Expectations and Perceptions of Service Quality among Users of Academic Affairs and Registration at Chaiyaphum Rajabhat University

Abstract

This study aimed to 1. examine the levels of expectations and perceptions of service quality among users of Academic Affairs and Registration services at Chaiyaphum Rajabhat University, 2. compare these expectations and perceptions, and 3. identify problems and obstacles in service use. The sample consisted of 400 students from a total population of 3,227 individuals who had previously used the services in the academic year 2024. Data were collected via an online questionnaire distributed through Google Form. Statistical analyses included descriptive statistics (frequencies, percentages, means, standard deviations) and inferential statistics (paired samples t-test, One-way ANOVA). Results revealed that: 1. Both the overall level of expectations (mean = 4.12, SD = 0.58) and perceptions (mean = 3.95, SD = 0.62) of service quality were rated as "high." However, expectations were significantly higher than perceptions (t(399) = 8.74, p < .001, Cohen’s dz = -0.44), indicating a statistically significant service quality gap (mean gap = -0.17, 95% CI [-0.23, -0.11]). 2. Among the five SERVQUAL dimensions, "Assurance" had the highest mean scores for both expectations (4.18) and perceptions (4.05). The largest service gaps were found in "Tangibles" (gap = -0.20) and "Empathy" (gap = -0.20). Perceptions of service quality did not differ significantly by gender or year of study, but did differ significantly by faculty (p = .023), with students from the Faculty of Arts and Science reporting lower perceptions, potentially linked to higher expectations regarding technology and infrastructure.         3. Content analysis of open-ended responses identified key issues: technological/system failures, staff behavior and physical environment. These findings provide actionable insights for service improvement, highlighting the need to prioritize digital infrastructure upgrades and enhance staff training in communication and personalized service delivery to bridge the identified gaps. A key limitation is the potential for self-selection bias inherent in online data collection and the single-institution context, which limits generalizability.