The role of employee personality in employee satisfaction and turnover: insights from online employee reviews

IF 3.3 3区 管理学 Q1 INDUSTRIAL RELATIONS & LABOR Personnel Review Pub Date : 2024-02-08 DOI:10.1108/pr-04-2023-0309
Ruigang Wu, Xuefeng Zhao, Zhuo Li, Yang Xie
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Abstract

PurposeOnline employee reviews have emerged as a crucial information source for business managers to evaluate employee behavior and firm performance. The purpose of this paper is to test the relationship between employee personality traits, derived from online employee reviews and job satisfaction and turnover behavior at the individual level.Design/methodology/approachThe authors apply text-mining techniques to extract personality traits from online employee reviews on Indeed.com based on the Big Five theory. They also apply a machine learning classification algorithm to demonstrate that incorporating personality traits can significantly enhance employee turnover prediction accuracy.FindingsPersonality traits such as agreeableness, conscientiousness and openness are positively associated with job satisfaction, while extraversion and neuroticism are negatively related to job satisfaction. Moreover, the impact of personality traits on overall job satisfaction is stronger for former employees than for current employees. Personality traits are significantly linked to employee turnover behavior, with a one-unit increase in the neuroticism score raising the probability of an employee becoming a former employee by 0.6%.Practical implicationsThese findings have implications for firm managers looking to gain insights into employee online review behavior and improve firm performance. Online employee review websites are recommended to include the identified personality traits.Originality/valueThis study identifies employee personality traits from automated analysis of employee-generated data and verifies their relationship with employee satisfaction and employee turnover, providing new insights into the development of human resources in the era of big data.
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员工个性在员工满意度和离职率中的作用:从在线员工评论中获得的启示
目的在线员工评论已成为企业管理者评估员工行为和公司业绩的重要信息来源。本文旨在检验从在线员工评论中得出的员工个性特征与个人层面的工作满意度和离职行为之间的关系。作者基于大五理论,运用文本挖掘技术从 Indeed.com 上的在线员工评论中提取个性特征。他们还应用机器学习分类算法证明,加入人格特质可显著提高员工离职预测的准确性。研究结果人格特质(如合意性、自觉性和开放性)与工作满意度呈正相关,而外向性和神经质与工作满意度呈负相关。此外,人格特质对离职员工整体工作满意度的影响要强于在职员工。人格特质与员工离职行为有明显关联,神经质得分每增加一个单位,员工成为前员工的概率就会增加 0.6%。建议在线员工评论网站加入已识别的人格特质。原创性/价值本研究通过自动分析员工生成的数据识别了员工的人格特质,并验证了这些人格特质与员工满意度和员工流失率之间的关系,为大数据时代的人力资源发展提供了新的见解。
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来源期刊
Personnel Review
Personnel Review Multiple-
CiteScore
7.10
自引率
7.70%
发文量
133
期刊介绍: Personnel Review (PR) publishes rigorous, well written articles from a range of theoretical and methodological traditions. We value articles that have high originality and that engage with contemporary challenges to human resource management theory, policy and practice development. Research that highlights innovation and emerging issues in the field, and the medium- to long-term impact of HRM policy and practice, is especially welcome.
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