The Impact of Supplementary Services on Customer Satisfaction and Customer Loyalty: A Study on Menoufia University Hospitals
| Main Author: | Wageeh A. Nafei |
|---|---|
| Format: | Article eJournal |
| Bahasa: | eng |
| Terbitan: |
, 2018
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| Subjects: | |
| Online Access: |
https://zenodo.org/record/3545129 |
Daftar Isi:
- This paper attempts to identify the role of Supplementary Services (SS) in affecting Customer Satisfaction (CS) and Customer Loyalty (CL) at Menoufia University hospitals (MUH). The research community is composed of all employees at MUH (University Hospitals, National Liver Institute and Students Hospitals) in Egypt. Using Lovelock, 1992; 1995 for measuring SS, Athanassopoulos, et al., 2001 for measuring CS and Parasuraman, 1996 for measuring CL. About 338 survey questionnaires were distributed. Multiple follow-ups yielded 275 statistically usable questionnaires. Survey responses were 81%. The research discovered a number of results which are (1) there is a positive relationship between SS, CS, and CL at MUH. In other words, increasing the level of SS leads to improved CS and CL. The positive impact of SS will encourage customers to be satisfied and loyal. In other words, SS is an important indicator of CS and CL, (2) the results of the analysis showed that hospitals in MUH, which increases the level of SS, it reflects positively on CS and CL. In other words, SS is a key factor for CS and CL, (3) the results of the analysis showed that SS has a significant impact on CS and CL at MUH. SS is an important tool for organizations to increase their income and market share, and (4) the researcher used CFA in order to verify the quality of the various research measures. It is clear that all the statement of SS, CS, and CL are greater than 0.50, which corresponds to the GFI. This is a good indicator of all other statistical analysis. In addition to that, the researcher depends on SEM because it is one of the best ways to use the multivariable test. SEM has been used to test the compatibility model using AMOS analysis. In order to ascertain whether the model is compatible with the sample data used. Also, it already measures the variable that should be measured. In general, it is clear that the previous indicators are good for making all other statistical analysis