人才保留:优秀员工留在组织中的意愿的前因分析

Veronika Škerháková, P. Korba, Michaela Harničárová, Viktória Ali Taha
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引用次数: 5

摘要

鉴于当今劳动力市场竞争激烈,加上COVID-19大流行加剧了人力资本和人才的缺乏,留住有才能的员工对组织来说是一个巨大的挑战。人力资源管理者普遍知道,招聘有才能和高绩效的员工是生存和可持续竞争力的关键。关于哪些因素是留住人才最有效的,学术界进行了大量的研究和讨论。本研究的目的是分析有才华的员工留在组织的意图的先决条件,重点是选定的人口特征。研究样本由391名受访者组成,他们是被认定为组织人才的员工(如果组织中存在人才库,可能包括在人才库中)。数据是用调查表收集的,调查表除了人口特征外,还载有着重于留在本组织的个别方面的说明。这项研究的目的之一是找出被检查变量之间更深层次的联系——通过因子分析找出变量之间如何以及为什么相互关联。为了确定因素的显著性,使用了Bartlett 's球形检验、Kaiser-Meyer-Olkin检验和主成分分析(PCA)等推理统计方法。重要的自变量(人口因素——性别、年龄、教育程度、职位和在组织中工作的时间)对提取因素的价值的影响通过方差分析(ANOVA)进行了检验。
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Talent Retention: Analysis of the Antecedents of Talented Employees’ Intention to Stay in the Organizations
Given the today’s hypercompetitive labour market and the lack of human capital and talents, which is exacerbated by the COVID-19 pandemic, retaining talented employees is a big challenge for organizations. Human resources managers generally know that recruitment of talented and high performing employees is crucial for survival and sustainable competitiveness. There is a lot of academic research and discussions on which factors are the most effective in talent retention. The aim of this study was to analyse the antecedents of talented employees’ intention to stay with the organizations with an accent on selected demographic characteristics. The research sample consisted of 391 respondents - employees who have been identified as organizational talents (possibly included in the talent pool, if such exists in the organization). Data was collected using a questionnaire which, in addition to demographic characteristics, contained statements focusing on individual aspects of remaining in the organization. One of the aims of the study is to find out the deeper connections between the examined variables - to find out how and why the variables are correlated with each other through factor analysis. In order to determine the significance of the factors, inference statistics methods such as the Bartlett’s Test of Sphericity, the Kaiser-Meyer-Olkin test and the principal component analysis (PCA) were used. The influence of significant independent variables (demographic factors - gender, age, education, position held and length of employment in the organization) on the value of extracted factors was examined by means of ANOVA (Analysis of Variance).
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来源期刊
European Journal of Interdisciplinary Studies
European Journal of Interdisciplinary Studies Multidisciplinary-Multidisciplinary
CiteScore
1.40
自引率
0.00%
发文量
16
审稿时长
16 weeks
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