|dc.description.abstract||In 2011, non-instructional employees comprised approximately 60% of the workforce at four-year, post-secondary institutions in the United States, according to the U.S. Department of Education (2011). While the performance of instructional staff at post-secondary institutions has been the subject of much empirical study, little is known about performance measures used with non-instructional staff. This quantitative case study of one public higher education institution’s performance management process fills a critical void by describing the staff workplace culture of that institution through its performance management practices.
This study evaluated the management tool of the staff performance appraisal, which is typically a corporate process that has been adapted for higher education. These management tools and corporate terminology, such as customer service, have increasingly been incorporated into the higher education culture, and little is understood about their effects on this environment (Birnbaum, 2000; Szekeres, 2006). This study utilized employee performance appraisal and demographic data for non-instructional university staff from 2,401 university employees at a large, urban research institution located in the Southwestern United States. This staff performance appraisal was divided into four components: (a) job goals; (b) job responsibilities; (c) customer focus; and (c) competencies (Human Resources, n.d.a). There were three research questions of interest in this study, including: (1) Within a university setting, how are employee competencies valued by job title within colleges and divisions? (2) How are competencies of individual university staff valued in comparison with job responsibilities, manager responsibilities, job goals and customer service? (3) How is university staff customer service valued in higher education, and are there individual and college/division differences in customer service?
Multiple correspondence analysis was used to answer research question 1. Findings included that, among non-manager employees (N=1,836), the first dimension accounted for 65.11% of adjusted inertia, or explained variance, while the second dimension accounted for 23.89% of adjusted inertia. For manager employees (N=565), the first dimension accounted for 86.57% of adjusted inertia, or explained variance, and the second dimension accounted for 8.26% of adjusted inertia. Visual data in symmetric plots illustrated similarities and differences across departments for competencies valued at this institution, and identified competencies that were outliers, or could be considered for elimination.
Principal components analysis was used to answer research question 2. For non-manager employees, one factor had eigenvalues greater than 1.00, cumulatively accounting for 75.74% of the total variance, and all loadings were greater than .800. For managerial employees, one factor had eigenvalues greater than 1.00, cumulatively accounting for 74.17% of the total variance, and all loadings were greater than .731.
To answer research question 3, a multiple linear regression was conducted to understand variables that predicted an employee’s customer focus score. The prediction model was statistically significant for non-supervisory employees (N=1,836), F(16, 1826) =24.27, p<.001, accounting for approximately 17% of the total variance of an employee’s score on the customer focus section of ePerformance (R2 = 0.18, adjusted
R2=0.17). An employee’s score on the customer focus section of ePerformance was primarily predicted by whether the employee worked in a college or department that performed the primary functions of instruction, research, academic support, institutional support, student services or auxiliaries. It was also predicted by years of service to the institution and, to a lesser extent, ethnicity.
Several themes emerged from the quantitative case study including: (a) that there were too many competencies in use by this institution to rate performance; (b) the four sections used to rate employees appeared redundant; and (c) there were potential rater biases and unclear definitions of customer service. In addition to thematic findings, policy alternatives to improve performance management at this institution were included, and these were guided by institutional policy goals, current institutional practices, study findings and the research literature.