Recommendations for Enhancing Student Satisfaction with Service Quality of Dormitory at Lac Hong University

Cite this:
Thi Hue, D. T., & Viet Hung, D. N. (2017). Recommendations for Enhancing Student Satisfaction with Service Quality of Dormitory at Lac Hong University. Journal of Business Management and Economics, 5(01), 12–18. https://doi.org/10.15520/jbme.2017.vol5.iss01.239.pp12-18
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Abstract

According to statistics by the Ministry of education and training announced the end of 2016, there are about 400 universities, colleges, with about three million students are studying at the universities, colleges. Of these, only about 20% to 30% of the students are to meet the demand for accommodation in the dormitory. In Dong Nai province, there are 5 universities and colleges with over 20,000 students, of which about 70% came from the provinces and other cities. Some existing dormitory town to meet about 17% of the total number of students in need. Even, some dormitories too old, peeling walls, leaking roofs, sub-district or district without makeshift side, not ensure sanitation, electricity and water supply system has deteriorated. However, because students have a very high demand in many cases still have to use for students. The necessities such as electricity, water, space for drying clothes is still pressing problem in some dormitories.

The research results showed that there were 200 students of LHU staying dormitory that interviewed and answered about 25 questions from 15/06/2016 to 15/12/2016. The researcher had analyzed KMO test, the result of KMO analysis used for multiple regression analysis. There are five factors, which included of factors following: Component 1 was Responsiveness (X1), Component 2 was dormitory service (X2), Component 3 was Empathy (X3), Component 4 is Staff behavior (X4) and Component 5 was Facility (X5) which affecting the student satisfaction with service quality of dormitory at LHU with 5 % significance level. The research results were processed from SPSS 20.0 software. The parameters of the model estimated by Least - Squares Method tested for the model assumption with 5% significance level.

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