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Students' Satisfaction and University Reputation through Service Quality in Private Higher Educational Institutions in Bangladesh

  • ALAM, Mohammad Manjur (Department of Computer Science and Engineering, International Islamic University Chittagong (IIUC)) ;
  • ALAUDDIN, Md. (Department of Marketing, City University of Hong Kong) ;
  • SHARIF, Mohd Yasin (Department of English Language and Literature, International Islamic University Chittagong) ;
  • DOOTY, Evana Nusrat (Department of Business Administration, International Islamic University Chittagong) ;
  • AHSAN, Syed Md. Hasib (Department of Business Administration, International Islamic University Chittagong) ;
  • CHOWDHURY, Mustafa Manir (Department of Business Administration, International Islamic University Chittagong)
  • Received : 2021.05.15
  • Accepted : 2021.08.02
  • Published : 2021.09.30

Abstract

Educational institutions play a critical role in national development through the advancement of skilled human resources and intellectual society. The number of higher educational institutions (HEIs) is increasing significantly in Bangladesh. Students have a number of options from which to select their preferred educational institutions. Hence, HEIs should think about the quality of services they provide to students. The objective of this study is to measure students' satisfaction and university reputation through service quality (SQ) in a private higher educational institution (PriHEI) in Bangladesh. Primary data was collected from 270 students of International Islamic University Chittagong (IIUC), Bangladesh, through a simple random sampling technique. In this study, data was analyzed through descriptive statistics, correlation, measurement model using confirmatory factor analyses, and structural equation modeling (SEM). The results showed that transport services have indirect but medical and physical facilities have both direct and indirect significant effects on overall students' satisfaction. Further, the administrative services and research facilities have significant indirect effects on overall students' satisfaction. Finally, the results of structural equation modeling (SEM) confirm that the reputation of the university is directly associated with overall students' satisfaction.

Keywords

1. Introduction

A service is an activity or advantage that’s offered to another that’s to a great extent imperceptible and does not come into the ownership of anything. Service quality is for the most part characterized as a comparison of a customer’s service desires because it relates to the execution of an organization. A firm with a high level of service quality is capable of meeting customer needs while also remaining economically competitive in its respective industry (Abbas, 2020). Traditionally, service sectors played an important and vital role in the development of a country’s economy. In today’s competitive business world, service quality can be interpreted as a means of achieving a specified benchmark. SQ experts agree that it is one of the most viable and influential current trends for shaping a business and hence promoting policy. SQ is linked to increased productivity and serves as a key facilitator for increased sales, favorable word-of-mouth, and increased competitive production capacity.

According to Zeithaml et al. (1996), the role of SQ in generating income and meaningful economic benefits are the most important. This is one of the reasons for SQ’s emergence as a useful strategic force as well as a critical topic for higher education research. Academics and industry specialists are increasingly interested in assessing SQ in areas like consumer experience, procedures, quality, and consumer loyalty. SQ is a driving force for some firms to assure higher service quality while also serving as a factor in their reputation. Consumer attention and SQ measurement are also vital and significant. For years, the conceptualization of SQ, as well as its relation to customer satisfaction, value constructs, and evaluation methods, have been considered inseparable research subjects in the tourism and hospitality education system at higher educational institutions (HEI) (Oldfield & Baron, 2000).

Presently, HEI education is on the rise, owing to competition and other significant economic factors. The commoditization of education has been fueling the growth of the worldwide education markets. Simultaneously, decreasing funding for educational administration in HEIs is forcing HEIs to look for alternative funding sources.

Private Higher Educational Institutions (PriHEIs) are under pressure not just because of students’ abilities and skills, but also because of students’ competing capacities in the labor market (Lawton, 1992). In a few cases, PriHEIs are unable to take adequate and effective efforts to understand students’ needs in order to provide good education (Anderson et al., 1994). Thus, the purpose of this study is to assess the satisfaction of students and the reputation of the university through SQ at PriHEI in Bangladesh.

2. Literature Review

2.1. Higher Educational Institution (HEI) and Private Higher Educational Institutions (PriHEI)

HEIs not only include colleges and universities but also many different professional schools that offer preparation in many fields including business, theology, law, theology, medicine, art, sport, tourism, and music. HEIs can also include schools for teacher training, junior colleges, and technology training institutes. Students are considered as the prime stakeholder in higher education institutions (HEIs). In his research, Abbas (2020) identifies SQ indicators from their viewpoints and suggests a more comprehensive tool to measure SQ exclusively in HEIs. HEISQUAL covers the technical as well as operational aspects of SQ by proposing seven SQ themes namely, teachers’ profile, curriculum, facilities and infrastructure, support and management staff, employment quality, safety and security, and students’ skills development. Le (2020) placed a great emphasis on facilities, stating that facilities are one of the most essential aspects that students consider before choosing an HEI.

In the context of Nepal, Joshi (2019) stated that the growth of private schools is substantial in lower-income countries. One of the key reasons for this development is the discernment of the disappointment of the government and expanded openness and accessibility of private schools inside different cost ranges. The findings about appeared that the foundations of private schools initiated to create work and speculations as well as social inspirations. However, the stakeholders with their overwhelming speculation within the instruction framework specified a few inadequacies as less antagonistic vibe, need of soundness, more monitoring, and their require and challenges appraisal as the citizens to get instruction from them. Hence, the investigation of structures of the local-level private schools with their functions can offer assistance to the government to get it private schooling success, differences, possibility, and challenges of regulations.

A good number of research studies is carried on HEI and PriHEI in the last couple of decades (Sohail et al., 2003; Wilkinson & Yussof, 2005; Nguyen et al., 2020; Tran & Bui, 2020). Liu and Bray (2020) in the Myanmar context observed that shadow education may subtract as well as supplement. For a few decades, public instruction in Myanmar has endured from monetary imperatives, bigger classes, and an over-burden curriculum module. Students and their families particularly looked for private mentoring from public school instructors as a complement to school instruction and invited the income that instructors and other suppliers seem to earn. As a result, private mentoring has become implanted within the lives of numerous students and instructors and has consumed time and vitality to spend on school instruction. In any case, private tutoring has too assisted to keep the school system running.

The government of Bangladesh seems unconcerned with the quality of higher education institutions in its pursuit of academic excellence. When higher education in the country merges with the service industry, a greater emphasis is placed on meeting the wants and expectations of the students who are the participants. In recent years, a large number of such schools have seen student enrolment decline as a result of ongoing quality issues and service issues.

2.2. Student Satisfaction (OS), University Reputation (UR), and Service Quality (SQ)

Service quality has been the subject of interest in marketing in recent years (Parasuraman et al., 1985). Several research studies have been conducted for outlining the extensive influence on student satisfaction based on SQ positive perception (Owlia & Aspinwall, 1996; Sahney et al., 2004; Abdullah, 2006; Abd Manaf et al., 2013; Sharabi, 2013; Yousapronpaiboon, 2014). In their research, Alves and Raposo (2010) showed that image is the construct that most influences student satisfaction. The influence of image is also relevant to student loyalty. It is proven that the construct which most influences student satisfaction in higher education is the image construct. Thus, if the institutional image rises or falls satisfaction as well as loyalty also increases or diminishes accordingly. Ahmed et al. (2010) demonstrated the significance of the relationship between dimensions of service quality that is, tangibles, assurance, and empathy with satisfaction while tangible, responsiveness, and assurance are significantly connected to student motivation. Finally, observing the performance aspects of students’ academic careers has shown that students’ satisfaction and motivation are important for the better performance of the students. Haw (2018) applied personalization principles to assignment feedback to examine its effect on student perceptions of teaching quality. Students evaluated the sum of time and response support significantly higher for the personalized group than for the non-personalized group. However, personalization does not influence other frameworks of good teaching. These comes about are talked about within the context of blending reading material with service arrangements to maximize the student involvement. Also, Pedro et al. (2018) found a positive connection between service quality and overall student satisfaction in HEI.

SERVQUAL scale is applied to evaluate SQ (i.e. assurance, empathy, reliability, responsiveness, and tangibility) by Parasuraman et al. (1988). Ten factors were identified by Parasuraman et al. (1985) that can be generalized as reliability, tangibility, efficiency, access, awareness, communication, protection, politeness, credibility, and empathy. Nadiri et al. (2009) tried to analyze the quality of services provided by administrative units such as registrars, libraries, faculty/ school offices, rector’s offices, dormitories, sports and health centers. Zhang et al. (2016) explored the impact of the Sport Management Program’s educational quality (including curriculum quality and quality of educational services) on students’ educational assessment. The results of structural relationship model propose that the effect of educational programs quality and quality of instructive administrations first leads to changes within the seen quality of students; this modification in perceived quality further unswervingly affect loyalty through satisfaction. Eurico et al. (2015) examined how employability and graduates’ satisfaction and loyalty have been assessed in HEIs.

Satisfaction is defined as a state felt by a person who has experienced performance or an outcome that fulfills his or her expectation (Kotler & Clarke, 1987). Satisfaction is a function of the relative level of expectations and it perceives performance. Satisfaction is also perceived as the intentional performance which results in one’s contentment (Palacio et al., 2002). Santos et al. (2020), identified the factors defining students’ perceptions of university social responsibility (USR) and analyze its impact on their satisfaction and service quality. The research was carried out in a Portuguese higher education institution, with a sample of 903 students. The results validated this explanatory model of USR and the latter’s impact on service quality and higher instruction students’ satisfaction. Concerning the effect of the USR, the outcomes about incorporate that, from the student’s point of view, the USR contributes the foremost to instruction through the cognitive impacts of the USR, i.e. those related to investigate. The comes about of this study further demonstrate that a procedure centered on maintainable improvement (i.e. advancing a mindful university) impacts students’ positive discernment and capacities as an forerunner of service quality and students fulfillment.

A large number of studies focused on the perspectives of clients, and researchers face various challenges in presenting a better definition of student satisfaction, prompting them to exclude any theory or notion related to student satisfaction. (Athiyaman, 1997; Chuah & Sri Ramalu, 2011). Student satisfaction has not been well defined from the student viewpoint rather it is regarded mostly from the clients’ end (Hom, 2002).

The reputation of a university is defined as the overall perception raised by the institution over time (Alessandri et al., 2006). Indrajit and Djokopranoto (2006) defined the reputation of the university can be measured by the ratio of the number of candidates to the number obtained. According to Jung and Seock (2016), there is a direct relationship between SQ and UR. Nevertheless, better SQ determines the reputation of the organization because the reputation of the organization can attract customer satisfaction (Selnes, 1993).

As a result of the growing number of higher education institutions, the private education industry is competing with one another to attract more students for economic purposes. The administration of PriHEIs in Bangladesh delivers productive and persuasive benefits for retaining and satisfying students to achieve the business goal. On this basis, this study aims to investigate students’ satisfaction with PriHEI’s service quality and its impact on university reputation.

2.3. Conceptual Model and Hypotheses

Based on the literature as well as PriHEIs concept of Bangladesh, the hypothesized conceptual model is as follows (Figure 1).

OTGHEU_2021_v8n9_91_f0001.png 이미지

Figure 1: Hypothesized Structural Model

Based on the above model, the following hypotheses have been developed:

H1–H7: Teaching and learning quality, accommodation facilities, infrastructure facilities, administrative and support services, research facilities, physical and medical facilities, transport facilities have a significant impact on the university’s reputation (UR).

H8–H9: Physical and medical facilities, transport facilities have a direct and indirect significant influence on overall students’ satisfaction (OS).

H10: The reputation of the university (UR) has a direct significant impact on overall student satisfaction (OS).

3. Research Methods and Materials

3.1. Data Collection and Methods

A questionnaire was designed to collect primary data from the students of IIUC. IIUC is one of the leading and top graded private universities in Bangladesh established in 1995 and approved by the government of Bangladesh (IIUC, 2018). At present, it has 14000 students including domestic and international students and 370 faculty members. The survey participants were both undergraduate and postgraduate students. With a simple random sampling technique, the survey was conducted on 270 respondents between January to March 2020. Further, the minimum sample for SEM is recommended as 150 (Bentler & Chou, 1987). Sample data was collected from all programs offered by the university in the year 2020 with CGPA (Cumulative Grade Point Average) of which 74.8% of students have a GPA of greater than 3. The number of male students and female students was 165 (61.1%) and 105 (38.5%), respectively. Most of the students were around 23 years old (60.7%).

3.2. Measurement Tools

The questionnaires prepared for this study were organized into two separate parts. In “Part A’’, the demographic profile of the students was collected while in “Part B” ‘37 items based on a five-point Likert scale were constituted covering students’ satisfaction and university reputation through SQ of PriHEI. In the questionnaire, 1 indicated “strongly disagree’’ and 5 indicated “strongly agree’’. A total of seven exogenous variables, one endogenous variable, and one mediating variable were considered in this study. Endogenous and mediating variables are overall students’ satisfaction (OS) and university reputation (UR). On the other hand, the seven exogenous variables are: the teaching and learning quality (TL), accommodation facilities (AF), infrastructure facilities (IF), transport facilities (TF), administrative and support services (AS), physical and medical facilities (MP), and research facilities (RF).

3.3. Statistical Tools

Data analysis followed descriptive statistics, correlation, measurement model through confirmatory factor analysis (CFA), and structural equation modeling (SEM) for estimating students’ satisfaction and UR through SQ in a PriHEI in Bangladesh. In the earlier stage, the measurement model is tested, and in the next stage, the SEM model is performed. CFA is run to assess the convergent and discriminant validity of the latent factors. The rationale for applying structural equation modeling (SEM) is that there is one endogenous variable and one mediating variable associated with various exogenous variables. Different fit indices are used in the literature. We only used the most common indices. The analysis of data was carried out by SPSS 24 and AMOS 22.0 version.

4. Results

4.1. Measurement Model

In the measurement model, CFA is the initial part of applying the SEM approach. Table 1 represents the CFA model fit summary. The different fit indices of the CFA model are found satisfactory. The Chi-square value (χ2) of the model is 860.242 with a degree of freedom (df = 585) and the ratio of χ2 over df is 1.470 (≤3.00). The CMIN/DF ratio is less than 3 indicating that the model’s overall fit is within acceptable limits (Meydan & Sesen, 2011). The Goodness-of-fit index (GFI) value is 0.901 which can be taken as acceptable and depends on the sample according to Byrne (2001) and Arbuckle (2003). The Root mean square error of approximation (RMSEA) value is 0.042, which is acceptable at less than 0.08 (Hair et al., 2010). The value of the adjusted goodness-of-fit index (AGFI) is 0.862, which is acceptable according to Byrne (2001) and Arbuckle (2003). The model’s normed fit index (NFI) and comparative fit index (CFI) are higher than 0.90 (Hair et al., 2010). All model fit indices lie within satisfactory limits, which indicated that the overall measurement model fit is good.

Table 1: CFA Model Fit Summary

OTGHEU_2021_v8n9_91_t0001.png 이미지

Table 2 shows the standard factor loadings of the CFA of each of the items along with standard error (SE) and critical ratio (C.R.). Hair et al. (2010) illustrated that the factor loading should be at least 0.50 when the standard value is 0.70 or higher and the construct reliability (CR) values should be greater than 0.70 to support the CR. Table 2 reported that all the factor loadings are higher than the threshold value of 0.50 and construct reliability (CR) values are greater than 0.70. Therefore, the convergent validity of the scales is fulfilled.

Table 2: Results of Confirmatory Factor Analysis

OTGHEU_2021_v8n9_91_t0002.png 이미지

Note: For all P-value < 0.01.

Table 3 illustrate the mean, standard deviation, Cronbach’s α, AVE, pairwise correlation, construct reliability (CR), and discriminant validity between the constructs. The mean of all constructs was above the midpoint on the 5-point Likert scale and the standard deviation was 0.876 and 1.077. Cronbach’s α was calculated by using the scale reliability of the SPSS 24 program. The AVE and CR values are calculated by putting the results of the CFA standard factor loadings into the formula. Fornell and Larcker (1981) argued that the AVE must be higher than the 0.50 threshold. Therefore, the results of the AVE in Table 3 had proven the satisfactory criteria. The result of the correlation analysis shows that all latent variables are significantly and positively correlated with each other at a 0.01 significance level. Hair et al. (2010) recommended that correlation above 0.30 is appropriate for factor analysis. He also suggested that if the pairwise correlation value is above 0.80 then a multicollinearity problem exists. The finding of this study shows that the highest value of the pairwise correlation is between infrastructure facilities (IF) and accommodation facilities (AF) (0.602), which is less than 0.80. Hence, no multicollinearity exists among the constructs. The diagonal value in Table 3 is the square root of the AVE values and it is higher than the correlation (off-diagonal) for each dimension. Therefore, all the latent variables show satisfactory discriminant validity. Moreover, Cronbach α and composite reliability values of all latent factors are greater than the threshold value of 0.70 (Nunnally, 1994; Hair et al., 2010). Thus, all latent factors revealed a high level of internal consistency reliability.

Table 3: Descriptive Statistics, Correlation Coefficient, Reliability Results, and Discriminant Validity

OTGHEU_2021_v8n9_91_t0003.png 이미지

Note: *P-value < 0.05. The diagonal elements within brackets indicate the square root of the AVE values.

4.2. Structural Equation Model

For examining the relationship between SQ of PriHEI on university reputation and students’ overall satisfaction, SEM is also employed in this research. The fundamental advantage of SEM is that it can visualize data and hypotheses in a realistic model.

Table 4 shows that the model is an adequate fit for sample data because the threshold of CMIN/DF is less than 2 (1.077) and GFI and AGFI are more than 0.90 (Tabachnick et al., 2007). The values of CFI and NFI are higher than the limiting value of 0.90 (Hu & Bentler, 1999). RMSEA is 0.017 which is lower than the marginal value of 0.08 (Byrne, 2013, Hair et al., 2010).

Table 4: Fit Indices for SEM

OTGHEU_2021_v8n9_91_t0004.png 이미지

Table 5 and Figure 2 present the regression weight output for the unstandardized MLE of the structural path relationships. Critical ratios (C.R.) describes the estimate divided by the standard error. Also, the probability value is shown in column p. The estimated parameter becomes significant at the value of P ≤ 0.05 and the value of C.R ≥ 1.96. Out of ten hypotheses, the hypotheses H4, H5, H6, H8, H9, and H10 are found to be significant. The probability of critical ratio (C.R.) remains high as 7.585, 5.548, 3.987, 3.691, 3.402, and 3.259.

Table 5: Hypothesis Results

OTGHEU_2021_v8n9_91_t0005.png 이미지

Note: **p-value < 0.05; ***p-value < 0.001.

OTGHEU_2021_v8n9_91_f0002.png 이미지

Figure 2: SEM of SQ and UR

5. Discussion

All the fit indices in the measurement model (Table 1) lie within satisfactory limits, which specifies that the overall fit is well. Table 2 illustrates that the standardized factor loadings of the items considered in this study are greater than the limiting value of 0.50 (Hair et al., 2010). The results of the reliability and discriminant validity (see in Table 3) offer high internal consistency of the scale as well as the items. Each path’s value (see in Figure 2) indicates the regression coefficient (β). The value of the regression coefficient illustrates that transport services (β = 0.438, P < 0.01) have direct significant influences on students’ overall satisfaction. Thus the hypothesis supports H8. This result is confirmed by Marzo (2013) and Rahman et al. (2020) observations, who also reported that there is a positive significant relationship between students’ satisfaction and university transport facilities. Furthermore, the findings of the study found that physical and medical facilities have not only direct (β = 0.209, P < 0.01) but also an indirect (β = 0.288, P < 0.01) significant positive effect on students’ overall satisfaction, thus the hypotheses H6 and H9 are accepted.

Physical facilities in the context of higher education, according to Douglas et al. (2006), are essential for student satisfaction. The majority of PriHEIs lack adequate physical and medical facilities, which could be one explanation for Bangladesh’s gap in the significance of physical and medical facilities. It was found that factors, namely, administrative and support services (β = 0.209, P < 0.0), and research facilities (β = 0.349, P < 0.01) have an indirect significant effect on students’ overall satisfaction, thus the hypotheses H4 and H5 is supported. Akareem and Hossain (2012) reported that both administrative and faculty characteristics of PriHEI in Bangladesh play an important role to a greater extent in affecting the quality of higher education. Finally, the mediating variable university reputation (β = 0.134, P < 0.01) directly influenced students’ overall satisfaction, thus H10 is supported. Thus, students who get better SQ from an institution tend to build a greater reputation and positive perception of that institution. The rest of the other hypotheses (H1, H2, H3, H7) considered in this study do not have a direct or indirect significant effect on overall student satisfaction. Meydan and Sesen (2011) stated that direct and indirect relationships among causal variables are the most significant part of the structural equation model. Further, our results are also supported by Mulyono et al. (2020).

6. Conclusion and Recommendation

A conceptual model based on the literature has been developed linking student satisfaction with service quality and university reputation. This research aimed at evaluating the SQ of PriHEI on university reputation and students’ overall satisfaction. The findings of the research suggest that the reputation of the university and students’ overall satisfaction in PriHEI mainly depend on the physical and medical facilities, transport services, administrative and support services, and research facilities. Furthermore, transport services have a direct significant and positive effect on students’ overall satisfaction. But physical and medical services have not only direct but also an indirect significant and positive effect on students’ overall satisfaction in PriHEI. Besides, administrative services and research facilities are also very crucial factors affecting students’ overall satisfaction in PriHEI in Bangladesh. The study found that both these variables have a strong indirect positive and significant effect on overall students’ satisfaction at IIUC.

This study can help IIUC management as well as other HEIs in Bangladesh to evaluate and improve the quality of their services. Thus based on the outcome of this research, the PriHEIs intending to enhance the satisfaction of their students should emphasize physical and medical services, transport services with an outstanding delivery of administrative and support services. More emphasis should be given to offering up-to-date physical and medical facilities and equipment in ensuring the basic demands of the students. The research facilities need to be developed and modernized for achieving more students’ satisfaction and university reputation. This study also reveals the importance of university personnel paying close attention to building a favorable and enhanced reputation for the university.

One of the basic drawbacks of this research is the inadequateness of respondents covering only one private university in Bangladesh while the contentions should be validated more by further research. In future research studies, more HEIs and PriHEIs in Bangladesh can be brought under research for SQ evaluation for getting a comprehensive outcome.

References

  1. Abbas, J. (2020). HEISQUAL: A modern approach to measuring service quality in higher education institutions. Studies in Educational Evaluation, 67, 100933. https://doi.org/10.1016/j.stueduc.2020.100933
  2. Abd Manaf, N. H., Ahmad, K., & Ahmed, S. (2013). Critical factors of service quality in a graduate school of Malaysia. International Journal of Quality and Service Sciences, 5(4), 415-431. https://doi.org/10.1108/IJQSS-07-2012-0006
  3. Abdullah, F. (2006). Measuring service quality in higher education: HEdPERF versus SERVPERF. Marketing Intelligence & Planning, 24(1), 31-47. https://doi.org/10.1108/02634500610641543
  4. Ahmed, I., Nawaz, M. M., Ahmad, Z., Ahmad, Z., Shaukat, M. Z., Usman, A., & Ahmed, N. (2010). Does service quality affect students' performance? Evidence from institutes of higher learning. African Journal of Business Management, 4(12), 2527-2533. https://doi.org/10.5897/AJBM.9000224
  5. Akareem, H. S., & Hossain, S. S. (2012). Perception of education quality in private universities of Bangladesh: a study from students' perspective. Journal of Marketing for Higher Education, 22(1), 11-33. https://doi.org/10.1080/08841241.2012.705792
  6. Alessandri, S. W., Yang, S. U., & Kinsey, D. F. (2006). An integrative approach to university visual identity and reputation. Corporate Reputation Review, 9(4), 258-270. https://doi.org/10.1057/Palgrave.crr.1550033
  7. Alves, H., & Raposo, M. (2010). The influence of university image on student behavior. International Journal of Educational Management, 24(1), 73-85. https://doi.org/10.1108/09513541011013060
  8. Anderson, E. W., Fornell, C., & Lehmann, D. R. (1994). Customer satisfaction, market share, and profitability: Findings from Sweden. Journal of Marketing, 58(3), 53-66. https://doi.org/10.1177/002224299405800304
  9. Arbuckle, J. L. (2003). Amos 5.0 update to the Amos user's guide. Chicago, IL: SPSS.
  10. Athiyaman, A. (1997). Linking student satisfaction and service quality perceptions: The case of university education. European Journal of Marketing, 31(7), 528-540. https://doi.org/10.1108/03090569710176655
  11. Bentler, P. M., & Chou, C. P. (1987). Practical issues in structural modeling. Sociological Methods & Research, 16(1), 78-117. https://doi.org/10.1177/0049124187016001004
  12. Byrne, B. M. (2001). Structural equation modeling with AMOS: Basic concepts, applications, and programming. Abingdon, UK: Routledge.
  13. Byrne, B. M. (2013). Structural equation modeling with Mplus: Basic concepts, applications, and programming. Abingdon, UK: Routledge.
  14. Chuah, C. W., & Sri Ramalu, S. (2011). Students' satisfaction towards the university: Do service quality matter? International Journal of Education, 3(2), 1-15. https://doi.org/10.5296/ije.v3i2.1065
  15. Douglas, J., Douglas, A., & Barnes, B. (2006). Measuring student satisfaction at a UK university, Quality Assurance in Education, 14(3), 251-267. https://doi.org/10.1108/09684880610678568
  16. Eurico, S. T., Da Silva, J. A. M., & Do Valle, P. O. (2015). A model of graduates' satisfaction and loyalty in tourism higher education: The role of employability. Journal of Hospitality, Leisure, Sport & Tourism Education, 16, 30-42. https://doi.org/10.1016/j.jhlste.2014.07.002
  17. Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50. https://doi.org/10.1177/002224378101800104
  18. Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate data analysis: A global perspective (7th ed.). Upper Saddle River, NJ: Pearson Education.
  19. Haw, J. (2018). Service quality improves students' evaluation of good teaching. Journal of Hospitality & Tourism Education, 30(3), 135-143. https://doi.org/10.1080/10963758.2018.1444492
  20. Hom, W. C. (2002). Applying customer satisfaction theory to community college planning of counseling services. https://files.eric.ed.gov/fulltext/ED481317.pdf
  21. Hu, L. T., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1-55. https://doi.org/10.1080/ 10705519909540118
  22. Indrajit, R. E., & Djokopranoto, R. (2006). Modern college management. Yogyakarta: Andi Offset.
  23. International Islamic University Chittagong (IIUC). (2018). IIUC history. https://www.iiuc.ac.bd/about/history#
  24. Joshi, P. (2019). The growth, roles, and needs of the private education system: Private stakeholder perspectives from Nepal. International Journal of Educational Development, 65, 57-67. https://doi.org/10.1016/j.ijedudev.2019.01.002
  25. Jung, N. Y., & Seock, Y. K. (2016). The impact of corporate reputation on brand attitude and purchase intention. Fashion and Textiles, 3(1), 1-15. https://doi.org/10.1186/s40691-016-0072-y
  26. Kotler, P., & Clarke, R. N. (1987). Marketing for health care organizations. Englewood Cliffs, NJ: Prentice Hall International Inc.
  27. Lawton, S. B. (1992). Why restructure? An international survey of the roots of reform. Journal of Education Policy, 7(2), 139-154. https://doi.org/10.1080/0268093920070202
  28. Le, H. Q. (2020). Factors affecting students' decision to select private universities in Vietnam. Journal of Asian Finance, Economics, and Business, 7(4), 235-245. https://doi.org/10.13106/jafeb.2020.vol7.no4.235
  29. Liu, J., & Bray, M. (2020). Private subtractory tutoring the negative impact of shadow education on public schooling in Myanmar. International Journal of Educational Development, 76, 102213. https://doi.org/10.1016/j.ijedudev. 2020.102213
  30. Marzo, M. (2013). A new management element for universities: Satisfaction with the courses offered. International Journal of Educational Management, 19(6), 505-526. https://doi.org/10.1108/09513540510617454
  31. Meydan, C. H., & Sesen, H. (2011). Structural equation modeling AMOS applications. Ankara: Detay Publishing.
  32. Mulyono, H., Hadian, A., Purba, N., & Pramono, R. (2020). Effect of service quality toward student satisfaction and loyalty in higher education. Journal of Asian Finance, Economics, and Business, 7(10), 929-938. https://doi.org/10.13106/jafeb.2020.vol7. no10.929
  33. Nadiri, H., Kandampully, J., & Hussain, K. (2009). Students' perceptions of service quality in higher education. Total Quality Management, 20(5), 523-535. https://doi.org/10.1080/14783360902863713
  34. Nguyen, Q. L. H. T. T., Nguyen, D. V., Chu, N. N. M., & Tran, V. H. (2020). Application of total quality management in developing quality assessment model: The case of Vietnamese higher education. Journal of Asian Finance, Economics, and Business, 7(11), 1049-1057. https://doi.org/10.13106/jafeb.2020.vol7.no11.1049
  35. Nunnally, J. C. (1994). Psychometric theory (3rd ed.). New Delhi: Tata McGraw-HillEducation.
  36. Oldfield, B. M., & Baron, S. (2000). Student perceptions of service quality in a UK university business and management faculty. Quality Assurance in Education, 8(2), 85-95. https://doi.org/10.1108/09684880010325600
  37. Owlia, M. S., & Aspinwall, E. M. (1996). A framework for the dimensions of quality in higher education. Quality Assurance in Education, 4(2), 12-20. https://doi.org/10.1108/09684889610116012
  38. Palacio, A. B., Meneses, G. D., & Perez, P. J. P. (2002). The configuration of the university image and its relationship with the satisfaction of students. Journal of Educational Administration, 40(5), 486-505. https://doi.org/10.1108/09578230210440311
  39. Parasuraman, A., Zeithaml, V. A., & Berry, L. L. (1985). A conceptual model of service quality and its implications for future research. Journal of Marketing, 49(4), 41-50. https://doi.org/10.1177/002224298504900403
  40. Parasuraman, A., Zeithaml, V. A., & Berry, L. L. (1988). Servqual: A multiple-item scale for measuring consumer perceptions of service quality. Journal of Retailing, 64(1), 12-37. https://edisciplinas.usp.br/pluginfile.php/2220966/mod_folder/content
  41. Pedro, E., Mendes, L., & Lourenco, L. (2018). Perceived service quality and student's satisfaction in higher education: The influence of teaching methods. International Journal for Quality Research, 12(1), 165-192. https://doi.org/10.18421/IJQR12.01-10
  42. Rahman, S., Mia, M., Ahmed, F., Thongrak, S., & Kiatpathomchai, S. (2020). Assessing students' satisfaction in public universities in Bangladesh: An empirical study. Journal of Asian Finance, Economics, and Business, 7(8), 323-332. https://doi.org/10.13106/jafeb.2020.vol7.no8.323
  43. Sahney, S., Banwet, D. K., & Karunes, S. (2004). A SERVQUAL and QFD approach to total quality education. International Journal of Productivity and Performance Management, 53(2), 143-166. https://doi.org/10.1108/17410400410515043
  44. Santos, G., Marques, C. S., Justino, E., & Mendes, L. (2020). Understanding social responsibility's influence on service quality and student satisfaction in higher education. Journal of Cleaner Production, 256, 120597. https://doi.org/10.1016/j.jclepro.2020.120597
  45. Selnes, F. (1993). An examination of the effect of product performance on brand reputation, satisfaction, and loyalty. European Journal Marketing, 27(9), 19-35. https://doi.org/10.1108/03090569310043179
  46. Sharabi, M. (2013). Managing and improving service quality in higher education. International Journal of Quality and Service Sciences, 5(3), 309-320. https://doi.org/10.1108/IJQSS-03-2013-0016
  47. Sohail, M. S., Rajadurai, J., & Rahman, N. A. A. (2003). Managing quality in higher education: A Malaysian case study. International Journal of Educational Management, 17(4), 141-146. https://doi.org/10.1108/09513540310474365
  48. Tabachnick, B. G., Fidell, L. S., & Ullman, J. B. (2007). Using multivariate statistics. Boston, MA: Pearson.
  49. Tran, V. D., & Bui, V. L. C. (2020). Factors Influencing the Decision of Vietnamese Students to Study English in the Philippines. Journal of Asian Finance, Economics, and Business, 7(11), 595-606. https://doi.org/10.13106/jafeb.2020.vol7.no11.595
  50. Wilkinson, R., & Yussof, I. (2005). Public and private provision of higher education in Malaysia: A comparative analysis. Higher Education, 50(3), 361-386. https://doi.org/10.1007/s10734-004-6354-0
  51. Yousapronpaiboon, K. (2014). SERVQUAL: Measuring higher education service quality in Thailand. Procedia-Social and Behavioral Sciences, 116, 1088-1095. https://doi.org/10.1016/j.sbspro.2014.01.350
  52. Zeithaml, V. A., Berry, L. L., & Parasuraman, A. (1996). The behavioral consequences of service quality. Journal of Marketing, 60(2), 31-46. https://doi.org/10.1177/002224299606000203
  53. Zhang, J., Wang, J., Min, S. D., Chen, K. K., & Huang, H. (2016). Influence of curriculum quality and educational service quality on student experiences: A case study in sport management programs. Journal of Hospitality, Leisure, Sport & Tourism Education, 18, 81-91. https://doi.org/10.1016/j.jhlste.2016.04.001

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