly large negative relationships, as job performance during the impending-exit period declines by 53.9% and 79.8% across two performance measures. Additionally, we predict and find that these performance decrements are more pronounced for junior-level employees and partially mitigated for those anticipating a continuing relationship with the organization after exit. We test our predictions using longitudinal data on 4,104 patent examiners who left the United States Patent and Trademark Office from 2001 to 2018.
中文翻译:
即将离职期和员工绩效:重新思考人力资本颠覆
员工流动对公司的公认破坏性影响通常归因于离职后的动态,例如人力和社会资本的损失。然而,人们对离职者离职前的工作表现知之甚少,如果随着离职的临近而下降到足够程度,可能会造成一些干扰。借鉴职业担忧研究,我们认为即将退出会削弱改善公司未来职业前景的激励措施,从而导致绩效下降。我们的分析揭示了显著的负相关关系,因为在即将离职期间,两项绩效指标的工作绩效分别下降了 53.9% 和 79.8%。此外,我们预测并发现,这些绩效下降对于初级员工来说更为明显,而对于那些预计在离职后与组织保持持续关系的人来说,这些下降会部分缓解。我们使用 2001 年至 2018 年离开美国专利商标局的 4,104 名专利审查员的纵向数据来检验我们的预测。
更新日期:2025-03-13
中文翻译:

即将离职期和员工绩效:重新思考人力资本颠覆
员工流动对公司的公认破坏性影响通常归因于离职后的动态,例如人力和社会资本的损失。然而,人们对离职者离职前的工作表现知之甚少,如果随着离职的临近而下降到足够程度,可能会造成一些干扰。借鉴职业担忧研究,我们认为即将退出会削弱改善公司未来职业前景的激励措施,从而导致绩效下降。我们的分析揭示了显著的负相关关系,因为在即将离职期间,两项绩效指标的工作绩效分别下降了 53.9% 和 79.8%。此外,我们预测并发现,这些绩效下降对于初级员工来说更为明显,而对于那些预计在离职后与组织保持持续关系的人来说,这些下降会部分缓解。我们使用 2001 年至 2018 年离开美国专利商标局的 4,104 名专利审查员的纵向数据来检验我们的预测。