students’ perceptions of service quality in higher education

Total Quality ManagementVol. 20, No. 5, May 2009, 523 – 535

Students’ perceptions of service quality in higher educationHalil Nadiria, Jay Kandampullyb and Kashif Hussainc

aDepartment of Business Administration, Eastern Mediterranean University, PO Box 95Gazimag˘ usa, North Cyprus, Via Mersin-10, Turkey; bDepartment of Consumer Sciences, TheOhio State University, USA; cInstitute of Educational Sciences, Near East University, Lefkosa, North Cyprus, Via Mersin-10, Turkey

This study aims to diagnose the applicability of the perceived service quality measurement scale to students; and to diagnose the student satisfaction level in higher education. It attempts to diagnose the perceived service quality of administrative units such as services provided by the registrar, library, faculty/ school offices, rector office, dormitories, sports and health centre. Descriptive and causal analysis is employed. Reliability and dimensionality of the scale is tested. Results indicate that the nature of perceived service quality measurement instrument is found to be two-dimensional: tangibles and intangibles for higher education services. The results and implications are discussed in detail.

Keywords: perceived service quality; student satisfaction; higher education

IntroductionHigher education is a fast growing service industry and every day it is more and more exposed to globalisation processes (Damme, 2001; O’Neil & Palmer, 2004). Service quality, emphasising student satisfaction, is a newly emerging field of concern. In order to attract students, serve their needs and retain them, higher education providers are actively involved in understanding students’ expectations and perceptions of service quality. They often need to adapt techniques of measuring the quality of their services just like in the business sector. Most conceptual frameworks for measuring service quality are based on marketing concepts (Gummesson, 1991). These frameworks measure quality through customer perceptions (Gro¨ nroos, 1984), customer expectations having a substantial influence on these perceptions. It is argued that only criteria defined by customers count in measuring quality (Zeithaml et al., 1990).

According to Hennig-Thurau et al. (2001, p. 332), educational services ‘fall into the field of services marketing’. Owing to the unique characteristics of services, namely intangibility, heterogeneity, inseparability and perishability (Parasuraman, 1986), service quality cannot be measured objectively (Patterson & Johnson, 1993). In the services literature, the focus is on perceived quality, which results from the comparison of customer service expectations with their perceptions of actual performance (Zeithaml et al., 1990).

During the last decade, quality initiatives have been the subject of an enormous amount of practitioner and academic discourse, and at various levels have found a gateway into

Corresponding author. Email: [email protected]

ISSN 1478-3363 print/ISSN 1478-3371 online# 2009 Taylor & Francis

DOI: 10.1080/14783360902863713 http://www.informaworld.com

524 H. Nadiri et al. Total Quality Management 524

higher education (Avdjieva & Wilson, 2002). Student satisfaction is often used to assess educational quality, where the ability to address strategic needs is of prime importance (Cheng, 1990). The conceptualisation of service quality, its relationship to the satisfaction and value constructs and methods of evaluation, have been a central theme of the education sector over recent years (Oldfield & Baron, 2000; Soutar & McNeil, 1996). Measuring the quality of service in higher education is increasingly important (Abdullah,2006).

In general, service quality promotes customer satisfaction, stimulates intention to return, and encourages recommendations (Nadiri & Hussain, 2005). Customer satisfaction increases profitability, market share and return on investment (Barsky & Labagh, 1992; Fornell, 1992; Hackl & Westlund, 2000; Halstead & Page, 1992; LeBlanc, 1992; Legoherel, 1998; Stevens et al., 1995). The higher education sector should recognise the importance of service improvements in establishing a competitive advantage.

The importance of quality in the service industry has attracted many researchers to empirically examine service quality within a wide array of service settings such as appliance repair, banking, hotels, insurance, long-distance telephone (Parasuraman et al.,1985; Zeithaml et al., 1990). Today, controversy continues concerning how service quality should be measured (Cronin & Taylor, 1992, 1994; Parasuraman et al., 1988,1991, 1994). One of the most controversial issues is the reliability of SERVQUAL: ascale developed to measure service quality by Parasuraman et al. (1985). SERVQUAL has been used to measure service quality in business schools (Carman, 1990), banking, dry cleaning, fast food services (Cronin & Taylor, 1992) and in many other institutions. Carman (1990) analysed the five dimensions of SERVQUAL by adding attributes that are pertinent to different situations, such as the fact that the failure rate is higher for colleges and universities than for either business or government organisations (Cameron & Tschirhart, 1992). In measuring service quality in higher education, it is important to study the meaning of service quality that relates to the situation under study. In service literatures, analyses of the practical basis of service quality measurement have been conducted on the definitions of quality in higher education (Lagrosen et al., 2004), service quality dimensions (Joseph & Joseph, 1997; Lagrosen et al., 2004; Owlia & Aspinwall,1996), perceived importance (Ford et al., 1999), service quality and customer satisfaction(Rowley, 1997). The intention of this study is to provide a practical basis for service quality measurement in the area of higher education of the island of Cyprus, especially for North Cyprus.

Harvey (2003, p. 4) notes that ‘it is not always clear how views collected from students fit into institutional quality improvement policies and processes.’ Moreover establishing the conditions under which student feedback can give rise to improvement ‘is not an easy task’. Indeed, Ford et al. (1993) have pointed out that SERVQUAL might assess students’ perceptions as to the quality of their educational institutions, but not the education itself. According to Oldfield and Baron (2000), student perceptions of service quality in higher education, particularly of the elements not directly involved with content and delivery of course units, are researched using a performance-only adaptation of the SERVQUAL research instrument. Therefore, this study attempts to approach service quality of administrative units in general rather than academic issues, e.g. services provided by the registrar, library, faculty/school offices, rector office, dormitories, sports, health centre, etc. rather than teaching, course content or curriculum. Service quality measurement in this study contributes to overall quality of the higher education institutes. Thus, the purpose of the study is twofold: to diagnose the applicability of the perceived


service quality measurement scale to students and to diagnose the student satisfaction level in higher education.

Background of the studyIf service quality is to be improved, it must be reliably assessed and measured. According to the SERVQUAL model (Parasuraman et al., 1988), service quality can be measured by identifying the gaps between customers’ expectations of the service to be rendered and their perceptions of the actual performance of the service.

Parasuraman et al. (1988, p. 15) defined service quality as ‘a global judgment or attitude relating to the overall excellence or superiority of the service’ and they conceptu- alised a customer’s evaluation of overall service quality by applying Oliver’s (1980) disconfirmation model, as the gap between expectations and perception (gap model) of service performance levels. Furthermore, they propose that overall service quality performance could be determined by a measurement scale called ‘SERVQUAL’ that uses five generic dimensions:

(1) Tangibles – the physical surroundings represented by objects (for example, interior design) and subjects (for example, the appearance of employees);

(2) Reliability – the service provider’s ability to provide accurate and dependable services;

(3) Responsiveness – a firm’s willingness to assist its customers by providing fast and efficient service performance;

(4) Assurance – diverse features that provide confidence to customers (such as thefirm’s specific service knowledge; polite and trustworthy behaviour from employees); and

(5) Empathy – the service firm’s readiness to provide each customer with personalservice.

The development of the gap model by Parasuraman et al. (1985) opened new horizons to the understanding of service quality. Moreover, the measurement of the gap between customers’ expectation of service and perception of service received (gap 5) led to a fre- quently used and highly debated service quality instrument called the SERVQUAL scale. Parasuraman et al. (1985) argued that the most important gap is between customers’ expectations of service and their perception of the service actually delivered (gap 5). The other four gaps (1, 2, 3 and 4) are the major causes of gap 5. Thus, firms should try to close or narrow down the other four gaps first in order to manage gap 5.

The original SERVQUAL scale was composed of two sections. The first section contains 22 items for customer expectations of excellent firms in the specific service industry. The second contains 22 items, which measure consumer perceptions of service performance of a company being evaluated. The results from the two sections are then compared and used to determine the level of service quality. The SERVQUAL instrument has been widely used to measure service quality in various service industries. However, despite its popularity, it has received its share of criticism since its development. A con- siderable number of criticisms focused on the use of expectation as a comparison standard (e.g. Cronin & Taylor, 1994; Teas, 1994).

According to Parasuraman et al. (1985, 1991) the concept of expectation has been emphasised as a key variable in the evaluation of service quality. However, Teas (1994) points out that some validity problems arise when customer expectation is used as a comparison standard. For example, expectation is dynamic in nature and may change


according to customers’ experiences and consumption situations. Boulding et al. (1993) reject the use of expectation as a comparison standard for the measurement of service quality and recommend performance-only measurement.

The negative empirical findings concerning the measurement of expectations led to some doubt about its value. Some scholars maintain that measurement of expectations does not provide unique information for estimating service quality; they argue that performance-only assessment has already taken into account much of this information (Babakus & Boller, 1992; Cronin & Taylor, 1992). In general, previous studies would recommend that performance-only measurement is sufficient.

Thus SERVQUAL has not been without criticisms. Particular research efforts by Cronin and Taylor (1992) cast doubts about the validity of the disconfirmation paradigm advocated by Parasuraman et al. (1985, 1988). These authors questioned whether or not customers routinely assess service quality in terms of expectations and perceptions. They advance the notion that service quality is directly influenced only by perceptions of service performance. Accordingly, they developed an instrument of service performance (SERVPERF) that seems to produce better results than SERVQUAL (Asubonteng et al., 1996).

Another major criticism of the SERVQUAL scale, reported in the literature, is aboutits dimensionality problem. Several researchers (Carman, 1990; Cronin & Taylor, 1992; Parasuraman et al., 1985, 1988, 1991; Teas, 1994) argue that the number of dimensions and the nature of the SERVQUAL construct may be industry-specific. The fit of five dimensions of SERVQUAL carried out in different service activities has always been an important question in several studies that these dimensions proposed in SERVQUAL do not replicate. In many studies, the SERVQUAL scale has been found uni-dimensional (Angur et al., 1999; Babakus & Boller, 1992; Babakus & Mangold, 1992), sometimes two-dimensional (Ekinci et al., 2003; Karatepe & Avci, 2002) and sometimes with even10 dimensions (Carman, 1990). It has also been argued that a performance-only(SERVPERF) measure explains more of the variance in an overall measure of service quality than the SERVQUAL instrument (Cronin & Taylor, 1994).

Apart from the debate among the above researchers for the merits of SERVQUAL overSERVPERF and vice versa, it seems, however, that on balance the emerging literature supports the performance-based paradigm over the disconfirmation-based paradigm (Cronin & Taylor, 1994). This research builds on these conclusions and adapts the performance-based SERVPERF paradigm.

MethodologyThe sample of the study consists of students studying at Eastern Mediterranean University (EMU) located in Famagusta, North Cyprus. Students were selected according to non- probability convenience sampling method (Aaker et al., 1995). The management of the university was informed about the purpose of the study and after permission wad gained,600 questionnaires were distributed to students. Of these, 522 questionnaires were returned.In all, 492 questionnaires were found to be useful, which represents an 82% response rate from the original sample of 600. The survey was conducted in April 2007.

The questionnaire was based on only service perceptions. There were 24 items in all –22 items for measuring service perception of perceived service quality (adapted from Parasuraman et al., 1991), and two items for measuring student satisfaction. A pilot test study was conducted with 50 students. As a result of the pilot study, the instrument was


reworded for measuring perceived service quality for higher education. A five-point Likert scale (Likert et al., 1934) was used for data collection – with ‘1’ being ‘strongly


disagree’ and ‘5’ being ‘strongly agree’. Research shows that self-reported performance may lead to response bias. However, a meta-analytic review by Churchill et al. (1985) demonstrates that self-report measures do not necessarily lead to response bias. In addition, the survey was prepared according to the back-translation method (McGorry, 2000).

SPSS 10.0 for Windows was employed in order to access the particular results requiredfor the scale measurement. Descriptive analyses of means, standard deviation and frequen- cies were conducted. Reliability of the scale was tested; dimensionality of the scale was confirmed through an exploratory factor analysis; correlation analysis produced discriminant validity and regression analysis produced causal results.

FindingsDimensions of SERVPERFThe results of exploratory factor analysis demonstrated that the SERVPERF instrument failed to form its five assumed dimensions – tangibles, reliability, responsiveness, assurance and empathy. The results formed only two dimensions – tangibles and intangibles. This is discussed further below.

The sampleDemographic breakdown of the sample in Table 1 shows that 56.1% of the respondents were males. As for the age distribution, the majority of respondents fall between the age group of 21 – 25 (76.8%). With respect to the educational programme of study and faculties/schools of respondents, 82.3% of them were enrolled for undergraduate pro- grammes, 35.4% of them were from the faculty of engineering and 40.9% of respondents were second year students. About 25.6% of respondents had CGPA (Cumulative Grade- Point Average) 2.5 – 2.99. In terms of nationality, 41.5% respondents were Turkish Cypriots and 58.5% were from European, Asian and African countries (including Britain, Germany, Albania, Bosnia, Kosovo, Palestine, Turkey, Sudan, Jordan, Saudi Arabia, Oman, Pakistan, India, Bangladesh, Nigeria and Ghana).

Reliability and dimensionality of the scaleThe results in Table 2 proved that the overall reliability of the scale had an alpha coefficient of 0.96 – which is deemed acceptable (Churchill, 1979; Nunnally, 1978). Explora- tory factor analysis using varimax rotation was employed to explore the dimensionality in the dataset. The two factors – tangibles and intangibles – had cumulative variance63.93%, and all the factor loadings were found to be greater than 0.50 (Hair et al.,1979) – which demonstrates two distinct dimensions in the study. The Cronbach alphas for tangibles and intangibles were found to be 0.96 and 0.85 respectively at the aggregate level – which exceeds the minimum standard 0.70 (Churchill, 1979; Nunnally, 1978). It was necessary to measure the reliability and dimensionality of the scale to avoid criticism.

Distribution of SERVPERF values of studentsTable 3 demonstrates that students have relatively high perception scores (mean 4.20) related to EMU’s ‘neat-appearing employees’ (4.20), ‘safe transactions’ (4.27) and ‘convenient operating hours’ (4.29). However, the minimum perception scores (mean 4.00)


were about EMU’s ‘modern looking equipment’ (3.98), ‘materials associated with service’


Table 1. Demographic breakdown of the sample (n ¼ 492).

Frequency (F) Percentage (%)

GenderFemale 216 43.9Male 276 56.1Total 492 100.0Age20 and below 54 11.021 – 25 378 76.826 – 30 51 10.431 and above 9 1.8Total 492 100.0Programme of studyPreparatory school 21 4.3Undergraduate 405 82.3Graduate (Master’s/doctorate) 66 13.4Total 492 100.0Faculty of studyFaculty of architecture 24 4.9Faculty of arts and science 9 1.8Faculty of business and economics 69 14.0Faculty of communication and media studies 33 6.7Faculty of education 48 9.8Faculty of engineering 174 35.4Faculty of law 30 6.1School of foreign languages 21 4.3School of tourism and hospitality management 57 11.6School of computing and technology 27 5.5Total 492 100.0Educational year1st year 72 14.62nd year 201 40.93rd year 132 26.84th year 87 17.7Total 492 100.0CGPANo credits earned 24 4.91.99 or below 33 6.72.0 – 2.49 117 23.82.5 – 2.99 126 25.63.0 – 3.49 123 25.03.5 or above 69 14.0Total 492 100.0NationalityTurkish Cypriot 204 41.5Others (from European, Asian and African countries) 288 58.5Total 492 100.0

(3.99) and ‘personal attention given by employees’ (3.98), which means that EMU fails to maintain their modern looking equipment and materials associated with service, also employees of EMU need to be well trained to provide minimum satisfactory services. Overall results reveal that students are happy (4.16%) and satisfied (4.27%) with the services provided by EMU.


Table 2. Results of exploratory factor analysis.

Dimensions and % of Cumulative variance items Eigenvalue variance %

Factor loading

Cronbach alpha

Intangibles 12.59 57.22 57.22 a ¼ 0.96When you have a problem, EMU shows a sincere interest in solving it. 0.79Employees of EMU give you prompt service. 0.79EMU performs the service right the first time. 0.78Employees of EMU are never too busy to respond to your requests. 0.78Employees of EMU tell you exactly when services will be performed. 0.77Employees of EMU are always willing to help you. 0.77EMU insists on error-free records. 0.76EMU provides its services at the time it promises to do so. 0.73You feel safe in your transactions with EMU. 0.73When EMU promises to do something by a certain time, it does so. 0.72Employees of EMU have the knowledge to answer your questions. 0.72EMU has operating hours convenient to all its students. 0.72EMU gives you individual attention. 0.70Employees of EMU are consistently courteous with you. 0.70The behaviour of employees of EMU instils confidence in students. 0.67Employees of EMU understand your specific needs. 0.67EMU has employees who give you personal attention. 0.66EMU has your best interest at heart. 0.60Tangibles 1.48 6.71 63.93 a ¼ 0.85EMU’s physical facilities are visually appealing. 0.88EMU has modern looking equipment. 0.84EMU’s employees are neat in appearance. 0.71Materials associated with the service are visually appealing at EMU. 0.65

Notes:Kaiser-Meyer-Olkin measures of sampling adequacy: 0.94.Bartlett’s test of sphericity: 9191.87, p , 0.000.Principal component analyses with a varimax rotation.Overall reliability score: 0.96.

Correlations of the study variablesIn the present study correlation analysis was employed since ‘correlation analysis involves measuring the closeness of the relationship between two or more variables; it considers the joint variation of two measures’ (Churchill, 1995, p. 887). In Table 4, the results of correlation analysis are significant at the 0.01 level. When the correlation coefficients matrix between two constructs is examined, no correlation coefficient is equal to 0.90 or above. This examination provides support for the discriminant validity about this study, which means that all the constructs are different/distinct (Amick & Walberg,1975). It can be seen in Table 4 that all the means for each construct are in between2.00 and 4.25, which refers to quite low social desirability effect (response bias). It means that the respondents understood the question very well and avoided marking a favourable response.

Regression analysisRegression analysis is ‘the technique used to derive an equation that relates the criterion variables to one or more predictor variables; it considers the frequency distribution of the criterion variable, when one or more predictor variables are held fixed at various


Table 3. Distribution of SERVPERF values of students.

Tangibles

Perceptions mean (SD)

EMU has modern looking equipment. 3.98 (0.77) EMU’s physical facilities are visually appealing. 4.02 (0.81)EMU’s employees are neat in appearance 4.20 (0.87) Materials associated with the service are visually appealing at EMU. 3.99 (0.87)IntangiblesWhen EMU promises to do something by a certain time, it does so. 4.14 (0.84) When you have a problem, EMU shows a sincere interest in solving it. 4.19 (0.86)EMU performs the service right the first time. 4.12 (0.88) EMU provides its services at the time it promises to do so. 4.18 (0.82) EMU insists on error-free records. 4.17 (0.84)Employees of EMU tell you exactly when services will be performed. 4.16 (0.92) Employees of EMU give you prompt service. 4.16 (0.90)Employees of EMU are always willing to help you. 4.16 (0.91) Employees of EMU are never too busy to respond to your requests. 4.11 (0.93) The behaviour of employees of EMU instils confidence in students. 4.12 (0.86)You feel safe in your transactions with EMU. 4.27 (0.79) Employees of EMU are consistently courteous with you. 4.18 (0.87)Employees of EMU have the knowledge to answer your questions. 4.16 (0.82) EMU gives you individual attention. 4.18 (0.90) EMU has operating hours convenient to all its students. 4.29 (0.82)EMU has employees who give you personal attention. 3.98 (0.81) EMU has your best interest at heart. 4.10 (0.82) Employees of EMU understand your specific needs. 4.13 (0.85)Student satisfactionI am happy with the service quality of EMU. 4.16 (1.01) I am a satisfied student. 4.27 (0.94)

Note: SD: standard deviation; all the standard deviations are in parentheses.

levels’ (Churchill, 1995, p. 887). Table 5 shows that the regression analysis was used having ‘student satisfaction’ as the dependent variable and ‘tangibles’ and ‘intangibles’ as the independent variables. It was necessary to use the regression analysis to predict the student satisfaction level of EMU students and the obtained results showed that there was a positive correlation with a R2 of 0.64 and a ‘F’ value of 434.51 at a signifi- cance level of p , 0.001. Tangibles (b ¼ 0.20) and intangibles (b ¼ 0.97) both exert significant positive effect on student satisfaction. Moreover, tangibles and intangibles

Table 4. Correlations of the study variables.

Variables

Scale Tangibles Intangibles Student satisfaction

Tangibles 1.00Intangibles 0.73 1.00Student satisfaction 0.65 0.79 1.00

Mean 4.04 4.15 4.22Standard deviation 0.69 0.66 0.93

Note: All correlations are significant at the 0.01 level (2-tailed).


Table 5. Regression analysis.

Independent variable: Tangibles and intangiblesDependent variable: Student satisfaction

Independent variable ba t-value pb

Tangibles 0.20 3.69 0.001Intangibles 0.97 17.45 0.001

R2 ¼ 0.64F ¼ 434.51 p , 0.001

Note: aStandardised coefficient; bp , 0.05.

jointly explain 64% of the variance (R2) in the student satisfaction which is very good. Overall, the results indicate that tangibles and intangibles are predictors of student satisfaction.

Discussion and implicationsIn general, SERVQUAL is a measurement of service quality based on the difference between the customer’s expectations of the quality of service he/she will receive, and his or her perceptions of the service received. SERVPERF, in contrast, is a performance-only measurement of service quality (Zhou, 2004).

This study aimed to diagnose the applicability of the perceived service qualitymeasurement scale to students; and to determine the student satisfaction level in higher education. The findings of this study reveal that the SERVPERF scale successfully maintains its reliability. Hence, students’ evaluation of perceived service quality in higher education consists of two dimensions: tangibles and intangibles. Such results of this study are also supported with previous empirical studies in literature (Ekinci et al.,2003; Karatepe & Avci, 2002).

This study attempted to diagnose the perceived service quality of administrative units such as services provided by the registrar, library, faculty/school offices, rector office, dormitories, sports and health centre. The findings of this study are important for prac- titioners in the higher education sector.

Management implicationsThe results of this study have a number of practical implications for the higher education sector where authorities seek to identify the student satisfaction level in their particular institutes:

(1) First, the findings of this study are important for higher education authorities who should note that students are likely to become more demanding in terms of the level of service they consider to be satisfactory. It is obvious from the results that tangibles and intangibles are predictors of student satisfaction.

(2) Secondly, authorities should pay attention to the physical facilities of the university if they are to improve the quality of services for higher education. Students expect universities to have modern looking equipment and appealing materials associated with the service such as brochures, pamphlets, etc. Authorities should take into


account the inanimate service environment so as to enhance perceived service quality and achieve student satisfaction.

(3) Finally, authorities should ensure that employees are well trained and understand the level of service that the university expects to provide for its students. Employees should be able to show adequate personal attention to students. Ensuring that employees are well trained, and giving attention to other factors that are required for the provision of a high level of service quality might incur increased costs, but will provide improved student satisfaction. Thus, authorities are expected to allocate more financial resources for the human resource applications, revealing that recruiting and selecting the most suitable candidates for the vacant posts and training staff permanently that will result in qualified personnel being able to provide students with caring, individualised attention and convenient operating hours. The allocation of financial resources for the human resource applications will equip employees with a better understanding of service excellence.

Limitations and avenues for future researchThis research has certain limitations, and interpretation of its findings therefore needs to be undertaken with caution:

(1) First, the sample in this study is small and is limited to students studying at Eastern Mediterranean University. There are in total six universities in North Cyprus; other universities should also be included in the sample for further research on service quality in higher education.

(2) Second, many of the issues in service quality literature remain to be explored – forexample, how marketing strategies can be designed to manage perceived service quality and how the higher education sector can use the service quality concept to formulate marketing strategies effectively.

ConclusionThis study also provides higher education service quality researchers with useful guide- lines for future research that would result in more rigorous theoretical and methodological processes. The terms ‘student satisfaction’ and ‘quality’ have been central to higher education authorities’ philosophy, and their importance continues with the promise of a renewed, foreseeable prosperity for the higher education of the future. Nevertheless, higher education research has not, on the whole, developed any substantive theories and innovations. Partial responsibility for this lies in the method-driven research traditions of the past. Therefore, using the SERVPERF scale, one of the apparent implications of this study turns out to be that higher education authorities should improve their service level and should update the structure of their available physical facilities. Also, the use of the SERVPERF scale to measure the service quality provides diagnostic capability about the level of service performance from the students’ perspective. Thus, the use of SERVPERF provides useful information to higher education authorities for developing quality improvement strategies. This study also supports the argument in the literature that performance-only (SERVPERF) is the better predictor of service quality (Babakus& Boller, 1992; Boulding et al., 1993; Cronin & Taylor, 1992). In general, this study also recommends that the SERVPERF measurement is sufficient.

Total Quality Management 533533 H. Nadiri et al.

ReferencesAaker, D.A., Kumar, V., & Day, G.S. (1995). Marketing research (5th ed.). New York: John Wiley. Abdullah, F. (2006). Measuring service quality in higher education: Three instruments compared.

International Journal of Research & Method in Education, 29(1), 71–89.Amick, D.J., & Walberg, H.J. (1975). Introductory multivariate analysis. Berkeley, CA: McCutchan. Angur, M.G., Nataraajan, R., & Jahera, J.S., Jr. (1999). Service quality in the banking industry: An

assessment in a developing economy. Journal of Services Marketing, 13(2), 132–150.Asubonteng, P., McCleary, K.J., & Swan, J.E. (1996). SERVQUAL revisited: A critical review of

service quality. Journal of Services Marketing, 10(6), 62–81.Avdjieva, M., & Wilson, M. (2002). Exploring the development of quality in higher education.

Managing Service Quality, 12(6), 372–383.Babakus, E., & Boller, G.W. (1992). An empirical assessment of SERVQUAL scale. Journal of

Business Research, 24(3), 253–268.Babakus, E., & Mangold, G.W. (1992). Adapting the SERVQUAL scale to hospital services: An

empirical investigation. Health Services Research, 26(6), 767–786.Barsky, J.D., & Labagh, R. (1992). A strategy for customer satisfaction. Cornell Hotel and

Restaurant Administration Quarterly, 35(3), 32–40.Boulding, W., Kalra, A., Staelin, R., & Zeithaml, V.A. (1993). A dynamic process model of service

quality: From expectations to behavioral intentions. Journal of Marketing Research, 30(1),7–27.

Cameron, K.S., & Tschirhart, M. (1992). Postindustrial environments and organizational effectiveness in colleges and universities. Journal of Higher Education, 63(1), 87–108.

Carman, J.M. (1990). Consumer perceptions of service quality: An assessment of the SERVQUALdimensions. Journal of Retailing, 66(1), 33–35.

Cheng, Y.C. (1990). Conception of school effectiveness and models of school evaluation: A dynamic perspective. Education Journal, 18(1), 47–62.

Churchill, A.G. (1979). A paradigm for developing better measures of marketing constructs. Journal of Marketing Research, 16(1), 64–73.

Churchill, A.G. (1995). Marketing research: Methodological foundations (6th ed.). New York: Dryden Press.

Churchill, G.A., Jr., Ford, N.M., Hartley, S.W., & Walker, O.C., Jr. (1985). The determinants of salesperson performance: A meta-analysis. Journal of Marketing Research, 22(2), 103–118.

Cronin, J.J., & Taylor, S.A. (1992). Measuring service quality: A reexamination and extension.Journal of Marketing, 56(3), 55–68.

Cronin, J.J., & Taylor, S.A. (1994). SERVPERF versus SERVQUAL: Reconciling performance- based and perceptions-minus-expectations measurement of service quality. Journal ofMarketing, 58(1), 125–131.

Damme, D. (2001). Quality issues in the internationalization of higher education. Higher Education,41(4), 415–441.

Ekinci, Y., Prokopaki, P., & Cobanoglu, C. (2003). Service quality in Cretan accommodations: Marketing strategies for the UK holiday market. International Journal of HospitalityManagement, 22(1), 47–66.

Ford, J.B., Joseph, M., & Joseph, B. (1993). Service quality in higher education: A comparison of universities in the United States and New Zealand using SERVQUAL. In Enhancing knowledgedevelopment in marketing: Proceedings of the American Marketing Association Annual

Summer Educators’ Conference (pp. 75 – 81). Boston, MA: American Marketing Association. Ford, J.B., Joseph, M., & Joseph, B. (1999). Importance-performance analysis as a

strategic tool forservice marketers: The case of service quality perceptions of business students in NewZealand and the USA. Journal of Services Marketing, 13(2), 171–186.

Fornell, C. (1992). A national customer satisfaction barometer: The Swedish experience. Journal ofMarketing, 56(1), 6–21.

Gro¨ nroos, C. (1984). A service quality model and its marketing implications. European Journal ofMarketing, 18(4), 36–44.

Gummesson, E. (1991). Truths and myths in service quality. Journal for Quality and Participation,14(4), 28–33.

Hackl, P., & Westlund, A.H. (2000). On structural equation modelling for customer satisfaction measurement. Total Quality Management, 11(4/5/6), 820–825.


Hair, J.F., Anderson, R.E., Tatham, R.L., & Grablowsky, B.J. (1979). Multivariate data analysis with readings. Tulsa, OK: Petroleum Publishing Company.

Halstead, D., & Page, T.J., Jr. (1992). The effects of satisfaction and complaining behaviour on consumers’ repurchase behaviour. Journal of Satisfaction, Dissatisfaction and Complaining Behaviour, 5(1), 1–11.

Harvey, L. (2003). Editorial: Student feedback. Quality in Higher Education, 9(1), 3–20.Hennig-Thurau, T., Langer, M.F., & Hansen, U. (2001). Modeling and managing student loyalty:

An approach based on the concept of relationship quality. Journal of Service Research, 3(4),331–344.

Joseph, M., & Joseph, B. (1997). Service quality in education: A student perspective. QualityAssurance in Education, 5(1), 15–21.

Karatepe, O.M., & Avci, T. (2002). Measuring service quality in the hotel industry: Evidence from northern Cyprus. Anatolia: An International Journal of Tourism and Hospitality Research,13(1), 19–32.

Lagrosen, S., Sayyed-Hashemi, R., & Leitner, M. (2004). Examination of the dimensions of quality in higher education. Quality Assurances in Education, 12(2), 61–69.

LeBlanc, G. (1992). Factors affecting customer evaluation of service quality in travel agencies: Aninvestigation of customer perceptions. Journal of Travel Research, 30(4), 10–16.

Legoherel, P. (1998). Quality of tourist services: The influence of each participating component on the consumer’s overall satisfaction regarding tourist services during a holiday. In Proceedingsof the Third International Conference on Tourism and Hotel Industry in Indo-China and Southeast Asia: Development, Marketing and Sustainability (pp. 47–54). Phuket: National Publishing Inc.

Likert, R., Roslow, S., & Murphy, G.A. (1934). A simple and reliable method of scoring the turnstone attitude scales. Journal of Social Psychology, 5(1), 228–238.

McGorry, S.Y. (2000). Measurement in a cross-cultural environment: Survey translation issues.Qualitative Market Research: An International Journal, 3(2), 74–81.

Nadiri, H., & Hussain, K. (2005). Perceptions of service quality in North Cyprus hotels.International Journal of Contemporary Hospitality Management, 17(6), 469–480.

Nunnally, J.C. (1978). Psychometric theory. New York: McGraw-Hill.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.Oliver, R.L. (1980). A cognitive model of the antecedents and consequences of satisfaction

decisions. Journal of Marketing Research, 17(4), 460–469.O’Neil, M.A., & Palmer, A. (2004). Importance-performance analysis: A useful tool for directing

continuous quality improvement in higher education. Quality Assurance in Education,12(1), 39–52.

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.

Parasuraman, A. (1986). Customer-orientated organizational culture: A key to successful servicesmarketing. In M. Venkatesan, D.M. Schmalensee, & C. Marshall (Eds.), Creativity in services marketing: What’s new, what works, what’s developing (pp. 73–77). Chicago: American Marketing Association.

Parasuraman, A., Berry, L.L., & Zeithaml, V.A. (1991). Refinement and reassessment of theSERVQUAL scale. Journal of Retailing, 67(4), 420–450.

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.

Parasuraman, A., Zeithaml, V.A., & Berry, L.L. (1988). SERVQUAL: A multiple-item scale formeasuring consumer perceptions of service quality. Journal of Retailing, 64(1), 12–40.

Parasuraman, A., Zeithaml, V.A., & Berry, L.L. (1994). Alternative scales for measuring servicequality: A comparative assessment based on psychometric and diagnostic criteria. Journalof Retailing, 70(41), 201–203.

Patterson, P.G., & Johnson, L.W. (1993). Disconfirmation of expectations and the gap model of service quality: An integrated paradigm. Journal of Satisfaction, Dissatisfaction andComplaining Behavior, 6(1), 90–99.

Rowley, J. (1997). Beyond service quality dimensions in higher education and towards a service contracts. Quality Assurance in Education, 5(1), 7–14.


Soutar, G., & McNeil, M. (1996). Measuring service quality in a tertiary institution. Journal ofEducational Administration, 34(1), 77–82.

Stevens, P., Knutson, B., & Patton, M. (1995). DINESERV: A tool for measuring service quality in restaurants. The Cornell Hotel and Restaurant Administration Quarterly, 36(2), 56–60.

Teas, K.R. (1994). Expectations as a comparison standard in measuring service quality: An assess-ment of a reassessment. Journal of Marketing, 58(1), 132–139.

Zeithaml, V., Parasuraman, A., & Berry, L. (1990). Delivering quality service: Balancing customer perceptions and expectations. New York: The Free Press.

Zhou, L. (2004). A dimension-specific analysis of performance only measurement of service quality and satisfaction in China’s retail banking. Journal of Services Marketing, 18(7), 534–546

students’ perceptions of service quality in higher education

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