探索休假管理实践及其与行政人员绩效的关系:来自加纳高等教育机构的证据

Mary Safowah Akom, Charles Obeng-Sarpong, Florence Enyonam Aflakpui, S. A. Sarpong
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摘要

有效的休假管理包括包括员工、主管和人力资源经理在内的综合流程。本研究以一所科技大学为个案,探讨休假管理实务及其与大学管理者绩效的关系。这是必要的,因为与当前休假管理实践相关的系统性挑战。这项研究的目的是征求工作人员对休假管理做法及其对工作成绩的影响的意见。使用Yamane(1967)的样本确定公式,从200名人口中方便地选择了96名大学管理人员参与研究。采用自我管理的问卷作为数据收集的主要工具。对结果进行回归分析,探讨休假管理与员工绩效之间的因果关系。预测因子与因变量之间没有线性关系的假设被拒绝。因此,本研究得出预测因子(休假制度)与因变量(员工绩效)之间存在线性关系的结论。这项研究进一步证实,大学的休假申请程序更多是手动的,而不是电子的,而且很官僚。在一年中的分布也不均匀,但在一年中的最后两个季度,大多数员工(86%)休年假的情况相当严重。因此,建议管理机构采取措施,通过自动化流程来提高休假管理实践的效率,以减少官僚主义和错误,并确保每年平均分配休假。
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Exploring Leave Management Practices and Relationship with Performance of Administrative Staff: Evidence from a Tertiary Institution in Ghana
Effective leave management encompasses integrated processes that involve employees, supervisors and human resource managers. This study explored leave management practices and relationship with the performance of University administrators, using a Technical University as a case study. This became necessary due to the systemic challenges associated with the current leave management practices. The purpose of this research was to solicit the views of staff on the leave management practices and how it affects performance. Using Yamane (1967) sample determination formula, a total of 96 University administrators were conveniently selected from a population of 200 to participate in the study. A self-administered questionnaire was adopted as the primary instrument for data collection. The analysis of the results focused on the cause-effect relationship between leave management and staff performance using regression. The hypothesis that there is no linear relationship between the predictor and dependent variable was rejected. The study, therefore, concludes that there exists a linear relationship between the predictor (Leave system) and the dependent variable (Staff performance). The study further established that the leave application process at the University is more manual than electronic and also bureaucratic. It is also unevenly distributed over the year but rather heavily tilted towards the last two quarters of the year where majority of staff (86%) take their annual leave. It is, therefore, recommended that management institutes measures to enhance the efficiencies in the leave management practices by automating the processes to reduce bureaucracies, errors, and also ensure yearly even distribution of the leave.
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