The impact of loyalty on the student satisfaction in higher education

Abstract

PurposeThe purpose of this paper is to examine whether the image of the university, environment, facilities, student expectations, internationalization, services, financial support and perceived value have direct effect on the satisfaction and loyalty of the students of social sciences at Meijo (Private) University, Japan.Design/methodology/approachTo analyze the data, a confirmatory factor analysis was applied where it explored the associations between items and constructs and, then, utilized structural equation model (SEM) to investigate the relationships existing between constructs with the application of the R program. A structured questionnaire comprising of 52 questions were used with 10 constructs. A total of 257 students from Meijo (private) university filled in the newly developed questionnaires using seven items Likert scales.FindingsThe study reveals a valuable insight on student satisfaction and loyalty toward the university. According to the findings, satisfaction has a positive direct impact from services and financial support provided by the university. And also loyalty has a positive strong impact on student satisfaction. On the contrary, satisfaction reveals a positive strong direct impact on loyalty too. Furthermore, there is an indirect impact of image, services and perceived value on loyalty. All the goodness of fit indices are at acceptable levels. Thus, the satisfaction of students seems to reflect quite well from the above construct, image, services, financial support and perceived values.Research limitations/implicationsThis study collected data from two faculties, Faculty of Business Management and Faculty of Economics. The results of this finding cannot be generalized to the entire Meijo university student as a whole.Originality/valueThis study successfully applied an SEM to identify the relationship among constructs. Thus, this research has hopefully opened up avenues for other researchers to carry out such behavioral studies with larger sample sizes by applying R program with SEM analysis.