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Chan, C., Entrekin, L. & Anderson, C. (2003). Psychometric Assessment of the Perception of Service Quality, Research and Practice in Human Resource Management, 11(1), 65-74.

Psychometric Assessment of the Perception of Service Quality

Christopher Chan & Lanny Entrekin & Chen Anderson


An intensification of competition in the health care industry is challenging hospital administrators to ensure the provision of quality service. The development of SERVQUAL by Parasuraman, Zeithaml and Berry (1988) gives academicians and practitioners an opportunity to assess service quality provided by an organisation. However, there is considerable debate about the psychometric properties of SERVQUAL. Consequently, this study explores the efficacy of SERVQUAL in an Australian health care provider context. Research results suggest a robust five-factor solution, and the implications for this study are discussed.


Increased levels of competition have compelled many health care organisations in industrialised countries to learn how to differentiate themselves (McAlexander, Kaldenberg & Koenig 1994, Kaldenberg, Becker, Browne & Browne 1997), and consequently, assessments of service quality have become critical for hospitals. In fact, Hurst, Crocker and Bell (1994) indicate a hospital’s success often rests upon its reputation to deliver quality services. One instrument that has been developed to measure service quality is SERVQUAL (Parasuraman et al. 1988), which is based on the difference between expectations of service quality and perceptions of service quality. Consequently, there is fervent research attention on the psychometric properties and application of SERVQUAL in the health care setting (Headley & Miller 1993, Vandamme & Leunis 1993, Walbridge & Delene 1993, McAlexander et al. 1994, Lam 1997). Nevertheless, the studies are predominantly American (Swan & Koehler 1994, Anderson 1995, Youssef, Nel & Bovaird 1995, Bowers, Dean 1999, O’Connor, Trinh & Shewchuck 2000, Duffy, Duffy & Kilbourne 2001) and European (Sargeant & Kaehler 1998). Thus, an exploration of the efficacy of SERVQUAL in the Australian health care sector is warranted and may provide hospital administrators with a potentially useful tool for assessing quality.

Although SERVQUAL is a popular tool for measuring service quality, the psychometric properties of the instrument are yet to be established. On the one hand, SERVQUAL was found to be reliable in estimating quality of service in the five dimensions of tangibles, reliabilities, responsiveness, assurance and empathy (Parasuraman et al. 1988, Parasuraman, Berry & Zeithaml 1991). On the other hand, critics (Carman 1990, Babakus & Boller 1992, Brown, Cronin & Taylor 1992, Babakus 1993, Churchill & Peter 1993, 1994, Teas 1993, 1994, Lam & Woo 1997) have questioned the conceptual foundation and psychometric properties of the SERVQUAL scale. For instance, Finn and Lamb (1991) have argued that the generic nature of the instrument may not be appropriate for any service and some adaptation of the items may be needed. Furthermore, Babakus and Mangold (1992), Carman (1990), and Orwig, Pearson and Cochran (1997) have failed to replicate the five factors of SERVQUAL and have suggested that the items represent only one factor rather than five. Several researchers (Cronin & Taylor 1992, Brown et al. 1993) have pinpointed the calculation of a difference score (expectation of service quality minus perception of service quality) in the SERVQUAL measure can result in psychometric problems and customers overstating their expectations because of prior bad experience with the organisation (Clow & Vorhies 1993). As a result, a few scholars (Shewchuk, O’Connor & White 1991, Taylor & Cronin 1994) have suggested the use of either the expected or perception scale, but not the difference between them. There is a possibility that SERVQUAL is context relevant, and an inspection of the validity and reliability of the instrument in this study has considerable relevance to the development of SERVQUAL.

In spite of these debates over the use of SERVQUAL to measure service quality, recent research endeavours (Jiang, Klein & Crampton 2000, Jiang, Klein & Carr 2002) have supported the findings of Parasuraman et al. (1988, 1991). This research attempts to evaluate the feasibility of utilising SERVQUAL in a hospital setting. Recognising the unceasing debate about SERVQUAL and the lack of reported evidence of the efficacy of SERVQUAL in Australian hospitals, it was considered appropriate and timely to reassess the dimensionality of the instrument using factor and reliability analyses, which signified a replication and extension of previous studies.



Respondents in the study were 189 staff members from various departments of a medium size Australian hospital. Staff members were surveyed for this study, as a few researchers (Blanchard & Galloway 1994, McCormack 1994) have sought to better understand service quality from the perspective of staff members as opposed to sampling customers solely. Hence, instead of sampling customers (in this case, patients), this study provides a departure by sampling internal staff to investigate the efficacy of SERVQUAL in a hospital setting. Important lessons could be drawn from the use of a different group. The organisation is an incorporated, private, metropolitan, and non-teaching hospital that has a 250-bed capacity. A prominent feature of the sample characteristics was that a majority of the respondents were female, reflecting the traditional nature of the hospital industry (Pearson & Duffy 1998). The second feature of the sample was related to job function. Specifically, nurses and administrative staff made up a majority of the hospital workforce, and indeed, a further feature of job function was that over 90 per cent of these incumbents were in the category of nurses and administrative staff. The third feature was most of the staff had formal educational qualifications, which illustrates the importance of education in the hospital industry. A final feature of the sample was that all age groups were well represented. Table 1 summarises the demographic profile of the sample.

Table 1
Demographics % (n = 189)
Gender Job Function/Category Educational Background Age (in years)
Female84.1 Executive3.2 Secondary schooling18.0 20-2915.3
Male15.9 Manager14.8 College/Certificate/Diploma37.0 30-3926.5
Supervisor2.6 Bachelor degree26.5 40-4935.4
Nurse47.2 Postgraduate14.8 Above 4922.8
Patient care assistant11.6 Hospital-based training3.7
Administration/clerical staff13.2
Other (few doctors, securities)7.4


Service quality was measured with SERVQUAL (Parasuraman et al. 1991). SERVQUAL is a twenty two-item instrument that is traditionally used for measuring customers’ perceptions of service quality. The instrument has five scales: tangibles, reliability, responsiveness, assurance, and empathy, and the respondents indicated their level of agreement on a seven-point Likert scale ranging from ‘strongly disagree’ (1) to ‘strongly agree’ (7). The measure is based on evaluating the difference between customers’ expectation and the perception of service they have received (Grönroos 1984, Parasuraman, Berry & Zeithaml 1993). Although the use of subjective measures for performance has been heavily criticised, because of the subjective nature and potential bias of self-report measures (Rich, Bommer, MacKenzie, Podsakoff & Johnson 1999, Tafarodi, Milne & Smith 1999), Dess and Robinson (1984) have argued in the absence of other objective criteria self evaluations could serve as appropriate and reliable alternative indicators. In order to avoid the potential occurrence of customers overstating their expectations, due to of prior bad experiences (Clow & Vorhies 1993), only the set of items relating to performance was used.


A proposal with an expression of interest to undertake research at the hospital and a sample questionnaire were sent to the hospital’s Quality Coordinator (QC). Subsequently, issues regarding the measures, confidentiality, and sampling were discussed during the meetings with the QC. The hospital was willing to participate in this research to obtain feedback on the research findings of this study. Further refinements of the survey instruments, such as using the term ‘This hospital’ instead of ‘This organisation,’ were undertaken before administering the questionnaire to hospital personnel. The respondents were drawn from all hospital staff - nurses, managers, patient care assistants, professions allied to health, administration and clerical workers. In total 700 questionnaires were administered by the Quality Unit of the hospital and staff were given one week to complete the questionnaires. Completed questionnaires were returned to a designated box (in the hospital) in the envelopes provided. A total of 189 completed questionnaires were returned, generating an overall response rate of 27.0 per cent. Although the response rate was slightly lower than other health care studies in Australia (Abernethy 1996, Pearson & Duffy 1998, Dawson, Brown, Gunn, McNair & Lumley 2000, Duffy & Chan 2001), under the circumstance the response rate was acceptable because the staff may have been fatigued from extensive in-house surveys, resulting in a lower than expected response rate.


An exploratory factor analysis (EFA) of the factor structure of SERVQUAL was undertaken with SPSS Version 9.0 to examine the construct validities of the variables. The EFA procedure employed principal components method for extraction, Varimax rotation, and factors with eigenvalues greater than one were retained (Hair, Anderson, Tatham & Black 1998). Given that the sample size is 189, Hair et al. (1998) suggested that conservative factor loadings of greater than .40 were to be considered significant at the .05 level. Once the dimensionalities of the instruments were verified, the internal consistencies of the scales were checked with reliability analyses.

The reliability for the SERVQUAL scale was estimated using Cronbach alpha coefficient (Cronbach 1951). Nunnally’s (1978) seminal work has been widely chosen for estimating the reliability of multiitem scales. Generally, items were retained in the scale when the item-to-total correlation was at least .35, when there was at least three items in the scale, and a coefficient alpha value in the order of .70 was obtained (Nunnally 1978). Although tangibles had a Cronbach alpha value of .67, elimination of items did not improve the reliability. As this reliability value was near the acceptable threshold of .70, and the four items that made up tangibles had item-to-total correlations of above .35, all items were retained. The other four dimensions of reliability, responsiveness, assurance, and empathy had itemto-total correlation of at least .35 and Cronbach alpha values of above .70. One item from the dimension of assurance loaded highly onto the dimension of reliability, which indicates this item (Employees get adequate support from the hospital to do their jobs well) is perceived by the respondents to be assessing the construct of reliability. An elimination of the cross-loaded item produced further cross-loading complications, and this item was, subsequently, retained. Therefore, a re-analysis of the internal consistency of reliability and assurance was necessary, with reliability as a six-factor construct and assurance as a three-factor construct. The final Cronbach alpha values of the five factors include .67 for tangibles, .88 for reliability, .75 for responsiveness, .83 for assurance, and .85 for empathy. Table 2 shows factor loadings for each item and also the eigenvalues, percentage of variance explained, and cumulative percentage of variance explained. The factor loading patterns for SERVQUAL items and Cronbach alpha values for the constructs supported a five-factor solution. The final result was a 21-item perception of service quality scale. Items measuring the dimension of reliability loaded onto Factor 1. Factors 2, 3, 4 and 5 were empathy, assurance, tangibles and responsiveness; respectively.

Table 2
Principal Components Factor Structure of SERVQUAL Items
1 2 3 4 5
Eigenvalue 8.28 1.73 1.58 1.50 1.23
Percentage of variance explained 37.65 7.84 7.16 6.82 5.61
Cumulative percentage of variance explained 37.65 45.49 52.65 59.47 65.08
The hospital has up-to-date equipment. .16 .12 -.03 .60 .06
The hospital’s physical facilities are visually appealing. .23 -.07 .13 .78 .00
The hospital’s employees are well dressed and appear neat. -.16 .31 .18 .68 .06
The appearance of the physical facilities of the hospital is consistent with the type of services provided. .28 -.02 .06 .68 .25
When the hospital promises to do something by a certain time, it does so. .60 .22 .31 .15 .28
When you have problems, the hospital is sympathetic and reassuring. .78 .23 .15 .08 .05
The hospital is dependable. .80 .20 .21 .27 .11
The hospital provides its services at the time it promises to do so. .72 .13 .16 .17 .22
The hospital keeps its records accurately. .64 .03 .22 .10 .20
The hospital does not tell customers exactly when services will be performed. .33 -.01 -.10 .04 .71
You do not receive prompt service from the hospital’s employees. .03 .25 .15 .13 .79
Employees of the hospital are not too busy to respond to customer requests promptly. .09 .39 .50 .10 .50
Employees of the hospital are too busy to respond to customer requests promptly. .23 .24 .22 .17 .64
You can trust employees of the hospital. .20 .09 .86 .00 .08
You feel safe in your transaction with the hospital employees. .32 .17 .79 .06 .11
Employees of the hospital are polite. .29 .09 .68 .27 .02
Employees get adequate support from the hospital to do their jobs well. .60 .39 .15 .16 .04
The hospital does not give you individual attention. .57 .52 .17 -.00 .14
Employees of the hospital do not give you personal attention. .26 .76 .29 .05 .15
Employees of the hospital do not know what your needs are. .23 .79 .22 .13 .06
The hospital does not have your best interests at heart. .57 .53 .10 .11 .14
The hospital does not have operating hours convenient to all their customers. .19 .70 -.10 .07 .28


Contribution to the debate about the feasibility of SERVQUAL (a scale developed by Parasuraman et al. 1988, 1991) to measure service quality is made by the results of this study. While some critics (Carmen 1990, Babakus & Mangold 1992, Orwig et al. 1997, Brady, Cronin & Brand 2002) argue the SERVQUAL instrument is uni-dimensional (after failing to replicate the five-factor structure) this instrument has also received considerable support as a fivefactor construct (Lam 1995a, 1995b). In response to the relentless debate about the feasibility of SERVQUAL in assessing quality of service provided by organisations, Shewchuk et al. (1991), and Taylor and Cronin (1994) have recommended the use of either the expected or perception scale, but not the difference between them. This study aimed to make a contribution to the existing literature on SERVQUAL by examining the efficacy of the perception section of SERVQUAL in a prominent Australian hospital.

An implication of this study involves the potential usefulness of SERVQUAL in assessing service quality in hospitals. The failure to provide quality health care is a major determinant of hospital failure and closure (Cleverly 1993). Consequently, a hospital’s success often rests upon the ability to deliver quality health care to its patients (Hurst et al. 1994), and a reliable measure of service quality is essential. The development of SERVQUAL by Parasuraman et al. (1991) has provided researchers and hospital managers an opportunity to assess service quality in the health care area. Traditionally, SERVQUAL is used for estimating customer satisfaction of a particular organisation’s products or services. Previous applications of SERVQUAL in health care settings have produced mixed results. On the one hand, Babakus and Mangold (1992: 780) have attested that “SERVQUAL is reliable and valid in the hospital environment.” On the other hand, Bowers et al. (1994) and Lam (1997) have found the generic nature of the SERVQUAL scale to be unsuitable for hospital settings. In the current study, hospital staff members, as internal customers, are asked to rate the service quality of their organisation. The results of psychometric assessments have shown that a modified approach could be applied to understand the quality of services offered by internal customers of the hospital. This finding is consistent with other studies in the health care industry (Babakus & Mangold 1992, Duffy et al. 2001), and thus adds to an emerging body of literature examining the psychometric properties of SERVQUAL (Van Dyke, Kappelman & Prybutok 1997, Llosa, Chandon & Orsingher 1998, Jiang et al. 2000). Indeed, the SERVQUAL instrument has considerable potential in providing health care providers with a perspective of their level of service quality, which can be incorporated into service design and planning process (Curry, Stark & Summerhill 1999).

There are several limitations regarding this study as well as opportunities for further research. First, the study evaluated the perception section of SERVQUAL. Perhaps future research endeavours can investigate the efficacy of the expectation section of SERVQUAL. Second, this research only provided support for the SERVQUAL instrument in an Australian hospital, and the literature on SERVQUAL could be enriched with investigations into other hospitals and different organisational settings. Future researchers could also compare the efficacy of SERVQUAL between patients and staff members.


This study assessed the efficacy of SERVQUAL as an instrument for assessing service quality in an Australian hospital. SERVQUAL was found to have acceptable validity and reliability, which means that the instrument has great potential in providing health care administrators with a perspective of their level of service quality. With increasing level of competition among health care providers, the provision of quality health care services is, without doubt, an important priority among hospital administrators.

A better understanding of measures for attaining best practice has consequences for HRM. Indeed, the study results have potential for hospital administrators to improve the quality of delivery of service. More generally, employees in the health industry are likely to demonstrate greater empathy to better health care practices when the relevant criteria are clearer to management and staff. Enhancing and consolidating effectiveness of the health care industry, which is a particularly important sector of any industrial society, is an imperative of HRM practitioners.


Dr. Christopher C. A. Chan is a lecturer in management at the Australian National University. His research interests include organisational learning, knowledge management, managerial work goals, cross-cultural management, and managerial practices.

Dr. Lanny Entrekin is an associate professor at the Murdoch Business School, Murdoch University. His research is in the area of human resource management, international management, and Asian business.

Chen Anderson is a national clinical risk coordinator at St John of God Health Care. Previously, she was a quality coordinator at St John of God Hospital in the Perth metropolitan area.


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