Examining the Relationships between Manager Ratings and Employees’ Performance in the US-Based Businesses Performance Appraisal System

Studies were abundant about performance appraisal (PA) system criteria, effectiveness, and performance management in the US government sector; no research has explored whether manager ratings reflect actual employee performance or whether managerial favoritism impedes fair PA and employees' praiseworthiness in US-based businesses. Yet, despite ongoing improvements to PA processes, managerial ratings of employees frequently do not reflect the employees' actual job performance. The purpose of this study was to examine the correlations among four predictor variables, which include fairness, favoritism, employees' actual performance, praiseworthiness and the dependent variable of manager ratings in US-based healthcare businesses. Four research questions were raised concerning to what extent do the four predictor variables relate with the dependent variable in US private sector hospitals and clinics. A quantitative method adopted a correlational design to investigate the relationships between the variables. The sample study comprised a total of 200 male and female nurses working in US private sector hospitals and clinics, and this sampling frame was obtained from the Qualtrics(R) online platform. Data were collected using a 30-item survey based on the work of Swanepoel et al. (2014) and Tziner et al. (1996). The trustworthiness of data was tested for reliability using IBM-SPSS 25 software and confirmatory factor analysis (CFA) to confirm the model fit and goodness-of-model-fit indices by AMOS 25. A multiple linear regression (MLR) test provided evidence that favoritism had the highest significant correlation with manager ratings, followed by fairness and employees' actual job performance. The empirical findings confirmed with the study's conceptual framework of human capital theory, AMO (ability, motivation, and opportunity) model, expectancy theory, and agency theory. The empirical findings of multi-collinearity also suggested further research recommendations that include other constructs.

• | Author: Raed Alamiri
• | Publisher: Independently published
• | Publication Date: Jan 04, 2019
• | Number of Pages: 139 pages
• | Language: English
• | Binding: Paperback
• | ISBN-10: 1793154481
• | ISBN-13: 9781793154484