Content uploaded by Bahari Mohamed
Author content
All content in this area was uploaded by Bahari Mohamed on Nov 19, 2015
Content may be subject to copyright.
エシアン
エシアンエシアン
エシアン ゾロナル
ゾロナルゾロナル
ゾロナル オフ
オフオフ
オフ ソシルサエニセズ
ソシルサエニセズソシルサエニセズ
ソシルサエニセズ アンドヒオメニテズ
アンドヒオメニテズアンドヒオメニテズ
アンドヒオメニテズ
ISSN: 2186-8492, ISSN: 2186-8484 Pri nt
Vol. 2 No. 3 August 2013
(
) アンド
アンドアンド
アンド
ル
ルル
ル
小山市、
小山市、小山市、
小山市、
.
www. leena-luna.co.jp
P a g e | 307
THE EFFECTS OF PERCEIVED SERVICE QUALITY ON PATIENT
SATISFACTION AT A PUBLIC HOSPITAL IN STATE OF PAHANG,
MALAYSIA
Noor Azlinna Azizan1, Bahari Mohamed2
1 Faculty of Technology, Universiti Malaysia Pahang, Lebuhraya Tun Razak,
2 University College Shahputra, BIM Point, Bandar Indera Mahkota,
MALAYSIA.
1 azlinna@ump.edu.my, 2 baharimohd@yahoo.com
ABSTRACT
This study focuses on the effects of perceived service quality on patient satisfaction in
a public hospital. Data was collected from 109 respondents that experienced the
hospital service. Using a PLS-SEM tool, the hypothesized effects among the
constructs were tested empirically. No statistically significant relationships were
found between perceived service quality construct and (i) the hospital infrastructure
constructs and it did not support the hypothesis H1 (beta= 0.000 and t-value= 0.004,
05.0
>
ρ
) (ii) interaction with care providers construct and it did not support the
hypothesis H2 (beta= -0.045 and t-value= 0.443, 05.0
>
ρ
). However, the results
indicate that the path coefficients were significant between perceived service quality
construct and (iii) patients’ perception of administrative procedure construct and it
supported the hypothesis H3 (beta= 0.317, t-value= 3.026, 01.0
<
ρ
), (iv) patients‘
perception of medical care construct and it supported the hypothesis H4 (beta=
0.182, t-value= 2.150, 05.0
<
ρ
) and (v) patients’ perception of nursing care
construct and it supported the hypothesis H5 (beta= 0.481, t-value= 5.190, 01.0
<
ρ
). The constructs were considered the key factors that influence the perceived service
quality in the current study. The path coefficient from perceived service quality to
patient satisfaction was very significant and it supported the hypothesis H6 (beta=
0.816, t-value= 19.460, 01.0
<
ρ
). The antecedents of service quality demonstrated
considerable power in explaining variance in perceived service quality. The
infrastructure, interaction, administrative, medical care, and nursing care constructs
explained 69.7% ( 2
R
= 0.697) of the variance in perceived service quality and
overall the model explained 66.6% ( 2
R
=0.666) of the variance in patient
satisfaction. Therefore, it can be concluded that the model is suitable in determining
the health care service quality.
Keywords: Health care service, Perceived service quality, Patient satisfaction
INTRODUCTION
The hospital is an organization that provides a service. It is a complex service organization
and according to Rose, Uli, Abdul, and Ng (2004) it is “a true people-based service industry”.
The service involves a high degree of intangibility, inseparability of production and
consumption, highly interaction between customer and service provider, and is taking place at
the same time (Grönroos, 1998; Reeves & Bednar, 1994; Parasuraman et al. 1985). In order
to receive the service, a patient has to be present in the service process and the successful
delivery of health care service requires a patient’s cooperation both during and after the
ISSN: 2186-8492, ISSN: 2186-8484 Print
Vol. 2 No. 3 August 2013
ASIAN JOURNAL OF SOCIAL SCIENCES & HUMANITIES
www.ajssh.leena-luna.co.jp
308 | P a g e
Leena and Luna International, Oyama, Japan.
Copyright © 2013
encounter. Therefore, the hospital service quality is viewed as a very important factor that has
an effect on patient satisfaction (Dagger, Sweeney & Johnson, 2007).
This stud y was to evaluate the perceived service quality effects on patient satisfaction. In an
effort to understand the relationship between health care service qualities constructs, specific
question about the relationship of the service quality antecedents, the perceived service
quality, and the patient satisfaction has to be answered. The current study was addressing the
following main question to interpret the constructs. What were the effects of service quality
antecedents to the perceived service quality and consequently to the patient satisfaction with
the health care service?
Although much research has been conducted in health care service quality, however less
attention has been paid to examine the effect of service quality antecedents in relation to
perceived service quality and patient satisfaction. Therefore, further empirical research was
conducted to confirm the relationships between service quality antecedents and perceived
service quality, and the effect of perceived service quality on patient satisfaction.
LITERATURE REVIEW
The literature shows the service quality is complex processes and difficult to evaluate. It is
because high-involvement relationships and some services are high in credence qualities,
making customer evaluations complex and difficult. In the literature, it is generally accepted
view that there might be no universal quality construct that is applicable to all service
contexts. By referring to the situation, the integrated and hierarchical model has been
modified to be able to use in different context and settings (e.g., model by Dabholkar et al.
1996, Dabholkar et al., 2000, Brady & Cronin, 2001, Zineldin, 2006, and Dagger et al.,
2007). Thus, a comprehensive framework combining various aspects of existing frameworks
and models appears possible. Therefore, in the context of health care service quality, a
number of new dimensions of service quality have emerged.
The current study based on models developed by Dabholkar et al. (2000) and incorporating
many of relevant constructs and items of service quality identified in literature, which are
appropriate in the health care context. Dabholkar et al. (2000) proposed that constructs
relevant to service quality are, in fact, better conceived as its antecedents rather than the
individual dimensions. The model concept reflects the complexity and multidimensionality of
the service quality scale in the healthcare sector. The model based on established
relationships among service quality and patient satisfaction. However, in the context of health
care, service quality may influence by many factors. As such, the need to understand the
factors are very important, among them is the service quality antecedents.
Service Quality Antecedents
In the literature, factors contributing to service quality in health care service are complex and
there is no consensus among researchers. SERVQUAL scales developed by Parasuraman et
al. (1988) have offered significant advances to the understanding and measurement of
perceived service quality. Perceived health service quality has been studied widely in the
healthcare service sector and researchers have listed a range of antecedents that contribute to
perceived service quality (Andaleeb, 1998; Hasin et al., 2001; Zineldin, 2006; Duggirala et
al., 2008).
The most widely recognized framework for the healthcare service quality has been developed
by Donabedian (2005). The framework consists of structure, process, and outcome
dimensions. The structure which comprises of the attributes of the facilities, equipment,
personnel, and organization where care is provided; process which include activities that take
エシアン
エシアンエシアン
エシアン ゾロナル
ゾロナルゾロナル
ゾロナル オフ
オフオフ
オフ ソシルサエニセズ
ソシルサエニセズソシルサエニセズ
ソシルサエニセズ アンドヒオメニテズ
アンドヒオメニテズアンドヒオメニテズ
アンドヒオメニテズ
ISSN: 2186-8492, ISSN: 2186-8484 Pri nt
Vol. 2 No. 3 August 2013
(
) アンド
アンドアンド
アンド
ル
ルル
ル
小山市、
小山市、小山市、
小山市、
.
www. leena-luna.co.jp
P a g e | 309
place between care providers and the patients who receive care; and the outcome which is the
ultimate health conditions resulting from services provided (Donabedian, 2005). Studies have
shown that of the three categories of quality assessment, the process quality/functional
quality is the most directly and most relevant in healthcare service context (Choi et al., 2004).
Therefore, the process quality or functional quality delivered by doctors, nurses and other
healthcare service providers are an important factor in evaluating healthcare service quality.
After reviewing the available literature on the healthcare service quality, it is noted that
antecedent of service quality consists of technical quality and functional quality components.
The technical quality mostly refers to the quality of medical care and nursing care provided;
it refers to the basic technical accuracy and procedures, which is defined based on the
technical accuracy of the diagnosis and medical procedures or compliance with professional
specifications (Lam, 1997). The technical quality also refers to the efficiency of the staff as
they go perform their routine; which includes clinical and medical skills, familiarity with the
administration of drugs, nursing skills, and laboratory technicians’ competence in carrying
out tests on blood samples (Tomes & Ng, 1995). Functional quality is the process of care
provided; it refers to the way in which the services delivered to customers. Patients often rely
on functional aspects such as infrastructure, interaction, and administrative construct rather
than technical aspects when assessing the quality of healthcare service. According to Lam
(1997) patients base their evaluation of health care service quality on the quality of
interpersonal factors and the environmental factors, which the medical professional has been
regarded as less important.
Hence, the following paragraphs briefly discuss the antecedents of healthcare service quality
which include technical and functional quality. The antecedents are infrastructure,
interaction; administrative, medical care and nursing care which are related to perceived
service quality construct and then to patient satisfaction construct.
Infrastructure
The concept of infrastructure is an indirect measure quality of care. Infrastructure includes
the tangible features of a service delivery, which is related to equipment, furniture, physical
appearance of the hospital, facilities, availability of resources, and environment. It is also
referred to as manmade organization’s physical facility or services capes, which include
exterior attributes such as parking, the signage, and the landscape, and interior attributes such
as design, layout, and equipment (Zeithaml et al., 2009; Sureshchandar et al., 2002). Since
the infrastructure is a concept that is quite stable and has a significant relationship with
quality of care, therefore, it can affect the performance of the health care system, that is, it
affects patient perception toward healthcare service quality delivered.
Interaction
Health care services are intangible and often require patient involvement in the treatment
process. This situation contributes to intimate interactions and extensive communications
between patient and care providers. Thus, in health care service the interaction between
patients and care providers is very important (Andaleeb, 1998; Hasin et al. 2001; Hausman,
2004; Zineldin, 2006). In this study, interaction is defined as patients’ dealings with doctors
and nurses during their stay in the hospitals. Andaleeb (1998) based on a sample of 130
respondents developed and tested five-factor model of hospital service quality which has
three of the five dimensions, “competence of staff”, “and demeanor of staff” and
“communication” to represent interaction constructs. The research found that two of the
dimensions, perceived competence of the hospital staff and their demeanor have strong
impact on service quality and patient satisfaction. The interactions between patients and care
ISSN: 2186-8492, ISSN: 2186-8484 Print
Vol. 2 No. 3 August 2013
ASIAN JOURNAL OF SOCIAL SCIENCES & HUMANITIES
www.ajssh.leena-luna.co.jp
310 | P a g e
Leena and Luna International, Oyama, Japan.
Copyright © 2013
providers have an effect on the patient’s perception of quality of care (Cunningham et al.
2006). This idea is supported by Van Dam et al. (2003), in the systematic review, they
establish that patient’s interaction with care providers affect their perception on service
quality and patient outcome.
Administrative
Administrative service assists the production of a core service at the same time adding value
to a customer’s use of the service (Baalbaki et al., 2008). Administrative procedure in
hospital includes the processes of admission, stay and discharge of patients, clinical
appointments, and waiting time for consultation. The ease of these administrative procedures
is important in ensuring patient satisfaction with the hospital service quality (Atinga et al.,
2011). According to Aagja and Garg (2010) patients in public hospitals relate the admission
process to the perceived service quality.
Medical Care
This is the core service or primary service or technical quality of hospital service. Although
medical care has the highest priority with patients, the evaluation of medical care is generally
not understood by the majority of them. Therefore, researchers have resorted to measuring
medical care by proxy. Thus, the medical care dimension is also known by different terms:
including doctor composite (Andaleeb, 2008), clinical quality (Marley, Collier, & Goldstein,
2004); skill and ability (Baldwin & Sohal, 2003); physician concern (Choi et al., 2004, 2005);
and technical quality (Dagger et al., 2007; Rose et al., 2004). Medical care explains “what”
service the patient receives from the doctor (Marley et al., 2004). Andaleeb (2008) study the
healthcare service quality delivered to children in Bangladesh and establish that doctor
composite (medical care) is one of the healthcare service quality construct which has a
significant and strong impact on patient satisfaction.
Nursing Care
The hospital workforce is composed of many disciplines, but typically nurses make up the
majority of employees in the settings. In this respect, the nurse is a primary care provider and
spent more time with patients as compared to other care providers (Tafreshi et al., 2007).
Accordingly, major service delivers in a hospital is nursing care. Thus, nursing care is
experienced and considered by patients as one of the factors influencing overall care quality
delivered in hospital (Wagner & Bear, 2009; Laschinger et al., 2005; Yellen, Davis, &
Ricard, 2002). Dagger et al. (2007) confirmed that the nursing care is strongly and
significantly related to service quality.
Relationship between Service Quality and Patient Satisfaction
The relationship between satisfaction and service quality has attracted great attention in the
literature. In the marketing literature several studies showed that perceived service quality
and service satisfaction have a mixed relationship. Often, the nature of the service quality and
satisfaction link is seen as linear, indicating that the level of higher service quality leads to
higher levels of satisfaction (Pollack, 2008). A number of studies have confirmed that service
quality is an antecedent to customer satisfaction (Cronin & Taylor, 1992; Dabholkar et al.,
2000; Brady & Robertson 2001; and Dagger & Sweeney, 2006). According to Dabholkar et
al. (2000) and Choi et al. (2004) customer satisfaction and service quality are two distinct but
related constructs. Dabholkar et al. (2000) recommended that customer satisfaction and
perceived service quality should be measured separately in order to understand how
customers evaluate service quality.
エシアン
エシアンエシアン
エシアン ゾロナル
ゾロナルゾロナル
ゾロナル オフ
オフオフ
オフ ソシルサエニセズ
ソシルサエニセズソシルサエニセズ
ソシルサエニセズ アンドヒオメニテズ
アンドヒオメニテズアンドヒオメニテズ
アンドヒオメニテズ
ISSN: 2186-8492, ISSN: 2186-8484 Pri nt
Vol. 2 No. 3 August 2013
(
) アンド
アンドアンド
アンド
ル
ルル
ル
小山市、
小山市、小山市、
小山市、
.
www. leena-luna.co.jp
P a g e | 311
Customer satisfaction in marketing concept has been applied in healthcare sector in order to
serve the patient in a more efficient and effective way (Kay, 2007). Satisfaction with health
care is related to concepts of health care quality. According to Donabedian (2005) patient
satisfaction has become an important outcome of healthcare service quality and is not only an
important component of quality of care, but also a key contributor to the definition of quality
from the perspective of patient expectations. The patient's perception of service quality is
believed to positively affect patient satisfaction, indicated that patient satisfaction is a key
outcome of care (Andaleeb, 2001). Therefore, exist a strong linked between healthcare
service quality and patient satisfaction.
In the health care literature, several studies have established the relationship between quality
of hospital services and patient satisfaction. The relationships have been investigated by
many researchers (e.g., Badri et al. 2009; Scotti et al., 2007; Sohail, 2003; Phillips, 1996). A
study conducted by Gotlieb et al. (1994) on 232 discharge patients found that perceived
service quality positively affects patient satisfaction. This finding was supported by Tucker
and Adams (2001), in a study of patient satisfaction at public hospitals; they confirmed that
the service quality has a positive relationship with patient satisfaction. Accordingly, Badri et
al. (2009) analyzed the relationship between healthcare service quality and patient
satisfaction using structural equation modeling among patients at United Arab Emirates
public hospitals and found that the perceived service quality is positively related to patient
satisfaction. This causal relationship between service quality and patient satisfaction is
supported by many empirical studies (e.g., Alrubaiee & Alkaa’ida, 2011; Dagger et al., 2007;
Scotti, Harmon, & Behson, 2007; Choi et al., 2005; Merkourisa, Papathanassogloub, &
Lemonidoub 2004). Thus, there is a strong link between perceived service quality and patient
satisfaction in health care service.
THEORETICAL FRAMEWORK
Based on the literature review and discussions presented above, the following theoretical
framework for health care service quality was developed. Figure 1 shows the service quality
antecedents, namely, infrastructure, interaction, administrative, medical care and nursing
care, perceived service quality, and patient satisfaction constructs. All the constructs have
been briefly explained in the above section.
Figure 1. Conceptual Framework
Sources: adapted from Dabholkar et al. (2000).
ISSN: 2186-8492, ISSN: 2186-8484 Print
Vol. 2 No. 3 August 2013
ASIAN JOURNAL OF SOCIAL SCIENCES & HUMANITIES
www.ajssh.leena-luna.co.jp
312 | P a g e
Leena and Luna International, Oyama, Japan.
Copyright © 2013
HYPOTHESES
Prior discussion has led to a brief examination of the existing literature and the resultant
research gaps led to the development of the hypotheses in this research. The six hypotheses
are:
H1: Infrastructure is positively related to perceived service quality.
H2: Interaction is positively related to perceived service quality.
H3: Administrative is positively related to perceived service quality.
H4: Medical care is positively related to perceived service quality.
H5: Nursing care is positively related to perceived service quality.
H6: Perceived service quality is positively related to patient satisfaction.
METHODOLOGY
Instrument
Basically, all indicators or items were adapted from previously validated scales and were
modified to measure the specific constructs in this study. The constructs’ items (indicators) in
the questionnaire were direct, simple and short sentences to fit the patients as the respondents
in this study. The questionnaires were designed based on a multiple indicator measurement
scale adapted from the past researchers namely Duggirala, Rajendran and Anantharaman
(2008), Andaleeb and Millet (2010), Dagger and Sweeney (2007), Dagger, Sweeney and
Johnson (2007), and Arasli, Ekiz and Katircioglu (2008). Most of the indicators re-worded to
fit the healthcare service quality being studied. To establish support for face validity a panel
of experts reviewed the constructs and the initial set of measure items. Based on their
suggestions a few of the items were rephrased but no item was deleted. This study adapted a
5-point Likert-type scale to assess the model. All constructs were reflective since the items
reflect the meaning of the constructs. Reflective indicators mean they measure the same
underlying phenomenon (Chin, 1998). To test the research model, the questionnaire has 43
indicators that form the exogenous and endogenous constructs. The indicators grouped under
7 latent constructs (see Figure 1).
Sample
The unit of analysis in this study is an individual who had experienced being hospitalized.
The population for this study comprised of residents of Kuantan town who had admitted into
Kuantan general hospital in the past 12 months. Discharged patients are suitable to be the
respondents in healthcare service quality study because being admitted into hospital
represents salient experience and it is not easily forgotten (Andaleeb, 2008; Andaleeb, 2000).
In the absence of reliable lists, purposive convenience sampling methods were used. The
general rule for the minimum number of respondents or sample size is ten-to-one ratio of the
number of independent (exogenous) variables to be tested as suggested by Hair et al. (1998).
Since there are 6 independent (exogenous) variables in this study, a minimum sample size of
60 respondents would be appropriate.
The survey questionnaire was distributed to the potential respondents during working day by
the researcher. The time allocated for the respondents to answer the questionnaire was
between 10 to 20 minutes. The potential respondents were first filtered b y asking them a few
questions which regards to their experience being admitted into the hospital before they were
given the set of the survey questionnaire. Confidentiality was ensured as the subjects were
not required to state their names or other particulars on the survey form. A total of 109
エシアン
エシアンエシアン
エシアン ゾロナル
ゾロナルゾロナル
ゾロナル オフ
オフオフ
オフ ソシルサエニセズ
ソシルサエニセズソシルサエニセズ
ソシルサエニセズ アンドヒオメニテズ
アンドヒオメニテズアンドヒオメニテズ
アンドヒオメニテズ
ISSN: 2186-8492, ISSN: 2186-8484 Pri nt
Vol. 2 No. 3 August 2013
(
) アンド
アンドアンド
アンド
ル
ルル
ル
小山市、
小山市、小山市、
小山市、
.
www. leena-luna.co.jp
P a g e | 313
useable samples was collected. Therefore, the response achieved was considered adequate for
the study. Table 1 shows the profile of the respondents
Table 1. Respondents' Profile
Demographic Variable Categories Frequency
(N = 109)
Percentage
(%)
Gender
Male 32 29.4
Female 77 70.6
Age
18 to 25 28 25.7
26 to 35 51 46.8
36 to 45 23 21.1
46 to 55 2 1.8
56 and above 5 4.6
Ethnic Background
Malay 104 95.4
Chinese 1 0.9
Indian 3 2.8
Other 1 0.9
Marital Status
Single 33 30.3
Married 76 69.7
Educational Level
Primary 2 1.8
SPM/MCE 14 12.8
STPM/HSC 1 0.9
Diploma 10 9.2
Graduate 63 57.8
Post Graduate 19 17.9
Results and Data Analysis
The current study used smartPLS (Ringle, Wende & Will, 2005) partial least square structural
equation modelling (PLS-SEM) tool to evaluate the manner in which the constructs presented
in Figure 1 might relate to each other. The PLS-SEM technique is a statistical method that
has been developed for the analysis of latent variable structural models involving multiple
constructs with multiple indicators. PLS-SEMs have a number of potential strengths,
including the ability for the testing of the psychometric properties of the scales used to
ISSN: 2186-8492, ISSN: 2186-8484 Print
Vol. 2 No. 3 August 2013
ASIAN JOURNAL OF SOCIAL SCIENCES & HUMANITIES
www.ajssh.leena-luna.co.jp
314 | P a g e
Leena and Luna International, Oyama, Japan.
Copyright © 2013
measure a variable, as well as the strength and the direction of relationships among the
variables (Akter et al., 2011).
The PLS-SEM consisted of two sets of testing equations: First, the assessment of
measurement model, and the second, the assessment of the structural model (Hair, Ringle &
Sarstedt, 2011). The measurement model which is the process of calculating the item
reliability and validity; and the structural model which is the method of determining the
appropriate nature of the relationships (paths) between the measures and constructs (Hair et
al. 1998). The estimated path coefficients indicate the sign and the power of the relationships
while loadings indicate the strength of the measures (Hair et al., 2011). The confirmatory
factor analysis was first conducted to assess the measurement model; then, the structural
relationships were examined (Anderson & Gerbing 1988; Hair et al. 1998).
Measurement Model
The two main criteria used for testing the measurement model are reliability or internal
consistency and validity. The reliability of a research instrument concerns the extent to which
the instrument produces consistent results in repeated measurements, whereas validity is the
degree to which a test of how well an instrument that is developed measures and what is
supposed to measure (Sekaran & Bougie, 2010). To validate our measurement model, two
basic approaches to validity were assessed: convergent validity, and discriminant validity.
Reliability Analysis
To analyze the reliability/internal consistency of the items, we used the Cronbach’s alpha
coefficient and composite reliability (CR) value. Table 2 shows all Cronbach’s alpha values
are above 0.6 cutoff values as suggested by Nunnally and Berstein (1994). Another way to
determine internal consistency is by looking at composite reliability values. The composite
reliability (CR) values also ranged from 0.876 to 0.944 (Table 2). According to Fornell and
Larcker (1981) a composite reliability value of 0.70 or greater is considered acceptable. As
such we concluded that the measurement model were reliable.
Convergent Validity
When multiple items are used to measure an individual construct, the item (indicator)
convergent validity should be one of the main concerns to the researcher. The measurement
model was tested for convergent validity which is the extent to which multiple items to
measure the same concept are in agreement (MacKinnon, 2008).
Anderson and Gerbing (1988) stated that convergent validity is established if all factor
loadings for the items measuring the same construct are statistically significant. According to
Hair et al. (1998) convergent validity could be accessed through factor loadings, composite
reliability and the average variance extracted. The results of the measurement model (Table
2) show that the loadings for all items exceeded the recommended value of 0.5 (Hair et al.
1998). Composite reliability (CR) values ranged from 0.876 to 0.944 which exceeded the
recommended value of 0.7 (Hair et al. 1998).
All values of the average variance extracted (AVE) which measures the variance captured b y
the indicators relative to measurement error were greater than 0.50 to indicate acceptability of
the constructs (Fornell & Larcker, 1981; Henseler, Ringle, & Sinkovics, 2009). The table
indicates that these indicators satisfied the convergent validity of the constructs.
エシアン
エシアンエシアン
エシアン ゾロナル
ゾロナルゾロナル
ゾロナル オフ
オフオフ
オフ ソシルサエニセズ
ソシルサエニセズソシルサエニセズ
ソシルサエニセズ アンドヒオメニテズ
アンドヒオメニテズアンドヒオメニテズ
アンドヒオメニテズ
ISSN: 2186-8492, ISSN: 2186-8484 Pri nt
Vol. 2 No. 3 August 2013
(
) アンド
アンドアンド
アンド
ル
ルル
ル
小山市、
小山市、小山市、
小山市、
.
www. leena-luna.co.jp
P a g e | 315
Table 2. Results of Measurement Model
Construct Items Loading t-value 2
R
Cronbachs
Alpha CR1 AVE2
Infrastructure
Interaction
INF1 0.621 6.718 0.837 0.876 0.505
INF2 0.637 9.882
INF3 0.693 9.922
INF4 0.697 9.514
INF5 0.735 15.892
INF6 0.762 14.237
INF7 0.813 21.632
INT1 0.761 13.212 0.932 0.944 0.677
INT2 0.825 26.678
INT3 0.793 16.679
INT4 0.822 21.237
INT5 0.890 33.653
INT6 0.826 14.864
INT7 0.864 35.619
INT8 0.792 18.895
Administrative
AMD1 0.759 16.076 0.898 0.921 0.664
AMD2 0.760 14.158
AMD3 0.700 8.485
AMD4 0.897 41.343
AMD5 0.844 31.478
AMD6 0.907 48.416
Medical Care
MC1 0.829 21.947 0.901 0.922 0.628
MC2 0.729 11.734
MC3 0.783 17.111
MC4 0.818 18.065
MC5 0.820 19.063
MC6 0.768 19.495
MC7 0.795 13.393
Nursing Care
NC1 0.781 17.247 0.875 0.909 0.666
NC2 0.774 17.196
NC4 0.872 26.019
NC5 0.837 23.513
NC6 0.813 21.317
Perceived
Service Quality
PSQ1 0.920 51.917 0.697
0.901 0.931 0.772
PSQ2 0.884 32.893
PSQ3 0.905 43.697
PSQ4 0.802 12.014
Patient
Satisfaction
PS1 0.854 37.330 0.666
0.905 0.929 0.724
PS2 0.805 13.722
PS3 0.890 32.268
PS4 0.856 24.685
PS5 0.847 20.890
ISSN: 2186-8492, ISSN: 2186-8484 Print
Vol. 2 No. 3 August 2013
ASIAN JOURNAL OF SOCIAL SCIENCES & HUMANITIES
www.ajssh.leena-luna.co.jp
316 | P a g e
Leena and Luna International, Oyama, Japan.
Copyright © 2013
Note:
1. Composite reliability (CR)= (square of the summation of the factor loading)/{(square of the
summation of the factor loading) + (square of the summation of the error variances)}
2. Average variance extracted (AVE) = (summation of the square of the factor loadings)/{(summation
of the square of the factor loadings) + (summation of the error variances)}
Table 2 also shows that the items of the constructs (the Infrastructure, the Interaction, the
Administrative, the Medical Care, the Nursing Care, the Perceived Service Quality and the
Patient Satisfaction) were all valid measures of their respective constructs based on their
loadings values (standardized estimates) and statistical significance (Chow & Chan 2008).
All t-values greater than 2.33, thus, all measures were significant at the level of 0.001.
Discriminant Validity
Next we validated the discriminant validity of our instrument. The discriminant validity
represents the extent to which measures of a given construct differ from measures of other
constructs in the same model (MacKinnon, 2008). In a PLS context, the most important
criteria for adequate discriminant validity is that a construct should share more variance with
its items than it is should share with other constructs in a given model (Hulland, 1999). It was
assessed by examining the correlations between the measures of potentially overlapping
constructs. Items should load more strongly on their own constructs in the model, and the
square root of the average variance extracted for each construct is greater than the levels of
correlations involving the construct (Fornell & Larcker, 1981). As shown in Table 3, the
square root of the average variance extracted for each construct is greater than the items on
off-diagonal in their corresponding row and column, thus, indicating the adequate
discriminant validity. The inter-construct correlations also show that each construct shares
larger variance with its own measures than with other measures. In sum, the measurement
model demonstrated adequate convergent validity and discriminant validity.
Table 3. Discriminant validity of constructs
1 2 3 4 5 6 7
1 INF 0.711
2 INT 0.552 0.823
3 AMD 0.573 0.624 0.815
4 MC 0.508 0.768 0.608 0.792
5 NC 0.607 0.721 0.707 0.604 0.816
6 PSQ 0.541 0.639 0.740 0.630 0.782 0.879
7 PS 0.586 0.691 0.666 0.686 0.691 0.816 0.851
Diagonals (in bold) represent the square root of the average variance extracted
while the other entries represent correlations.
Hypotheses Testing
The hypothesis testing was carried out by examining the path coefficients (beta) between
latent constructs and their significance. To test the significance of the path coefficients the
エシアン
エシアンエシアン
エシアン ゾロナル
ゾロナルゾロナル
ゾロナル オフ
オフオフ
オフ ソシルサエニセズ
ソシルサエニセズソシルサエニセズ
ソシルサエニセズ アンドヒオメニテズ
アンドヒオメニテズアンドヒオメニテズ
アンドヒオメニテズ
ISSN: 2186-8492, ISSN: 2186-8484 Pri nt
Vol. 2 No. 3 August 2013
(
) アンド
アンドアンド
アンド
ル
ルル
ル
小山市、
小山市、小山市、
小山市、
.
www. leena-luna.co.jp
P a g e | 317
bootstrapping technique was utilized with a re-sampling of 500 (e.g., Bradley et al., 2012).
The 2
R
value of endogenous latent construct illustrates the predictive relevance of the model.
Table 4 presents the results and hypothesis testing. The findings support the hypotheses H3,
H4, H5 and H8 (t-values range from 2.150 to 19.460); however hypotheses H1 and H2 were
not supported. The 2
R
value of Perceived Service Quality construct was 0.697 suggesting that
69.7% of the variance in Perceived Service Quality was explained by the Infrastructure, the
Interaction, the Administrative, the Medical Care, the Nursing Care constructs (see, Table 2).
The 2
R
value of Patient Satisfaction construct was 0.666 suggesting that 66.6% of the
variance in Patient Satisfaction was explained by Perceived Service Quality (see, Table 2).
Thus, the 2
R
of the endogenous constructs in this model were considered significant at
0.01level (Hair et al., 1998).
Table 4. Path coefficients and hypothesis testing
Hyp Relationship Beta t-value Supported
H1 InfrastructurePerceived Service Quality 0.000 0.004, 05.0
>
ρ
No
H2 Interaction Perceived Service Quality -0.045 0.443, 05.0
>
ρ
No
H3 Administrative Perceived Service Quality
0.317 3.026, 01.0
<
ρ
Yes
H4 Medical Care Perceived Service Quality 0.182 2.150, 05.0
<
ρ
Yes
H5 Nursing Care Perceived Service Quality 0.481 5.190, 01.0
<
ρ
Yes
H6
Perceived Service Quality
Patient
Satisfaction
0.816 19.460, 01.0
<
ρ
Yes
DISCUSSION AND CONCLUSION
The main objective of this study is to investigate the relationship between the antecedents of
service quality, perceived service quality (PSQ) and patient satisfaction (PS). Patient
satisfaction is distinguished as being the ultimate endogenous construct of the research
model. We tried to compose a conceptual model that would better predict and explain
perceived service quality and patient satisfaction in a health care context. The model was
evaluated based on data collected from 109 respondents. Our model seemed to have better
power to explain the respondents/patient's attitude toward perceived service quality and
patient satisfaction in the health care context. The perceived service quality and patient
satisfaction accounted for 69.7 and 66.6 percent of the variance explain respectively.
Infrastructure to Perceived Service Quality (H1)
The infrastructure construct focuses on appearance, food and physical facilities available in
the ward; it is also referred to tangible dimension. Previous studies of health care service
quality found that infrastructure influences perceived service quality (e.g., Duggirala,
Rajendran, and Anantharaman, 2008). Our findings were different. The infrastructure was not
significantly influences the perceived service quality (H1). The results can be explained b y
the fact that most of the respondents were university graduates (84.9%, see Table 1) that, due
to their knowledge and intellectual capacities, they can easily adapt to the situation and could
endure with the facilities provided. Thus, linking the infrastructure construct to the patient’s
evaluation of the perceived service quality in this setting was not supported theoretically.
ISSN: 2186-8492, ISSN: 2186-8484 Print
Vol. 2 No. 3 August 2013
ASIAN JOURNAL OF SOCIAL SCIENCES & HUMANITIES
www.ajssh.leena-luna.co.jp
318 | P a g e
Leena and Luna International, Oyama, Japan.
Copyright © 2013
Interaction to Perceived Service Quality (H2)
Interaction refers to the relationship between care providers (doctors and nurses) with patients
during their hospitalization. In this study, we found that the interaction construct was not
significantly related to perceived service quality (H2). However, the interaction construct was
found to be significantly influenced perceived service quality in a number of studies (e.g.,
Andaleeb, 1998; Cunningham et al. 2006; Van Dam et al., 2003). The findings could be
explained that doctors and nurses in the hospital were busy they could not attend to the
individual patient. However, more plausible explanation could be that during the patient’s
hospitalization, daily care was provided by several doctors and nurses. The opportunity for
the patient and the care provider to develop into service relationship and to maximize the
interaction for the evaluation of service quality was limited. Thus, relating the patient and the
care provider in this study did not provide an adequate test of the theoretical relationship
between the interaction and the perceived service quality constructs.
Administrative and Perceived Service Quality (H3)
The administrative procedure in this study refers to the processes of admission, clinic
appointments, and waiting time for consultation. In this study, the hypothesis stated that
administrative is positively related to perceived service quality. Hypothesis testing
demonstrated a very strong relationship between administrative and perceived service quality
(Table 3). The finding regarding to the relationship between the administrative with
perceived service quality is consistent with findings of previous studies examining the
relationship between administrative procedure and service quality (Atinga et al., 2011; Aagja
& Garg, 2010).
Medical Care and Perceived Service Quality (H4)
This is the technical quality construct of hospital service that the patient receives from the
doctor. The hypothesis 4 stated that the medical care is positively related to perceived service
quality. The hypothesis was supported. The results of the hypothesis testing indicated that the
magnitude of the relationship between medical care and perceived service quality was weak
with little significance (Table 3). Previous studies examination the same relationship found
that strong and very significance relation between the constructs (Andaleeb, 2008; Rose et
al., 2004). The results can be explained by the fact that doctors are very busy with many
patients under their care. Thus, they spend very little consultation time with individual
patients. As such, it was very difficult for the patient to evaluate the care provided by the
doctor. Therefore, linking the patient and doctor did provide little significance of the
theoretical relationship between the medical care and the perceived service quality constructs.
Nursing Care and Perceived Service Quality (H5)
The nurse is considered as a primary care provider that spent more time with patients during
their hospitalization and nursing care is one of the technical quality construct of health care
service. The hypothesis 5 stated that the nursing care is positively related to perceived service
quality. Hypothesis testing in this study showed a very strong relationship between nursing
care and perceived service quality (Table 3). Previous studies examining the nursing care in
relation to perceived service quality supported the finding (Wagner & Bear, 2009; Laschinger
et al., 2005; Yellen, Davis, & Ricard, 2002; Dagger et al., 2007). The results could be
explained that nurses available almost 24 hours in the ward. Thus, the patients getting
familiar with their routine and they could evaluate nursing care more precise. Therefore,
relating patient and nurse in hospital service did provide very strong theoretical relationships
between the nursing care and the perceived service quality constructs.
エシアン
エシアンエシアン
エシアン ゾロナル
ゾロナルゾロナル
ゾロナル オフ
オフオフ
オフ ソシルサエニセズ
ソシルサエニセズソシルサエニセズ
ソシルサエニセズ アンドヒオメニテズ
アンドヒオメニテズアンドヒオメニテズ
アンドヒオメニテズ
ISSN: 2186-8492, ISSN: 2186-8484 Pri nt
Vol. 2 No. 3 August 2013
(
) アンド
アンドアンド
アンド
ル
ルル
ル
小山市、
小山市、小山市、
小山市、
.
www. leena-luna.co.jp
P a g e | 319
Perceived Service Quality and Patient Satisfaction (H6)
The relationship between satisfaction and service quality has been studied by many
researchers in various disciplines including health care service quality. This positive
relationship between service quality and patient satisfaction is supported by many empirical
studies (e.g., Alrubaiee & Alkaa’ida, 2011; Dagger et al., 2007; Scotti, Harmon, & Behson,
2007; Choi et al., 2005; Merkourisa, Papathanassogloub, & Lemonidoub, 2004). Hypothesis
6 in the current study stated that perceived service quality is positively related to patient
satisfaction. Table 3 shows a very strong relationship between perceived service quality and
patient satisfaction. Thus, it could be explained that perceived service quality and patient
satisfaction in this study did provide very strong theoretical relationships between the
constructs.
Our final conclusion was that the infrastructure and interaction constructs were not very
important in determining the perceived service quality from the respondent’s perspective. It
was also apparent from the higher item loading values (Table 2) that the respondents
perceived the two constructs were being delivered effectively. The results demonstrate that
administrative, medical care and nursing care were the most influential factor and related to
perceived service quality. Taking into consideration the significance levels of the path
coefficients between perceived service quality and patient satisfaction, this study confirmed
that they are two distinct constructs. Therefore, hospital leaders should place more emphasis
on these constructs. Such insights can help the leaders when making decisions concerning the
hospital future and patients’ welfare.
Due to the various sizes of hospitals exist and they also have different facilities, equipment
and the number of health care man powers. Thus, this study may only be generalized in a
limited way to other hospitals. Hence, it is recommended that every hospital carries out a
similar study so that a model with a greater conformity can be produced for purposes of
theoretical, planning and further improving hospital service quality.
ISSN: 2186-8492, ISSN: 2186-8484 Print
Vol. 2 No. 3 August 2013
ASIAN JOURNAL OF SOCIAL SCIENCES & HUMANITIES
www.ajssh.leena-luna.co.jp
320 | P a g e
Leena and Luna International, Oyama, Japan.
Copyright © 2013
REFERENCES
Aagja, J. P. & Garg, R. (2010). Measuring perceived service quality for public hospitals
(PubHosQual) in the Indian context. International Journal of Pharmaceutical and
Healthcare Marketing, 4(1), 60-83.
Akter, S., D’Ambra, J. & Ray, P. (2011). Trustworthiness in mHealth Information Services:
An assessment of a hierarchical model with mediating effects using partial least
square (PLS). Journal of the American Society for Information Science and
Technology, 62(1), 100-116.
Alrubaiee, L. & Alkaa'ida, F. (2011). The Mediating Effect of Patient Satisfaction in the
Patients' Perceptions of Healthcare Quality – Patient Trust Relationship. International
Journal of Marketing Studies, 3(1), 103-127.
Andaleeb, S. (1998). Determinants of customer satisfaction with hospitals: a managerial
model. International Journal of Health Care Quality Assurance, 11(6), 181-187.
Andaleeb, S. S. (2000). Service quality in public and private hospitals in urban Bangladesh:
A comparative study. Health Policy, 53, 25-37.
Andaleeb, S. S. (2001). Service quality perceptions and patient satisfaction: a study of
hospitals in a developing country. Social Science & Medicine, 52, 1359–1370.
Andaleeb, S. (2008). Caring for children: a model of healthcare service quality in
Bangladesh. International Journal for Quality in Health Care, 20(5), 339–345.
Andaleeb, S. S. & Millet, I. (2010). Service experiences in hospitals in Bangladesh: are there
gender inequities? International Journal of Health Care Quality Assurance, 23(6),
591-606.
Anderson, J. C. & Gerbing, D. W. (1988). Structural Equation Modeling in Practice: A
Review and Recommended Two-Step Approach. Psychological Bulletin, 103(3), 41-
423.
Arasli, H., Ekiz, E. H. & Katircioglu, S. T. (2008). Gearing service quality into public and
private hospitals in small islands: empirical evidence from Cyprus. International
Journal of Health Care Quality Assurance, 21(1), 8-23.
Atinga, R.A., Abekah-Nkrumah, G., & Domfeh, K.A. (2011). Managing healthcare quality in
Ghana: a necessity of patient satisfaction. International Journal of Health Care
Quality Assurance, 24(7), 548-563.
Baalbaki, I., Ahmed, Z. U., Pashtenko, V. H. & Makarem, S. (2008). Patient satisfaction with
healthcare delivery systems. International Journal of Pharmaceutical and Healthcare
Marketing, 2(1), 47-62.
Badri, M.A., Attia, S. & Ustadi, A M. (2009). Healthcare quality and moderators of patient
satisfaction: testing for causality. International Journal of Health Care Quality
Assurance, 22(4), 382 - 410.
Baldwin, A. & Sohal, A. (2003). Service quality factors and outcomes in dental care.
Managing Service Quality, 13(3), 207-216.
Bradley, R.V., Byrd, T. A., Pridmore, J. L., Thrasher, E., Pratt, R. M. E. & Mbarika. (2012).
An empirical examination of antecedents and consequences of IT governance in US
hospitals. Journal of Information Technology, 27, 156-177.
エシアン
エシアンエシアン
エシアン ゾロナル
ゾロナルゾロナル
ゾロナル オフ
オフオフ
オフ ソシルサエニセズ
ソシルサエニセズソシルサエニセズ
ソシルサエニセズ アンドヒオメニテズ
アンドヒオメニテズアンドヒオメニテズ
アンドヒオメニテズ
ISSN: 2186-8492, ISSN: 2186-8484 Pri nt
Vol. 2 No. 3 August 2013
(
) アンド
アンドアンド
アンド
ル
ルル
ル
小山市、
小山市、小山市、
小山市、
.
www. leena-luna.co.jp
P a g e | 321
Brady, M. K. & Cronin, J. J. (2001). Some new thoughts on conceptualizing perceived
service quality: a hierarchical approach. Journal of Marketing, 65, 34-49.
Brady, M. K. & Robertson, C. J. (2001). Searching for a consensus on the antecedent role of
service quality and satisfaction: an exploratory cross-national study. Journal of
Business Research, 51, 53- 60.
Chin, W. W. (1998). Issues and opinion on structural equation modelling. MIS Quarterly,
22(1), 7-16.
Choi, K. S., Cho, W. H., Leec, S. Leed, H. & Kim, C. (2004). The relationships among
quality, value, satisfaction and behavioural intention in health care provider choice: A
South Korean study. Journal of Business Research, 57, 913– 921.
Choi, K. S., Lee, H., Kim, C. & Lee, S. (2005). The service quality dimensions and patient
satisfaction relationships in South Korea: comparisons across gender, age and types of
service. Journal of Service Marketing, 19(3), 140-149.
Chow, W. S. & Chan, L. S. (2008). Social network, social trust and shared goals in
organizational knowledge sharing, Information & Management, 45(7), 458–465.
Cronin, J. J. & Taylor, S. A. (1992). Measuring service quality: A reexamination and
extension. Journal of Marketing, 56(3), 55-68.
Cunningham, T. T., Carpenter, C. C., Charlip, R. B., Goodle, J. L., Griffin, D. L., Macchione,
N., Snyder, J. M., Stevenson, M. J., Stier, M. K., West, W. K., Young, F. C. &
Zuckerman, A.M. (2006). Patient Satisfaction understanding and Managing the
Experience Care. (2nd Edition). Irwin Press.
Dabholkar, P. A., Thorpe, D. I. & Rentz, J. O. (1996). A measure of service quality for retail
stores: scale development and validation. Journal of the Academy of Marketing
Science, 24(1), 3-16.
Dabholkar, P. A., Shepherd, C. D. & Thorpe, D. I. (2000). A comprehensive framework for
service quality: an investigation of critical conceptual and measurement issues
through a longitudinal study. Journal of Retailing, 76(2), 139-173.
Dagger, T. S. & Sweeney, J. C. (2007). Service quality attribute weights: how do novice and
longer-term customers construct service quality perceptions? Journal of Service
Research, 10(1), 22-42.
Dagger, T. S., Sweeney, J. C. & Johnson, L. W. (2007). A hierarchical model of health
service quality: scale development and investigation of integrated model. Journal of
Service Research, 10(2), 123-142.
Donabedian, A. (2005). Evaluating the Quality of Medical Care. The Milbank Quarterly,
83(4), 691–729.
Duggirala, M., Rajendran, C. & Anantharaman, R. N. (2008). Patient-perceived dimensions
of total quality service in healthcare. Benchmarking: An International Journal, 15(5),
560-583.
Fornell, C. & Larcker, D. F. (1981). Evaluating structural equation models with unobservable
variables and measurement error. Journal of Marketing Research, 18(1), 39-50.
Gotlieb, J. B., Grewal, D. & Brown, S.W. (1994). Consumer satisfaction and perceived
quality:complimentary or divergent constructs. Journal of Applied Psychology, 79(6),
875-85.
ISSN: 2186-8492, ISSN: 2186-8484 Print
Vol. 2 No. 3 August 2013
ASIAN JOURNAL OF SOCIAL SCIENCES & HUMANITIES
www.ajssh.leena-luna.co.jp
322 | P a g e
Leena and Luna International, Oyama, Japan.
Copyright © 2013
Grönroos, C. (1998). Marketing services: the case of a missing product. Journal of Business
& Industrial Marketing, 13(4/5), 322-338.
Hair, J. F., Ringle, C. M. & Sarstedt, M. (2011). PLS-SEM: Indeed a silver bullet. Journal of
Marketing Theory and Practice, 19(2), 139-151.
Hair, J. F., Anderson, R. E., Tatham, R. & Black, W.C. (1998). Multivariate Data Analysis.
Upper Saddle River, NJ: Prentice Hall.
Hasin, M. A. A. & Seeluangsawat, R. (2001). Statistical measures of customer satisfaction for
health care quality assurance: a case study. International Journal of Health Care
Quality Assurance, 14(1), 6-13.
Hausman, A. (2004). Modeling the patient-physician service encounter: Improving patient
outcomes. Academy of Marketing Science Journal, 32(4), 403-417.
Henseler, J., Ringle, C. M. & Sinkovics, R. R. (2009). The use of partial least squares path
modelling in international marketing. New Challenges to International Marketing
Advances in International Marketing, 20, 227-319.
Hulland, J. (1999). Use of Partial Least Squares (PLS) in strategic management research: a
view of four recent studies. Strategic Management Journal, 20, 195-204.
Kay, M. K. (2007). Healthcare marketing: what is salient? International Journal of
Pharmaceutical and Healthcare Marketing, 1(3), 247-263.
Lam, S. S. K. (1997). SERVQUAL: A tool for measuring patients' opinions of hospital
service quality in Hong Kong. Total Quality Management, 8(4), 145-152.
Laschinger, J. H., Hall, L. M., Pedersen, C. & Almost, J. 2005. A psychometric analysis of
the patient satisfaction with nursing care quality questionnaire: an actionable approach
to measuring patient satisfaction. Journal of Nursing Care Quality, 20(3), 220-230.
MacKinnon, D. P. (2008). Introduction to Statistical Mediation Analysis. Taylor and Francis
group: New York
Marley, K. A., Collier, D. A. & Goldstein, S. M. (2004). The role of clinical and process
quality in achieving patient satisfaction in hospitals. Decision Sciences, 35(3), 349-
369.
Merkourisa, A., Papathanassogloub, E. D. E. & Lemonidoub, C. (2004). Evaluation of patient
satisfaction with nursing care: quantitative or qualitative approach? International
Journal of Nursing Studies, 41, 355–367.
Nunnally, J. & Berstein, I. (1994). Psychometric Theory. New York: McGraw-Hill.
Parasuraman, A., Berry, L. L. & Zeithaml, V. A. (1985). A conceptual model of service
quality and its implications for future research. Journal of Marketing, 49, 41-50.
Parasuraman, A., Zeithaml, E. V. & Berry, L. L. (1988). SERVQUAL: a multiple items scale
for measuring customers perception of service quality. Journal of Retailing, 64, 12-
23.
Phillips, D. (1996). Medical professional dominance and client dissatisfaction. Social Science
& Medicine, 42(10), 1419-1425.
Pollack, B. L. (2008). The nature of the service quality and satisfaction relationship.
Managing Service Quality, 18(6), 537-558.
エシアン
エシアンエシアン
エシアン ゾロナル
ゾロナルゾロナル
ゾロナル オフ
オフオフ
オフ ソシルサエニセズ
ソシルサエニセズソシルサエニセズ
ソシルサエニセズ アンドヒオメニテズ
アンドヒオメニテズアンドヒオメニテズ
アンドヒオメニテズ
ISSN: 2186-8492, ISSN: 2186-8484 Pri nt
Vol. 2 No. 3 August 2013
(
) アンド
アンドアンド
アンド
ル
ルル
ル
小山市、
小山市、小山市、
小山市、
.
www. leena-luna.co.jp
P a g e | 323
Reeves, C. A. & Bednar, D. A. (1994). Defining quality: alternatives and implications.
Academy of Management Review, 19(3), 419-445.
Ringle, C. M., Wende, S. & Will, S. (2005). smartPLS 2.0 (M3) Beta (online). Retrieved on
May 21, 2010, from http://www.smartpls.de
Rose, R. C., Uli, J., Abdul, M. & Ng, K. L. (2004). Hospital service quality: a managerial
challenge. International Journal of Health Care Quality Assurance, 17(3), 146-159.
Scotti, D. J., Harmon, J. & Behson, S.J. (2007). Links among high-performance work
environment, service quality, and customer satisfaction: an extension to the healthcare
sector. Journal of Healthcare Management, 52(2), 109-124.
Sekaran, U. & Bougie, R. (2010). Research Methods for Business: A Skill Building
Approach. UK: John Wiley and Sons.
Sohail, M. S. (2003). Service quality in hospitals: more favourable than you might think.
Managing Service Quality, 13(3), 197-207.
Sureshchandar, G. S., Rajendran, C. & Anantharaman, R. H. (2002). Determinants of
customer-perceived service quality: a confirmatory factor analysis approach. Journal
of Services Marketing, 16(1), 9-34.
Tafreshi, M. Z., Pazargadi, M. & Saeedi, Z. A. (2007). Nurses’ perspectives on quality of
nursing care: a qualitative study in Iran. International Journal of Health Care Quality
Assurance, 20(4), 320-328.
Tomes, A. E. & Ng, C. P. (1995). Service quality in hospital care: the development of an in-
patient questionnaire. International Journal of Health Care Quality Assurance, 8(3),
25-34.
Tucker III, J. L. & Adams, S. R. (2001). Incorporating patients' assessments of satisfaction
and quality: An integrative model of patients’ evaluations of their care. Managing
Service Quality, 11(4), 272-286.
Van Dam, H. A., Van Der Horst, F., Van Den Borne, B., Ryckman, R. & Crebolder, H.
(2003). Provider-patient interaction in diabetes care: effects on patient self-care and
outcomes. A systematic review. Patient Education and Counseling, 51(1), 17-28.
Wagner, D. & Bear, M. (2009). Patient satisfaction with nursing care: a concept analysis
within a nursing framework. Journal of Advanced Nursing, 65(3), 692–701.
Yellen, E., Davis, G. C. & Ricard, R. (2002). The measurement of patient satisfaction.
Journal of Nursing Care Quality, 16(4), 23–29.
Zeithaml, V. A., Bitner, M. J. & Gremler, D. D. (2009). Services marketing:integrating
customer focus across the firm. (5ft Edition). New York: McGraw-Hill.
Zineldin, M. (2006). The quality of health care and patient satisfaction: An exploratory
investigation of the 5Qs model at some Egyptian and Jordanian medical clinics.
International Journal of Health Care Quality Assurance, 19(1), 60-92.
