Investigating the Influence of Performance Evaluation on Employee Turnover Intention in a Federal Government Agency in Nigeria

Abstract

The primary goal of this study is to investigate the influence of performance evaluation on employee turnover intention in the public sector, with the case being a government agency established by an Act of National Assembly in Nigeria. The study design is descriptive, with primary data collected via questionnaire and secondary data collected via articles, conference proceedings, the internet, and a textbook. The quantitative method used total enumeration technique, with the population equaling the sample size (275). To analyze the gathered data, one hypothesis was developed and an inferential statistical tool, Structural Equation Modelling (SmartPLS-SEM) version, was used. The results revealed that performance evaluation significantly influences employee turnover intention in the federal government agency used as a study (Adj R2=0.406; p=0.000, Q2 =0.253). The study concluded that performance evaluation has a significant impact on employee turnover intention; thus, the researcher recommended that the agency's leadership implement a system that combines satisfaction with financial incentives, material rewards, and psychological rewards to reduce employee turnover.

The Impact of Human Resource Management Practices on Turnover Intention: A Literature Review

“…In a survey conducted by Cheng and Waldenberger (2013), data from 292 employees across eight Chinese organizations were analyzed, revealing that employees who have their training expectations met are more likely to decrease their intention to resign. Additionally, performance appraisal, as a human resource management practice aimed at enhancing employee attitudes and behaviors, is associated with lower employee turnover rates (Arowolo & Akinbo, 2022). When employees perceive that performance ratings are manipulated due to personal biases and intentions to penalize subordinates, it leads to a decrease in job satisfaction and a stronger TI (Murtaza & Abbas, 2022).…”